Information processing system, information processing method and program

Abstract

The objective is to provide an information processing system that can evaluate the quality of information reception of content from multiple perspectives. [Solution] An information processing system for analyzing content is provided, comprising a physiological index acquisition unit, a psychological index acquisition unit, an acceptance analysis unit, and a presentation unit, wherein the physiological index acquisition unit is configured to acquire physiological indexes, the physiological indexes corresponding to potentials indicating the redox state of the saliva of an evaluator who has come into contact with the content, the psychological index acquisition unit is configured to acquire psychological indexes, the psychological indexes being data that quantifies an evaluation related to the evaluator's interest in the content, the acceptance analysis unit is configured to analyze whether the content falls into one of a plurality of predetermined acceptance states based on the physiological index and the psychological index, each acceptance state being a state that indicates how the evaluator who has come into contact with the content is accepting the content, and the presentation unit causes the analysis results of the acceptance analysis unit to be presented to an output unit.

Description

[Technical Field]

[0001] The present invention relates to an information processing system, an information processing method, and a program. [Background technology]

[0002] Patent Document 1 discloses a method for measuring emotional stimuli and the like using electrical conductivity of the skin. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6159261 Summary of the Invention [Problem to be solved by the invention]

[0004] When using a physiological index (skin electrical conductivity) such as that in Patent Document 1 alone to evaluate content such as a video, the evaluation tends to be limited to a one-dimensional one, such as whether the content is emotionally stimulating, and there is a problem in that it is difficult to evaluate the reception state of the content from multiple perspectives.

[0005] An object of the present invention is to provide an information processing system that can evaluate the quality of information reception of content from multiple perspectives. [Means for solving the problem]

[0006] According to the present invention, there is provided an information processing system for analyzing content, comprising a physiological index acquisition unit, a psychological index acquisition unit, an acceptance analysis unit, and a presentation unit, wherein the physiological index acquisition unit is configured to acquire physiological indexes, the physiological indexes corresponding to potentials indicating the redox state of the saliva of an evaluator who has come into contact with the content, the psychological index acquisition unit is configured to acquire psychological indexes, the psychological indexes being data that quantifies the evaluator's evaluation of his or her interest in the content, the acceptance analysis unit is configured to analyze whether the content falls into a plurality of predetermined acceptance states based on the physiological index and the psychological index, each acceptance state being a state that indicates how the evaluator who has come into contact with the content is accepting the content, and the presentation unit causes an output unit to present the analysis results of the acceptance analysis unit.

[0007] According to the present invention, the acceptance analysis unit is configured to analyze whether the content falls into one of a number of predetermined acceptance states based on both physiological and psychological indices, thereby enabling a multifaceted evaluation of the quality of information acceptance of the content. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 shows an example of a system configuration of an information processing system 100 according to an embodiment. [Figure 2] FIG. 2 is a block diagram showing the hardware configuration of the information processing device 1. As shown in FIG. [Figure 3] FIG. 3 is a functional block diagram of the control unit 12 shown in FIG. [Figure 4] FIG. 4 is an explanatory diagram of a map showing the relationship between a plurality of acceptance states and physiological and psychological indices in the information processing system according to the embodiment. [Figure 5] FIG. 5 is an explanatory diagram that schematically shows the analysis result of the state of acceptance (current state of acceptance) and the state of acceptance that the creator of the content aims to achieve in the information processing system according to the embodiment. [Figure 6]Fig. 6A is a perspective view schematically showing a human saliva ORP measuring device for acquiring a physiological index in an information processing system according to an embodiment, and Fig. 6B is an explanatory diagram schematically showing the configuration of the arrow A shown in Fig. 6A. [Figure 7] FIG. 7 is an example of a flowchart of the information processing system according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. Various features shown in the following embodiments can be combined with each other. Furthermore, each feature can be an invention independently.

[0010] 1. System Configuration of Information Processing System 100 The information processing system 100 according to the embodiment has a function for analyzing content. Specifically, it is capable of analyzing the evaluator's acceptance of the content and presenting the analysis results. The content may be in the form of data (e.g., image data, video data, or audio data). However, the system may also be applied to audiences at venues such as live events (e.g., lectures, exhibitions, symposiums, musical concerts, theatrical performances, corporate events, in-house award ceremonies, corporate top message presentations, meetings, and shareholders' meetings). Furthermore, the content may be interactive content such as XR (cross-reality) content. Here, XR content includes, for example, virtual reality (VR), augmented reality (AR), and mixed reality (MR). Conventionally, content evaluations have relied on quantitative data such as viewership ratings, number of plays, and time spent on the content, or subjective evaluations based on questionnaires. However, these evaluation methods make it difficult to objectively and in real time grasp how evaluators accept the content, i.e., qualitative acceptance states such as the level of awareness and caution toward the content.

