Information processing device, information processing method, and information processing system

Abstract

[Problem] To assist with interactions between people. [Solution] An information processing device comprising a control unit, wherein the control unit can perform control so as to analyze the relationship between information regarding one person and information regarding another person.

Description

Information processing device, information processing method, and information processing system

[0001] The present invention relates to an information processing device, an information processing method, and an information processing system.

[0002] Conventionally, a server capable of performing compatibility diagnosis has been known (see Patent Document 1).

[0003] Japanese Patent Application Laid-Open No. 2002-73787

[0004] In the course of thorough research into the compatibility between people, the inventor came to the idea that by applying ingenuity to the analysis of information, it may be possible to create a new form of support for interaction between people.

[0005] The present invention has been made in view of the above-mentioned circumstances, and has an object to provide an information processing device, an information processing method, and an information processing system that are capable of supporting interactions between people.

[0006] In order to achieve the above object, the present invention provides the following information processing device, information processing method, and information processing system.

[0007] (1) An information processing device including a control unit, wherein the control unit is capable of performing control to analyze a relationship between information about one person and information about another person.

[0008] (2) The information processing device of (1) is characterized in that it includes a communication unit, and the control unit is capable of controlling communication via the communication unit so as to cause an external device to output according to the results of the analysis.

[0009] (3) The information processing device of (1) or (2), wherein the control unit is capable of controlling, when the one person and the other person are having a conversation, the analysis is to analyze the relationship between the change over time of information about the one person and the change over time of information about the other person during the conversation.

[0010] (4) The information processing device of (3), wherein the control unit is capable of controlling the analysis to calculate a correlation coefficient between information about the one person and information about the other person according to each of a plurality of timings during the conversation.

[0011] (5) The information processing device of (2), wherein the control unit is capable of calculating a correlation coefficient between information about the one person and information about the other person in accordance with each of a plurality of timings in the analysis, and then controlling communication via the communication unit so as to cause an external device to output, as the output, a value corresponding to a normalized value of the correlation coefficient.

[0012] (6) The information processing device of (3) or (4) is characterized in that the control unit is capable of acquiring voice data corresponding to a conversation between the one person and the other person, and is capable of being controlled to identify a topic based on information about the one person, information about the other person, and the voice data.

[0013] (7) The information processing device of (6) is characterized in that it includes a communication unit, and the control unit is capable of controlling communication via the communication unit so as to cause an external device to perform output according to the identified topic.

[0014] (8) An information processing device according to any one of (1) to (7), further comprising a communication unit, wherein the control unit is capable of controlling communication via the communication unit so as to cause an external device to output advice according to the advice generated by the large-scale language model.

[0015] (9) An information processing method, comprising: a first step of controlling to analyze the relationship between information about one person and information about another person.

[0016] (10) The information processing method according to (9) above, further comprising a second step of controlling to output an output according to the result of the analysis.

[0017] (11) The information processing method of (9) or (10), wherein in the first step, when the one person and the other person are having a conversation, the analysis is controlled to analyze the relationship between the change over time of information about the one person and the change over time of information about the other person during the conversation.

[0018] (12) The information processing method of (11), wherein in the first step, the analysis is controlled to calculate a correlation coefficient between information about the one person and information about the other person according to each of a plurality of timings during the conversation.

[0019] (13) The information processing method of (10), characterized in that in the first step, in the analysis, control is performed to calculate a correlation coefficient between information about the one person and information about the other person according to each of a plurality of timings, and in the second step, control is performed to output the output according to a normalized value of the correlation coefficient.

[0020] (14) The information processing method of (11) or (12) is characterized by including: a third step of controlling to acquire voice data corresponding to a conversation between the one person and the other person; and a fourth step of controlling to identify a topic based on information about the one person, information about the other person, and the voice data.

[0021] (15) The information processing method according to (14) above, further comprising a fifth step of controlling to output information according to the identified topic.

[0022] (16) The information processing method according to any one of (9) to (15), further comprising a sixth step of controlling to output advice according to the advice generated by the large-scale language model.

[0023] (17) An information processing system including an information terminal, the information terminal including a control unit and a storage unit, the control unit being capable of controlling the storage unit to associate information about a person with information about timing when the person is interacting with another person.

[0024] (18) The information processing system of (17) is characterized in that it includes a communication unit, and the control unit is capable of controlling communication via the communication unit so as to transmit information about the person associated with information about the timing to an external device.

[0025] (19) The information processing system of (17) or (18), characterized in that the control unit is capable of controlling the storage unit to store voice data when the one person and the other person are having a conversation.

[0026] (20) The information processing system according to any one of (17) to (19), further comprising an output unit, wherein the control unit is capable of controlling the output unit to output according to the results of an analysis of the relationship between the information about the one person and the information about the other person.

[0027] According to the present invention, it is possible to support interactions between people.

[0028] 1 is a diagram illustrating an overview of the exchange support system. FIG. 1 is a functional block diagram of an exchange support server. FIG. 2 is a functional block diagram of an administrator terminal. FIG. 3 is a functional block diagram of an organizer terminal. FIG. 4 is a functional block diagram of a participant terminal. FIG. 5 is a diagram illustrating the appearance of a biometric detector. FIG. 6 is a functional block diagram of a biometric detector. FIG. 7 is a flowchart illustrating new event setting processing on the administrator terminal side, new event setting processing on the exchange support server side, and new event setting processing on the organizer terminal side. FIG. 8 is a diagram illustrating an example of a new event creation operation acceptance screen. FIG. 9 is a diagram illustrating an example of an event information management table. FIG. 10 is a flowchart illustrating event start processing on the organizer terminal side and event start processing on the exchange support server side. FIG. 11 is a diagram illustrating an example of an authentication operation acceptance screen. FIG. 12 is a diagram illustrating an example of an original setting operation acceptance screen. FIG. 13 is a diagram illustrating an example of an event start operation acceptance screen. FIG. 14 is a flowchart illustrating conversation start processing on the participant terminal side and conversation start processing on the exchange support server side. FIG. 15 is a diagram illustrating an example of a conversation preparation operation acceptance screen. FIG. 16 is a diagram illustrating an example of a storage area specification table. FIG. 17 is a diagram illustrating an example of a biometric detector connection operation acceptance screen. FIG. 18 is a diagram illustrating an example of a conversation partner name input operation acceptance screen. FIG. 19 is a diagram illustrating an example of a conversation start operation acceptance screen. 1 is a diagram schematically showing an example of time-series biometric data stored in a participant terminal. FIG. 2 is a flowchart showing conversation end processing on the participant terminal side and conversation end processing on the exchange support server side. FIG. 3 is a diagram showing an example of a conversation end operation acceptance screen. FIG. 4 is a diagram schematically showing the configuration of a conversation result storage area. FIG. 5 is a diagram schematically showing an example of time-series biometric data stored in the exchange support server. FIG. 6 is a flowchart showing synchronization analysis processing performed in the exchange support server. FIG. 7 is a flowchart showing event end processing on the organizer terminal side, event end processing on the exchange support server side, and event end processing on the participant terminal side. FIG. 8 is a flowchart showing event end processing on the organizer terminal side, event end processing on the exchange support server side, and event end processing on the participant terminal side. FIG. 9 is a diagram showing an example of an event end operation acceptance screen. FIG. 10 is a diagram showing an example of an event result display operation acceptance screen. FIG. 11 is a diagram showing an example of an event result screen. FIG. 12 is a diagram showing an example of an event result screen.1 is a diagram showing an example of a matching result initial screen. FIG. 2 is a diagram showing an example of a matching result detail screen. FIG. 3 is a diagram showing an example of a questionnaire response operation reception screen. FIG. 4 is a diagram showing an example of a matching pair screen. FIG. 5 is an explanatory diagram showing the flow of information in the exchange support system. FIG. 6 is an explanatory diagram showing the flow of information in the exchange support system. FIG. 7 is an explanatory diagram showing the flow of information in the exchange support system. FIG. 8 is a diagram showing an example of a conversation information database. FIG. 9 is a diagram showing an example of a heart rate information database. FIG. 10 is a diagram showing an example of a matching degree information database. FIG. 11 is a diagram showing an example of a topic extraction information database. FIG. 12 is a flowchart showing conversation start processing on the participant terminal side and conversation start processing on the exchange support server side. FIG. 13 is a flowchart showing conversation start processing on the participant terminal side and conversation start processing on the exchange support server side. FIG. 14 is a diagram showing an example of a conversation start operation reception screen. FIG. 15 is a diagram showing an example of a conversation start operation reception screen. FIG. 16 is a flowchart showing conversation end processing on the participant terminal side, conversation end processing on the exchange support server side, and conversation end processing on the organizer terminal side. FIG. 17 is a flowchart showing conversation end processing on the participant terminal side, conversation end processing on the exchange support server side, and conversation end processing on the organizer terminal side. 1 is a flowchart showing a conversation end process on the participant terminal side, a conversation end process on the exchange support server side, and a conversation end process on the organizer terminal side. FIG. 2 is a diagram showing an example of a matching result screen. FIG. 3 is a diagram showing an example of an excitement result screen. FIG. 4 is a diagram showing an example of an excitement reference screen. FIG. 5 is a diagram showing an example of an advice generation information input operation reception screen. FIG. 6 is a diagram showing an example of an advice screen. FIG. 7 is a flowchart showing an excitement level analysis process performed on the exchange support server. FIG. 8 is a flowchart showing a matching information transmission process on the participant terminal side, and a matching information reception process on the exchange support server side. FIG. 9 is a flowchart showing an excitement level analysis process performed on the exchange support server. FIG. 10 is a diagram showing an example of a graph visualizing per-window correlation level values ​​and time-series biometric data. FIG. 11 is a diagram showing per-window correlation level values ​​and time-series biometric data. FIG. 12 is a diagram showing per-window correlation level values ​​and time-series biometric data.1 is an example of a graph visualizing per-window correlation level values ​​and time-series biological data. FIG. 1 is an example of a graph visualizing per-window correlation level values ​​and time-series biological data. FIG. 2 is an example of a graph visualizing per-window correlation level values ​​and time-series biological data. FIG. 3 is an example of a graph visualizing per-window correlation level values ​​and time-series biological data. FIG. 4 is an example of a graph visualizing per-window correlation level values ​​and time-series biological data. FIG. 5 is an example of a graph visualizing per-window correlation level values ​​and time-series biological data. FIG. 6 is an example of a graph visualizing per-window correlation level values ​​and time-series biological data. FIG. 7 is an example of a graph visualizing per-window correlation level values ​​and time-series biological data. FIG. 8 is an example of a graph visualizing per-window correlation level values ​​and time-series biological data. FIG. 9 is an example of a graph visualizing per-window correlation level values ​​and time-series biological data. 1 is an example of a graph visualizing correlation level values ​​for each window and time-series biological data; FIG. 2 is an example of a graph visualizing correlation level values ​​for each window and time-series biological data; FIG. 3 is an example of a graph visualizing correlation level values ​​for each window and time-series biological data; FIG. 4 is an example of a graph visualizing correlation level values ​​for each window and time-series biological data.

[0029] First Embodiment Hereinafter, an exchange support system 10 according to a first embodiment will be described.

[0030] [Interaction Support System] FIG. 1 is a diagram showing an overview of an interaction support system.

[0031] As shown in Fig. 1, the exchange support system 10 includes an exchange support server 20, an administrator terminal 30, a host terminal 40, and a participant terminal 50. The administrator terminal 30 is a terminal device operated by an administrator. The host terminal 40 is a terminal device operated by a host. The participant terminal 50 is a terminal device operated by a participant.

[0032] The administrator performs various administrative tasks using the administrator terminal 30 to ensure smooth operation of the exchange support system 10. The organizer performs various operational tasks using the organizer terminal 40 with the aim of making the exchange event using the exchange support system 10 a success. Participants refer to multiple individuals who participate in the exchange event using the exchange support system 10.

[0033] Networking events include matchmaking events (e.g., matchmaking parties and matchmaking at marriage agencies), business-related events (e.g., networking events that provide opportunities for matching business partners), social events (e.g., networking events that provide opportunities for people to develop social relationships), events held around a specific theme (e.g., networking events for people with a common hobby), and events held at retail or commercial facilities (e.g., interactive demonstrations that allow customers to experience the features of a product). There is no upper limit to the number of participants in a networking event, as long as it is two or more people.

[0034] Furthermore, the social event may be an offline event or an online event. In an offline event, participants meet in person at the event location and interact through face-to-face conversations, etc. On the other hand, in an online event, participants interact through conversations, etc. using a web conferencing service (e.g., Zoom (registered trademark), Skype (registered trademark), Microsoft Teams (registered trademark), etc.) on their own participant terminals 50.

[0035] The administrator terminal 30, the organizer terminal 40, and the participant terminal 50 can each be configured with an information processing device such as a general personal computer, laptop computer, smartphone, tablet terminal, etc. The communication support server 20 can also be configured with an information processing device such as a general personal computer, laptop computer, smartphone, tablet terminal, etc. Alternatively, the communication support server 20 may be configured with a cloud server (e.g., Google Cloud Platform).

[0036] The communication support server 20 is capable of communicating with each of the administrator terminal 30, the organizer terminal 40, and the participant terminal 50 via a network N. The network N may be, for example, the Internet using the communication protocol IP, or a network (data communication network) such as an intranet, an extranet, a mobile communication network, a wide area network (WAN), a local area network (LAN), a metropolitan area network (MAN), or a satellite communication network.

[0037] The participant terminal 50 is capable of communicating with the biometric tester 60 using wireless communication technology such as Bluetooth (registered trademark) or Wi-Fi (Wireless Fidelity). The biometric tester 60 is a device for detecting biometric information of participants. The biometric tester 60 can be designed as a wearable device and can be formed in a shape that is easy for participants to use on a daily basis, such as a wristwatch, wristband, earrings, glasses, hat, ring, collar, or clothing. Alternatively, the participant terminal 50 may be configured to have the functions of the biometric tester 60.

[0038] Biometric information is information that can be measured according to a person's physiological phenomena. Physiological phenomena are a concept that encompasses phenomena occurring inside a living organism (e.g., metabolic activity of cells, secretion of hormones, neurotransmission, etc.) and phenomena expressed externally (e.g., facial expressions, sweating, muscle contraction, etc.). Phenomena occurring inside a living organism and phenomena expressed externally are a series of processes induced in the living organism due to interactions with the environment (e.g., interactions with others), and are closely and inseparably related. Any phenomenon in the process can be measured as biometric information.

[0039] For example, information that is difficult to see or hear directly from the outside (e.g., information about heart rate, information about skin conductance, information about brain waves, information about physiological stress indicators, etc.) can be measured using various sensors. Also, information that can be seen or heard directly from the outside (e.g., information about facial expressions (such as movements of specific muscles in the face), information about the direction of gaze, information about tone of voice, etc.) can be measured by analyzing image data or audio data. This information can change over time depending on human emotions and attention, and is useful for inferring a person's psychological state.

[0040] [Interaction Support Server] FIG. 2 is a functional block diagram of the interaction support server.

[0041] 2, the exchange support server 20 includes a control unit 110, a storage unit 111, and a communication unit 112. The control unit 110 controls the entire exchange support server 20. The storage unit 111 stores programs and data used when the control unit 110 executes processing based on the programs. The communication unit 112 (network I / F (interface)) connects the exchange support server 20 to a network N and establishes communication with external devices.

[0042] The control unit 110 includes a communication control unit 121, an event information management unit 122, an email creation unit 123, a matching information management unit 124, a matching measurement unit 125, and a matching result output unit 126. The communication control unit 121 transmits and receives various information and data between the administrator terminal 30, the organizer terminal 40, and the participant terminal 50 via the communication unit 112. The event information management unit 122 acquires information about the social event (information indicating the organizer's email address, event ID, participant names, etc.) and stores it in the memory unit 111. The email creation unit 123 creates an email to be sent to the organizer terminal 40.

[0043] The matching information management unit 124 acquires matching information including the biometric information of the participants and stores it in the memory unit 111. The matching measurement unit 125 calculates the degree of matching between one participant and another participant. The matching degree is an index that indicates the compatibility between one participant and another participant, and includes the degree of synchronization as an important element. The degree of synchronization is a value that indicates the relationship (degree of similarity) between the temporal changes in the biometric information of one participant (participant A) and the temporal changes in the biometric information of another participant (participant B). The more similar the temporal changes in the biometric information of participant A and the biometric information of participant B are, the higher the degree of matching generally becomes. The matching result output unit 126 controls the screen display on the organizer terminal 40 and the participant terminal 50 according to the matching degree calculated by the matching measurement unit 125.

[0044] The control unit 110 is configured by, for example, a CPU (Central Processing Unit) and the like. The storage unit 111 is configured by, for example, a ROM (Read Only Memory), a RAM (Random Access Memory), a HDD (Hard Disk Drive), a SSD (Solid State Drive), or a combination of these. The control unit 110 executes processing based on the program stored in the storage unit 111, thereby realizing functional configurations such as a communication control unit 121, an event information management unit 122, an email creation unit 123, a matching information management unit 124, a matching measurement unit 125, and a matching result output unit 126.

[0045] [Administrator Terminal] FIG. 3 is a functional block diagram of the administrator terminal.

[0046] 3, the administrator terminal 30 includes a control unit 130, a storage unit 131, a display unit 132, an operation input unit 133, and a communication unit 134. The control unit 130 is configured, for example, by a CPU or the like, and controls the entire administrator terminal 30. The storage unit 131 is configured, for example, by a ROM, RAM, HDD, SSD, or a combination thereof, and stores programs and data used when the control unit 130 executes processing based on the programs. The control unit 130 executes processing based on the programs stored in the storage unit 131, thereby realizing the functional configuration of the administrator terminal 30.

[0047] The display unit 132 is configured, for example, by a display (e.g., a liquid crystal display or an organic EL display) and displays various information. The operation input unit 133 is configured, for example, by a keyboard, a mouse, a capacitive touch panel, etc. and accepts operation inputs from the administrator. For example, if a smartphone is used as the administrator terminal 30, the display unit 132 and the operation input unit 133 can be configured by a touch panel LCD. The communication unit 134 (network I / F (interface)) connects the administrator terminal 30 to the network N and establishes communication with external devices.

[0048] [Organizer Terminal] FIG. 4 is a functional block diagram of the organizer terminal.

[0049] 4 , the organizer terminal 40 includes a control unit 140, a storage unit 141, a display unit 142, an operation input unit 143, and a communication unit 144. The control unit 140 is configured, for example, by a CPU or the like, and controls the entire organizer terminal 40. The storage unit 141 is configured, for example, by a ROM, RAM, HDD, SSD, or a combination thereof, and stores programs and data used when the control unit 140 executes processing based on the programs. The control unit 140 executes processing based on the programs stored in the storage unit 141, thereby realizing the functional configuration of the organizer terminal 40.

[0050] The display unit 142 is configured, for example, by a display (e.g., a liquid crystal display or an organic EL display) and displays various information. The operation input unit 143 is configured, for example, by a keyboard, a mouse, a capacitive touch panel, etc. and accepts operation inputs from the organizer. For example, if a smartphone is used as the organizer terminal 40, the display unit 142 and the operation input unit 143 can be configured by a touch panel LCD. The communication unit 144 (network I / F (interface)) connects the organizer terminal 40 to the network N and establishes communication with external devices.

[0051] [Participant Terminal] FIG. 5 is a functional block diagram of a participant terminal.

[0052] 5 , the participant terminal 50 includes a control unit 150, a storage unit 151, a display unit 152, an operation input unit 153, an audio input unit 154, an audio output unit 155, an imaging unit 156, a network communication unit 157, a short-range wireless communication unit 158, and a timing unit 159. The control unit 150 is configured, for example, by a CPU or the like, and controls the entire participant terminal 50. The storage unit 151 is configured, for example, by a ROM, a RAM, a HDD, an SSD, or a combination thereof, and stores programs and data used when the control unit 150 executes processing based on the programs. The control unit 150 executes processing based on the programs stored in the storage unit 151, thereby realizing the functional configuration of the participant terminal 50.

[0053] The display unit 152 is, for example, a display (such as a liquid crystal display or an organic EL display) and displays various information. The operation input unit 153 is, for example, a keyboard, a mouse, a capacitive touch panel, or the like and accepts operation inputs from participants. For example, if a smartphone is used as the participant terminal 50, the display unit 152 and the operation input unit 153 can be configured with a touch panel LCD. The audio input unit 154 is, for example, a microphone and inputs audio (for example, conversations between participants). The audio output unit 155 is, for example, a speaker and outputs audio.

[0054] The imaging unit 156 is, for example, configured with a camera (such as a CMOS camera or a CCD camera) and captures images of the surrounding environment of the participant terminal 50 (such as the faces of participants). The network communication unit 157 (network I / F (interface)) connects the participant terminal 50 to the network N and establishes communication with external devices. The short-range wireless communication unit 158 ​​establishes communication with the biometric tester 60 using short-range wireless communication technology (such as Bluetooth (registered trademark) or Wi-Fi). The timekeeping unit 159 is, for example, configured with a real-time clock and measures the current time.

[0055] The control unit 150 includes a short-range wireless communication control unit 170, a biometric information management unit 171, and a network communication control unit 172. The short-range wireless communication control unit 170 receives biometric information from the biometric tester 60 via the short-range wireless communication unit 158. The biometric information management unit 171 obtains the current time (time information) from the clock unit 159, and stores the biometric information received from the biometric tester 60 in association with the time information in the storage unit 151. The network communication control unit 172 transmits the biometric information (time-series biometric data) associated with the time information to the interaction support server 20 via the network communication unit 157.

[0056] [Biomedicine] Fig. 6 is a diagram showing the appearance of the biomedicine, and Fig. 7 is a functional block diagram of the biomedicine.

[0057] Here, an example will be described in which a wristband-type biometric tester 60 is used. As shown in Fig. 6, the biometric tester 60 is composed of a main body 61 and a band member 62. The main body 61 is attached to the band member 62, and the band member 62 is worn on the upper arm or forearm of a participant.

[0058] As shown in FIG. 7 , the biometric tester 60 includes a control unit 160, a storage unit 161, a sensor unit 162, and a short-range wireless communication unit 163. The control unit 160, the storage unit 161, the sensor unit 162, and the short-range wireless communication unit 163 are housed in a housing provided in the main body 61 of the biometric tester 60. The control unit 160 is configured, for example, by a CPU or the like, and controls the entire biometric tester 60. The storage unit 161 is configured, for example, by a ROM, a RAM, a HDD, an SSD, or a combination thereof, and stores programs and data used when the control unit 160 executes processing based on the programs. The functional configuration of the biometric tester 60 can be realized by the control unit 160 executing processing based on the programs stored in the storage unit 161.

[0059] The sensor unit 162 includes an LED light source 180 and a light receiving element 181. The LED light source 180 irradiates the detection target (living body) with light. A portion of the irradiated light is absorbed by the blood flowing through the blood vessels of the detection target, and the remainder is reflected. The light receiving element 181 is configured, for example, with a photodiode, and detects the reflected light and converts it into an electrical signal (pulse wave signal) corresponding to the intensity of the light. The short-range wireless communication unit 163 establishes communication with the participant terminal 50 using short-range wireless communication technology (Bluetooth (registered trademark), Wi-Fi, etc.).

[0060] The control unit 160 includes a heart rate measurement unit 185 and a communication control unit 186. The heart rate measurement unit 185 performs a filtering process on the generated electrical signal, detects signal peaks, and calculates the heart rate (the number of heart beats per unit time) based on the time between peaks. Here, the value (instantaneous heart rate) obtained by multiplying the reciprocal of the time interval between peak positions (positions of maximum values) by 60 (seconds) is treated as the heart rate. Furthermore, the following description will be given assuming that the heart rate and pulse rate are the same.

[0061] When communication is established between the biometric tester 60 and the participant terminal 50, the communication control unit 186 transmits information indicating the heart rate calculated by the heart rate measurement unit 185 as biometric information to the participant terminal 50. The heart rate measurement unit 185 calculates the heart rate every predetermined time (for example, at one-second intervals), and the timing at which the heart rate measurement unit 185 calculates the heart rate is synchronized with the timing at which the communication control unit 186 transmits the information indicating the heart rate.

[0062] The biological information transmitted from the biological tester 60 to the participant terminal 50 includes information according to the heart rate, information according to the pulse rate interval (PPI), various HRV (Heart Rate Variability) indices (e.g., LF / HF (Low Frequency / High Frequency), SDNN (Standard Deviation of the Normal to Normal Interval), RMSSD (Root Mean Square Successive Difference), etc.), information according to the RR interval (RRI), etc. The sensor unit 162 can be configured as a PPG (Photoplethysmography) sensor unit, but may also be configured as an ECG (Electrocardiogram) sensor unit, or may be configured by combining a PPG sensor unit and an ECG sensor unit.

[0063] Furthermore, the sensor unit 162 is not limited to the sensor (heart rate sensor) for acquiring information related to the heart rate as described above. The sensor unit 162 may be, for example, a heart rate sensor, or one or more sensors selected from the following: a sensor for acquiring information on skin conductance (e.g., electrical conductivity of the skin) (e.g., a Galvanic Skin Response (GSR) sensor incorporated in a bracelet or ring); a sensor for acquiring information on brain waves (e.g., brain wave indices such as alpha waves, beta waves, and gamma waves) (e.g., an Electroencephalography (EEG) sensor incorporated in a hat or headband); a sensor for acquiring information on electromyography (e.g., an EMG sensor incorporated in an adhesive facial gel pad); a sensor for acquiring information on breathing (e.g., breathing frequency, depth, pattern, etc.) (e.g., a breathing sensor incorporated in a chest belt, smart shirt, or earphones); and a sensor for acquiring information on body movement and posture (e.g., a motion sensor composed of an accelerometer or gyroscope incorporated in a bracelet or hat).