[0011] The information processing system 100 according to the embodiment has a function of acquiring the physiological index (salivary oxidation-reduction potential) and psychological index (evaluator's subjective evaluation of the content) of the evaluator, and automatically analyzing multiple acceptance states (in one embodiment, acceptable acceptance, reassuring acceptance, warning acceptance, and cognitive rejection acceptance) based on these indices. This makes it possible to evaluate the quality of the evaluator's acceptance of the content in a multifaceted and objective manner. Furthermore, the information processing system 100 according to the embodiment also has a function of identifying areas for improvement in content based on the analysis results relating to the state of reception, and generating optimized content based on the results of the identification. This allows users such as content creators to receive not only data such as the state of reception, but also useful feedback data for brushing up their content.

[0012] The information processing system 100 is a system that can automate the evaluation of the reception state of content by integrating the acquisition of physiological and psychological indices, analysis of the reception state, support for improvement, and presentation of various data. As shown in FIG. 1, the information processing system 100 includes an information processing device 1, a large-scale language model server 2, a user terminal 3, and an index measurement device 4. These are connected to each other so as to enable the exchange of information via a communication network 5. Note that the communication network 5 may be a closed network separated in part or in whole from the Internet, or may be configured as a local network.

[0013] Each component of the information processing system 100, such as the information processing device 1, has one or more functions (functional units). Each component may be configured as a single device as shown in FIG. 1, or may be configured as multiple independent devices configured to be able to exchange information. The same applies to each functional unit, such as the control unit 12 of the information processing device 1, which will be described later. Each component included in the information processing system 100 will be further described below.

[0014] 1-1. Information processing device 1 2, the information processing device 1 has a communication unit 10, a storage unit 11, a control unit 12, an output unit 13, and an input unit 14, and these components are electrically connected via a communication bus 15 inside the information processing device 1. As shown in FIG. 3, the control unit 12 has a data acquisition unit 121, a physiological index acquisition unit 122, a psychological index acquisition unit 123, an acceptance analysis unit 124, an improvement support unit 125, an optimization unit 126, and a presentation unit 127.

[0015] Each of the above components may be implemented by software or hardware. When implemented by software, various functions can be realized by a CPU executing a computer program. The program may be stored on a non-transitory computer-readable recording medium, provided as a downloadable file from an external server, or implemented by so-called cloud computing, in which a program stored in an external storage unit is read and functions are realized. Each of the above components may be implemented in conjunction with a large-scale language model server. When implemented by hardware, it can be implemented by various circuits such as an ASIC, FPGA, or DRP. The embodiments deal with various information and concepts encompassing it. These are represented by high and low signal values ​​or quantum bits as a binary bit set consisting of 0 or 1, and communication and calculations can be performed by the above software or hardware aspects. The software may be a general-purpose OS or a dedicated OS.

[0016] The communication unit 10 can employ wired communication means such as USB, IEEE1394, Thunderbolt (registered trademark), wired LAN network communication, etc. The communication unit 10 may be configured to be connected to the communication network 5 via wireless communication means such as wireless LAN network communication, mobile communication such as 3G / LTE / 5G, Bluetooth (registered trademark) communication, etc. The communication unit 10 may also be configured to use both the wired communication means and wireless communication means described above. As shown in Figure 1, the communication unit 10 may also be configured to be connectable to an index measurement device 4 (a physiological index measurement device 4A as a saliva ORP measurement device and a psychological index measurement device 4B as a questionnaire implementation terminal) via a communication network 5.

[0017] The storage unit 11 stores various values, such as various programs, constants, coefficients, variables, setting values, formulas, and tables, of the information processing device 1 executed by the control unit 12. For example, the storage unit 11 stores reference values ​​(reference physiological indices, reference psychological indices) for determining a plurality of acceptance states (convinced acceptance state, relieved acceptance state, warning acceptance state, and cognitive rejection acceptance state), data defining the characteristics of each acceptance state, and the like. The storage unit 11 also stores data acquired by communicating with various information processing devices, such as the user terminal 3. The storage unit 11 may be, for example, a storage device such as a solid-state drive (SSD), or a storage medium such as a random access memory (RAM) that stores temporarily required information (arguments, arrays, etc.) related to program calculations. The information processing device 1 may also use an external storage unit (e.g., an external storage medium, cloud, etc.) in addition to the storage unit 11.