[0064] [Creating a new event] Fig. 8 is a flowchart showing the process for setting a new event on the administrator terminal, the process for setting a new event on the exchange support server, and the process for setting a new event on the organizer terminal. Fig. 9 is a diagram showing an example of a new event creation operation acceptance screen. Fig. 10 is a diagram showing an example of an event information management table.

[0065] The new event setting process on the administrator terminal side is a process performed on the administrator terminal 30 when a new event is set up. The new event setting process on the exchange support server side is a process performed on the exchange support server 20 when a new event is set up. The new event setting process on the organizer terminal side is a process performed on the organizer terminal 40 when a new event is set up.

[0066] In the process for setting a new event on the administrator terminal side, the control unit 130 of the administrator terminal 30 executes the processes of steps S301 to S304 shown in Fig. 8. In the process for setting a new event on the exchange support server side, the control unit 110 of the exchange support server 20 executes the processes of steps S201 to S205 shown in Fig. 8. In the process for setting a new event on the organizer terminal side, the control unit 140 of the organizer terminal 40 executes the process of step S401 shown in Fig. 8.

[0067] Specifically, in the process for setting a new event on the administrator terminal side, first, the control unit 130 of the administrator terminal 30 executes a process for accepting an operation to create a new event (step S301). In this process, the control unit 130, in response to login, causes the display unit 132 to display a screen for accepting an operation to create a new event, and determines whether a command to create a new event has been input via the operation input unit 133.

[0068] 9, the new event creation operation reception screen has an email address input area 601, an event ID input area 602, and a new event creation instruction input area 603. The email address input area 601 is an area for inputting an email address. The event ID input area 602 is an area for inputting an event ID. The new event creation instruction input area 603 is an area for displaying an image corresponding to a button containing the word "Create" (new event creation instruction button).

[0069] By operating the operation input unit 133, the administrator can input the email address of the organizer (business) in the email address input area 601. Furthermore, by operating the operation input unit 133, the administrator can input any character (alphanumeric) string as an event ID in the event ID input area 602. Furthermore, by operating the operation input unit 133, the administrator can input an instruction to select the new event creation instruction button in the new event creation instruction input area 603 (input of an instruction to create a new event). In order to input an instruction to create a new event, it is necessary to input an email address, but it is not essential to input an event ID.

[0070] If it is determined in step S301 that a command to create a new event has been input, the control unit 130 of the administrator terminal 30 transmits new event creation information to the exchange support server 20 via the communication unit 134 (step S302). The new event creation information includes at least information input by the administrator, such as information indicating the organizer's email address (email address information), and, if the administrator inputs an event ID, information indicating the event ID (event ID information). The new event creation information may also include information indicating the organizer's name (organizer name information).

[0071] In the exchange support server-side new event setting process, the control unit 110 of the exchange support server 20 receives new event creation information transmitted from the administrator terminal 30 via the communication unit 112 (step S201). Next, the control unit 110 of the exchange support server 20 generates an authentication code (step S202). The authentication code is a character (alphanumeric) string required for logging in to the organizer terminal 40. The control unit 110 of the exchange support server 20 then stores the information included in the new event creation information in the event information management table in the storage unit 111 (step S203).

[0072] The event information management table shown in Figure 10 is configured to be able to store information indicating the "organizer name" (organizer name information), information indicating the "email address" of the organizer (email address information), information indicating the "event ID" (event ID information), information indicating the "authentication code" (authentication code information), information indicating the "ranking display number" (ranking display number information), information indicating the "status" of the event ("before event starts", "event in progress", "event ends, results being analyzed", "event ends, results analysis completed", etc.) (status information), information indicating the names of the "participants" in the event (participant name information), and information indicating the "ranking results" (ranking result information).

[0073] The organizer name information, email address information, and event ID information can be received from the administrator terminal 30 in step S201. If the event ID information is not included in the information for creating a new event, the control unit 110 generates a random character (alphanumeric) string as the event ID. The authentication code information is information indicating the character (alphanumeric) string generated by the control unit 110 in step S202. The status information corresponds to the progress of the event and is updated as the event progresses. In step S203, information indicating "before the event starts" is stored as the status information. The participant name information, ranking display number information, and ranking result information will be described in detail later.

[0074] After executing the process of step S203, the control unit 110 of the exchange support server 20 transmits the event list information to the administrator terminal 30 via the communication unit 112 (step S204). The event list information is information for displaying a list of the contents of currently set events, and includes, for example, email address information, event ID information, status information, etc., from the information stored in the event information management table.

[0075] In the administrator terminal-side new event setting process, the control unit 130 of the administrator terminal 30 receives the event list information transmitted from the social networking support server 20 via the communication unit 134 (step S303). The control unit 130 of the administrator terminal 30 then displays an event list screen on the display unit 132 (step S304). The event list screen includes the organizer's "email address," "event ID," and "event status," allowing the administrator to grasp the overall picture of the currently set events. After executing the process of step S304, the control unit 130 of the administrator terminal 30 terminates the administrator terminal-side new event setting process.

[0076] In the exchange support server-side new event setting process, after executing the process of step S204, the control unit 110 of the exchange support server 20 generates an event information email as an email and sends the generated event information email to the organizer terminal 40 via the communication unit 112 (step S205). Thereafter, the control unit 110 of the exchange support server 20 ends the exchange support server-side new event setting process.

[0077] In the host terminal-side new event setting process, the control unit 140 of the host terminal 40 receives an event information email sent from the social networking support server 20 via the communication unit 144 (step S401). The event information email includes an "event ID" and an "authentication code," and the event information email allows the host to know the event ID and authentication code of the event they are hosting. After executing the process of step S401, the control unit 140 of the host terminal 40 ends the host terminal-side new event setting process.

[0078] [Event Start] Fig. 11 is a flowchart showing the event start process on the organizer terminal side and the event start process on the exchange support server side. Fig. 12 is a diagram showing an example of an authentication operation reception screen. Fig. 13 is a diagram showing an example of an original setting operation reception screen. Fig. 14 is a diagram showing an example of an event start operation reception screen.

[0079] The event start processing on the organizer terminal side is processing that is performed on the organizer terminal 40 when an event starts. The event start processing on the exchange support server side is processing that is performed on the exchange support server 20 when an event starts.

[0080] In the event start processing on the organizer terminal side, the control unit 140 of the organizer terminal 40 executes the processing of steps S421 to S428 shown in Fig. 11. In the event start processing on the exchange support server side, the control unit 110 of the exchange support server 20 executes the processing of steps S221 to S227 shown in Fig. 11.

[0081] Specifically, in the event start process on the organizer terminal side, first, the control unit 140 of the organizer terminal 40 executes an authentication operation reception process (step S421). In this process, the control unit 140 displays an authentication operation reception screen on the display unit 142 and determines whether an authentication instruction has been input via the operation input unit 143.

[0082] 12, the authentication operation reception screen has an email address input area 621, an event ID input area 622, an authentication code input area 623, and an authentication instruction input area 624. The email address input area 621 is an area for inputting an email address. The event ID input area 622 is an area for inputting an event ID. The authentication code input area 623 is an area for inputting an authentication code. The authentication instruction input area 624 is an area for displaying an image corresponding to a button containing the word "authenticate" (authentication instruction button).

[0083] The organizer can input his / her own email address in the email address input area 621 by operating the operation input unit 143. Furthermore, while referring to the event information email, the organizer can input an event ID and an authentication code in the event ID input area 622 and the authentication code input area 623, respectively, by operating the operation input unit 143. Furthermore, the organizer can input an instruction to select the authentication instruction button in the authentication instruction input area 624 (authentication instruction input) by operating the operation input unit 143.

[0084] If it is determined in step S421 that an authentication instruction has been input, the control unit 140 of the organizer terminal 40 transmits authentication information to the exchange support server 20 via the communication unit 144 (step S422). The authentication information includes information input by the organizer, such as information indicating an email address (email address information), information indicating an event ID (event ID information), and information indicating an authentication code (authentication code information).

[0085] In the exchange support server-side event start processing, the control unit 110 of the exchange support server 20 receives authentication information transmitted from the organizer terminal 40 via the communication unit 112 (step S221). Next, the control unit 110 of the exchange support server 20 executes authentication processing (step S222). In this processing, the control unit 110 performs authentication by determining whether the email address information, event ID information, and authentication code information contained in the authentication information match the email address information, event ID information, and authentication code information stored in the event information management table, respectively. The control unit 110 of the exchange support server 20 then transmits authentication result information to the organizer terminal 40 via the communication unit 112 (step S223). The authentication result information includes information indicating whether the authentication result was successful or unsuccessful.

[0086] In the event start process on the organizer terminal side, the control unit 140 of the organizer terminal 40 receives authentication result information transmitted from the exchange support server 20 via the communication unit 144 (step S423). If the authentication result is successful, the control unit 140 of the organizer terminal 40 executes a unique setting operation reception process (step S424). In this process, the control unit 140 displays a unique setting operation reception screen on the display unit 142 and determines whether a unique setting instruction has been input via the operation input unit 143. If the authentication result is unsuccessful, the control unit 140 displays on the display unit 142 that the content entered on the authentication operation reception screen is incorrect.

[0087] 13 , the unique setting operation reception screen has a ranking display setting input area 641 and a unique setting instruction input area 642. The ranking display setting input area 641 is an area for inputting a number related to the ranking display setting (number of rankings to display). The unique setting instruction input area 642 is an area for displaying an image corresponding to a button containing the word “Next” (unique setting instruction button).

[0088] The organizer can input any number as the ranking display number in the ranking display setting input area 641 by operating the operation input unit 143. In addition, the organizer can input an instruction to select the unique setting instruction button (input of a unique setting instruction) in the unique setting instruction input area 642 by operating the operation input unit 143. Note that input of a ranking display number is not essential for input of a unique setting instruction.

[0089] In this embodiment, after a participant has a conversation with multiple participants at an event, a screen display can be performed on the participant terminal 50 according to the degree of matching between the participant and each of the conversation partners. In this case, the organizer can set how many of the highest matching degrees between the participant and each of the conversation partners will be displayed on the screen. The ranking display number is a value that specifies the number of conversation partners for which such a screen display will be performed. In the example shown in FIG. 13, "5" is entered as the ranking display number. As a result, the top five conversation partners with the highest matching degrees will be displayed on the screen.

[0090] If it is determined in step S424 that a unique setting instruction has been input, the control unit 140 of the organizer terminal 40 transmits the unique setting information to the interaction support server 20 via the communication unit 144 (step S425). The unique setting information includes information indicating the ranking display number (ranking display number information) as information input by the organizer.

[0091] In the exchange support server-side event start processing, the control unit 110 of the exchange support server 20 receives the unique setting information transmitted from the organizer terminal 40 via the communication unit 112 (step S224). Next, the control unit 110 of the exchange support server 20 updates the information stored in the event information management table (step S225). In this processing, the control unit 110 stores the ranking display number information included in the unique setting information received from the organizer terminal 40 as information indicating the "ranking display number" in the event information management table. Note that if the unique setting information does not include ranking display number information (i.e., the organizer did not set the ranking display number), the control unit 110 stores information indicating a default value (e.g., 3) as the ranking display number information in the event information management table.

[0092] In the event start processing on the organizer terminal side, after executing the processing of step S425, the control unit 140 of the organizer terminal 40 executes an event start operation acceptance processing (step S426). In this processing, the control unit 140 displays an event start operation acceptance screen on the display unit 142 and determines whether an event start instruction has been input via the operation input unit 143.

[0093] 14, the event start operation reception screen has an event start instruction input area 661, an event end instruction input area 662, and an event result display instruction input area 663. The event start instruction input area 661 is an area where an image corresponding to a button (event start instruction button) containing the characters "Start matching event." The event end instruction input area 662 is an area where an image corresponding to a button (event end instruction button) containing the characters "End matching event." The event result display instruction input area 663 is an area where an image corresponding to a button (event result display instruction button) containing the characters "Go to results."

[0094] When the event start operation reception screen is displayed, the organizer can operate the operation input unit 143 to input an input indicating that the event start instruction button is selected in the event start instruction input area 661 (event start instruction input). Meanwhile, at this time, the organizer cannot input an input indicating that the event end instruction button is selected (event end instruction input) or an input indicating that the event result display instruction button is selected (event result display instruction input). In FIG. 14 , the outer edge of the event start instruction input area 661 is displayed with a solid line, suggesting that the operation of the event start instruction button is valid. Meanwhile, the outer edges of the event end instruction input area 662 and the event result display instruction input area 663 are displayed with dotted lines, suggesting that the operations of the event end instruction button or the event result display instruction button are invalid.

[0095] If it is determined in step S426 that an event start instruction has been input, the control unit 140 of the organizer terminal 40 transmits event start information to the exchange support server 20 via the communication unit 144 (step S427). The event start information includes information for requesting the exchange support server 20 to perform a series of processes required to hold the event. The control unit 140 of the organizer terminal 40 then sets an event in progress flag to on (step S428). The event in progress flag indicates that the event is currently being held. Thereafter, the control unit 140 of the organizer terminal 40 terminates the organizer terminal-side event start processing.

[0096] In the exchange support server-side event start processing, the control unit 110 of the exchange support server 20 receives event start information transmitted from the organizer terminal 40 via the communication unit 112 (step S226). The control unit 110 of the exchange support server 20 then updates the status information (step S227). In this processing, the control unit 110 stores information indicating "event in progress" as status information in the event information management table. The control unit 110 of the exchange support server 20 then terminates the exchange support server-side event start processing.

[0097] [Start of conversation] Fig. 15 is a flowchart showing conversation start processing on the participant terminal side and conversation start processing on the exchange support server side. Fig. 16 is a diagram showing an example of a conversation preparation operation acceptance screen. Fig. 17 is a diagram showing an example of a storage area specification table. Fig. 18 is a diagram showing an example of a biometric tester connection operation acceptance screen. Fig. 19 is a diagram showing an example of a conversation partner name input operation acceptance screen. Fig. 20 is a diagram showing an example of a conversation start operation acceptance screen.

[0098] The participant terminal-side conversation start processing is processing performed on the participant terminals 50 (participant terminal 50 of participant A and participant terminal 50 of participant B) when a conversation between one participant (participant A) and another participant (participant B) starts. The exchange support server-side conversation start processing is processing performed on the exchange support server 20 when a conversation between one participant (participant A) and another participant (participant B) starts.

[0099] In the conversation start process on the participant terminal side, the control unit 150 of the participant terminal 50 executes the processes of steps S501 to S510 shown in Fig. 15. In the conversation start process on the exchange support server side, the control unit 110 of the exchange support server 20 executes the processes of steps S241 to S245 shown in Fig. 15.

[0100] Specifically, in the participant terminal-side conversation start process, first, the control unit 150 of the participant terminal 50 executes a conversation preparation operation acceptance process (step S501). In this process, the control unit 150 displays a conversation preparation operation acceptance screen on the display unit 152 and determines whether a conversation preparation instruction has been input via the operation input unit 153.

[0101] 16 , the conversation preparation operation reception screen has an event ID input area 681, a participant name input area 682, and a conversation preparation instruction input area 683. The event ID input area 681 is an area for inputting an event ID. The participant name input area 682 is an area for inputting the name of the participant (yourself). The conversation preparation instruction input area 683 is an area for displaying an image corresponding to a button (conversation preparation instruction button) containing the word "Next."

[0102] By operating the operation input unit 153, a participant can input the event ID notified in advance by the organizer in an event ID input area 681. Furthermore, by operating the operation input unit 153, a participant can input their own name in a participant name input area 682. Furthermore, by operating the operation input unit 153, a participant can make an input to select the conversation preparation instruction button in a conversation preparation instruction input area 683 (conversation preparation instruction input).

[0103] If it is determined in step S501 that a conversation preparation instruction has been input, the control unit 150 of the participant terminal 50 transmits conversation preparation information to the exchange support server 20 via the network communication unit 157 (step S502). The conversation preparation information includes, as information input by the participant, information indicating the event ID (event ID information) and information indicating the participant's own name (participant name information), as well as information (identification information) indicating the storage medium identifier of the participant terminal 50 (e.g., app ID, device ID, serial number, MAC address, telephone number, etc.).

[0104] In the exchange support server-side conversation start process, the control unit 110 of the exchange support server 20 receives conversation preparation information transmitted from the participant terminal 50 via the communication unit 112 (step S241). Next, the control unit 110 of the exchange support server 20 executes a determination process (step S242). In this process, the control unit 110 performs authentication by determining whether the event ID information included in the conversation preparation information matches any of the event ID information stored in the event information management table. If it is determined that the event ID information included in the conversation preparation information matches any of the event ID information stored in the event information management table, the control unit 110 stores the participant name information included in the conversation preparation information in association with the identification information of the participant terminal 50 that transmitted the conversation preparation information as information indicating the name of the “participant” of the event corresponding to the event ID information in the event information management table.

[0105] The control unit 110 also stores the participant name information in a storage area designation table in the storage unit 111. In the storage area designation table shown in FIG. 17 , information indicating the names of the "participants" (participant name information) is stored in the left column, and information indicating the names of the "participants" (participant name information) is also stored in the upper row. When conversation preparation information is received from the participant terminal 50, if the Mth participant name information is stored from the top in the left column and the Mth participant name information is stored from the left in the upper row, the control unit 110 stores the participant name information included in the conversation preparation information in the (M+1)th position from the top in the left column and the (M+1)th position from the left in the upper row. As a result, the participant name information in the left column (ordered from top to bottom) and the participant name information in the upper row (ordered from left to right) match. Figure 17 shows an example in which conversation preparation information (participant name information) is first received from the participant terminal 50 of "Donald," then conversation preparation information (participant name information) is received from the participant terminal 50 of "Olivia," then conversation preparation information (participant name information) is received from the participant terminal 50 of "Kathy," then conversation preparation information (participant name information) is received from the participant terminal 50 of "Lisette," and then conversation preparation information (participant name information) is received from the participant terminal 50 of "Mark."

[0106] Furthermore, in the storage area designation table, information (storage area designation information) for designating a storage area is defined in association with the participant name information in the left column and the participant name information in the row above. The storage area designation information is information indicating the top address of one of the storage areas provided in the storage unit 111. For example, in FIG. 17 , the storage area designation information of "Area 1-1" is defined for the participant name information indicating "Donald" in the left column and the participant name information indicating "Olivia" in the row above, and the storage area designation information of "Area 2-1" is defined for the participant name information indicating "Olivia" in the left column and the participant name information indicating "Donald" in the row above.

[0107] After executing the process of step S242, the control unit 110 of the exchange support server 20 transmits determination result information to the participant terminal 50 via the communication unit 112 (step S243). The determination result information includes authentication result information, which includes information indicating whether the authentication result is successful or unsuccessful. Furthermore, if the information indicating the names of the "participants" of the event corresponding to the event ID information included in the conversation preparation information includes participant name information that is the same as the participant name information included in the conversation preparation information, and the identification information of the participant terminals 50 associated with these participant name information are different from each other, the determination result information includes name duplication information.

[0108] In the participant terminal-side conversation start process, the control unit 150 of the participant terminal 50 receives the determination result information transmitted from the communication support server 20 via the network communication unit 157 (step S503). If the authentication result is successful and no name duplication information is received, the control unit 150 of the participant terminal 50 executes a biometric device connection operation reception process (step S504). In this process, the control unit 150 displays a biometric device connection operation reception screen on the display unit 152 and determines whether a biometric device connection completion instruction has been input via the operation input unit 153. If the authentication result is unsuccessful, the control unit 150 displays on the display unit 152 that the event ID entered on the conversation preparation operation reception screen is incorrect. If name duplication information is received, the control unit 150 displays on the display unit 152 that a participant with the same name has already been registered and that a different name must be entered again.

[0109] 18 , the operation reception screen for connecting a biometric device has a biometric device ID input area 701, a biometric device connection preparation input area 702, and a biometric device connection completion instruction input area 703. The biometric device ID input area 701 is an area for inputting a biometric device ID. The biometric device connection preparation input area 702 is an area where an image corresponding to a toggle button is displayed. The biometric device connection completion instruction input area 703 is an area where an image corresponding to a button containing the word "Next" (biometric device connection completion instruction button) is displayed.

[0110] A participant can input a biometric tester ID in a biometric tester ID input area 701 by operating the operation input unit 153. The biometric tester ID is an ID uniquely assigned to each biometric tester 60 and is printed, for example, on the side of the housing of the biometric tester 60. Furthermore, a participant can operate the operation input unit 153 to input an input to turn on a toggle button in a biometric tester connection preparation input area 702. When the toggle button is turned on, a pop-up display for selecting a biometric tester 60 to be connected appears, and the participant can operate the operation input unit 153 to input an input to select one of the biometric testers 60 to be connected. Thereafter, the participant can operate the operation input unit 153 to input an input to select the biometric tester connection completion instruction button in a biometric tester connection completion instruction input area 703 (biometric tester connection completion instruction input).

[0111] If it is determined in step S504 that a biometric device connection completion instruction has been input, the control unit 150 of the participant terminal 50 transmits information for requesting connection to the biometric device 60 selected as the connection target via the short-range wireless communication unit 158 ​​(step S505). When short-range wireless communication (Bluetooth (registered trademark), Wi-Fi, etc.) is established with the biometric device 60, the control unit 150 of the participant terminal 50 sets a connection in progress flag to on (step S506). The connection in progress flag is a flag indicating that short-range wireless communication has been established between the participant terminal 50 and the biometric device 60.

[0112] Next, the control unit 150 of the participant terminal 50 executes a conversation partner name input operation reception process (step S507). In this process, the control unit 150 displays a conversation partner name input operation reception screen on the display unit 152 and determines whether a conversation partner name specification instruction has been input via the operation input unit 153.

[0113] 19 , the conversation partner name input operation reception screen has a conversation partner name input area 721, a conversation start instruction input area 722, a conversation end instruction input area 723, and a matching result display instruction input area 724. The conversation partner name input area 721 is an area for inputting the name of the conversation partner (partner). The conversation start instruction input area 722 is an area for displaying an image corresponding to a button containing the characters "start conversation" (conversation start instruction button). The conversation end instruction input area 723 is an area for displaying an image corresponding to a button containing the characters "end conversation" (conversation end instruction button). The matching result display instruction input area 724 is an area for displaying an image corresponding to a button containing the characters "result screen" (matching result display instruction button).

[0114] When the conversation partner name input operation reception screen is displayed, a participant can operate the operation input unit 153 to input an instruction to specify the name of a conversation partner in the conversation partner name input area 721 (input of an instruction to specify a conversation partner name). Meanwhile, at this time, the participant cannot input an instruction to select the conversation start instruction button (input of an instruction to start a conversation), an instruction to select the conversation end instruction button (input of an instruction to end a conversation), or an instruction to select the matching result display instruction button (input of an instruction to display a matching result). In FIG. 19 , the outer edge of the conversation partner name input area 721 is displayed with a solid line, indicating that the operation to enter the name of the conversation partner is valid. Meanwhile, the outer edges of the conversation start instruction input area 722, the conversation end instruction input area 723, and the matching result display instruction input area 724 are displayed with dotted lines, indicating that the operations on the conversation start instruction button, the conversation end instruction button, or the matching result display instruction button are invalid. In addition, the system may be configured so that participant name information is received from the communication support server 20, and the names of participants who could be conversation partners are displayed in a pull-down menu in the conversation partner name input area 721, and a conversation partner name specification instruction can be input by selecting the name of one conversation partner.

[0115] 19 , the conversation partner name input operation reception screen includes a heart rate image 725 and a heart image 726. The heart rate image 725 is an image indicating the current heart rate, and the heart image 726 is a heart-shaped image (representing a heart). When the conversation partner name input operation reception screen is displayed, communication is established between the participant terminal 50 and the biometric tester 60, and information indicating the current heart rate is transmitted as biometric information from the biometric tester 60 to the participant terminal 50 every time a predetermined time elapses (e.g., every one second). Each time the control unit 150 of the participant terminal 50 receives information indicating the latest heart rate ("69 bpm" in the example shown in FIG. 19 ), it reflects the information in the heart rate image 725 and displays the heart beating in a manner (e.g., size and speed) corresponding to the heart rate as the heart image 726.

[0116] If it is determined in step S507 that a conversation partner name specifying instruction has been input, the control unit 150 of the participant terminal 50 transmits conversation partner information to the exchange support server 20 via the network communication unit 157 (step S508). The conversation partner information includes information input by the participant indicating the name of the conversation partner (conversation partner name information), as well as identification information of the participant terminal 50.

[0117] In the exchange support server-side conversation start processing, the control unit 110 of the exchange support server 20 receives conversation partner information transmitted from the participant terminal 50 via the communication unit 112 (step S244). The control unit 110 of the exchange support server 20 then stores partner combination information in the storage unit 111 (step S245). The partner combination information is information for identifying a conversation partner (partner) of a participant. The partner combination information associates participant name information received from a participant terminal 50 in step S241, conversation partner name information received from that participant terminal 50 in step S244, and identification information of that participant terminal 50. By referencing the partner combination information, the control unit 110 can determine, for each participant terminal 50, who the conversation partner of the participant who owns that participant terminal 50 is. After executing the processing of step S245, the control unit 110 of the exchange support server 20 terminates the exchange support server-side conversation start processing.

[0118] In the participant terminal side conversation start processing, after executing the processing of step S508, the control unit 150 of the participant terminal 50 executes a conversation start operation acceptance processing (step S509). In this processing, the control unit 150 displays a conversation start operation acceptance screen on the display unit 152 and determines whether a conversation start instruction has been input via the operation input unit 153.

[0119] 20 , the conversation start operation acceptance screen has a conversation partner name input area 721, a conversation start instruction input area 722, a conversation end instruction input area 723, and a matching result display instruction input area 724. Most of the display content of the conversation start operation acceptance screen is the same as the display content of the conversation partner name input operation acceptance screen, but the operations that can be input when the conversation partner name input operation acceptance screen is displayed differ from those when the conversation start operation acceptance screen is displayed.

[0120] Specifically, when the conversation start operation reception screen is displayed, the participant can input an instruction to select the conversation start instruction button (conversation start instruction input) in the conversation start instruction input area 722. However, at this time, the participant cannot input an instruction to specify the name of the conversation partner (conversation partner name identification instruction input), an instruction to select the conversation end instruction button (conversation end instruction input), or an instruction to select the matching result display instruction button (matching result display instruction input). In FIG. 20 , the outer edge of the conversation start instruction input area 722 is displayed with a solid line, indicating that the operation to input the conversation start instruction is valid. On the other hand, the outer edges of the conversation partner name input area 721, the conversation end instruction input area 723, and the matching result display instruction input area 724 are displayed with dotted lines, indicating that the operation in these areas is invalid. Note that the conversation start operation reception screen, like the conversation partner name input operation reception screen, includes a heart rate image 725 and a heart image 726. The heart rate image 725 and the heart image 726 have been described above, and therefore will not be described here.

[0121] If it is determined in step S509 that a conversation start instruction has been input, the control unit 150 of the participant terminal 50 sets a conversation start flag to ON (step S510). The conversation start flag is a flag indicating that a conversation start instruction has been input in the participant terminal 50. After executing the process of step S510, the control unit 150 of the participant terminal 50 ends the participant terminal-side conversation start process.

[0122] Thus, when a conversation between one participant (Participant A) and another participant (Participant B) begins in an event, participant terminal-side conversation start processing (processing of steps S501 to S510) is performed in the participant terminal 50 (participant A's participant terminal 50 and participant B's participant terminal 50), and exchange support server-side conversation start processing (processing of steps S241 to S245) is performed in the exchange support server 20. Here, the processing of steps S501 to S506 and the processing of steps S241 to S243 may be performed only when Participant B (Participant A) is Participant A's (Participant B's) first conversation partner in the event. In other words, when a participant sequentially converses with multiple participants in an event, the processing of steps S501 to S506 and the processing of steps S241 to S243 can be configured to be performed only when the participant converses with the first conversation partner, and to be omitted when the participant converses with the second or subsequent conversation partners. In this case, when a command to start a conversation is input, information for requesting reconnection may be transmitted to the biometric tester 60 selected as the connection target in step S504.

[0123] In the above description, the participant name information in the event information management table and the storage area designation table is updated based on the participant name information received from the participant terminal 50. However, the process for providing the participant name information to the exchange support server 20 is not limited to this example. For example, the participant name information in the event information management table and the storage area designation table may be updated based on the participant name information received from the organizer terminal 40. For example, the organizer may be configured to be able to input the names of all participants before the event start operation acceptance screen is displayed (for example, on the custom setting operation acceptance screen).

[0124] [Time-series biometric data] Fig. 21 is a flowchart showing a biometric information management process performed at a predetermined timing in a participant terminal. Fig. 22 is a diagram schematically showing an example of time-series biometric data stored in a participant terminal.

[0125] In the biometric information management process, first, the control unit 150 of the participant terminal 50 determines whether the connection in progress flag (see step S506 in FIG. 15) is set to on (step S521). If it is determined that the connection in progress flag is not set to on, the control unit 150 of the participant terminal 50 ends the biometric information management process.

[0126] On the other hand, if it is determined that the connection in progress flag is set to ON, the control unit 150 of the participant terminal 50 determines whether it is time to receive biometric information (step S522). In this process, the control unit 150 determines that it is time to receive biometric information when a predetermined time (e.g., one second) has passed since the previous reception of biometric information. If it is determined that it is not time to receive biometric information, the control unit 150 of the participant terminal 50 ends the biometric information management process.

[0127] On the other hand, if it is determined that it is time to receive biometric information, the control unit 150 of the participant terminal 50 receives the biometric information transmitted from the biometric tester 60 via the short-range wireless communication unit 158 ​​(step S523). Next, the control unit 150 of the participant terminal 50 converts the received biometric information into a decimal number (step S524). Next, the control unit 150 of the participant terminal 50 acquires the current time (time information) from the clock unit 159 (step S525). The time information is measured to the order of 1 / 1000 of a second and includes information on the year, month, day, hour, minute, second, and millisecond. Next, the control unit 150 of the participant terminal 50 associates the biometric information converted in step S524 with the time information acquired in step S525 and stores them in the memory unit 151 (step S526).

[0128] In the storage unit 151, each time biometric information (e.g., information indicating a heart rate) is received from the biometric tester 60, the biometric information associated with time information is sequentially stored. When multiple pieces of biometric information associated with time information are stored, the collection of the multiple pieces of biometric information is referred to as time-series biometric data. Figure 22 shows an example of time-series biometric data stored in the storage unit 151 of Donald's participant terminal 50 and the storage unit 151 of Olivia's participant terminal 50 in a situation where Donald and Olivia are having a conversation.

[0129] In this example, the time-series biometric data stored in the memory unit 151 of Donald's participant terminal 50 is composed of biometric information associated with the time "12:00:00.111" (heart rate: 72), biometric information associated with the time "12:00:01.111" (heart rate: 73), biometric information associated with the time "12:00:02.111" (heart rate: 73), biometric information associated with the time "12:00:03.111" (heart rate: 72), etc. Furthermore, the time-series biometric data stored in the memory unit 151 of Olivia's participant terminal 50 is composed of biometric information associated with the time "12:00:00.777" (heart rate: 62), biometric information associated with the time "12:00:01.777" (heart rate: 63), biometric information associated with the time "12:00:02.777" (heart rate: 63), biometric information associated with the time "12:00:03.777" (heart rate: 63), etc. Note that date information is omitted in Figure 22, and only hour, minute, second, and millisecond information is shown.

[0130] Here, the biometric information constituting the time-series biometric data will be referred to as the first biometric information, second biometric information, third biometric information, fourth biometric information, etc. in order of oldest to newest time associated with the biometric information. In this case, for both the time-series biometric data stored in the storage unit 151 of Donald's participant terminal 50 and the time-series biometric data stored in the storage unit 151 of Olivia's participant terminal 50, the time associated with the (N+1)th biometric information constituting the time-series biometric data is one second after the time associated with the Nth biometric information. In other words, in the example shown in Fig. 22, the biometric information is stored in the storage unit 151 of the participant terminal 50 sequentially every second.

[0131] Furthermore, the last three digits (values ​​less than one second) of the time associated with each piece of biometric information constituting the time-series biometric data stored in the storage unit 151 of Donald's participant terminal 50 are 111 milliseconds, whereas the last three digits (values ​​less than one second) of the time associated with each piece of biometric information constituting the time-series biometric data stored in the storage unit 151 of Olivia's participant terminal 50 are 777 milliseconds. Thus, there is an error of less than one second between the time associated with each piece of biometric information constituting the time-series biometric data stored in the storage unit 151 of Donald's participant terminal 50 and the time associated with each piece of biometric information constituting the time-series biometric data stored in the storage unit 151 of Olivia's participant terminal 50.

[0132] After executing the process of step S526, the control unit 150 of the participant terminal 50 determines whether the conversation start flag (see step S510 in FIG. 15) is set to on (step S527). If it is determined that the conversation start flag is not set to on, the control unit 150 of the participant terminal 50 ends the biometric information management process.

[0133] On the other hand, if it is determined that the conversation start flag is set to ON, the control unit 150 of the participant terminal 50 clears the biometric information (time-series biometric data) stored in the storage unit 151 (step S528). Then, the control unit 150 of the participant terminal 50 sets the conversation start flag to OFF (step S529) and sets the conversation in progress flag to ON (step S530). Thereafter, the control unit 150 of the participant terminal 50 ends the biometric information management process.

[0134] As a result, the biometric information (time-series biometric data) stored in the storage unit 151 of the participant terminal 50 from the time the connection flag is set to on (from the time short-range wireless communication is established between the participant terminal 50 and the biometric tester 60) until the conversation start flag is set to on (from the time a conversation start instruction is input at the participant terminal 50) is erased, and then storage of the biometric information (time-series biometric data) begins anew. The conversation in progress flag is a flag indicating that biometric information (time-series biometric data) has been sequentially stored since the conversation start instruction was input. By using such a conversation in progress flag, each time a conversation with a new conversation partner is started, it is possible to appropriately accumulate the time-series biometric data (used as an analysis target) during the period in which the conversation with the conversation partner is being conducted.

[0135] [End of conversation] Fig. 23 is a flowchart showing the conversation end process on the participant terminal side and the conversation end process on the interaction support server side. Fig. 24 is a diagram showing an example of a conversation end operation acceptance screen. Fig. 25 is a diagram showing a schematic configuration of a conversation result storage area. Fig. 26 is a diagram showing a schematic example of time-series biometric data stored in the interaction support server.

[0136] The participant terminal-side conversation end processing is processing performed on the participant terminals 50 (participant terminal 50 of participant A and participant terminal 50 of participant B) when a conversation between one participant (participant A) and another participant (participant B) ends. The exchange support server-side conversation end processing is processing performed on the exchange support server 20 when a conversation between one participant (participant A) and another participant (participant B) ends.

[0137] In the participant terminal-side conversation end process, the control unit 150 of the participant terminal 50 executes the processes of steps S541 to S544 shown in Fig. 23. In the exchange support server-side conversation end process, the control unit 110 of the exchange support server 20 executes the processes of steps S261 to S264 shown in Fig. 23.

[0138] Specifically, in the participant terminal-side conversation end process, first, the control unit 150 of the participant terminal 50 determines whether the conversation in progress flag (see step S530 in FIG. 21) is set to on (step S541). If it is determined that the conversation in progress flag is not set to on, the control unit 150 of the participant terminal 50 ends the participant terminal-side conversation end process.

[0139] On the other hand, if it is determined that the conversation in progress flag is set to ON, the control unit 150 of the participant terminal 50 executes a conversation end operation acceptance process (step S542). In this process, the control unit 150 displays a conversation end operation acceptance screen on the display unit 152 and determines whether a conversation end instruction has been input via the operation input unit 153.

[0140] 24, the conversation end operation acceptance screen has a conversation partner name input area 721, a conversation start instruction input area 722, a conversation end instruction input area 723, and a matching result display instruction input area 724. Most of the display content of the conversation end operation acceptance screen is the same as the display content of the conversation partner name input operation acceptance screen, but the operations that can be input when the conversation partner name input operation acceptance screen is displayed differ from those when the conversation end operation acceptance screen is displayed.

[0141] Specifically, when the conversation end operation reception screen is displayed, the participant can input an instruction to select the conversation end instruction button (conversation end instruction input) in the conversation end instruction input area 723. However, at this time, the participant cannot input an instruction to specify the name of the conversation partner (conversation partner name identification instruction input), an instruction to select the conversation start instruction button (conversation start instruction input), or an instruction to select the matching result display instruction button (matching result display instruction input). In FIG. 24 , the outer edge of the conversation end instruction input area 723 is displayed with a solid line, indicating that the operation to input the conversation end instruction is valid. On the other hand, the outer edges of the conversation partner name input area 721, the conversation start instruction input area 722, and the matching result display instruction input area 724 are displayed with dotted lines, indicating that the operation in these areas is invalid. Note that the conversation end operation reception screen, like the conversation partner name input operation reception screen, includes a heart rate image 725 and a heart image 726. The heart rate image 725 and the heart image 726 have been described above, and therefore will not be described here.

[0142] If it is determined in step S542 that a conversation end instruction has been input, the control unit 150 of the participant terminal 50 transmits the biometric information (time-series biometric data) stored in the storage unit 151 together with conversation end information to the exchange support server 20 via the network communication unit 157 (step S543). The conversation end information includes information indicating that a conversation end instruction has been input, as well as identification information of the participant terminal 50. After executing the processing of step S543, the control unit 150 of the participant terminal 50 sets the conversation in progress flag to off (step S544) and terminates the participant terminal-side conversation end processing.

[0143] In the exchange support server-side conversation end process, the control unit 110 of the exchange support server 20 receives conversation end information and biometric information (time-series biometric data) transmitted from the participant terminal 50 via the communication unit 112 (step S261). The control unit 110 then stores the received biometric information (time-series biometric data) in the storage unit 111 according to the partner combination information (see step S245 in FIG. 15 ) (step S262). In this process, the control unit 110 refers to the storage area designation table (see FIG. 17 ) to identify one of multiple storage areas provided in the storage unit 111 as a storage area (conversation result storage area) for storing the received biometric information (time-series biometric data), and stores the time-series biometric data in the identified conversation result storage area.

[0144] Specifically, the control unit 110 identifies a conversation result storage area and stores the time-series biometric data by the following steps (i) to (vi): (i) By referencing the partner combination information, it identifies participant name information associated with the identification information of the participant terminal 50 included in the conversation end information received in step S261 (which participant the time-series biometric data received in step S261 belongs to). (ii) By referencing the partner combination information, it identifies conversation partner name information associated with the participant name information identified in (i) above (with whom the time-series biometric data was obtained). (iii) From the participant name information in the left column of the storage area designation table, it identifies participant name information that matches the participant name information identified in (i) above (the number of participants stored from the top). (iv) From the participant name information in the upper row of the storage area designation table, it identifies participant name information that matches the conversation partner name information identified in (ii) above (the number of participants stored from the left). (v) In the storage area designation table, the storage area designation information defined in association with the participant name information identified in (iii) above and the participant name information identified in (iv) above is identified. (vi) The time-series biometric data received in step S261 is stored in the storage area (conversation result storage area) designated by the storage area designation information identified in (v) above.

[0145] 17, the conversation result storage areas include "area 1-1," "area 1-2," "area 1-3," "area 1-4," ..., "area 2-1," "area 2-2," "area 2-3," "area 2-4," .... As shown in FIG. 25, the conversation result storage area includes an area for storing time-series biometric data (time-series biometric data storage area), an area for storing information corresponding to the synchrony analysis process (see FIG. 27) (matching degree storage area), and an area for storing information corresponding to the questionnaire result (questionnaire result storage area). The time-series biometric data received in step S261 is stored in the time-series biometric data storage area.

[0146] 26 shows an example in which, after a conversation between Donald and Olivia has ended, time-series biometric data is received from Donald's participant terminal 50 and also from Olivia's participant terminal 50. The time-series biometric data received from Donald's participant terminal 50 is stored in the time-series biometric data storage area of ​​"Area 1-1" (conversation result storage area) through the above steps (i) to (vi). On the other hand, the time-series biometric data received from Olivia's participant terminal 50 is stored in the time-series biometric data storage area of ​​"Area 2-1" (conversation result storage area) through the above steps (i) to (vi).

[0147] Here, the time-series biometric data received from Donald's participant terminal 50 is composed of biometric information associated with the time "12:00:00.111" (heart rate: 72), biometric information associated with the time "12:00:01.111" (heart rate: 73), biometric information associated with the time "12:00:02.111" (heart rate: 73), biometric information associated with the time "12:00:03.111" (heart rate: 72), etc., while Olivier The time series biometric data received from participant terminal 50 a is shown as being composed of biometric information associated with the time "12:00:00.777" (heart rate: 62), biometric information associated with the time "12:00:01.777" (heart rate: 63), biometric information associated with the time "12:00:02.777" (heart rate: 63), biometric information associated with the time "12:00:03.777" (heart rate: 63), etc. (see Figure 22).

[0148] After executing the process of step S262, the control unit 110 of the communication support server 20 determines whether the time-series biometric data of two participants has been stored (step S263). In this process, when the control unit 110 receives conversation end information from one participant terminal 50 and then receives conversation end information from another participant terminal 50, and the participant name information identified by the above (i) triggered by the receipt of the conversation end information from the other participant terminal 50 matches the conversation partner name information identified by the above (ii) triggered by the receipt of the conversation end information from the one participant terminal 50, and the conversation partner name information identified by the above (ii) triggered by the receipt of the conversation end information from the other participant terminal 50 matches the participant name information identified by the above (i) triggered by the receipt of the conversation end information from the one participant terminal 50, the control unit 110 can determine that the time-series biometric data of two participants (both participants who conversed with each other) has been stored.

[0149] If it is determined in step S263 that the time-series biometric data for two people has been stored, the control unit 110 of the exchange support server 20 executes a synchrony analysis process (step S264). The synchrony analysis process will be described later with reference to FIG. 27. If it is determined in step S263 that the time-series biometric data for two people has not been stored, or after executing the process of step S264, the control unit 110 of the exchange support server 20 ends the exchange support server-side conversation end process.

[0150] [Correlation Analysis] FIG. 27 is a flowchart showing the synchronicity analysis process performed in the interaction support server.

[0151] The synchronicity analysis process shown in FIG. 27 is a process performed by the exchange support server in step S264 of FIG. 23 (interaction support server-side conversation end process).

[0152] In the synchronization analysis process, first, the control unit 110 of the exchange support server 20 identifies the time-series biometric data of two people based on the partner combination information (see step S245 in FIG. 15 ) (step S101). In this process, when the control unit 110 receives conversation end information from one participant terminal 50 and then conversation end information from another participant terminal 50, the control unit 110 identifies the time-series biometric data (first time-series biometric data) stored in accordance with the above (vi) triggered by the receipt of the conversation end information from the one participant terminal 50, and the time-series biometric data (second time-series biometric data) stored in accordance with the above (vi) triggered by the receipt of the conversation end information from the other participant terminal 50.

[0153] Next, the control unit 110 of the communication support server 20 converts the unit of time information associated with the biometric information constituting the time-series biometric data (step S102). In this process, for the first time-series biometric data and the second time-series biometric data identified in step S101, the control unit 110 discards information of less than one second (milliseconds) from the time information associated with the biometric information constituting these time-series biometric data (converting the unit of time information from milliseconds to seconds). For example, if the time-series biometric data stored in "Area 1-1" shown in FIG. 26 is identified as the first time-series biometric data and the time-series biometric data stored in "Area 2-1" shown in FIG. 26 is identified as the second time-series biometric data, the times associated with each piece of biometric information constituting the first time-series biometric data ("12:00:00.111," "12:00:01.111," "12:00:02.111," ...) are converted into milliseconds. The time information after the conversion is common to both the first time-series biometric data and the second time-series biometric data. In this embodiment, when converting the unit of time information, information less than one second (millisecond) is uniformly rounded down, but the method of converting the unit is not particularly limited. For example, information less than one second (millisecond) may be rounded up across the board, or the millisecond portion may be rounded down if it is less than 500 milliseconds, while the millisecond portion may be rounded up (to the nearest whole number) if it is 500 milliseconds or more. In short, it is possible to adopt a method for reducing the accuracy of the time information as appropriate.

[0154] Next, the control unit 110 of the communication support server 20 merges the time-series biometric data of the two people (step S103). In this process, the control unit 110 merges the first time-series biometric data and the second time-series biometric data using the time information from which the information in millisecond units has been removed (converted to seconds) in step S102 as a key. Specifically, the control unit 110 groups the biometric information constituting the first time-series biometric data and the biometric information constituting the second time-series biometric data by the time information converted to seconds (time in one-second units), and integrates the biometric information in each group.

[0155] As a result, the biological information constituting the first time-series biological data and the biological information constituting the second time-series biological data are collected every second. For example, if the first time-series biometric data converted into seconds is composed of the first biometric information (heart rate: 72) associated with the time "12:00:00", the second biometric information (heart rate: 73) associated with the time "12:00:01", the third biometric information (heart rate: 73) associated with the time "12:00:02", etc., while the second time-series biometric data converted into seconds is composed of the first biometric information (heart rate: 62) associated with the time "12:00:00", the second biometric information (heart rate: 63) associated with the time "12:00:01", the third biometric information (heart rate: 63) associated with the time "12:00:02", etc., then the Nth biometric information constituting the first time-series biometric data will be associated with the Nth biometric information constituting the second time-series biometric data. It is possible to configure the system so that time information contained in only one of the first time-series biometric data and the second time-series biometric data, and the biometric information associated with that time information, are discarded when merging (biometric information associated with time information common to the first time-series biometric data and the second time-series biometric data is combined). Here, as described above, the biometric information is expressed as the first biometric information, the second biometric information, the third biometric information, the fourth biometric information, etc. in order of oldest to newest time associated with the biometric information constituting the time-series biometric data.

[0156] Next, the control unit 110 of the exchange support server 20 sets T=t (initial value) as the start time information T of the window (step S104). Next, the control unit 110 of the exchange support server 20 calculates a correlation coefficient within the window (step S105). In the processing of step S105, the control unit 110 calculates a correlation coefficient R for the merged first time-series biometric data and second time-series biometric data, with respect to a plurality of pieces of biometric information included in the window of the first time-series biometric data (referred to as "biometric information group A") and a plurality of pieces of biometric information included in the window of the second time-series biometric data (referred to as "biometric information group B"). The correlation coefficient R is expressed by the following equation (1):

[0157]

[0158] In formula (1), x ｉ is the i-th biometric information in the biometric information group A, and x ＡＶＥ is the average value of the biometric information group A, and y ｉ is the i-th biometric information in the biometric information group B, and y ＡＶＥ is the average value of the biometric information group B. The correlation coefficient R is a value obtained by dividing the average (covariance) of the value (product) obtained by multiplying the deviation in the biometric information group A (the value obtained by subtracting the average value) by the deviation in the biometric information group B (the value obtained by subtracting the average value), by the standard deviation in both the biometric information group A and the biometric information group B.

[0159] The range of the window is defined by the start time information T and the window size W, and the biometric information group A and the biometric information group B each include biometric information associated with any time information from "T" to "T+W." The initial value t of the start time information T can be set to the time information associated with the first biometric information (the oldest time information among the time information included in the first time-series biometric data and the second time-series biometric data). For example, if the initial value t of the start time information T is "12:00:00" and W=10 (seconds), the range of the window is "12:00:00," "12:00:01," "12:00:02," ..., "12:00:10." In other words, in this case, the number of biometric information items constituting the biometric information group A and the number of biometric information items constituting the biometric information group B are each 11.

[0160] After executing the process of step S105, the control unit 110 of the communication support server 20 sets T = T + X as the window start time information T (step S106). In this process, the control unit 110 adds X to the window start time information T. As an example, in this embodiment, X = 5 (seconds). For example, if the window start time information T before the process of step S106 is "12:00:00," the window start time information T after the process of step S106 will be "12:00:05." If W = 10 (seconds), the window range will be "12:00:05," "12:00:06," "12:00:07," ..., "12:00:15." It should be noted that W can be any time (for example, 5 seconds, 10 seconds, 30 seconds, 1 minute, 2 minutes, etc.), and X can be any time (for example, about 1 / 4 to 1 / 2 of W).

[0161] After executing the process of step S106, the control unit 110 of the communication support server 20 determines whether it is time to end the loop (step S107). In this process, the control unit 110 determines that it is time to end the loop if the end time information of the window after the process of step S106 is later than the most recent time information among the time information included in the first time-series biometric data and the second time-series biometric data (i.e., if it is later than the last time information in the data set). The end time information of the window is "T + W." For example, as described above, if the start time information T of the window after the process of step S106 is "12:00:05" and W = 10 (seconds), the end time information of the window is "12:00:15."

[0162] If it is determined in step S107 that it is not time to end the loop, the control unit 110 of the communication support server 20 proceeds to step S105. As a result, the correlation coefficient R is calculated every 5 seconds while the window is moved along the time information (time axis). If the number of pieces of biometric information included at 1-second intervals in the merged first time-series biometric data and the second time-series biometric data is M, the number P of correlation coefficients R calculated in step S105 until the loop ends is expressed as P = {(M - W) / 5} + 1. For example, if M = 200 (pieces) and W = 10 (seconds), P = {(200 - 10) / 5} + 1 = 39 (pieces).

[0163] If it is determined in step S107 that it is time to end the loop, the control unit 110 of the communication support server 20 normalizes the value of the correlation coefficient R calculated for each window (step S108). In this process, the control unit 110 normalizes the P values ​​of the correlation coefficient R calculated in step S105 within a predetermined range until the loop ends. The predetermined range is not particularly limited, and ranges such as "0 to 1.0," "0.7 to 1.0," and "0.5 to 1.0" can be used. For example, when "0.7 to 1.0" is used, the normalized value (correlation level value for each window) Q is expressed by the following equation (2):

[0164]

[0165] In formula (2), R ｉ is the i-th correlation coefficient R among the P correlation coefficients R, and Q ｉ is R ｉ is the normalized value of R ＭＡＸ is the maximum value among the P correlation coefficients R, and R ＭＩＮ is the smallest value among the P correlation coefficients R. As a result, P values ​​are calculated as per-window correlation level values ​​Q. Each of the P per-window correlation level values ​​Q corresponds to one window position, and information indicating the per-window correlation level values ​​Q may be stored in the conversation result storage area in association with information indicating the window position (for example, window start time information T). This makes it possible to perform more detailed correlation analysis using the per-window correlation level values ​​Q.

[0166] Next, the control unit 110 of the exchange support server 20 calculates the average of the per-window correlation level values ​​Q (step S109). In this process, the control unit 110 calculates the number (average correlation level) obtained by dividing the sum of the P per-window correlation level values ​​Q by P. For example, if P=39 (number of windows) and the sum of the 39 per-window correlation level values ​​Q is 35.10, the average correlation level is 0.90. The control unit 110 of the exchange support server 20 then determines the average correlation level calculated in step S109 as the degree of synchrony and stores information indicating the degree of synchrony in the storage unit 111 (step S110). As described above, the degree of synchrony is a value indicating the relationship (degree of similarity) between the temporal changes in the biometric information of one participant (participant A) and the temporal changes in the biometric information of another participant (participant B). After executing the process of step S110, the control unit 110 of the exchange support server 20 terminates the synchrony analysis process.