[0018] The control unit 12 is configured to execute information processing of the information processing device 1. The control unit 12 can be configured, for example, by a central processing unit (CPU), and in the embodiment, the control unit 12 is an example of a processor capable of executing programs related to the operations (steps) of the information processing device 1, which will be described later. The control unit 12 realizes various functions related to the information processing device 1, for example, by reading out programs stored in the storage unit 11. The control unit 12 executes, for example, a process of identifying an acceptance state by comprehensively analyzing both physiological indices and psychological indices, and a process of identifying areas for improvement in content based on the analysis results. Furthermore, the information processing of the software in the information processing device 1 is realized, for example, by the control unit 12 as hardware processing various programs stored in the storage unit 11.

[0019] The output unit 13 is, for example, a display unit of the information processing device 1. The output unit 13 may be included in the housing of the information processing device 1 or may be externally attached. The output unit 13 displays a graphical user interface (GUI) screen that can be operated by a user. The output unit 13 may be, for example, a display device such as a CRT display, a liquid crystal display, an organic EL display, a plasma display, or an electronic paper display, as well as a display device such as an illuminable light or a projector. It is optional whether or not the information processing device 1 includes the output unit 13. For example, the output of the information processing device 1 may be displayed on a display unit located at a location independent of the location where the information processing device 1 is installed. The output unit 13 may also have a device that outputs audio.

[0020] The input unit 14 is configured to receive, for example, an operation input made by an administrator of the information processing device 1. The input unit 14 may be included in the housing of the information processing device 1 or may be attached externally. For example, the input unit 14 may be a touch panel, a switch button, a mouse, a keyboard, a camera, a scanner, or the like. It is optional whether or not the information processing device 1 includes the input unit 14. For example, the information processing device 1 may receive an operation input to the information processing device 1 via an information processing terminal located at a location separate from the location where the information processing device 1 is installed.

[0021] 1-2. Large-scale language model server The large-scale language model server 2 is a server that provides AI analysis functions in supporting content improvement. The large-scale language model server 2 operates in cooperation with the optimization unit 126, and generates improvement proposal data (adjusted content) based on the results of an analysis of the acceptance state of content data, etc. In the embodiment, the optimization unit 126 is described as working in cooperation with the large-scale language model server 2, but the improvement support unit 125 may also be configured to identify areas to be improved in cooperation with the large-scale language model server.

[0022] 1-3. User terminal 3 The user terminal 3 shown in FIG. 1 is an information processing device (e.g., a personal computer, a smartphone, or a tablet device) used by a person (e.g., a content creator, a marketing person, etc.) who receives the analysis results of the reception state of content, and is a terminal that can access the information processing device 1. The user terminal 3 is capable of information processing, such as outputting content (image data, video data, audio data) to be evaluated to the information processing device 1. The user terminal 3 is also capable of information processing, such as receiving data, such as the reception state analysis results, improvement data, and adjusted content generated by the information processing device 1, and outputting the data as images or audio. Note that the user terminal 3 is not necessarily required for the information processing system 100, and the information processing device 1 may be sufficient alone. In other words, the user may operate the input unit 14 of the information processing device 1 to evaluate the reception state of content and confirm the output of the evaluation results on the output unit 13 of the information processing device 1. However, in the embodiment, a form in which a user uses the user terminal 3 will be described as an example.

[0023] The user terminal 3 as an information processing device also has the same components as the information processing device 1. That is, the user terminal 3 has, for example, a communication unit, a storage unit, a control unit, an output unit, and an input unit, and these components are electrically connected via a communication bus. The description of the communication unit, storage unit, control unit, output unit, and input unit is omitted because they are the same as those described for the information processing device in Section 1-1.

[0024] 1-4. Indicator measuring device 4 The index measuring devices 4 are a group of devices that measure physiological and psychological indices of the evaluator, and include a physiological index measuring device 4A and a psychological index measuring device 4B.