[0167] In this embodiment, the correlation level average value (synchronization degree) calculated by the synchronization degree analysis process is directly adopted as the matching degree. The control unit 110 of the communication support server 20 stores information (matching degree information) indicating the matching degree (synchronization degree) in both a matching degree storage area included in the conversation result storage area in which the first time-series biometric data is stored and a matching degree storage area included in the conversation result storage area in which the second time-series biometric data is stored. In the example shown in Figure 26, information corresponding to "0.90" is stored as matching degree information in both "Area 1-1" and "Area 2-1."

[0168] As will be described in detail in the second embodiment, the matching degree may be a value calculated by performing correlation analysis based on one type of biometric information (e.g., information related to heart rate), or may be a value calculated by performing correlation analysis based on multiple types of biometric information (e.g., information related to heart rate, information related to skin conductance, information related to brain waves, information related to physiological stress indexes, information related to facial expressions (such as movements of specific muscles in the face), information related to the direction of gaze, information related to tone of voice, etc.). The biometric information is information (information related to biometric reactions) corresponding to features extracted from data acquired by the various sensors, cameras, microphones, etc. described above (devices capable of detecting biometric reactions).

[0169] [End of Event] Figures 28 and 29 are flowcharts showing the event end processing on the organizer terminal side, the event end processing on the exchange support server side, and the event end processing on the participant terminal side. Figure 30 is a diagram showing an example of an event end operation reception screen. Figure 31 is a diagram showing an example of an event result display operation reception screen. Figures 32 and 33 are diagrams showing examples of an event result screen. Figure 34 is a diagram showing an example of a matching result display operation reception screen. Figure 35 is a diagram showing an example of a matching result initial screen. Figure 36 is a diagram showing an example of a matching result detail screen. Figure 37 is a diagram showing an example of a questionnaire response operation reception screen. Figure 38 is a diagram showing an example of a matching pair screen.

[0170] The event end processing on the organizer terminal side is processing performed on the organizer terminal 40 when the event ends. The event end processing on the exchange support server side is processing performed on the exchange support server 20 when the event ends. The event end processing on the participant terminal side is processing performed on the participant terminal 50 when the event ends.

[0171] In the event end processing on the organizer terminal side, the control unit 140 of the organizer terminal 40 executes the processing of steps S441 to S449 shown in Figures 28 and 29. In the event end processing on the exchange support server side, the control unit 110 of the exchange support server 20 executes the processing of steps S281 to S287 shown in Figures 28 and 29. In the event end processing on the participant terminal side, the control unit 150 of the participant terminal 50 executes the processing of steps S561 to S565 shown in Figures 28 and 29.

[0172] Specifically, in the event end process on the organizer terminal side, the control unit 140 of the organizer terminal 40 first determines whether the event in progress flag (see step S428 in FIG. 11) is set to on (step S441). If it is determined that the event in progress flag is not set to on, the control unit 140 of the organizer terminal 40 ends the event end process on the organizer terminal side.

[0173] On the other hand, if it is determined that the event in progress flag is set to ON, the control unit 140 of the organizer terminal 40 executes an event end operation acceptance process (step S442). In this process, the control unit 140 displays an event end operation acceptance screen on the display unit 142 and determines whether an event end instruction has been input via the operation input unit 143.

[0174] 30 , the event end operation acceptance screen has an event start instruction input area 661, an event end instruction input area 662, and an event result display instruction input area 663. Most of the display content of the event end operation acceptance screen is the same as the display content of the event start operation acceptance screen, but the operations that can be input when the event start operation acceptance screen is displayed differ from those when the event end operation acceptance screen is displayed.

[0175] Specifically, when the event end operation acceptance screen is displayed, a participant can input an instruction to select the event end instruction button (event end instruction input) in the event end instruction input area 662. However, at this time, the participant cannot input an instruction to select the event start instruction button (event start instruction input) or an instruction to select the event result display instruction button (event result display instruction input). In FIG. 30 , the outer edge of the event end instruction input area 662 is displayed with a solid line, indicating that the operation to input the event end instruction is valid. On the other hand, the outer edges of the event start instruction input area 661 and the event result display instruction input area 663 are displayed with a dotted line, indicating that the operation on these areas is invalid.

[0176] If it is determined in step S442 that an event end instruction has been input, the control unit 140 of the organizer terminal 40 transmits event end information to the exchange support server 20 via the communication unit 144 (step S443). The event end information includes information for requesting the exchange support server 20 to perform a series of processes required to end the event. The control unit 140 of the organizer terminal 40 then sets the event in progress flag to off (step S444).

[0177] In the exchange support server-side event end processing, the control unit 110 of the exchange support server 20 receives event end information transmitted from the organizer terminal 40 via the communication unit 112 (step S281). Then, the control unit 110 of the exchange support server 20 transmits event result information to the organizer terminal 40 via the communication unit 112 (step S282). In this processing, the control unit 110 identifies the conversation result information (time-series biometric data and matching degree information) stored in the conversation result storage area associated with the participant name information and conversation partner name information by referencing the storage area designation table (see FIG. 17 ). The conversation result information is stored for each combination of participant name information and conversation partner name information. The event result information is a collection of conversation result information for all combinations of participant name information and conversation partner name information. The control unit 110 can grasp the conversation result information for each conversation partner for all participants in the event, and provides this information to the organizer terminal 40 as event result information, with the participant name information, conversation partner name information, and conversation result information associated with each other.

[0178] In the event end processing on the organizer terminal side, after executing the processing of step S444, the control unit 140 of the organizer terminal 40 receives the event result information transmitted from the exchange support server 20 via the communication unit 144 (step S445). Then, the control unit 140 of the organizer terminal 40 executes an event result display operation acceptance processing (step S446). In this processing, the control unit 140 displays an event result display operation acceptance screen on the display unit 142 and determines whether an event result display instruction has been input via the operation input unit 143.

[0179] 31 , the event result display operation reception screen has an event start instruction input area 661, an event end instruction input area 662, and an event result display instruction input area 663. Most of the display content on the event result display operation reception screen is the same as the display content on the event start operation reception screen, but the operations that can be input when the event start operation reception screen is displayed differ from those when the event result display operation reception screen is displayed.

[0180] Specifically, when the event result display operation reception screen is displayed, a participant can input an instruction to select the event result display instruction button (input an event result display instruction) in the event result display instruction input area 663. However, at this time, the participant cannot input an instruction to select the event start instruction button (input an event start instruction) or an instruction to select the event end instruction button (input an event end instruction). In FIG. 31 , the outer edge of the event result display instruction input area 663 is displayed with a solid line, indicating that the operation to input an instruction to display the event results is valid. On the other hand, the outer edges of the event start instruction input area 661 and the event end instruction input area 662 are displayed with a dotted line, indicating that the operation on these areas is invalid.

[0181] If it is determined in step S446 that an event result display instruction has been input, the control unit 140 of the organizer terminal 40 causes the display unit 142 to display an event result screen (step S447). As shown in FIG. 32, the event result screen has multiple participant name selection areas 741 (741a to 741i in this example). Each participant name selection area 741 is an area where an image corresponding to a button (participant name selection button) containing characters indicating the name of one participant is displayed. The organizer can operate the operation input unit 143 to input an input indicating that the participant name selection button is selected in any of the participant name selection areas 741 (participant name selection input).

[0182] When an input is made to select one of the participant name selection buttons, the matching degree for each conversation partner of the participant corresponding to that participant name selection button is displayed on the event result screen. In the example shown in FIG. 33 , a participant name selection input is made in the participant name selection field 741 a corresponding to “Donald,” and the matching degree between Donald and each conversation partner is displayed. Note that the matching degree information stored in the exchange support server 20 corresponds to a numerical value with an upper limit of 1.0, but when displaying the matching degree, the control unit 140 of the organizer terminal 40 multiplies the numerical value by 100 to display it as a percentage.

[0183] In the exchange support server-side event end processing, after executing the processing of step S282, the control unit 110 of the exchange support server 20 updates the status information (step S283). In this processing, the control unit 110 stores information indicating "Event Ended, Result Analysis Completed" as status information in the event information management table. Note that after executing the processing of step S281 and before executing the processing of step S282, the control unit 110 may store information indicating "Event Ended, Result Analysis in Progress" as status information in the event information management table.

[0184] For example, in this embodiment, the synchrony analysis process is executed in the conversation end process (see FIG. 23 ) on the exchange support server side. However, the synchrony analysis process can also be configured to be executed in the event end process on the exchange support server side. In such a case, since correlation analysis may require time between the execution of step S281 and the execution of step S282, the event status may be temporarily set to "Event Ended, Results Analyzing." At this time, the organizer terminal 40 may be configured to display a standby screen indicating "Results Analyzing" on the display unit 142, disabling operations to input an instruction to display the event results.

[0185] After executing the process of step S283, the control unit 110 of the exchange support server 20 transmits the matching result information to the participant terminal 50 via the communication unit 112 (step S284). In this process, the control unit 110 references each conversation result storage area (e.g., "Area 1-1," "Area 1-2," "Area 1-3," "Area 1-4," etc.) designated by the storage area designation information defined in the same row (e.g., the first row) in the storage area designation table, and compares the matching degree information stored in those conversation result storage areas to identify the participant (e.g., Donald) corresponding to that row in descending order of matching degree with each conversation partner. The control unit 110 then stores the conversation partner name information corresponding to the matching degree in the event information management table in descending order of matching degree. For example, the matching degree with Donald is first place for Olivia (0.9011), second place for Peggy (0.8822), third place for Kathy (0.8763), fourth place for Lisette (0.8602), and fifth place for Emma (0.8476) (see FIG. 33). FIG. 10 shows how information indicating the rankings is stored as ranking result information in the event information management table. The control unit 110 performs this processing for all rows (participants) in the storage area specification table, and provides the ranking result information stored in the event information management table for each row, along with conversation partner name information and matching degree information corresponding to each ranking, to the participant terminal 50 of the participant corresponding to that row.

[0186] The matching result information includes not only conversation partner name information, matching degree information, and ranking result information, but also the time-series biometric data used to calculate the matching degree (the first time-series biometric data and the second time-series biometric data merged in step S103 of FIG. 27 ) and ranking display number information. For example, if the biometric tester 60 is not properly attached to the body, the time-series biometric data used to calculate the matching degree may be inappropriate. For example, if a value corresponding to the biometric information (e.g., heart rate) in the time-series biometric data remains zero for a predetermined period of time or longer, it is assumed that the biometric tester 60 has been removed. When such a situation occurs, the matching degree calculated using the time-series biometric data can be configured to be excluded from the ranking.

[0187] In the participant terminal-side event end processing, the control unit 150 of the participant terminal 50 receives the matching result information transmitted from the interaction support server 20 via the network communication unit 157 (step S561). Then, the control unit 150 of the participant terminal 50 executes a matching result display operation acceptance process (step S562). In this process, the control unit 150 displays a matching result display operation acceptance screen on the display unit 152, and determines whether a matching result display instruction has been input via the operation input unit 153.

[0188] 34, the matching result display operation reception screen has a conversation partner name input area 721, a conversation start instruction input area 722, a conversation end instruction input area 723, and a matching result display instruction input area 724. Most of the display content of the matching result display operation reception screen is the same as the display content of the conversation partner name input operation reception screen, but the operations that can be input when the conversation partner name input operation reception screen is displayed differ from those when the matching result display operation reception screen is displayed.

[0189] Specifically, when the matching result display operation reception screen is displayed, the participant can input an instruction to select the matching result display instruction button (matching result display instruction input) in the matching result display instruction input area 724. However, at this time, the participant cannot input an instruction to specify the name of the conversation partner (conversation partner name identification instruction input), an instruction to select the conversation start instruction button (conversation start instruction input), or an instruction to select the conversation end instruction button (conversation end instruction input). In FIG. 34 , the outer edge of the matching result display instruction input area 724 is displayed with a solid line, indicating that the operation to input the matching result display instruction is valid. On the other hand, the outer edges of the conversation partner name input area 721, the conversation start instruction input area 722, and the conversation end instruction input area 723 are displayed with dotted lines, indicating that the operation in these areas is invalid. The matching result display operation reception screen, like the conversation partner name input operation reception screen, includes a heart rate image 725 and a heart image 726. The heart rate image 725 and the heart image 726 are as described above, and therefore will not be described here. As described above, while the event status is set to "Event ended, results being analyzed," the participant terminal 50 may be configured so that a standby screen indicating "results being analyzed" is displayed on the display unit 152, and operations to input a command to display the matching results are disabled.

[0190] If it is determined in step S562 that a matching result display instruction has been input, the control unit 150 of the participant terminal 50 causes the display unit 152 to display a matching result initial screen (step S563). As shown in Fig. 35, the matching result initial screen includes a plurality of top-ranked conversation partner images 761 (761a to 761e in this example) and top-ranked target message images 762 (762a to 762c in this example), and also has a survey response operation reception screen display instruction input area 763.

[0191] The top-ranked conversation partner images 761 are images that include the name of the conversation partner, the degree of matching with the conversation partner (heartbeat synchronization rate), and text indicating the ranking according to the degree of matching. Here, since "5" is set as the ranking display number (see FIG. 13 ), the top-ranked conversation partner images 761 corresponding to conversation partners with matching degrees from 1st to 5th are displayed. Note that the matching degree information stored in the exchange support server 20 corresponds to a numerical value with an upper limit of 1.0, but when displaying the degree of matching, the control unit 150 of the participant terminal 50 multiplies the numerical value by 100 to display it as a percentage.

[0192] The top-ranked conversation partner image 761 is also an image corresponding to the matching result details screen display instruction button. The top-ranked target message image 762 is an image including characters or the like indicating a message regarding conversation partners ranked 1st to 3rd in matching degree. The survey response operation reception screen display instruction input area 763 is an area where an image corresponding to a button including the characters "Request for dating partner" (survey response operation reception screen display instruction button) is displayed.

[0193] By operating the operation input unit 153, a participant can make an input to select one matching result details screen display instruction button (corresponding to that higher-ranked conversation partner image 761) in the display area of ​​one higher-ranked conversation partner image 761 (matching result details screen display instruction input). Also, by operating the operation input unit 153, a participant can make an input to select the survey answer operation acceptance screen display instruction button in the survey answer operation acceptance screen display instruction input area 763 (survey answer operation acceptance screen display instruction input).

[0194] When an input is made to select one of the matching result detail screen display instruction buttons, the control unit 150 of the participant terminal 50 causes the matching result detail screen corresponding to the matching result detail screen display instruction button to be displayed on the display unit 152. In the example shown in Fig. 36, on Donald's participant terminal 50, a matching result detail screen display instruction input is made in the display area of ​​the top-ranked conversation partner image 761a corresponding to the first-place conversation partner (Olivia), and as a result, a matching result detail screen corresponding to the conversation result information of the conversation between Donald and Olivia is displayed.

[0195] The matching result details screen includes a matching degree image 781 and a heart rate variability graph image 782, and also includes a survey response operation reception screen display instruction input area 783, a relationship preference input area 784, and a matching result initial screen display instruction input area 785. The matching degree image 781 is an image including a number corresponding to the matching degree and a pie chart. The number is rounded to an integer, and in the example shown in FIG. 36, "90%" is displayed as the number corresponding to the matching degree between Donald and Olivia. The heart rate variability graph image 782 is an image corresponding to a graph visualizing the first time-series biometric data and the second time-series biometric data merged in step S103 of FIG. 27. The survey response operation reception screen display instruction input area 783 is an area where an image corresponding to a button containing the words "Request for Relationship" (survey response operation reception screen display instruction button) is displayed. The relationship preference input area 784 is an area where an image corresponding to a button containing the words "Looking for Relationship" (relationship preference input button) is displayed. The matching result initial screen display instruction input area 785 is an area where an image corresponding to a button (matching result initial screen display instruction button) including the text "Go to ranking screen" is displayed.

[0196] By operating the operation input unit 153, the participant can make an input to select the survey response operation reception screen display instruction button (survey response operation reception screen display instruction input) in the survey response operation reception screen display instruction input area 783. Furthermore, by operating the operation input unit 153, the participant can make an input to select the relationship desire input button (relationship desire input) in the relationship desire input area 784. Furthermore, by operating the operation input unit 153, the participant can make an input to select the matching result initial screen display instruction button in the matching result initial screen display instruction input area 785 (matching result initial screen display instruction input).

[0197] When a survey response operation reception screen display instruction input is made in the survey response operation reception screen display instruction input area 763 on the matching result initial screen or the survey response operation reception screen display instruction input area 783 on the matching result detail screen, the control unit 150 of the participant terminal 50 executes a survey response operation reception process (step S564). In this process, the control unit 150 displays the survey response operation reception screen on the display unit 152 and determines whether a dating preference ranking confirmation input has been made via the operation input unit 153.

[0198] As shown in FIG. 37 , the questionnaire response operation reception screen has a first preference input area 801, a second preference input area 802, a third preference input area 803, a relationship preference ranking confirmation input area 804, and a matching result initial screen display instruction input area 805. The first preference input area 801 is an area for inputting the person who is most desired to date (first preference) from among multiple conversation partners. The second preference input area 802 is an area for inputting the person who is second most desired to date (second preference) from among multiple conversation partners. The third preference input area 803 is an area for inputting the person who is third most desired to date (third preference) from among multiple conversation partners. The relationship preference ranking confirmation input area 804 is an area for displaying an image corresponding to a button containing the words "Save / Exit" (a relationship preference ranking confirmation button). The matching result initial screen display instruction input area 805 is an area for displaying an image corresponding to a button containing the words "Go to ranking screen" (a matching result initial screen display instruction button).

[0199] The first preference input area 801, the second preference input area 802, and the third preference input area 803 can display the names of all conversation partners in a pull-down menu in response to operation of the operation input unit 153. By operating the operation input unit 153, a participant can input their first, second, and third preference conversation partners by selecting the name of one conversation partner in each of the first preference input area 801, the second preference input area 802, and the third preference input area 803. Furthermore, by operating the operation input unit 153, a participant can make an input to select the relationship preference order confirmation button in the relationship preference order confirmation input area 804 (a relationship preference order confirmation input). Furthermore, by operating the operation input unit 153, a participant can make an input to select the matching result initial screen display instruction button in the matching result initial screen display instruction input area 805 (a matching result initial screen display instruction input).

[0200] If it is determined in step S564 that a confirmation input for the relationship preference order has been made, the control unit 150 of the participant terminal 50 transmits survey result information to the exchange support server 20 via the network communication unit 157 (step S565). The survey result information includes information input by the participant, such as information indicating the name of the first preference partner, information indicating the name of the second preference partner, and information indicating the name of the third preference partner. When a confirmation input for the relationship preference order is made with the name of a conversation partner selected in each of the first preference input area 801, the second preference input area 802, and the third preference input area 803, the control unit 150 determines the selected conversation partners as the first preference partner, the second preference partner, and the third preference partner, respectively, and includes information indicating the names of these partners (relationship preference order information) in the survey result information.

[0201] It is possible to input a confirmation of the relationship preference order even when the name of a conversation partner is not selected in any of the first preference input area 801, the second preference input area 802, and the third preference input area 803 (for example, as shown in FIG. 37 , only the name of the first preference partner is selected). It is also possible to input a confirmation of the relationship preference order even when the name of a conversation partner is not selected in any of the first preference input area 801, the second preference input area 802, and the third preference input area 803.

[0202] Furthermore, the relationship preference input area 784 of the matching result detail screen can display a pull-down menu of "first preference," "second preference," and "third preference" in response to operation of the operation input unit 153. When the matching result detail screen for one conversation partner is displayed, the participant can input the desired ranking of the conversation partner by operating the operation input unit 153 to select one of "first preference," "second preference," and "third preference" in the relationship preference input area 784. If an instruction to display the questionnaire response operation reception screen is input with the desired ranking of the conversation partner selected in the relationship preference input area 784, the questionnaire response operation reception screen is displayed with the selection in the relationship preference input area 784 reflected (the name of the conversation partner is selected in either the first preference input area 801, the second preference input area 802, or the third preference input area 803).

[0203] Furthermore, if a command to display the matching result initial screen is input in the matching result initial screen display command input area 785 on the matching result detail screen or in the matching result initial screen display command input area 805 on the questionnaire response operation reception screen, the matching result initial screen is displayed again. After executing the process of step S565, the control unit 150 of the participant terminal 50 ends the participant terminal-side event end process.

[0204] In the event end processing on the exchange support server side, the control unit 110 of the exchange support server 20 receives the survey result information transmitted from the participant terminal 50 via the communication unit 112 (step S285). Each time the control unit 110 receives the survey result information from each participant terminal 50, it is possible to ascertain which participant desires which conversation partner and in what order (survey result) based on the relationship preference ranking information contained in the survey result information, and store information corresponding to the survey result in a survey result storage area contained in the conversation result storage area. In the example shown in FIG. 26, because Donald selected Olivia as his first choice, information indicating "first choice" is stored in "Area 1-1," and because Olivia selected Donald as her second choice, information indicating "second choice" is stored in "Area 2-1."

[0205] Next, the control unit 110 of the communication support server 20 identifies pairs for which a match has been established (step S286). In this process, when one participant selects another participant as one of their first, second, or third choices, and the other participant also selects the participant as one of their first, second, or third choices, the control unit 110 treats the pair (combination) of participants as a match. Specifically, the control unit 110 determines whether a match has been established for each combination by referencing the corresponding survey result storage area for all combinations of participants and conversation partners. In the example shown in FIG. 26, a match has been established for the pair (combination) of Donald and Olivia.

[0206] The control unit 110 of the exchange support server 20 then transmits the matching pair information to the organizer terminal 40 via the communication unit 112 (step S287). The matching pair information indicates the pair for which a match has been established. The control unit 110 of the exchange support server 20 then terminates the exchange support server-side event end process.

[0207] In the event end processing on the organizer terminal side, the control unit 140 of the organizer terminal 40 receives the matching pair information transmitted from the exchange support server 20 via the communication unit 144 (step S448). The control unit 140 of the organizer terminal 40 then displays a matching pair screen corresponding to the received matching pair information on the display unit 142 (step S449). FIG. 38 shows the matching pair screen when a match is made between Donald and Olivia. The matching pair screen includes a pair name image 821, a first participant detail display instruction input area 822, a second participant detail display instruction input area 823, and a detail display area 824.

[0208] The pair name image 821 is an image showing the name of the pair (two participants) with whom a match has been made. The first participant detail display instruction input area 822 and the second participant detail display instruction input area 823 are areas in which images corresponding to buttons (detail display instruction buttons) containing characters indicating the name of one of the two participants are displayed. The organizer can input to select one of the detail display instruction buttons by operating the operation input unit 143. The detail display area 824 is an area that appears when the detail display instruction button corresponding to one participant is selected, and displays an image containing characters indicating the name of the person with whom a match has been made, the degree of matching with that person, and the results of a survey for that participant.

[0209] After executing the process of step S449, the control unit 140 of the organizer terminal 40 ends the organizer terminal-side event end process.

[0210] <Second Embodiment> The first embodiment has been described above. The second embodiment will now be described. The basic configuration of the exchange support system 10 according to the second embodiment is the same as that of the exchange support system 10 according to the first embodiment. In the following description, components that are the same as those of the exchange support system 10 according to the first embodiment will basically be assigned the same reference numerals. Furthermore, explanations of parts that apply to the second embodiment as well as the first embodiment will be omitted.

[0211] In the above description, even if there is a statement that is limited to the communication support system 10 according to the first embodiment, such as "in the first embodiment," it can also be applied to the communication support system 10 according to the second embodiment, as long as it does not deviate from the spirit of the second embodiment. Therefore, each configuration shown in the first embodiment (including each configuration shown in the modified example) can be partially replaced with or combined with the configuration shown in the second embodiment.

[0212] Furthermore, even if the configuration is different from that of the communication support system 10 according to the first embodiment, the same reference numerals may be used for the sake of convenience to designate components having similar functions. Furthermore, even if the configuration is the same as that of the communication support system 10 according to the first embodiment, different reference numerals may be used for the sake of convenience.

[0213] [Interaction Support Device] FIG. 39 is an explanatory diagram showing the flow of information in the interaction support system.

[0214] The exchange support system 10 according to the second embodiment includes an exchange support device 20. The exchange support device 20 is a device corresponding to the exchange support server 20 described in the first embodiment. In the following description, a case will be described in which heart rate is used as the main analysis data for the matching analysis, but as described in the first embodiment, other matching elements may be used as the main analysis data.

[0215] 39 , the exchange support device 20 has an exchange support unit 210 that calculates the degree of matching between multiple participants 1 when they are having a conversation. The exchange support unit 210 is a functional configuration included in the control unit 110 described in the first embodiment. The exchange support unit 210 has a matching information management unit 124 that acquires matching information including changes over time in the heart rates of the participants 1 during the conversation, and a matching measurement unit 125 that calculates the correlation level of the changes over time in the heart rates as the degree of matching between the participants 1.

[0216] Here, "participant 1" refers to multiple individuals who use the communication support system 10, and is a group of people who are the target of the communication support system 10. Specifically, participant 1 is a person who aims to communicate smoothly with other participants and evaluate their compatibility and matching degree at a matchmaking event, social event, business networking event, or the like.

[0217] "Conversation between multiple participants 1" refers to a situation in which multiple participants 1 gather in one place (physical or virtual) and communicate with each other, including gatherings with specific purposes such as matchmaking events, social events, and business networking events. An example of a matchmaking event is a system in which male and female participants 1 gather at a venue, introduce themselves to each other, converse on topics of interest, and, as the event progresses, engage in dialogue with different people in turn to explore compatibility and the degree of commonality of interests. Social events include, for example, class reunions, local community events, and hobby gatherings, where people from diverse backgrounds gather to deepen their interactions. Business networking events are events in which business people build relationships and exchange information.

[0218] A "conversation between participants 1" occurs when multiple participants 1 using the communication support system 10 gather in the same physical or virtual location and exchange words with each other. For example, conversations between participants 1 at matchmaking events typically involve participants of the opposite sex introducing themselves and discussing each other's hobbies and interests. At such matchmaking events, participants 1 have the opportunity to converse with many people in a short period of time, so the content of the conversations is brief, yet important information is exchanged. For example, participants 1 talk about their hobbies and work, and compatibility is judged by observing the other person's reaction to that.

[0219] The "matching degree between participants 1" is an index that quantitatively indicates the compatibility and chemistry between multiple participants 1, measured using the communication support system 10. This matching degree evaluates how well the participants 1 are compatible with each other and how much common interests and emotional connections they have, and is calculated mainly based on matching information that includes changes in heart rate over time.

[0220] "Heart rate change over time" refers to the fluctuation of heart rate over time and is an important indicator reflecting an individual's physiological and emotional state. When people are emotionally engaged, their heart rate fluctuates according to the intensity of their emotions. For example, heart rate increases when a topic is interesting or a tense situation is occurring, while heart rate decreases when a person is relaxed or at ease. During analysis, correlations between heart rate changes over time are evaluated to measure emotional synchrony between two participants 1. For example, if heart rates fluctuate in the same pattern during a conversation, it is determined that there is a strong emotional connection between the two people. In this way, heart rate changes over time provide important data for assessing the emotional state and compatibility of participants 1.

[0221] The "matching information including changes in heart rate over time" includes various physiological and behavioral data in addition to heart rate. This information is used to more accurately evaluate the compatibility and degree of matching between participants 1. For example, matching elements such as facial expression, tone and volume of voice, gaze, galvanic skin response (GSR), body movements and posture, electroencephalogram (EEG), physiological stress indicators, and text analysis of conversation content can be used as matching information. Note that the matching element of heart rate may be used as the primary analysis data for the matching analysis, and other matching elements may be used as secondary analysis data for the matching analysis, or a combination of one or more matching elements may be used as data for the matching analysis.

[0222] Specifically, "facial expression" is acquired using facial recognition technology, and by analyzing changes in Participant 1's facial expression in real time, it is possible to evaluate emotional reactions (happiness, surprise, interest, tension, etc.) during the conversation. "Voice tone and volume" are important indicators of emotion and excitement, and make it possible to evaluate the excitement and level of interest in the conversation. "Gaze" is acquired in real time using eye tracking technology to acquire Participant 1's eye movements, and indicates where Participant 1 is paying attention and how focused they are, making it possible to evaluate their interest and level of concentration during the conversation.

[0223] "Galvanic skin response (GSR)" is data that evaluates stress and excitement by measuring the electrical characteristics of the skin and can be used as an indicator of whether Participant 1 is tense or relaxed. "Body movement and posture" is data obtained using a motion sensor or accelerometer. Since body movement and posture reflect emotions and levels of interest, it can be used to evaluate the consistency of movements and postures during conversation. "Electroencephalogram" is data obtained using an EEG (electroencephalograph). By recording brain activity in real time, it is possible to evaluate concentration, relaxation, and excitement. "Physiological stress indicators" are data such as heart rate variability (HRV), blood pressure, and respiration rate, which indicate Participant 1's stress level and relaxation level, allowing for a comprehensive evaluation of physiological responses during conversation. "Text analysis of conversation content" uses natural language processing technology to convert the content of the conversation into text and analyze it, allowing for evaluation of the frequency of keywords and phrases in the conversation, the proportion of positive and negative expressions, and so on.

[0224] The "correlation level of heart rate changes over time" is an index that quantitatively indicates the degree to which the heart rates of two or more participants 1 fluctuate in synchronization over time. This correlation level is used to evaluate the emotional connection and compatibility between participants 1, and is calculated through an analysis of heart rate data.

[0225] "Calculating the correlation level of changes in heart rate over time as the degree of matching between participants 1" is a method for evaluating compatibility and chemistry based on the degree of synchronization of heart rate data between participants 1. The correlation level and the degree of matching are closely related in order to evaluate the emotional connection and chemistry between participants 1.

[0226] Specifically, the correlation level is an indicator of the degree to which the heart rates of two or more participants 1 fluctuate in a similar pattern over time. A high correlation level indicates that the heart rates of two participants 1 fluctuate in sync, suggesting the presence of emotional empathy or synchronization. This situation occurs when participants 1 share common interests and feel a strong emotional connection in conversations and activities. On the other hand, the matching level is an indicator of the overall compatibility between participants 1, and includes the correlation level as an important factor. A high correlation level indicates a high degree of matching, while a low correlation level indicates a low degree of matching. Specifically, if the heart rate fluctuation patterns match, it is evaluated that the emotional connection between participants 1 is strong and that there is a high possibility of building a good relationship with each other. Conversely, if the heart rate fluctuation patterns do not match, it is evaluated that there is an emotional gap and that there are barriers to building a relationship.

[0227] For example, if the heart rates of both participants 1 rise in sync when they are talking about a topic of mutual interest, this indicates a high correlation level, resulting in a high matching score. This means that the two participants are equally excited and interested, indicating good chemistry. On the other hand, if one participant 1 is excited and his heart rate rises, while the other participant 1's heart rate barely fluctuates, this indicates a low correlation level, resulting in a low matching score. This indicates little emotional synchronization between the two participants and poor chemistry. In this way, the correlation level of heart rate changes over time is an important indicator for objectively evaluating the emotional connection between participants 1. Calculating the matching score based on this correlation level allows for a scientific and accurate evaluation of the compatibility of participants 1.

[0228] To determine the level of correlation between heart rate changes over time, the heart rate of each participant 1 is measured over time and the data is compared. Statistical methods are used for correlation analysis to clarify patterns of heart rate fluctuations over time and to assess the degree to which the heart rates of the two people are synchronized.

[0229] A high level of correlation between heart rate changes over time indicates that the heart rates of two participants 1 fluctuate in similar patterns over time. This means that the two people are emotionally synchronized, meaning that empathy and synchronization are occurring. For example, if heart rates increase in unison when talking about an interesting topic or a common hobby, it is determined that there is a strong emotional connection between the two people.

[0230] On the other hand, if the correlation level is low, the heart rates of the two people fluctuate in different patterns, indicating little emotional synchronization. In this case, it is likely that the content of the conversation or interests do not match, and it may be determined that the compatibility is poor. For example, if one participant 1 is excited and his heart rate is rising, while the other participant 1's heart rate remains unchanged, it is thought that there is an emotional gap between the two people.

[0231] In addition to the method described in the first embodiment, examples of the correlation analysis method include an analysis method using moving average correlation, a correlation analysis method using Pearson's product-moment correlation coefficient, a correlation analysis method using Spearman's rank correlation coefficient, a correlation analysis method using Kendall's tau coefficient, a correlation analysis method using partial correlation coefficient, a correlation analysis method using cross-correlation, and a correlation analysis method using mutual information.

[0232] The correlation analysis may be performed using machine learning. Correlation analysis using machine learning is particularly effective when performing correlation analysis using multiple matching factors. For example, when correlation analysis is performed using facial expressions, voice, gaze, galvanic skin response (GSR), body movements and posture, and electroencephalograms in addition to heart rate, multidimensional data can be analyzed in an integrated manner, enabling more accurate evaluation of correlations. Furthermore, the detection of nonlinear relationships and high-level feature extraction can maximize the potential information contained in the data. Therefore, utilizing machine learning is expected to deepen understanding of compatibility evaluations and emotional connections between users, thereby improving the effectiveness of the interaction support system 10.

[0233] To explain the correlation analysis method using machine learning in more detail, various sensors are used to collect data on matching elements such as heart rate, facial expression, tone and volume of voice, gaze, GSR, body movements, and brain waves. This data is sampled at regular time intervals. Preprocessing such as noise removal and standardization is then performed to improve the quality of the data. The data is also converted into an appropriate format to make it easier to use in analysis. Features are extracted from each data. For example, possible features include fluctuations in heart rate, changes in facial expression, fluctuations in tone and volume of voice, gaze direction, fluctuations in GSR, body movement patterns, and frequency components of brain waves.

[0234] After this, an appropriate machine learning model is selected. The dataset is then divided into training data and test data, and the machine learning model is trained. The performance of the models is evaluated, and the optimal machine learning model is selected. The trained machine learning model is used to analyze the correlation between each feature. For example, the correlation coefficient between the predicted value of the machine learning model and the actual value is calculated, and the relationship between the data is evaluated. This makes it possible to evaluate the compatibility and emotional connection between participants 1 based on the obtained correlation coefficient and other analysis results.

[0235] Furthermore, text analysis of the conversation content may be added as a matching element, and correlation analysis may be performed using a large-scale language model. Specifically, first, various sensors are used to collect data such as heart rate, facial expression, tone and volume of voice, gaze, GSR (galvanic skin response), body movements, and brain waves. These data are sampled at regular time intervals. Audio data of the conversation content is also collected at the same time and converted into text data. This text data is a detailed record of what Participant 1 said and the flow of the conversation.

[0236] Next, the collected data is preprocessed, including noise removal and standardization, to improve data quality. Various types of data are also converted into a format suitable for analysis, allowing them to be handled uniformly. Features are then extracted from each piece of data. Possible features include heart rate fluctuations, facial expression changes, voice tone and volume fluctuations, gaze direction, GSR fluctuations, body movement patterns, and EEG frequency components. Additionally, text analysis is performed to obtain text features such as keyword extraction from conversation content, topic frequency analysis, and sentiment analysis.

[0237] Next, an appropriate machine learning model is selected. The dataset is divided into training data and test data, and the selected machine learning model is trained. The performance of the models is evaluated, and the optimal machine learning model is selected. The trained machine learning model is used to analyze the correlation between each feature. For example, the correlation coefficient between the model's predicted value and the actual value is calculated, and the relationship between the data is evaluated. By analyzing the correlation between physiological data such as heart rate and facial expression and text data of the conversation content, it is possible to comprehensively evaluate the emotional connection and compatibility between participants 1.

[0238] Next, a large-scale language model is used for advanced analysis of the text data of the conversation content. In other words, by using a large-scale language model, advanced semantic and emotional analysis of the conversation content can be performed, resulting in a deeper understanding than simple keyword matching. For example, how participant 1 talks about the same topic and the emotions they express toward that topic can be analyzed, and this can be combined with other physiological data (matching element data) to evaluate the correlation. In this way, by integrating the text analysis of the conversation content and the analysis of the physiological data and performing correlation analysis using a machine learning model and a large-scale language model, the degree of matching between participants 1 can be evaluated with higher accuracy.

[0239] The communication support system 10 configured as described above can monitor changes in heart rate over time in real time or offline, and evaluate the emotional connection between participants 1 based on that data. Because heart rate reflects emotional changes and excitement, analyzing the degree of heart rate synchronization can scientifically and objectively evaluate the compatibility between participants 1. This allows for highly reliable matching based on data, without relying on conventional subjective evaluations.

[0240] The matching information management unit 124 also accurately collects heart rate data from participants 1 and records its changes over time in detail. This data not only captures heart rate fluctuations but also reflects emotional changes in real time as the conversation progresses, allowing for a detailed analysis of participants 1's emotional reactions. This makes it possible to gain a deeper understanding of the relationships between participants 1 and provide specific feedback to support better interactions.

[0241] Furthermore, the matching measurement unit 125 analyzes the correlation level of the acquired heart rate data and calculates the degree of matching between the participants 1. This correlation analysis makes it possible to quantitatively evaluate the degree to which the participants 1 are emotionally synchronized during the conversation. A high correlation level indicates a strong emotional connection between the participants 1 and good compatibility. This information serves as a guide for the participants 1 to understand their compatibility and build better relationships. Furthermore, if the communication support system 10 provides real-time feedback to the participants 1, it promotes immediate behavioral improvements and improved communication. For example, better communication can be achieved by adjusting one's own behavior in response to fluctuations in the other person's heart rate. Feedback based on such data is an effective means for the participants 1 to understand each other's emotions and deepen empathy.

[0242] In this way, the interaction support system 10 has the excellent effect of supporting better interactions by scientifically evaluating the degree of matching using heart rate data between participants 1 and providing specific feedback to deepen emotional connections.

[0243] In addition, the exchange support unit 210 of the exchange support device 20 has a matching result output unit 126 that displays the matching degree determined by the matching measurement unit 125 and the changes in the heart rates of all participants 1 over time on the screen of the participant terminal 50 operated by participant 1.

[0244] As a result, the communication support device 20, by including the matching result output unit 126, has the function of providing visual feedback to the participant 1 in real time and offline. Specifically, the communication support device 20 can display the matching degree calculated by the matching measurement unit 125 and changes over time in the heart rates of all participants 1 on the screen of the participant terminal 50 operated by the participant 1. As a result, the matching result output unit 126 visually displays the matching degree analyzed by the matching measurement unit 125 on the participant terminal 50, allowing the participant 1 to intuitively understand the matching degree. Note that it is preferable that the matching degree be displayed as a numerical value, a graph, a color scale, or the like.

[0245] Furthermore, the matching result output unit 126 preferably has a function for displaying on a screen the changes in the heart rates of all participants 1 over time. In this case, participants 1 can compare their own heart rate data with the heart rate data of other participants 1. For example, participants 1 can check how their heart rate changed during or after a particular conversation or event, and how synchronized their heart rate is with that of the other participants 1. This allows participants 1 to gain a deeper understanding of their own physiological responses and obtain valuable information for evaluating their emotional connection with others.

[0246] The exchange support unit 210 of the exchange support device 20 has a topic extraction unit 127 that acquires the content of the conversation between participants 1 as matching information, analyzes the content of the conversation, extracts the topic and the topic period during which the topic continued, and determines the correlation level, and a topic output unit 128 that displays the topic extracted by the topic extraction unit 127 on the screen of the participant terminal 50 operated by participant 1 at an emphasis level according to the correlation level.

[0247] The topic extraction unit 127 utilizes natural language processing (NLP) technology to extract meaningful information from the text data of the conversation and has the function of acquiring basic data for improving communication between participants 1. Specifically, the topic extraction unit 127 collects the audio data of the conversation and converts it into text data. This allows the content of the conversation to be handled as written information. Next, the collected text data is preprocessed to improve the accuracy of analysis. This preprocessing includes tokenization, removal of stop words, stemming, which extracts stems by truncating the ends of words, and lemmatization, which converts words into their basic forms taking into account their grammatical roles and contexts.

[0248] Next, to extract important keywords from the text data, a keyword extraction algorithm such as TF-IDF (Term Frequency-Inverse Document Frequency) or RAKE (Rapid Automatic Keyword Extraction) is used. This identifies important words and phrases that frequently appear in the conversation. Furthermore, to identify the overall topic of the conversation, a topic modeling method such as LDA (Latent Dirichlet Allocation) or NMF (Non-negative Matrix Factorization) is used. This allows the conversation data to be classified into multiple topics and keywords related to each topic to be identified. By combining the above methods, the topic extraction unit 127 understands the flow and context of the conversation and analyzes how long a particular topic has been ongoing. Through sentence dependency analysis and semantic analysis, the structure and intent of the conversation are grasped and the duration of each topic is accurately identified.The topic extraction unit 127 then calculates a correlation level based on the extracted topics and their duration.This correlation level is analyzed in combination with physiological data such as heart rate and facial expression, and is used to evaluate the emotional connection between participants 1.

[0249] The topic output unit 128 receives data on topics and their durations provided by the topic extraction unit 127. This data includes particularly important topics in the conversation and how long those topics lasted. In addition, a correlation level during the topic period is also provided to evaluate the emotional connection between the participants 1. The topic output unit 128 then displays each topic on the screen of the participant terminal 50 at an emphasis level according to the correlation level.

[0250] According to the above configuration, the topic extraction unit 127 of the communication support device 20 analyzes the content of the conversation between the participants 1 and identifies the topic and its duration, thereby extracting particularly important or popular topics from the conversation. This information becomes important data for evaluating the quality of the conversation and clarifies what topics the participants 1 are interested in. This allows for detailed analysis of the conversation and acquires basic data for improving the quality of communication between the participants 1.

[0251] Furthermore, the communication support device 20 can analyze the correlation level during the topic period extracted by the topic extraction unit 127 and evaluate the emotional connection between the participants 1 based on this. A high correlation level indicates strong emotional synchronization between the participants 1 and an active conversation. Conversely, a low correlation level suggests low empathy or interest in the conversation. This allows for a detailed emotional evaluation of each part of the conversation, allowing for a deeper understanding of the compatibility and relationship between the participants 1.

[0252] Furthermore, the topic output unit 128 has a function of displaying topics on the screen with an emphasis level according to the correlation level. This function allows participant 1 to grasp at a glance the particularly important topics or topics that generated excitement in the conversation. The highlighting provides visual feedback, helping participant 1 intuitively understand which parts of their conversation particularly attracted their attention and which topics resonated with them. This allows for effective topic selection and improved communication in the next conversation or date.

[0253] Here, "highlighting" refers to displaying topics with a high correlation level in bold, with a different color, a different background color, or by adding an icon, allowing Participant 1 to immediately grasp, just by looking at the screen, which topics particularly resonated with them and which parts created a strong emotional connection.Specific examples include bolding, changing the font size, changing the color, changing the background color, adding icons or marks, and using animation.

[0254] The exchange support unit 210 of the exchange support device 20 has an interest content acquisition unit 129 that determines common interest content between participants 1 based on the correlation level during the topic period extracted by the topic extraction unit 127 and the topics continued during the topic period, and the topic output unit 128 has a configuration that displays the interest content on the screen of the participant terminal 50.

[0255] According to the above configuration, the interaction support device 20 can identify a topic that particularly attracted interest from among the topics shared between the participants 1 using the interest content acquisition unit 129. Specifically, the correlation level during the topic period extracted by the topic extraction unit 127 is analyzed, and the shared interest content between the participants 1 is extracted from the results. This interest content is identified based on topics that were particularly popular during the conversation or topics that both participants were interested in, and therefore is very important information in evaluating the degree of matching between the participants 1.

[0256] Furthermore, by having the topic output unit 128 display the content of interest on the participant terminal 50, participant 1 can intuitively grasp the content of their common interests. This allows for effective communication based on the content of their common interests in the next conversation or date. For example, by displaying common hobbies or interests, participant 1 can develop a conversation centered on those topics, leading to deeper understanding and intimacy.

[0257] The communication support unit 210 of the communication support device 20 includes a communication control unit 121. The communication control unit 121 has a function of transmitting various information and data to the participant terminal 50, the administrator terminal 30, and the organizer terminal 40 via the communication unit 112. The communication control unit 121 has a function of managing the transmitted information and data to ensure accuracy and data integrity. That is, the communication control unit 121 has a function of detecting errors that may occur during communication and ensuring reliability by retransmitting or correcting the data. Furthermore, the communication control unit 121 has a function of managing the transmission of data using an appropriate communication protocol when transmitting information and data to the participant terminal 50, etc., a function of detecting errors during data transmission and taking appropriate action, and a function of encrypting the transmitted information to prevent unauthorized access by third parties and information leaks.

[0258] The exchange support unit 210 of the exchange support device 20 has an information receiving unit 211 that receives exchange information including conversation information and instruction information. The information receiving unit 211 has a text input function that receives exchange information in text format input from the participant terminal 50, the administrator terminal 30, or the organizer terminal 40. In addition to the text input function, the information receiving unit 211 also has a voice input function that allows questions and requests to be input by voice, a file attachment function that allows files related to questions and requests to be attached, and the like.

[0259] Furthermore, the information receiving unit 211 has an activation function. The activation function enables data communication only with authenticated participant terminals 50, administrator terminals 30, and organizer terminals 40. The administrator terminal 30 is a terminal device operated by an administrator who manages the communication support system 10. The activation function verifies whether an activation signal transmitted from a specific participant terminal 50, administrator terminal 30, or organizer terminal 40 matches pre-set authentication information. Examples of authentication methods include authentication modes that combine one or more authentication elements, such as password authentication, biometric authentication, one-time password authentication, and smart card authentication using a card with an embedded IC chip. This allows the communication support device 20 to communicate data only with authenticated participant terminals 50, administrator terminals 30, and organizer terminals 40, making it less likely for information to leak.

[0260] The activation function may be used for authentication of specific terminals 30, 40, and 50. The activation function may also be provided between the relationship building unit 230 and the exchange support database 220 (storage unit) in FIG. 40, enabling data communication only between the authenticated relationship building unit 230 and the exchange support database 220. In this case, when the exchange support database 220 is installed in a location away from the relationship building unit 230 and is accessible via a data communication network such as the Internet 5, unauthorized access from outside can be prevented.

[0261] The communication support device 20 includes a communication unit 112. The communication unit 112 has a communication function for establishing communication with a participant terminal 50 operated by the participant 1. The communication unit 112 is configured to establish communication with the participant terminal 50, as well as with the administrator terminal 30 and the organizer terminal 40. The communication unit 112 may also be connected to a biometric tester 60 that detects biometric information, including the heart rate, of the participant 1. The communication unit 112 is capable of communicating with the terminals 30, 40, and 50 via a data communication network (network N) such as the Internet 5. Here, examples of the "data communication network" include the Internet 5, an intranet, an extranet, a mobile communication network, a wide area network (WAN), a local area network (LAN), a metropolitan area network (MAN), and a satellite communication network.

[0262] The communication unit 112 is constructed with a highly reliable hardware configuration to reliably establish communication and facilitate smooth information exchange between the participant terminals 50, the administrator terminal 30, and the organizer terminal 40. Specifically, the communication unit 112 is equipped with a network interface card (NIC) to ensure high-speed data transfer and stable connections and minimize the risk of delays and data loss. The communication unit 112 also includes routers and switches for efficient routing and distribution of data packets and for optimizing network traffic management. Furthermore, the communication unit 112 is equipped with a firewall and an intrusion detection system (IDS) to protect the network from external unauthorized access and internal security threats and enhance data protection for the participant 1.

[0263] Note that data communication between the communication unit 112 and the participant terminal 50, etc., is not limited to a data communication network such as the Internet 5, and Bluetooth (registered trademark), a wireless communication standard for short-range communication, may also be used. Furthermore, data communication may be via a dedicated line to prevent information leakage. Furthermore, when data communication is performed between the communication unit 112 and the participant terminal 50, etc., via the Internet 5, it is preferable that the communication unit 112 and the participant terminal 50, etc., have a VPN (Virtual Private Network) function. If a VPN function is incorporated into the communication unit 112, the participant terminal 50, etc., data communication from the participant terminal 50, for example, is routed via a VPN connection, thereby protecting the data from unauthorized external access and ensuring secure communication.

[0264] As described above, the communication support device 20 includes the communication support unit 210 and the communication unit 112. Some or all of the components of the communication support unit 210, excluding the communication unit 112, may be configured using either hardware or software. The communication support device 20 may also include an input device and a display device (not shown). Examples of the input device include a keyboard, mouse, touch panel, and voice input device. Examples of the display device include a liquid crystal display device. This allows the communication support device 20 to be configured using information processing devices such as general personal computers, laptop computers, smartphones, and tablet terminals. The communication support device 20 may lack at least one of the input device and the display device. In this case, at least one of the input device and the display device is provided in an external terminal (not shown), allowing the communication support device 20 to be used as a communication support server. Furthermore, the communication support device 20 may also be used as a participant terminal 50, an administrator terminal 30, or an organizer terminal 40.

[0265] In this embodiment, the case where the functions of the communication support device 20 are installed in an information processing device is described, but the present invention is not limited to this, and the functions of the communication support device 20 may be installed in cloud computing. In this case, cloud computing allows computer resources to be added as needed, making it possible to process large amounts of information, enabling faster and more efficient processing, and also making it possible to easily expand processing capacity to accommodate a significant increase in the number of participants 1.

[0266] The participant terminal 50 is a terminal device operated by the participant 1, the administrator terminal 30 is a terminal device operated by the administrator, and the organizer terminal 40 is a terminal device operated by the organizer. The participant terminal 50, the administrator terminal 30, and the organizer terminal 40 are information processing devices such as general personal computers, laptop computers, smartphones, and tablet terminals. The participant terminal 50 communicates with the exchange support database 220 (see FIG. 40) via the Internet 5 and provides an interface for the participant 1 to search for information about themselves and their exchange partners and to check matching results. This allows the participant terminal 50 to easily engage in exchange activities at home or while on the move.

[0267] The administrator terminal 30 is a terminal device operated by an administrator and is used to operate and manage the entire exchange support system 10 implemented by the exchange support device 20. The administrator uses the administrator terminal 30 to perform various management tasks to ensure smooth operation of the exchange support system 10. Specifically, the administrator uses the administrator terminal 30 to view, update, and delete information such as participant 1's profile information, activity history, and matching results, thereby keeping the data in the system accurate and up-to-date. The administrator also adjusts the settings and parameters of the exchange support system 10. Furthermore, the administrator responds to inquiries and support requests from participants 1, receives feedback and problem reports from participants 1, and responds to them promptly and appropriately to improve participant 1 satisfaction. The administrator is also involved in planning and running exchange events, managing the event schedule, participant registration, and operational support on the day of the event through the administrator terminal 30.