[0025] 1-4-1.Physiological index measuring device 4A The physiological index measuring device 4A is a device that measures the oxidation-reduction potential (ORP) of the evaluator's saliva, which is an example of a physiological index. In the following description, this oxidation-reduction potential is also referred to as ORP, ORP value, or potential difference. As the physiological index measuring device 4A, for example, a saliva oxidation-reduction potential measuring device (ORPreader (registered trademark)) manufactured by Orp Corporation can be used.

[0026] As shown in FIGS. 6A and 6B, in one embodiment, the physiological index measuring device 4A is a human saliva ORP measuring device, and includes a physiological index measuring device main body . In one embodiment, the physiological index measuring device main body 36 includes a measurement start button 38, a measurement result print button 37, a display unit 39, a display unit 40, a print unit 41, and multiple (three in one embodiment, but this number may also be single) measurement boxes 42.

[0027] When the measurement start button 38 is pressed, measurement of the ORP value of the evaluator's saliva is started. The measurement result print button 37 is a button that is pressed when printing out the measurement results of the ORP value. Display unit 39 has a function of displaying the measured ORP value and can be configured with, for example, a liquid crystal display. Display unit 40 has a function of displaying the year, time, etc. and can be configured with, for example, a liquid crystal display. The printing unit 41 is driven when the measurement result print button 37 is pressed, and can be configured, for example, with a thermal printing mechanism. The measurement box 42 is provided with an electrode mechanism 4AT (see FIG. 6B) having electrodes such as a reference electrode 32 and an indicator electrode 26.

[0028] 6B includes a silver-silver chloride reference electrode 32 and a pure gold indicator electrode 26. The use of the two opposing electrodes, the reference electrode 32 and the indicator electrode 26, makes it possible to obtain the electrolyte concentrations of saliva components and the activity ratios of oxidized and reduced forms, and to measure the potential difference between oxidation and reduction.

[0029] As shown in Fig. 6B, the cotton portion 23 of the shaft (in one embodiment, a cotton swab 22) for impregnating saliva is impregnated with saliva. The contact area between the cotton portion 23 and the head of the indicator electrode 26 is shown as area 25 in Fig. 6B.

[0030] The KCl solution 34 is impregnated with the reference electrode 32, and functions to exchange positive and negative electrons (electrons) in the ORP of saliva. The liquid junction 30 also serves as a contact point for the cotton part 23 of the cotton swab 22, which is soaked in saliva and wet. At the liquid junction 30, a portion of the KCl solution 34 is drawn into the cotton portion 23 by capillary action, resulting in the exchange of positive and negative electrons between the reference electrode 32 and the indicator electrode 26 via the KCl solution 34. The physiological index measuring device 4A measures the oxidation-reduction potential (mV) between the electrodes in this electron exchange, and the measurement result is displayed on the display unit 39.

[0031] The electrode mechanism 4AT includes a sample reservoir 29A into which the shaft portion (cotton portion 23 of the swab 22) impregnated with saliva is inserted, a base portion 24 on which the sample reservoir 29A is provided, and a tank lid 33 for storing a KCl solution. An indicator electrode 26 is fixed and adhered to the bottom 29 of the sample vessel. Furthermore, the portion 27 is where the indicator electrode 26 and the lead wire 28 are connected by adhesive. Furthermore, the portion 31 is where the reference electrode 32 and the lead wire 28 are bonded and connected. Furthermore, the electrode mechanism 4AT has a measurement unit 35. The measurement unit 35 has a function of measuring the oxidation-reduction potential (mV). That is, the measurement unit 35 has a function of measuring the potential difference between the positive and negative electron transfers at the reference electrode 32 and the indicator electrode 26.

[0032] 1-4-2.Psychological index measuring device 4B The psychological index measurement device 4B is a device for quantifying an evaluator's evaluation of interest in content, and acquires an NPS value, which is an example of a psychological index, as the quantified value. In one embodiment, the psychological index measurement device 4B is configured as an information processing device such as a tablet terminal, a smartphone, or a PC terminal, and presents a questionnaire about the content (e.g., questions based on NPS (registered trademark): Net Promoter Score) to the evaluator and accepts the questionnaire results. The psychological index measurement device 4B processes the questionnaire response results using a predetermined algorithm based on the rules of NPS, and quantifies the evaluation results.

[0033] 2. Functional configuration The functional configuration of the information processing device 1 according to this embodiment will be described with reference to Fig. 3. Information processing by software stored in the storage unit 11 is specifically realized by the control unit 12, which is an example of hardware, and each functional unit included in the control unit 12 is executed.