[0268] The organizer terminal 40 is a terminal device operated by the organizer and is used to plan, operate, and manage the social event. The organizer uses the organizer terminal 40 to perform various operational tasks with the aim of ensuring the success of the social event. Specifically, the organizer uses the organizer terminal 40 to plan and schedule the event, as well as to register and manage participants (participants 1) who will participate in the event. Furthermore, the organizer manages the operation on the day of the event, monitors the progress of the event in real time using the organizer terminal 40, and takes prompt action as necessary. Examples of such tasks include confirming the arrival of participants, managing the progress of the program, and responding to unexpected problems. The organizer also performs follow-up after the event ends. The organizer uses the organizer terminal 40 to collect feedback from participants and identify evaluations and areas for improvement.

[0269] The biometric tester 60 is a device for detecting biometric information of the participant 1. The biometric tester 60 has the function of collecting various biometric information, including the participant 1's heart rate, in real time. The biometric tester 60 has the function of recording the participant 1's physiological responses in detail and transmitting the data to the participant terminal 50. Specifically, the biometric tester 60 detects biometric information such as heart rate, respiratory rate, galvanic skin response (GSR), and body temperature using sensors. This information serves as basic data for evaluating the participant 1's emotional state, stress level, relaxation level, and so on. For example, by the communication support device 20 grasping the fluctuations in the participant 1's heart rate during a conversation in real time, it is possible to analyze which parts of the conversation the participant 1 was particularly excited or relaxed in. This makes it possible to provide important indicators for evaluating the level of excitement and compatibility of the conversation.

[0270] The biometric tester 60 is typically designed as a wearable device, and is formed in a shape that is easy for the participant 1 to use on a daily basis, such as a wristwatch, wristband, earring, or chest-mounted heart rate sensor. This allows the participant 1 to wear it comfortably and enables data collection over long periods of time. The biometric tester 60 can also be connected to the participant terminal 50 using wireless communication technology such as Bluetooth or Wi-Fi, and transmits collected data in real time. This data is stored in the communication support database 220 (see FIG. 40 ) of the communication support device 20 and used for later analysis and feedback.

[0271] [Large-Scale Language Model] FIGS. 40 and 41 are explanatory diagrams showing the flow of information in the communication support system.

[0272] 40 and 41 show a modified example of the exchange support system 10 according to the second embodiment. In this example, the exchange support device 20 has a relationship building unit 230 that supports the building of relationships between the participants 1 based on the matching degree between the participants 1, their profile information, and their interests. The relationship building unit 230 is a functional configuration included in the control unit 110 described in the first embodiment. That is, the control unit 110 has the exchange support unit 210 and the relationship building unit 230.

[0273] The relationship building unit 230 has functions to effectively support interactions between participants 1, and is a computer (control unit) that has various functions to provide optimal matching using a large-scale language model based on the degree of matching between participants 1 and the profile information and interest information of participants 1, and to support smooth communication.

[0274] Specifically, the relationship building unit 230 has a large-scale language model unit 231 having a large-scale language model that combines one or more types of natural language processing to probabilistically predict how likely words and sentences given in the prompt are to occur in natural language; an exchange support prompt generation unit 232 that, when it receives interest content information from the topic extraction unit 127, includes the interest content in the prompt of the large-scale language model unit 231 and causes the large-scale language model to generate exchange support information with content suitable for relationship building based on the matching degree between participants 1 and profile information in the exchange support database 220; and a support information output unit 233 that transmits the exchange support information generated by the large-scale language model to the participant terminal 50, administrator terminal 30, and organizer terminal 40 via the communication unit 112.

[0275] The large-scale language model unit 231 includes a large-scale language model. Here, the "large-scale language model" is a type of probabilistic model used in natural language processing, and is a model for probabilistically predicting how likely a given word or sentence is to occur in natural language. Specifically, the language model calculates the occurrence probability of a given word string or sentence, or compares the occurrence probabilities of multiple word strings or sentences, thereby enabling the automatic generation of the most likely word or sentence based on the context when predicting the next word or sentence, or the generation of a sentence that satisfies specific conditions. That is, the large-scale language model is a language model that probabilistically predicts how likely a word or sentence given in a prompt is to occur in natural language by combining one or more types of natural language processing processes, such as morphological analysis, syntactic analysis, semantic analysis, context analysis, and intention analysis. The large-scale language model unit 231 is configured to analyze a prompt that instructs the generation of communication support information using the large-scale language model, and to predict and generate communication support information using the large-scale language model based on the content of the analyzed prompt.

[0276] "Natural language processing" enables a computer to understand text and audio data written in natural language and execute processing appropriate to the purpose. Specific examples include morphological analysis, which breaks natural language down into "morphemes," the smallest units that make up the language, and assigns information such as parts of speech; syntactic analysis, which analyzes the grammatical structure of natural language to clarify the structure and meaning of a sentence; semantic analysis, which analyzes the meaning of natural language to understand the meaning of words and sentences and make logical judgments and inferences; contextual analysis, which understands natural language while taking into account the context before and after a sentence; and intent analysis, which extracts the intention of a speaker or writer from a conversation or sentence using natural language. "Natural language processing" processes natural language by combining processes such as morphological analysis, syntactic analysis, semantic analysis, contextual analysis, and intent analysis, and enables the generation of communication support information to support the communication activities of this embodiment, machine translation, automatic summarization, question-answering systems, and speech recognition.

[0277] A "prompt" refers to a word or sentence input to the large-scale language model unit 231, and serves as a starting point for the large-scale language model to generate interaction support information. The generation of interaction support information by a large-scale language model based on a prompt is a major difference from normal (conventional) machine learning. In normal machine learning, a model learns from training data and predicts output data for input data. For example, an image recognition machine learning model learns from training data of images of cats and dogs and classifies the input image as either a cat or a dog. On the other hand, in generating interaction support information using a large-scale language model, the model learns from training data as well as prompts that provide instructions and information regarding the output data that the model is desired to generate.

[0278] To explain in more detail, while in conventional machine learning, the model can only generate content contained in the training data, a large-scale language model can generate new content that is not contained in the training data by using prompts. For example, by entering a prompt such as "Please suggest a topic that the user will share an interest in in the next conversation," the model can understand the context of the conversation and generate new topics.

[0279] Furthermore, while conventional machine learning models can only generate variations of content contained in training data, large-scale language models can generate new variations of output data that are not contained in training data using prompts. For example, by entering the prompt "Please suggest a new movie genre in the context of the user talking about movies," the model can suggest new movie genres that are not based on previous data.

[0280] Furthermore, while conventional machine learning models can only generate new content by recursively combining content contained in training data, large-scale language models can generate creative content not contained in training data using prompts. For example, by entering the prompt "Please suggest some creative ideas to talk about on our next date," the model can creatively suggest completely new date plans and conversation topics. In this way, by using prompts, large-scale language models can provide new content, variations, and creative information that cannot be generated by conventional machine learning models.

[0281] According to the above configuration, when interest content information is received from the interaction support unit 210, this interest content information is included in a prompt and input to the large-scale language model, and the large-scale language model generates interaction support information suitable for interactions between participants 1. If profile information is insufficient, interaction support information requesting additional information is generated and sent to participant 1, thereby completing the necessary profile information.

[0282] Furthermore, it is preferable that the large-scale language model unit 231 has a large-scale language model specialized for creating communication support information. That is, the large-scale language model is trained and adjusted to generate communication support information through sentence generation and question answering based on the profile information in the communication support database 220, thereby being specialized for creating communication support information. Specifically, it is preferable that the large-scale language model unit 231 has a large-scale language model specialized for creating communication support information, which is trained and adjusted to probabilistically predict how likely words and sentences given in the prompt are to occur in natural language based on the profile information in the communication support database 220 by combining one or more types of natural language processing, and generate communication support information through sentence generation and question answering. As a result, the large-scale language model unit 231 has a large-scale language model specialized for creating communication support information using natural language processing based on the information in the communication support database 220, thereby improving generation accuracy and efficiency. In other words, the large-scale language model unit 231 can generate more realistic and specific communication support information by having the large-scale language model focus on learning vocabulary, grammar, example sentences, templates, etc. related to the communication support information, and can generate the information in a shorter time by optimizing the generation process.

[0283] The large-scale language model unit 231 may be configured to provide communication support information to others through an API (Application Programming Interface). The large-scale language model unit 231 can widely share the high-value communication support information it generates with other businesses and systems, thereby extending the efficiency of the communication support process to other businesses and systems. The large-scale language model unit 231 may also use a large-scale language model provided by another organization (such as a company or a university) via an API. Furthermore, the large-scale language model of the large-scale language model unit 231 may be linked to a large-scale language model of another organization via an API.

[0284] According to the above configuration, the large-scale language model learns based on the detailed profile information in the communication support database 220 and generates communication support information suited to the needs and characteristics of the participant 1, thereby improving the quality and accuracy of information for smooth communication between the participants 1. In addition, support information customized according to the specific communication needs of each participant 1 is provided, enabling communication support optimized for each participant 1.

[0285] When the exchange support prompt generation unit 232 receives interest content information from the interest content acquisition unit 129 of the exchange support unit 210, it has the function of including the interest content information in the prompt of the large-scale language model unit 231 and causing the large-scale language model to generate exchange support information with content suitable for exchange based on the profile information in the exchange support database 220 and the matching degree information between participants 1.

[0286] The exchange support prompt generation unit 232 exists as a module independent of the large-scale language model unit 231. The reason for this is that the exchange support prompt generation unit 232 has the role of generating appropriate prompts based on the content of interest from the exchange support unit 210, which is different from the natural language processing role of the large-scale language model unit 231. For this reason, treating the two as independent modules makes it possible to clearly distinguish their respective roles and facilitate system design and maintenance. Furthermore, implementing the exchange support prompt generation unit 232 as an independent module makes it possible to flexibly respond when the large-scale language model is updated.

[0287] The interaction support prompt generation unit 232 has an interface for accepting the interest content received from the interaction support unit 210 and prompt generation logic for generating a prompt with content instructing the creation of interaction support information based on the received interest content. The prompt generation logic is for selecting a prompt template appropriate for the interaction support information. This selection uses conditional branching to select a prompt template that matches the interaction support information. The interaction support prompt generation unit 232 also has a prompt transmission interface for transmitting the generated prompt to the large-scale language model unit 231.

[0288] The prompt templates for the communication support prompt generation unit 232 are prepared in advance. The prompt templates provide a framework for document structure and content that serves as the basis for effectively creating communication support information in the communication support prompt generation unit 232. These templates are customized and designed in advance according to the needs and circumstances of participant 1. Specifically, the prompt templates predefine questions and information formats that match the interests and intentions of participant 1.

[0289] For example, if participant 1 is interested in sports, the prompt template may include specific questions such as "Tell me about a sporting event that you've been following recently" or "Who is your favorite athlete? Why?" This allows the large-scale language model unit 231 to provide detailed information and topics related to topics that interest participant 1. Furthermore, if participant 1 is interested in traveling, the prompt template may include questions such as "What places would you recommend for our next trip?" or "What was the most memorable place on your recent trip?" In this way, the prompt template can be flexibly customized according to participant 1's specific interests, making the generated interaction support information more valuable to participant 1.

[0290] Furthermore, the prompt template is designed taking into consideration the participant 1's past activity history and profile information. For example, by constructing questions based on events the participant has previously attended and interests previously expressed, the participant 1 can receive more personalized feedback. This allows the exchange support device 20 to provide support for the participant 1 to continue a natural and interesting conversation and promote relationship building. In this way, the exchange support prompt generation unit 232 plays a role in generating effective exchange support information and supporting the participant 1's communication by utilizing prompt templates based on the participant 1's interests and concerns. This allows the participant 1 to receive specific advice and topics of conversation to build deeper relationships and achieve effective communication.

[0291] The exchange support prompt generation unit 232 may be constructed using a rule-based logic circuit or a machine learning model. In the rule-based case, prompts are generated using explicit conditional branching and transition rules. On the other hand, in the case of a machine learning model, more flexible prompt generation is possible using a model learned from data (information) in the exchange support database 220. With this configuration, the exchange support prompt generation unit 232 generates appropriate prompts and transmits them to the large-scale language model unit 231, thereby enabling effective conversations according to the exchange process.

[0292] Preferably, the exchange support prompt generator 232 is configured to receive various information, such as profile information, stored in the exchange support database 220. Based on this information, the needs of participant 1 are continuously evaluated and the prompt template is updated. In this case, for example, for participant 1 who has interacted with a particular participant multiple times in the past, a prompt containing updated information about new interactions and progress from the same participant is generated. This allows the exchange support device 20 to encourage participant 1 to build a sustainable relationship with participants who have interacted with participant 1, thereby encouraging continuous interaction.

[0293] Furthermore, for participant 1 who has participated in a particular event in the past, for example, new event suggestions may be made based on feedback and results from the event they previously participated in, and prompts may be generated to help participant 1 understand how their own interaction attitude and abilities were received and what impact they had. Furthermore, by utilizing information accumulated in the interaction support database 220, prompts may be generated to understand the relationship between participant 1 and participants with whom they are currently interacting and to make corresponding improvement suggestions. This allows participant 1 to receive specific advice and improvement suggestions to continue better interactions.

[0294] According to the above configuration, as shown in FIG. 41, the large-scale language model unit 231 of the communication support device 20 learns using information such as profile information from the communication support database 220, which has each database 221 to 226, and generates communication support information in response to the interest content information identified by the interest content acquisition unit 129 and prompts from the communication support prompt generation unit 232.

[0295] As a result, the exchange support device 20 can fully support exchange activities by generating exchange support information using a large-scale language model specialized for creating exchange support information. In particular, by using a large-scale language model to generate exchange support information rather than ordinary machine learning, it is possible to generate new content and variations that are not included in the training data, making it possible to generate flexible and diverse exchange support information tailored to the content of the exchange, and to generate creative content that is not included in the training data.

[0296] Furthermore, because the accuracy of the large-scale language model can be improved through learning, it is possible to learn from past successes and continuously generate more effective communication support information. That is, it is possible to analyze the results of interactions stored in the communication support database 220 and generate communication support information that reflects improvements, or to reflect feedback from participant 1 and generate communication support information that provides even greater satisfaction to participant 1.

[0297] In this way, when using a large-scale language model, the communication support device 20 provides advanced functions that are difficult to achieve with conventional machine learning approaches. Specifically, the device utilizes the unique capabilities of large-scale language models, such as complex text generation using natural language processing and context-based content generation. Conventional machine learning models typically perform prediction, classification, clustering, and other tasks using primarily numerical and categorical data, and are limited in their ability to process large amounts of text data and generate new text. On the other hand, large-scale language models are adept at learning language patterns from large amounts of text data and generating new text based on given prompts. Therefore, in situations that require the use of diverse and complex language, such as communication support information, an approach using a large-scale language model is more appropriate, and it is possible to provide functions that are difficult to achieve with conventional machine learning methods alone.

[0298] When the interaction support prompt generation unit 232 receives a request for matching results suitable for interaction between participants 1 from the participant terminal 50 or the like, the prompt may include content requesting display of a list of a predetermined number of matching results (matching degrees) in order from the most suitable to the least suitable. According to the above configuration, the interaction support information generated by the large-scale language model displays the most suitable matching results, or matching degrees, in order from highest to lowest, thereby enabling the participant 1 to efficiently and effectively find an interaction partner, thereby improving the success rate of interaction and satisfaction.

[0299] [Interaction Support Database] Fig. 42 is a diagram showing an example of a conversation information database. Fig. 43 is a diagram showing an example of a heart rate information database. Fig. 44 is a diagram showing an example of a matching degree information database. Fig. 45 is a diagram showing an example of a topic extraction information database.

[0300] Next, the exchange support database 220 will be described in detail. The exchange support database 220 is a storage unit corresponding to the storage unit 111 described in the first embodiment. The exchange support database 220 is connected to the exchange support unit 210 and the relationship building unit 230 so that data can be communicated therewith. The exchange support database 220 may be configured with a hard disk, or may be configured with a combination of a hard disk and memory. In the case of a configuration that combines a hard disk and memory, some of the data and indexes used by the database are cached in the memory as needed, thereby enabling faster access to the database. The exchange support database 220 may be a data server connected to an information communication network such as the Internet 5, separate from the exchange support device 20. The exchange support database 220 may also be configured with multiple data servers, one for each database.

[0301] As shown in FIG. 41, the communication support database 220 includes a basic information database 221, a profile information database 222, a conversation information database 223, a heart rate information database 224, a matching degree information database 225, a topic extraction information database 226, and other databases 227.

[0302] The basic information database 221 is a database for recording basic information about the participants 1 in the interaction support device 20. This database records detailed personal information about the participants 1, and serves to provide a foundation for effectively matching participants 1 and supporting interactions.

[0303] Specifically, the basic information database 221 includes items such as user ID, name, gender, age, address, telephone number, email address, and registration date. The user ID is an identification number that uniquely identifies each user and is used for linking with and searching other databases. The name is the user's name and is basic information for identifying an individual. Gender and age are important elements for forming a user profile and also play important roles in the matching algorithm.

[0304] The address provides information about the user's place of residence and is used to provide opportunities for participation in local events and social interactions. The phone number and email address are recorded as means of contacting the user and are used to contact the user in emergencies and send important notices. The registration date indicates the date the user registered in the system and is important information for tracking the user's activity history.

[0305] The profile information database 222 is a database for recording detailed profile information of the participants 1 in the interaction support device 20. The profile information database 222 records detailed information about the participants 1, such as their hobbies and interests, occupation, educational background, self-introduction, and ideal partner criteria. This information is used to realize effective matching and interaction support between the participants 1.

[0306] The hobbies and interests section records the activities and hobbies that Participant 1 is interested in. This makes it easier for Participant 1 to find people with common interests and improves the quality of their interactions. For example, specific hobbies such as reading, watching movies, and sports are recorded. The occupation section records Participant 1's current occupation. This allows Participant 1 to find people with similar occupations and job types, helping to deepen common topics and understanding. For example, occupations include engineer, designer, and teacher. The education section records Participant 1's highest level of education. This allows Participant 1 to find people with similar educational backgrounds and to engage in intellectual exchanges and share common educational experiences. For example, university department and major are recorded.

[0307] The self-introduction section records a brief self-introduction by Participant 1. This allows Participant 1 to convey his or her personality and interests to other users, improving the first impression on the person he or she meets for the first time. For example, a specific introduction such as "Hello, I'm Taro Sato. My hobbies are reading and traveling" is included. The ideal partner conditions section records the conditions that Participant 1 considers ideal in a partner. This makes it easier for Participant 1 to find a partner who is close to his or her ideal, enabling effective matching. For example, specific conditions such as "someone who likes reading and is interested in traveling" are included.

[0308] The conversation information database 223 is a database for recording in detail the content of conversations between participants 1. The conversation information database 223 records the content of conversations between participants 1 and other participants 1 by time. This allows for a detailed analysis of what topics were discussed during the conversation and what exchanges took place.

[0309] For example, as shown in Fig. 42, the conversation information database 223 records the contents of conversations that Participant 1 with Participant ID 0001 had with Participant 1 with Participant ID 0002, Participant ID 0003, and Participant ID 0004, each lasting 10 minutes. Specifically, the following data is included:

[0310] In the conversation between participant ID 0001 and participant ID 0002, the content of the conversation is recorded every minute, such as "Hello, how are you?" at 12:00, "Tell me about your recent trip" at 12:01, and "What kind of book are you reading?" at 12:02. This data makes it possible to track in detail the changes in topics as the conversation progresses. Next, in the conversation between participant ID 0001 and participant ID 0003, the following are recorded: "Hello, how are you doing lately?" at 12:11, "Do you like watching sports?" at 12:12, and "What's your favorite sport?" at 12:13. This makes it possible to compare the differences and similarities in topics in conversations with different participants.

[0311] Furthermore, the conversation between participant ID 0001 and participant ID 0004 is recorded as follows: "Hello, how are you today?" at 12:22, "Show me some photos you've taken recently" at 12:23, and "Do you like going to cafes?" at 12:24. By recording the specific content of each conversation in detail in this way, it becomes possible to objectively evaluate participant 1's interests and the flow of the conversation.

[0312] The conversation information database 223 stores these detailed conversation contents, thereby providing valuable information for evaluating the quality of communication between participants 1. By utilizing the conversation information database 223, the exchange support device 20 can provide effective feedback and advice to participants 1 and support the building of better relationships. Furthermore, by analyzing the conversation contents, it is possible to understand which topics were particularly popular and what topics participant 1 is interested in, which can be used for future exchanges.

[0313] The heart rate information database 224 is a database for recording in detail the physiological responses of the participant 1. The heart rate information database 224 records the heart rate of the participant 1 at predetermined time intervals when the participant 1 is conversing with another participant 1. This provides basic data for analyzing the physiological responses during the conversation and evaluating the quality of the interaction between the participants.

[0314] For example, as shown in Fig. 43, heart rate data is recorded when participant 1 with participant ID 0001 had a 10-minute conversation with participants 1 with participant IDs 0002, 0003, and 0004. Specifically, the following data is included:

[0315] In a conversation between participant ID 0001 and participant ID 0002, participant ID 0001's heart rate was recorded as 80 at 12:00, 85 at 12:01, and 88 at 12:02. Similarly, participant ID 0002's heart rate was also recorded at the same time, making it possible to compare and analyze the physiological responses of both participants. This data allows for detailed tracking of changes in heart rate as the conversation progresses. Furthermore, in a conversation between participant ID 0001 and participant ID 0003, participant ID 0001's heart rate was recorded as 79 at 12:11, 82 at 12:12, and 85 at 12:13, and participant ID 0003's heart rate was also recorded in the same way. This makes it possible to compare heart rate fluctuations during conversations with different participants. Furthermore, for the conversation between participant ID 0001 and participant ID 0004, the heart rate of participant ID 0001 is recorded as 81 at 12:22, 84 at 12:23, and 87 at 12:24, and the heart rate of participant ID 0004 is also recorded in the same manner. In this way, by recording detailed conversation data with multiple participants, it becomes possible to objectively evaluate the level of excitement and tension in each conversation.

[0316] By accumulating this detailed heart rate data, the heart rate information database 224 provides valuable information for evaluating the emotional connection and quality of communication between the participants 1. By utilizing the heart rate information database 224, the communication support device 20 can provide effective feedback and advice to the participants 1 and support building better relationships. While FIG. 43 shows the heart rate of each participant 1 every minute for convenience, in reality, the heart rate is recorded at shorter time intervals (e.g., 0.5-second intervals, 1-second intervals, 2-second intervals, 5-second intervals, 10-second intervals, etc.). For example, similar to the first embodiment, the heart rate of each participant 1 can be configured to be recorded in the storage unit at 1-second intervals.

[0317] 44, the matching degree information database 225 is a database for recording in detail the degree of matching between participants 1. The matching degree information database 225 records detailed data when a participant 1 has a conversation with another participant 1. This provides basic data for evaluating the compatibility of each conversation session and proposing effective matching and interactions.

[0318] Specifically, the matching degree information database 225 contains the following information: A conversation ID is an identification number that uniquely identifies each conversation session and is used to distinguish conversations between participants. Participant ID 1 is the ID of the first participant who joined the conversation, and participant ID 2 is the ID of the other participant 1. This makes it possible to accurately determine which participant 1 participated in which conversation.

[0319] The event ID is an identification number that uniquely identifies the event in which the conversation took place. The event date indicates the date on which the conversation took place. The conversation start time and conversation end time indicate the start and end times of each conversation, which allow the duration of each conversation session to be identified. The matching degree indicates the compatibility between participants, evaluated based on changes in heart rate over time. The higher the matching degree, the better the compatibility between participants, and the better the interaction can be expected.

[0320] For example, the matching degree is 80.35 in a conversation between participant ID 0001 and participant ID 0002. The matching degree can be calculated using the correlation analysis method described in the first embodiment, but as described above, a text analysis of the conversation content may be added as a matching element, and correlation analysis may be performed using a large-scale language model.

[0321] By accumulating such detailed conversation data, the matching degree information database 225 evaluates the compatibility between participants 1 and provides valuable information for proposing more effective matching and interactions. By utilizing the matching degree information database 225, the exchange support device 20 can provide appropriate feedback and advice to participants 1 and support relationship building. This makes it easier for participants 1 to find partners and exchange partners that suit them, enabling better communication and relationship building.

[0322] 45, the topic extraction information database 226 is a database for recording in detail the degree of excitement of each topic in a conversation between participants 1. The topic extraction information database 226 records in detail the conversation ID, the title (topic) extracted from the conversation content, the start time and end time of each topic, and the degree of excitement from the start time to the end time of each topic.

[0323] 45, in the conversation session with conversation ID "001_01_02" (a conversation between participant 1 with participant ID 0001 and participant 1 with participant ID 0002), the first topic is "greetings," which is discussed between 12:00 and 12:01, with an excitement level of 79.18 during this period. The next topic is "recent travel," which is discussed between 12:01 and 12:02, with an excitement level of 88.32 during this period.

[0324] The excitement level is the correlation level of the change in heart rate over time from the start time to the end time of each topic. The correlation analysis method for calculating the excitement level can be the same as the correlation analysis method for calculating the matching level. In other words, the matching level is calculated by performing a correlation analysis on the change in heart rate over time from the start to the end of a conversation between one participant 1 and another participant 1. In contrast, the excitement level is calculated by performing a correlation analysis on the change in heart rate over time from the start to the end of a topic.

[0325] In this way, the topic extraction information database 226 can extract specific content from the conversation and quantify the participants' physiological responses to each topic, thereby evaluating which topics were particularly popular. Based on this data, it is possible to analyze which topics particularly attracted the interest of participants 1.

[0326] The topic extraction information database 226 provides a foundation for the interaction support device 20 to provide more effective feedback and advice to the participant 1. By using the topic extraction information database 226, the participant 1 can understand which topics were particularly popular and use this information as a reference for future conversations and interactions.

[0327] Other examples of databases 227 include an activity history database that records participant 1's past activities and event participation history, a message history database that records the history of messages exchanged between participants, an evaluation feedback database that records participants' feedback and evaluations of events and activities, a hobby / interest tag database that records participant 1's specific hobbies and interests in tag form, an image / media database that stores media files such as images and videos uploaded by participants, a survey database that records the results of surveys answered by participant 1, and a behavioral analysis database that records and analyzes participant 1's behavioral history within the system.

[0328] <Third Embodiment> The first and second embodiments have been described above. The third embodiment will now be described. The basic configuration of the exchange support system 10 according to the third embodiment is the same as that of the exchange support system 10 according to the first and second embodiments. In the following description, components that are the same as those of the exchange support system 10 according to the first and second embodiments will basically be assigned the same reference numerals. Furthermore, explanations of parts that apply to the third embodiment as well as the first and second embodiments will be omitted.

[0329] In the above description, even if a statement is made that is limited to the exchange support system 10 according to the first embodiment, such as "in the first embodiment," it can also be applied to the exchange support system 10 according to the third embodiment, so long as it does not deviate from the spirit of the third embodiment. Similarly, in the above description, a statement that is made that is limited to the exchange support system 10 according to the second embodiment can also be applied to the exchange support system 10 according to the third embodiment, so long as it does not deviate from the spirit of the third embodiment. Therefore, it is possible to partially replace or combine each configuration shown in the first and second embodiments (including each configuration shown in the modified examples) with the configuration shown in the third embodiment.

[0330] Furthermore, even if the configuration is different from that of the communication support system 10 according to the first and second embodiments, the same reference numerals may be used for convenience to designate components having similar functions. Furthermore, even if the configuration is the same as that of the communication support system 10 according to the first and second embodiments, different reference numerals may be used for convenience to designate components having similar functions.

[0331] 46 and 47 are flowcharts showing the conversation start process on the participant terminal side and the conversation start process on the interaction support server side. Fig. 48 is a diagram showing an example of a conversation start operation acceptance screen.

[0332] The participant terminal-side conversation start processing is processing performed on the participant terminals 50 (participant terminal 50 of participant A and participant terminal 50 of participant B) when a conversation between one participant (participant A) and another participant (participant B) starts. The exchange support server-side conversation start processing is processing performed on the exchange support server 20 when a conversation between one participant (participant A) and another participant (participant B) starts.

[0333] In the conversation start process on the participant terminal side, the control unit 150 of the participant terminal 50 executes the processes of steps S1501 to S1511 shown in Figures 46 and 47. In the conversation start process on the exchange support server side, the control unit 110 of the exchange support server 20 executes the processes of steps S1201 to S1205 shown in Figures 46 and 47.

[0334] The processing in steps S1501 to S1508 and step S1511 is similar to the processing in steps S501 to S508 and step S510 in Fig. 15, and therefore a description thereof will be omitted here. Also, the processing in steps S1201 to S1205 is similar to the processing in steps S241 to S245 in Fig. 15, and therefore a description thereof will be omitted here. The processing in steps S1509 and S1510 will be described below.

[0335] In the participant terminal-side conversation start processing, after executing the processing of step S1508, the control unit 150 of the participant terminal 50 executes a recording start operation acceptance processing (step S1509). In this processing, the control unit 150 displays a conversation start operation acceptance screen on the display unit 152. In the third embodiment, a conversation between one participant (participant A) and another participant (participant B) is recorded at the participant terminal 50. Accordingly, as shown in FIG. 48 , the conversation start operation acceptance screen has a recording start instruction input area 1001.

[0336] The recording start instruction input area 1001 is an area where an image corresponding to a round button (recording start instruction button) is displayed. When the conversation start operation reception screen is displayed, a participant can input an instruction to select the recording start instruction button (recording start instruction input) in the recording start instruction input area 1001. When the recording start instruction is input, recording begins, and the control unit 150 of the participant terminal 50 continuously stores data (audio data) corresponding to the audio input from the audio input unit 154 in the storage unit 151. Note that a conversation between one participant (participant A) and another participant (participant B) can be configured to be recorded only on the participant terminal 50 of one of the participants. Participant A and participant B can decide in advance which participant terminal 50 will record the conversation, and only the participant in charge of recording (recording staff) needs to input the recording start instruction.

[0337] Alternatively, the organizer may designate a person in charge of recording in advance by operating the organizer terminal 40. In this case, for example, the following configuration is possible. The organizer terminal 40 transmits information indicating the person in charge of recording (recording person information) in association with information indicating the participants (participant A and participant B) to the exchange support server 20, and the exchange support server 20 manages the recording person information. The exchange support server 20 then identifies which of participant A and participant B is the person in charge of recording based on the partner combination information (see step S1205), and transmits recording permission information to the participant terminal 50 of the person in charge of recording, while transmitting recording prohibition information to the participant terminal 50 of the person not in charge of recording (non-recording person). At a participant terminal 50 that receives the recording permission information, operation of the start recording instruction button on the conversation start operation acceptance screen is enabled, whereas at a participant terminal 50 that receives the recording prohibition information, operation of the start recording instruction button on the conversation start operation acceptance screen is disabled.

[0338] When a start recording instruction is input at the participant terminal 50 of the person in charge of recording (even if a start recording instruction is not input at the participant terminal 50 of the non-person in charge of recording), the control unit 150 of the participant terminal 50 executes a conversation start operation acceptance process (step S1510). The display contents of the conversation start operation acceptance screen shown in Fig. 48 and the display contents of the conversation start operation acceptance screen shown in Fig. 20 are common except for the presence or absence of the start recording instruction input area 1001, and the process of step S1510 is the same as the process of step S509 of Fig. 15, so further description will be omitted.

[0339] [Specific Participant Terminal] FIG. 49 is a diagram showing an example of a conversation start operation acceptance screen.

[0340] In this embodiment, when there is one participant (participant A) and another participant (participant B) participating in a social event, in order to realize the functions (social interaction support) of the social interaction support system 10, it is described that both the participant terminal 50 of participant A and the participant terminal 50 of participant B are basically used. However, it is also possible to use only one of the participant terminals 50 of participant A (e.g., male) and participant terminal 50 of participant B (e.g., female). This one participant terminal 50 will be referred to as the specific participant terminal 50.

[0341] In the first embodiment, the name of one participant is entered in the conversation preparation operation reception screen (see FIG. 16 ), and the name of another participant is entered in the conversation partner name input operation reception screen (see FIG. 19 ). In contrast, in this modification, when the conversation preparation operation reception screen (not shown) is displayed on the specified participant terminal 50, the names of two participants (participant A and participant B) are entered. Then, when the biometric device connection operation reception screen (not shown) is displayed, an operation is performed to connect both the biometric device 60 worn by participant A and the biometric device 60 worn by participant B to the specified participant terminal 50 via short-range wireless communication. In this state, the specified participant terminal 50 displays the conversation start operation reception screen shown in FIG. 49 . This conversation start operation reception screen includes a male participant name input area 1021 a, a female participant name input area 1021 b, a conversation start instruction input area 1022, a conversation end instruction input area 1023, and a matching result display instruction input area 1024.

[0342] The male participant name input area 1021a is an area for inputting the name of a male participant. The female participant name input area 1021b is an area for inputting the name of a female participant. The male participant name input area 1021a and the female participant name input area 1021b are also included in the conversation preparation operation reception screen, and when the conversation preparation operation reception screen is displayed, a participant can input the name of a male participant in the male participant name input area 1021a and the name of a female participant in the female participant name input area 1021b by operating the operation input unit 153. In the example shown in FIG. 49, "Donald" is input as the name of the male participant and "Olivia" is input as the name of the female participant.

[0343] 49 includes heart rate images 1025 (1025a, 1025b) and heart images 1026 (1026a, 1026b). The heart rate image 1025 and the heart image 1026 are basically the same as the heart rate image 725 and the heart image 726 (see FIG. 20), respectively. However, in this example, since two biometric testers 60 are connected to one participant terminal 50, the heart rate image 1025a and the heart image 1026a corresponding to the male participant (Donald) and the heart rate image 1025b and the heart image 1026b corresponding to the female participant (Olivia) are displayed. The conversation start instruction input area 1022, conversation end instruction input area 1023, and matching result display instruction input area 1024 are basically the same as the conversation start instruction input area 722, conversation end instruction input area 723, and matching result display instruction input area 724 (see FIG. 20), and therefore description thereof will be omitted here. Note that the conversation start instruction input area 1022 also serves as the recording start instruction input area 1001, and recording starts when a conversation start instruction is input.

[0344] In this variation, the control unit 150 of the specified participant terminal 50 can be configured to receive two people's biometric information from each biometric tester 60 during the biometric information management process (see FIG. 21 ), store the biometric information in the storage unit 151 as time-series biometric data in a manner that allows identification of which participant each piece of biometric information belongs to, and transmit the time-series biometric data for the two people to the exchange support server 20 during the participant terminal-side conversation end process (see FIGS. 23 and 50 ). Note that the manager terminal 30, the organizer terminal 40, or another terminal (a terminal dedicated to the exchange support system 10) may be used instead of the specified participant terminal 50. In this case, the manager terminal 30, the organizer terminal 40, or another terminal performs processes corresponding to the participant terminal-side conversation start process, the biometric information management process, and the participant terminal-side conversation end process. This configuration can be suitably employed, for example, when a matchmaking session is held at a marriage consultation office as a social event using the exchange support system 10.

[0345] [End of conversation] Figures 50 to 52 are flowcharts showing conversation end processing on the participant terminal side, conversation end processing on the interaction support server side, and conversation end processing on the organizer terminal side. Figure 53 is a diagram showing an example of a matching result screen. Figure 54 is a diagram showing an example of an excitement result screen. Figure 55 is a diagram showing an example of an excitement reference screen. Figure 56 is a diagram showing an example of an operation reception screen for inputting information for generating advice. Figure 57 is a diagram showing an example of an advice screen.

[0346] The participant terminal-side conversation end processing is processing performed on the participant terminals 50 (participant terminal 50 of participant A and participant terminal 50 of participant B) when a conversation between one participant (participant A) and another participant (participant B) ends. The exchange support server-side conversation end processing is processing performed on the exchange support server 20 when a conversation between one participant (participant A) and another participant (participant B) ends. The organizer terminal-side conversation end processing is processing performed on the organizer terminal 40 when a conversation between one participant (participant A) and another participant (participant B) ends.

[0347] In the conversation end process on the participant terminal side, the control unit 150 of the participant terminal 50 executes the processes of steps S1521 to S1532 shown in Figures 50 to 52. In the conversation end process on the exchange support server side, the control unit 110 of the exchange support server 20 executes the processes of steps S1221 to S1231 shown in Figures 50 to 52. In the conversation end process on the organizer terminal side, the control unit 140 of the organizer terminal 40 executes the processes of steps S1401 to S1410 shown in Figures 50 to 52.

[0348] Specifically, in the participant terminal-side conversation end processing, first, the control unit 150 of the participant terminal 50 executes the processes of steps S1521 to S1524, which are basically the same as the processes of steps S541 to S544 in FIG. 23. Here, in step S1523, the control unit 150 of the participant terminal 50 transmits the matching information stored in the storage unit 151 together with conversation end information to the exchange support server 20 via the network communication unit 157. The conversation end information is as described in the first embodiment. The matching information is as described in the first and second embodiments, and here, biometric information (time-series biometric data) and voice data may be included in the matching information. For example, if a conversation between one participant (participant A) and another participant (participant B) is recorded only on the participant terminal 50 of one of the participants (the person in charge of recording), the matching information transmitted from the participant terminal 50 of the person in charge of recording includes time-series biometric data and voice data, whereas the matching information transmitted from the participant terminal 50 of the person not in charge of recording includes only time-series biometric data. Note that the conversation end instruction input area 723 also serves as an area for inputting an instruction to end recording, and recording ends when an instruction to end conversation is input.

[0349] In the exchange support server-side conversation end processing, the control unit 110 of the exchange support server 20 executes steps S1221 to S1224, which are essentially the same as steps S261 to S264 in FIG. 23. In the first embodiment, the conversation result storage area is described as including a time-series biometric data storage area, a matching degree storage area, and a questionnaire result storage area. In this embodiment, the conversation result storage area includes, in addition to the time-series biometric data storage area, the matching degree storage area, and the questionnaire result storage area, an area for storing voice data (voice data storage area) and an area for storing information corresponding to the excitement level analysis processing (see FIG. 58) (excitement level storage area). In step S1222, the control unit 110 of the communication support server 20 identifies a conversation result storage area through steps (i) to (vi) described in the first embodiment, and stores the biometric information (time-series biometric data) of the matching information received from the participant terminal 50 in a time-series biometric data storage area provided in the conversation result storage area, and stores the voice data in a voice data storage area provided in the conversation result storage area.

[0350] If it is determined in step S1223 that matching information for two people (both participants who conversed with each other) has been stored, the control unit 110 of the communication support server 20 executes a synchronization analysis process (step S1224). In this process, the control unit 110 determines the synchronization level by dividing the sum of P per-window correlation level values ​​Q by P (correlation level average value), and stores information indicating the synchronization level (matching level information) in the storage unit 111. Details of the synchronization analysis process have been explained using FIG. 27 , so further explanation will be omitted here.

[0351] After executing the process of step S1224, the control unit 110 of the exchange support server 20 executes an excitement level analysis process (step S1225). In this process, the control unit 110 calculates the excitement level for each topic and stores information indicating the excitement level (excitement level information) in the storage unit 111. The excitement level is a value that serves as an index indicating the degree of excitement of each topic that appeared in a conversation between one participant (participant A) and another participant (participant B). Details of the excitement level analysis process will be described later with reference to FIG. 58. After executing the process of step S1225, the control unit 110 of the exchange support server 20 transmits the matching degree information and the excitement level information to the organizer terminal 40 and the participant terminal 50 via the communication unit 112 (step S1226).

[0352] In the participant terminal-side conversation end processing, after executing the processing of step S1524, the control unit 150 of the participant terminal 50 receives the matching degree information and the excitement level information transmitted from the interaction support server 20 via the network communication unit 157 (step S1525). Then, the control unit 150 of the participant terminal 50 displays a matching result screen corresponding to the received matching degree information on the display unit 152 (step S1526). Figure 53 shows the matching result screen displayed on Donald's participant terminal 50 when Donald and Olivia have a conversation.

[0353] The matching result screen includes a matching degree image 1041 and a heart rate variability graph image 1042, and also has an excitement result screen display instruction input area 1043. The matching degree image 1041 and the heart rate variability graph image 1042 are basically the same as the matching degree image 781 and the heart rate variability graph image 782 on the matching result detail screen (see FIG. 36 ), and therefore a description thereof will be omitted here. The excitement result screen display instruction input area 1043 is an area where an image corresponding to a button (excitement result screen display instruction button) containing the words "Check the popular topic" is displayed. By operating the operation input unit 153, a participant can input an instruction to select the excitement result screen display instruction button in the excitement result screen display instruction input area 1043 (excitement result screen display instruction input).

[0354] When the excitement result screen display instruction input is performed, the control unit 150 of the participant terminal 50 causes the display unit 152 to display the excitement result screen (step S1527). As shown in Fig. 54, the excitement result screen has a topic display area 1061 and an advice screen display instruction input area 1062. The topic display area 1061 is an area where an excitement level image 1065 corresponding to the excitement level of each topic is displayed. The advice screen display instruction input area 1062 is an area where an image corresponding to a button containing the words "Go to next step" (advice screen display instruction button) is displayed.

[0355] The excitement level image 1065 is composed of a circular image and a text image corresponding to the topic. In the example shown in FIG. 54 , the excitement level images 1065 include an excitement level image 1065a corresponding to the topic "movie," an excitement level image 1065b corresponding to the topic "watching baseball," and an excitement level image 1065c corresponding to the topic "ramen." The excitement level images 1065 are displayed in sizes corresponding to the excitement level, with larger circles being displayed as higher excitement levels. In this example, the excitement level corresponding to the topic "movie" is the highest, the excitement level corresponding to the topic "watching baseball," the next highest, and the excitement level corresponding to the topic "ramen." Note that in the state shown in FIG. 54 , participants cannot input an instruction to select the advice screen display instruction button (input an advice screen display instruction). In FIG. 54 , the advice screen display instruction input area 1062 is displayed with a dotted line, indicating that operations in this area are invalid.

[0356] In the host terminal-side conversation end process, the control unit 140 of the host terminal 40 receives the matching degree information and the excitement level information transmitted from the interaction support server 20 via the communication unit 144 (step S1401). Then, the control unit 140 of the host terminal 40 causes the display unit 142 to display a matching result screen corresponding to the received matching degree information (step S1402). Although not shown, the matching result screen is similar to the screen shown in Fig. 53. When an instruction to display the excitement level result screen is input, the control unit 140 of the host terminal 40 causes the display unit 142 to display an excitement level reference screen (step S1403).

[0357] 55 , the excitement reference screen has a topic display area 1081, an advice generation information input operation reception screen display instruction input area 1082, and an advice screen display instruction input area 1083. The topic display area 1081 is similar to the topic display area 1061 on the excitement result screen, and therefore a description thereof will be omitted here. The advice generation information input operation reception screen display instruction input area 1082 is an area where an image corresponding to a button containing the characters "counselor input screen" (advice generation information input operation reception screen display instruction button) is displayed. The advice screen display instruction input area 1083 is an area where an image corresponding to a button containing the characters "advice display" (advice screen display instruction button) is displayed.

[0358] When the excitement reference screen is displayed, the organizer can operate the operation input unit 143 to input an input to select the advice generation information input operation acceptance screen display instruction button in the advice generation information input operation acceptance screen display instruction input area 1082 (advice generation information input operation acceptance screen display instruction input). On the other hand, at this time, the organizer cannot input an input to select the advice screen display instruction button (advice screen display instruction input). In FIG. 55 , the outer edge of the advice generation information input operation acceptance screen display instruction input area 1082 is displayed with a solid line, suggesting that the operation on the advice generation information input operation acceptance screen display instruction button is valid. On the other hand, the outer edge of the advice screen display instruction input area 1083 is displayed with a dotted line, suggesting that the operation on the advice screen display instruction button is invalid.

[0359] When an instruction to display the advice generation information input operation reception screen is input, the control unit 140 of the organizer terminal 40 executes an advice generation information input operation reception process (step S1404). In this process, the control unit 140 displays the advice generation information input operation reception screen on the display unit 142 and determines whether advice generation information confirmation input has been performed via the operation input unit 143. As shown in FIG. 56 , the advice generation information input operation reception screen includes a comment input area 1101, a view on marriage input area 1102, a hobby input area 1103, an activity history input area 1104, and an advice generation information confirmation input area 1105. By operating the operation input unit 143, the organizer can freely input sentences (advice generation information) related to "A word from the counselor," "View on marriage," "Hobbies," and "Activity history" in these areas, respectively. The advice generation information confirmation input area 1105 is an area where an image corresponding to a button containing the word "input" (advice generation information confirmation button) is displayed. The organizer can make an input to select the advice generation information confirmation button in the advice generation information confirmation input area 1105 (advice generation information confirmation input).

[0360] Here, a scenario is assumed in which a matchmaking event is held at a marriage consultation office as a social event using the social interaction support system 10. A marriage consultation office is a business that provides services such as introducing members of the opposite sex and providing dating support to those seeking marriage (marriage seekers). By joining a marriage consultation office, a marriage seeker can obtain membership status of the marriage consultation office (or a federation that oversees individual marriage consultation offices), and the marriage consultation office then arranges matchmaking between members. The matchmaking event is organized by the marriage consultation office (counselor), and the participants are members. The counselor is familiar with the members' profile information, matchmaking and relationship history, etc., and can provide detailed information about the members to the social interaction support server 20 through the counselor's input on the advice generation information input operation reception screen. Generally, at a matchmaking party, many participants gather at the venue, and one participant converses with multiple other participants in turn, but the conversation time between each pair is relatively short (e.g., approximately 1 to 5 minutes). In contrast, in matchmaking sessions at marriage consultation offices, participants are basically only two people (one man and one woman), and the two people converse for a relatively long period of time (for example, about one hour).

[0361] When advice generation information is input in step S1404, the control unit 140 of the organizer terminal 40 transmits the advice generation information to the interaction support server 20 via the communication unit 144 (step S1405). Note that the content input here can be configured to be stored in, for example, the interaction support database 220 (see FIG. 41) described in the second embodiment.

[0362] In the exchange support server-side conversation end processing, after executing the processing of step S1226, the control unit 110 of the exchange support server 20 receives the advice generation information transmitted from the organizer terminal 40 via the communication unit 112 (step S1227). Then, the control unit 110 of the exchange support server 20 executes advice generation processing (step S1228) and transmits information corresponding to the generated advice (advice information) to the organizer terminal 40 and the participant terminal 50 via the communication unit 112 (step S1229).

[0363] In the processing of step S1228, the control unit 110 generates a prompt based on information corresponding to the results of the synchronization analysis processing (see FIG. 27) (e.g., matching degree information), information corresponding to the results of the excitement level analysis processing (see FIG. 58) (e.g., excitement level information for each topic), advice generation information received from the organizer terminal 40, etc., and transmits the generated prompt to the large-scale language model. Based on the given prompt, the large-scale language model can generate interaction support information (advice) with content suitable for interactions between participants (e.g., dating with the aim of getting married between members of a marriage consultation agency).

[0364] The functions of the large-scale language model and prompts in generating such interaction support information are the same as those described in the second embodiment, and therefore will not be described here. Information corresponding to the results of the synchronization analysis process can be configured to be stored in the heart rate information database 224 or the matching degree information database 225, and information corresponding to the results of the excitement level analysis process can be configured to be stored in the conversation information database 223 or the topic extraction information database 226. The interest content information identified by the interest content acquisition unit 129 (see FIG. 39 ) can be excitement level information for each topic, and the excitement level information (interest content information) can also be configured to be stored in the topic extraction information database 226, etc. The large-scale language model is not particularly limited, and may be a large-scale language model unit 231 (see FIG. 40 ) included in the control unit 110 of the interaction support server 20, or a large-scale language model provided as an external service (e.g., GPT, BERT, etc.).

[0365] In the participant terminal-side conversation end processing, after executing the processing of step S1527, the control unit 150 of the participant terminal 50 receives advice information transmitted from the communication support server 20 via the network communication unit 157 (step S1528). Then, the control unit 150 of the participant terminal 50 executes an advice confirmation operation acceptance processing (step S1529). In this processing, the control unit 150 displays an advice confirmation operation acceptance screen on the display unit 152 and determines whether an advice screen display instruction has been input via the operation input unit 153. Although not shown, most of the display content of the advice confirmation operation acceptance screen is the same as the display content of the excitement result screen. The advice confirmation operation acceptance screen includes an advice screen display instruction input area 1062, which allows the participant to input an advice screen display instruction.

[0366] If it is determined that an advice screen display instruction has been input, the control unit 150 of the participant terminal 50 displays an advice screen on the display unit 152 (step S1530). As shown in FIG. 57, the advice screen includes text images and the like corresponding to the advice information received from the communication support server 20. In this example, in the advice generation process, only information corresponding to the results of the synchrony analysis process (see FIG. 27) (e.g., matching degree information) and information corresponding to the results of the excitement analysis process (see FIG. 58) (e.g., excitement level information for each topic) are used, and it is considered that the counselor hardly input any information for advice generation. Such advice can be generated by providing a predetermined format in the communication support server 20 and applying the results of the synchrony analysis process and the excitement level analysis process to the format, without using a large-scale language model.

[0367] After executing the process of step S1530, the control unit 150 of the participant terminal 50 executes a relationship desire operation reception process (step S1531). The advice screen includes a relationship desire input area 1121. The relationship desire input area 1121 is an area where an image corresponding to a button (relationship desire input button) containing the words "provisional relationship" is displayed. By operating the operation input unit 153, the participant can input (relationship desire input) the intention to select the relationship desire input button in the relationship desire input area 1121. In the process of step S1531, the control unit 150 determines whether a relationship desire input has been made. Note that provisional dating is a preliminary stage of dating that leads to serious dating in the activities of a marriage consultation agency, and is also called pre-dating. Generally, marriage consultation agencies require that serious relationships be limited to one partner, but there is a rule that multiple partners are acceptable for provisional dating.

[0368] If it is determined in step S1531 that a relationship desire input has been made, the control unit 150 of the participant terminal 50 transmits relationship desire information to the exchange support server 20 via the network communication unit 157 (step S1532). The relationship desire information includes information indicating that the participant has input a relationship desire. The advice screen includes a message input area 1122 for the counselor. The participant can freely input a message to the counselor in the message input area 1122 by operating the operation input unit 153. The relationship desire information also includes information indicating the message (message information). Alternatively, if a message is input without a relationship desire input, only the message information may be transmitted to the exchange support server 20. After executing the process of step S1532, the control unit 150 of the participant terminal 50 terminates the participant terminal-side conversation end process.

[0369] In the exchange support server-side conversation end processing, after executing the processing of step S1229, the control unit 110 of the exchange support server 20 receives the relationship desire information and message information transmitted from the participant terminal 50 via the communication unit 112 (step S1230). Then, the control unit 110 of the exchange support server 20 transmits the relationship desire information and message information received from the participant terminal 50 to the organizer terminal 40 via the communication unit 112 (step S1231). Thereafter, the control unit 110 of the exchange support server 20 terminates the exchange support server-side conversation end processing.

[0370] After executing step S1405 in the host terminal-side conversation end process, the control unit 140 of the host terminal 40 receives advice information transmitted from the interaction support server 20 via the communication unit 144 (step S1406). The control unit 140 of the host terminal 40 then executes an advice confirmation operation reception process (step S1407), and if it determines that an advice screen display instruction has been input, the control unit 140 of the host terminal 40 displays an advice screen on the display unit 142 (step S1408). The same explanation as for steps S1528 to S1530 applies to these processes, and therefore further explanation will be omitted here.

[0371] After executing the process of step S1408, the control unit 140 of the organizer terminal 40 receives the relationship desire information transmitted from the social networking support server 20 via the communication unit 144 (step S1409). The control unit 140 of the organizer terminal 40 then displays a relationship desire result screen corresponding to the received relationship desire information on the display unit 142 (step S1410). Although not shown, the relationship desire result screen includes a text image indicating that the participant has entered a relationship desire. This allows the organizer (counselor) to understand that the participant (member) is interested in a provisional relationship. Furthermore, if message information is received from the social networking support server 20, the control unit 140 of the organizer terminal 40 also causes the display unit 142 to display a screen corresponding to the message information. After executing the process of step S1410, the control unit 140 of the organizer terminal 40 terminates the organizer terminal-side conversation end process.

[0372] [Excitement Level] FIG. 58 is a flowchart showing the excitement level analysis process performed by the interaction support server.

[0373] The excitement level analysis process shown in FIG. 58 is a process performed by the exchange support server in step S1225 of FIG. 50 (interaction support server-side process at the end of conversation).

[0374] In the excitement level analysis process, the control unit 110 of the communication support server 20 first analyzes the characteristics of the window correlation level value Q (step S1101). As described in the first embodiment, the synchronization analysis process is executed to calculate P window correlation level values ​​Q. In the process of step S1101, the control unit 110 identifies, among the P window correlation level values ​​Q, a window correlation level value Q that is equal to or greater than a predetermined value (e.g., 0.90). Alternatively, the control unit 110 identifies a window correlation level value Q corresponding to a maximum value (peak value) for time-series data composed of the P window correlation level values ​​Q. To identify the peak value, for example, smoothing (e.g., moving average) the time-series data, calculating the derivative of the smoothed data, and finding the point where the sign of the derivative changes from positive to negative among the points where the derivative is zero. Alternatively, the peak value may be identified using a predetermined peak detection algorithm (e.g., a function in the SciPy library).

[0375] Next, the control unit 110 of the communication support server 20 identifies the voice data to be converted into text data (step S1102). The control unit 110 of the communication support server 20 then converts the voice data identified as the conversion target into text data (step S1103). The method for converting voice data into text data is not particularly limited, and voice recognition technology using machine learning or deep learning (neural network) (e.g., Google Cloud Speech-to-Text, etc.) can be appropriately adopted. When converting the voice data into text data, the control unit 110 also assigns time information to the recognized words and phrases.

[0376] Here, the data to be converted into text data is a portion of the voice data stored in a voice data storage area included in the conversation result storage area in which the first and second time-series biometric data subjected to the synchrony analysis process are stored. Information indicating a window position (e.g., window start time information T) is associated with the per-window correlation level value Q. In the process of step S1102, the control unit 110 identifies voice data for a predetermined time before and after the window position based on the per-window correlation level value Q identified in step S1101 and the information indicating the window position associated with the per-window correlation level value Q as data to be converted into text data. For example, the control unit 110 identifies voice data for a predetermined time (e.g., 10 seconds, 30 seconds, 1 minute, 3 minutes, 5 minutes, etc.) before the start time of the window, voice data for the time from the start time to the end time of the window, and voice data for a predetermined time (e.g., 10 seconds, 30 seconds, 1 minute, 3 minutes, 5 minutes, etc.) after the end time of the window as data to be converted into text data. For example, if the start time information T of the window associated with the per-window correlation level value Q identified in step S1101 is "12:30:00," the range of the window is "12:30:00," "12:30:01," "12:30:02," ..., "12:30:10." When specifying audio data for 30 seconds before and after the window position as the target for conversion to text data, the target for conversion to text data is the audio data from "12:29:30" to "12:30:40."

[0377] If there are multiple per-window correlation level values ​​Q identified in step S1101, the control unit 110 identifies a target for conversion to text data for each of the multiple per-window correlation level values ​​Q. Alternatively, if a predetermined number of consecutive per-window correlation level values ​​Q are all equal to or greater than a predetermined value (e.g., 0.85), the control unit 110 may identify the audio data for the range of these windows (from the start time of the window associated with the first per-window correlation level value Q to the end time of the window associated with the last per-window correlation level value Q among the predetermined number of per-window correlation level values ​​Q) as a target for conversion to text data. The control unit 110 extracts a segment of the time period identified as a target for conversion from the audio data and converts it into text data.

[0378] Next, the control unit 110 of the communication support server 20 executes a topic extraction process (step S1104). In this process, the control unit 110 extracts topics from the text based on the text data converted from the voice data in step S1103. In this embodiment, a large-scale language model is used to extract topics from the text. The large-scale language model is not particularly limited, and for example, a transformer-based model (e.g., GPT or BERT) or a recurrent neural network (RNN)-based model can be appropriately adopted. A transformer-based model uses a self-attention mechanism to understand the relationships between words in the text, extract important phrases through this analysis, summarize the text, and further cluster documents based on similar topics. The control unit 110 also associates the extracted topics with segments of the original text to identify the start and end times of the topics. As a method for extracting topics from text, a topic modeling method may be adopted as described in the second embodiment, or a method that combines topic modeling and a large-scale language model may be adopted.

[0379] Next, the control unit 110 of the communication support server 20 calculates the average of the per-window correlation level values ​​Q for each topic period (step S1105). In this process, the control unit 110 identifies the per-window correlation level values ​​Q that belong to the period from the start time to the end time (topic period) for each topic extracted in step S1104. For example, if the start time of a window associated with a per-window correlation level value Q is included in the topic period for a topic, the per-window correlation level value Q is treated as belonging to the topic period. Then, for each topic, the control unit 110 calculates the average of the per-window correlation level values ​​Q that belong to the topic period (average correlation level during the topic period). (If there are multiple per-window correlation level values ​​Q that belong to a topic period, the total of the multiple per-window correlation level values ​​Q is divided by the number of per-window correlation level values ​​Q to obtain the number.)

[0380] Next, the control unit 110 of the exchange support server 20 determines the correlation level average value during the topic period calculated in step S1105 as the excitement level, and stores information indicating the excitement level in the storage unit 111 (step S1106). In this process, the control unit 110 stores information indicating the excitement level during each topic period (excitement level information) in both an excitement level storage area included in the conversation result storage area where the first time-series biometric data is stored and an excitement level storage area included in the conversation result storage area where the second time-series biometric data is stored. After executing the process of step S1106, the control unit 110 of the exchange support server 20 terminates the excitement level analysis process.

[0381] [Modification] Fig. 59 is a flowchart showing the process performed by the participant terminal when transmitting matching information and the process performed by the exchange support server when receiving matching information. Fig. 60 is a flowchart showing the excitement level analysis process performed by the exchange support server.

[0382] In the participant terminal-side matching information transmission process, the control unit 150 of the participant terminal 50 executes the processes of steps S1551 to S1555 shown in Fig. 59. In the interaction support server-side matching information reception process, the control unit 110 of the interaction support server 20 executes the processes of steps S1251 to S1256 shown in Fig. 59.

[0383] Specifically, in the participant terminal-side matching information transmission process, the control unit 150 of the participant terminal 50 first executes the process of step S1551. However, since this process is the same as the process of step S541 in Fig. 23, its description will be omitted here. If it is determined in step S1551 that the conversation in progress flag is set to on, the control unit 150 of the participant terminal 50 determines whether it is time to transmit matching information (step S1552). In this process, the control unit 150 determines that it is time to transmit matching information when a predetermined time (e.g., one minute) has elapsed since the previous transmission of matching information.

[0384] If it is determined that it is not the timing to send the matching information, the control unit 150 of the participant terminal 50 ends the participant terminal-side matching information sending process. On the other hand, if it is determined that it is the timing to send the matching information, the control unit 150 of the participant terminal 50 sends the matching information stored in the memory unit 151 to the interaction support server 20 via the network communication unit 157. As described above, the matching information may include biometric information (time-series biometric data) and voice data.

[0385] In the exchange support server-side matching information reception process, the control unit 110 of the exchange support server 20 executes steps S1251 to S1255. These steps are essentially the same as steps S1221 to S1225 of FIG. 50, and therefore will not be described here. Note that in step S1254, only steps S101 to S107 of FIG. 27 may be executed (steps S108 to S110 may not be executed). In step S1255 (steps S1101 and S1105 of FIG. 58), the correlation coefficient R may be used instead of the per-window correlation level value Q. After executing step S1255, the control unit 110 of the exchange support server 20 transmits excitement level information to the participant terminal 50 via the communication unit 112 (step S1256), thereby terminating the exchange support server-side matching information reception process.

[0386] In the participant terminal-side matching information transmission process, the control unit 150 of the participant terminal 50 executes the processes of steps S1554 and S1555. These processes are basically the same as the processes of steps S1525 to S1527 of FIG. 51, and therefore will not be described here. In addition to the excitement level information, information indicating the current degree of synchronization (synchronization level information) may also be transmitted from the exchange support server 20 to the participant terminal 50, and the synchronization level may be displayed on the screen of the participant terminal 50 along with the excitement level. Furthermore, based on the synchronization level information or the excitement level information, the exchange support server 20 may generate advice (see step S1228 of FIG. 51), and an advice screen (see step S1530 of FIG. 52) may be displayed on the participant terminal 50.

[0387] As described above, the timing of transmitting matching information from the participant terminal 50 to the communication support server 20 is not particularly limited. For example, the matching information may be transmitted when an event or conversation ends, or may be transmitted at a predetermined timing (e.g., every minute) during the conversation. If the matching information is transmitted during the conversation, feedback on the degree of synchronization and excitement can be provided to the participants in real time during the conversation, which in itself can contribute to deepening the interaction between the participants. Furthermore, the timing of transmission from the participant terminal 50 to the communication support server 20 may vary depending on the type of matching information. For example, biometric information (time-series biometric data) may be transmitted when the event or conversation ends, while audio data may be transmitted at a predetermined timing (e.g., every minute) during the conversation, or vice versa.

[0388] In the excitement level analysis process shown in FIG. 60 , first, the control unit 110 of the exchange support server 20 converts the entire voice data into text data (step S1151). Next, the control unit 110 of the exchange support server 20 executes a topic extraction process (step S1152). In this process, the control unit 110 extracts topics from the text using the large-scale language model or topic modeling described above, or a combination of these, and identifies the start and end times of each topic. Then, the control unit 110 of the exchange support server 20 calculates the average of the per-window correlation level values ​​Q (or correlation coefficients R) for each topic period (the average correlation level value during the topic period) (step S1153).

[0389] Thereafter, the control unit 110 of the exchange support server 20 determines the average correlation level during the topic period calculated in step S1153 as the excitement level, stores information indicating the excitement level in the storage unit 111 (step S1154), and terminates the excitement level analysis process. Note that when a numerical value corresponding to the excitement level is displayed on the screen of the participant terminal 50, it is possible to configure the participant terminal 50 to obtain the numerical value by multiplying the excitement level calculated by the excitement level analysis process by a predetermined number so that the numerical value falls within the range of 0 to 100 (%).

[0390] The interaction support system 10 according to the first to third embodiments of the present invention has been described above.

[0391] <Additional Note> Conventionally, a server capable of performing compatibility diagnosis has been known (see Japanese Patent Laid-Open Publication No. 2002-73787).

[0392] In the course of thorough research into the compatibility between people, the inventor came to the idea that by applying ingenuity to the analysis of information, it may be possible to create a new form of support for interaction between people.

[0393] The present invention has been made in view of the above-mentioned circumstances, and has an object to provide an information processing device, an information processing method, and an information processing system that are capable of supporting interactions between people.

[0394] In this regard, the interaction support system 10 according to the first to third embodiments has the following features.

[0395] (1) An information processing device including a control unit, wherein the control unit is capable of performing control to analyze a relationship between information about one person and information about another person.

[0396] (2) The information processing device of (1) is characterized in that it includes a communication unit, and the control unit is capable of controlling communication via the communication unit so as to cause an external device to output according to the results of the analysis.

[0397] (3) The information processing device of (1) or (2), wherein the control unit is capable of controlling, when the one person and the other person are having a conversation, the analysis is to analyze the relationship between the change over time of information about the one person and the change over time of information about the other person during the conversation.

[0398] (4) The information processing device of (3), wherein the control unit is capable of controlling the analysis to calculate a correlation coefficient between information about the one person and information about the other person according to each of a plurality of timings during the conversation.

[0399] (5) The information processing device of (2), wherein the control unit is capable of calculating a correlation coefficient between information about the one person and information about the other person in accordance with each of a plurality of timings in the analysis, and then controlling communication via the communication unit so as to cause an external device to output, as the output, a value corresponding to a normalized value of the correlation coefficient.

[0400] (6) The information processing device of (3) or (4) is characterized in that the control unit is capable of acquiring voice data corresponding to a conversation between the one person and the other person, and is capable of being controlled to identify a topic based on information about the one person, information about the other person, and the voice data.

[0401] (7) The information processing device of (6) is characterized in that it includes a communication unit, and the control unit is capable of controlling communication via the communication unit so as to cause an external device to perform output according to the identified topic.

[0402] (8) An information processing device according to any one of (1) to (7), further comprising a communication unit, wherein the control unit is capable of controlling communication via the communication unit so as to cause an external device to output advice according to the advice generated by the large-scale language model.

[0403] (9) An information processing method, comprising: a first step of controlling to analyze the relationship between information about one person and information about another person.

[0404] (10) The information processing method according to (9) above, further comprising a second step of controlling to output an output according to the result of the analysis.

[0405] (11) The information processing method of (9) or (10), wherein in the first step, when the one person and the other person are having a conversation, the analysis is controlled to analyze the relationship between the change over time of information about the one person and the change over time of information about the other person during the conversation.

[0406] (12) The information processing method of (11), wherein in the first step, the analysis is controlled to calculate a correlation coefficient between information about the one person and information about the other person according to each of a plurality of timings during the conversation.

[0407] (13) The information processing method of (10), characterized in that in the first step, in the analysis, control is performed to calculate a correlation coefficient between information about the one person and information about the other person according to each of a plurality of timings, and in the second step, control is performed to output the output according to a normalized value of the correlation coefficient.

[0408] (14) The information processing method of (11) or (12) is characterized by including: a third step of controlling to acquire voice data corresponding to a conversation between the one person and the other person; and a fourth step of controlling to identify a topic based on information about the one person, information about the other person, and the voice data.

[0409] (15) The information processing method according to (14) above, further comprising a fifth step of controlling to output information according to the identified topic.

[0410] (16) The information processing method according to any one of (9) to (15), further comprising a sixth step of controlling to output advice according to the advice generated by the large-scale language model.

[0411] (17) An information processing system including an information terminal, the information terminal including a control unit and a storage unit, the control unit being capable of controlling the storage unit to associate information about a person with information about timing when the person is interacting with another person.

[0412] (18) The information processing system of (17) is characterized in that it includes a communication unit, and the control unit is capable of controlling communication via the communication unit so as to transmit information about the person associated with information about the timing to an external device.

[0413] (19) The information processing system of (17) or (18), characterized in that the control unit is capable of controlling the storage unit to store voice data when the one person and the other person are having a conversation.

[0414] (20) The information processing system according to any one of (17) to (19), further comprising an output unit, wherein the control unit is capable of controlling the output unit to output according to the results of an analysis of the relationship between the information about the one person and the information about the other person.

[0415] (21) An exchange support device for determining the compatibility between multiple participants when they are having a conversation, the exchange support device comprising: a compatibility information acquisition unit for acquiring compatibility information including changes in the heart rates of the participants over time during the conversation; and a compatibility measurement unit for determining the correlation level of the changes in the heart rates over time as the compatibility level between the participants.

[0416] The communication support device (21) described above is a system for accurately measuring the compatibility of multiple participants (any two of them) during a conversation. First, a compatibility information acquisition unit acquires compatibility information, including changes in the participants' heart rates over time during the conversation. This compatibility information acquisition unit uses a highly sensitive heart rate sensor to collect accurate heart rate data in real time. This allows for a detailed understanding of the participants' physiological responses during the conversation. Changes in heart rate over time are important data that reflect changes in the participants' psychological states and emotions. Acquiring this data can clarify the emotional connections and reactions between the participants. Next, a compatibility measurement unit analyzes the correlation level of the acquired heart rate changes over time and determines the compatibility level between the participants based on the results. This analysis uses advanced statistical methods to accurately evaluate the degree of synchronization between the participants' heart rate data. A higher degree of heart rate synchronization indicates greater emotional synchronization between the participants and suggests better compatibility. This compatibility level is visually displayed as numbers and graphs, allowing participants to intuitively understand it.

[0417] The effects of this device include, first, that it enables objective compatibility assessment based on participants' physiological responses. This allows for compatibility measurement based on scientific evidence, rather than simply relying on conversation content or impressions. Second, real-time data acquisition and analysis provides quick and accurate feedback, allowing participants to check their compatibility assessment on the spot and reflect it in their next actions. Third, this system can be used as a tool to improve the quality of communication between participants at matchmaking events and social events, supporting better matching. As described above, the communication support device described in (21) above enables highly accurate compatibility assessment using heart rate data and effectively supports interactions between participants. This significantly improves the matching process at matchmaking and social events, increasing participant satisfaction.

[0418] (22) The communication support device of (21) further includes a compatibility result output unit that displays the compatibility level determined by the compatibility measurement unit and the changes over time in the heart rates of at least some of the participants on a screen of a participant terminal operated by the participant.

[0419] The communication support device (22) described above, in addition to the configuration described in (21), includes a compatibility result output unit, thereby adding a function for providing real-time feedback to participants. This device is capable of displaying the compatibility level determined by the compatibility measurement unit and the changes in each participant's heart rate over time on a screen operated by the participant. First, the compatibility result output unit has a function for visually displaying the compatibility level analyzed by the compatibility measurement unit. This function allows participants to intuitively understand their own compatibility level. The compatibility level is displayed as a number, graph, or color scale, allowing participants to receive feedback in a visually easy-to-understand format. This visualized data allows participants to instantly understand the compatibility evaluation results and reflect them in their next actions. Furthermore, the compatibility result output unit also has a function for displaying the changes in the heart rates of multiple participants over time on the screen. This display allows participants to compare their own heart rate data with that of other participants. For example, participants can check in real time how their heart rate changed during a particular conversation or event and how synchronized their heart rate is with that of other participants. This allows participants to gain a deeper understanding of their own physiological responses and provides valuable information for assessing their emotional connection with the other person.

[0420] The effects of this device include: first, real-time feedback allows participants to check their compatibility assessments on the spot. This allows participants to instantly adjust their behavior and communication styles, promoting better interactions. second, providing visualized data allows participants to intuitively understand their compatibility assessments, improving the quality of interactions and maximizing the effectiveness of the event. third, comparative display of heart rate data between participants allows participants to objectively evaluate their own physiological responses, providing information useful for deepening self-understanding and building relationships with others. As described above, the communication support device described in (22) above has the excellent function of providing real-time feedback to participants through the visualization of compatibility measurement results and heart rate data, more effectively supporting interactions between participants. This allows participants to more easily understand their own and others' physiological responses, improving the quality of interactions.

[0421] (23) The communication support device of (21), wherein the compatibility information acquisition unit acquires the content of the conversation between the participants as the compatibility information, and includes a topic extraction unit that analyzes the content of the conversation and extracts a topic and a topic period during which the topic continued, and a topic output unit that calculates a correlation level during the topic period extracted by the topic extraction unit and displays the topic continued during the topic period on a screen of a participant terminal operated by the participant at an emphasis level according to the correlation level.

[0422] In addition to the configuration of the communication support device of (21), the compatibility information acquisition unit has a function for acquiring conversation content as compatibility information, thereby enabling compatibility evaluation based on the conversation content between participants. Specifically, the addition of two components, a topic extraction unit and a topic output unit, further improves the quality of the conversation and the accuracy of the compatibility evaluation. First, the compatibility information acquisition unit acquires the conversation content between participants as compatibility information. This function allows important topics and topics during the conversation to be captured by the communication support device, enabling detailed analysis. Analyzing the conversation content makes it possible to determine what topics participants are interested in and which topics were particularly popular. Next, the topic extraction unit extracts topics and topic periods during which the topics continued based on the acquired conversation content. This makes it possible to accurately determine how long a particular topic lasted. Extracting topic periods is an important step for clearly indicating which topics were important in the conversation, allowing participants to recognize particularly important parts of what they talked about. The topic output unit analyzes the correlation level of the extracted topic periods and displays the topic periods with an emphasis level based on the results. This display allows participants to intuitively understand how much interest there was in a particular topic and how much emotional synchronization there was with the other person. It is preferable that the display of emphasis levels be designed to allow participants to grasp important information at a glance by using visual elements such as color and size.

[0423] The effects of this device include: first, a more accurate compatibility assessment based on the content of the conversation is possible. This allows for a comprehensive compatibility assessment that takes into account not only biometric information but also the quality and content of the conversation. second, topic extraction and highlighting make it easier for participants to understand particularly important parts of the conversation, which can be effectively utilized in the next conversation or date. third, real-time feedback allows participants to immediately check the quality of their conversation and improve their behavior. As described above, the communication support device described in (23) above can accurately assess the compatibility between participants and improve the quality of their interactions through the analysis of conversation content and visual feedback. This allows participants to receive specific assistance in improving their communication skills and building better relationships.

[0424] (24) The communication support device of (23) has an interest content acquisition unit that determines common interest content among the participants based on the correlation level during the topic period extracted by the topic extraction unit and the topic continued during the topic period, and the topic output unit displays the common interest content on the screen of the participant terminal.

[0425] The communication support device (24) described above adds a function for determining common interests between participants to the configuration described in (23). This device can identify common interests based on the correlation level during the topic period extracted by the topic extraction unit and the topics continued during the topic period, and display them on the participant's terminal. First, the interest acquisition unit can identify topics that particularly attracted interest from the topics shared between participants. Specifically, it analyzes the correlation level during the topic period extracted by the topic extraction unit and extracts common interests between participants from the results. These interests are identified based on topics that were particularly popular during the conversation or topics that both parties were interested in, making them very important information for evaluating the ...

Claims

1. An information processing device comprising a control unit, wherein the control unit is capable of performing control to analyze the relationship between information about one person and information about another person.

2. An information processing device according to claim 1, further comprising a communication unit, wherein the control unit is capable of controlling communication via the communication unit so as to cause an external device to output according to the results of the analysis.

3. The information processing device according to claim 1 or 2, characterized in that, when the one person and the other person are having a conversation, the control unit is capable of controlling the analysis to analyze the relationship between changes over time in information about the one person and changes over time in information about the other person during the conversation.

4. The information processing device according to claim 3, characterized in that the control unit is capable of controlling the analysis to calculate a correlation coefficient between information about the one person and information about the other person according to each of multiple timings during the conversation.

5. The information processing device according to claim 2, characterized in that the control unit is capable of calculating a correlation coefficient between information about the one person and information about the other person according to each of a plurality of timings in the analysis, and then controlling communication via the communication unit so as to cause an external device to output, as the output, a value corresponding to a normalized value of the correlation coefficient.

6. The information processing device according to claim 3, characterized in that the control unit is capable of acquiring voice data corresponding to a conversation between the one person and the other person, and is capable of controlling the device to identify a topic based on information about the one person, information about the other person, and the voice data.

7. An information processing device according to claim 6, further comprising a communication unit, wherein the control unit is capable of controlling communication via the communication unit so as to cause an external device to perform output according to the identified topic.

8. An information processing device according to claim 1, further comprising a communication unit, wherein the control unit is capable of controlling communication via the communication unit so as to cause an external device to output advice according to the advice generated by the large-scale language model.

9. An information processing method comprising a first step of controlling to perform an analysis of the relationship between information about one person and information about another person.

10. The information processing method according to claim 9, further comprising a second step of controlling to output in accordance with the results of said analysis.

11. The information processing method according to claim 9 or 10, characterized in that in the first step, when the one person and the other person are having a conversation, the analysis is controlled so as to analyze the relationship between changes over time in information about the one person and changes over time in information about the other person during the conversation.

12. The information processing method described in claim 11, characterized in that in the first step, the analysis is controlled to calculate a correlation coefficient between information about the one person and information about the other person according to each of multiple timings during the conversation.

13. The information processing method according to claim 10, characterized in that in the first step, the analysis is controlled to calculate a correlation coefficient between information about one person and information about another person according to each of a plurality of timings, and in the second step, the output is controlled to be an output according to a normalized value of the correlation coefficient.

14. The information processing method according to claim 11, further comprising: a third step of controlling to acquire voice data corresponding to a conversation between the one person and the other person; and a fourth step of controlling to identify a topic based on information about the one person, information about the other person, and the voice data.

15. The information processing method according to claim 14, further comprising a fifth step of controlling to perform output according to the identified topic.

16. The information processing method according to claim 9, further comprising a sixth step of controlling output in accordance with advice generated by a large-scale language model.

17. An information processing system comprising an information terminal, the information terminal comprising a control unit and a memory unit, the control unit being capable of controlling the memory unit to associate information about a person with information about timing when the person is interacting with another person, and store the information in the memory unit.

18. An information processing system as described in claim 17, further comprising a communication unit, wherein the control unit is capable of controlling communication via the communication unit so as to transmit information about the person associated with information about the timing to an external device.

19. The information processing system according to claim 17 or 18, characterized in that the control unit is capable of controlling the storage unit to store voice data when the one person and the other person are having a conversation.

20. An information processing system as described in claim 17 or 18, characterized in that it comprises an output unit, and the control unit is capable of controlling the output unit to output according to the results of an analysis of the relationship between the information about the one person and the information about the other person.

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