[0034] 2-1. Data Acquisition Unit 121 The data acquisition unit 121 is a functional unit that acquires, for example, content (content data) to be evaluated. That is, the data acquisition unit 121 acquires content (content data) such as image data, video data, and audio data transmitted from the user terminal 3 via, for example, the communication unit 10, and stores the content in the storage unit 11. Note that, in the case of real-time content such as a live event, for example, the data acquisition unit 121 may acquire video and audio signals from cameras and microphones installed at the venue and acquire them as digital data. In an example of an embodiment, the data acquisition unit 121 can acquire supplementary data in addition to the content (content data). In an example of an embodiment, the supplementary data includes at least one of electroencephalogram data (e.g., EEG) of the evaluator and free description data of the evaluator. In the embodiment, the description will be given assuming that both are included. It is not essential for the data acquisition unit 121 to acquire supplementary data. That is, supplementary data is not essential for information processing in the information processing device 1. The electroencephalogram data and free description data are used, for example, in analysis by the improvement support unit 125 and analysis by the optimization unit 126.

[0035] 2-2. Physiological index acquisition section 122 The physiological index acquiring unit 122 is a functional unit that acquires the physiological index (saliva oxidation-reduction potential) of the evaluator from the physiological index measuring device 4A. An example of the physiological index in the embodiment is an ORP value, and the physiological index corresponds to a potential that indicates the oxidation-reduction state of the saliva of the evaluator who has come into contact with the content. The physiological index acquiring unit 122 acquires numerical data of the measured oxidation-reduction potential, for example, via the communication unit 10. The acquired physiological index is stored in the storage unit 11. Here, the process of acquiring data is considered to be data exchange, but is not limited to this and may include various types of calculation processes. For example, the physiological index acquiring unit 122 may receive a voltage value of an electrode of the physiological index measuring device 4A and calculate the redox potential of saliva from this voltage value. In other words, the specific value of the redox potential may be calculated by the information processing device 1, rather than by the physiological index measuring device 4A.

[0036] 2-3.Psychological index acquisition part 123 The psychological index acquisition unit 123 is a functional unit that acquires the psychological index of the evaluator (the evaluator's subjective evaluation of the content) from the psychological index measurement device 4B. That is, the psychological index acquisition unit 123 acquires psychological indexes, which are data that quantify (quantify) the evaluation related to the evaluator's interest in the content, based on, for example, the response results of an NPS questionnaire or the like. The acquired psychological indexes are stored in the storage unit 11. Here, the process of acquiring data is considered to be data exchange, but is not limited to this and may include various types of calculation processes. For example, the psychological index acquiring unit 123 may receive questionnaire responses from the psychological index measurement device 4B and calculate a quantified (digitized) psychological stress from the responses. In other words, the specific psychological stress value may be calculated by the information processing device 1, rather than by the psychological index measurement device 4B.

[0037] 2-4. Acceptance Analysis Section 124 The acceptance level analysis unit 124 is a functional unit that determines the acceptance state of the evaluator based on the respective indices (physiological and psychological indices) acquired from the physiological index acquisition unit 122 and the psychological index acquisition unit 123. In other words, the acceptance level analysis unit 124 is configured to analyze whether the evaluator corresponds to one of a plurality of predetermined acceptance states based on the physiological and psychological indices. Based on the map shown in FIG. 4 , the acceptance level analysis unit 124 classifies the combination of the physiological index (in one embodiment, the ORP value) and the psychological index (in one embodiment, the NPS value) into one of the following acceptance states: a satisfactory acceptance state (corresponding to region Rg1), a warning acceptance state (corresponding to region Rg2), a relieved acceptance state (corresponding to region Rg3), a cognitive rejection acceptance state (corresponding to region Rg4), and an intermediate acceptance state (corresponding to region Rg5). These acceptance states indicate how the evaluator, who has come into contact with the content, accepts the content. These acceptance states will be described in detail in Section 3 below. The acceptance level analysis unit 124 can classify the acceptance state by referring to a threshold value stored in the storage unit 11 (for example, s1 in FIG. 4, etc.).

[0038] 2-5. Improvement Support Department 125 The improvement support unit 125 is a functional unit that identifies areas for improvement in the content based on the analysis results of the acceptance level analysis unit 124 (data indicating which acceptance state the evaluator who came into contact with the content belongs to) and supplementary data (in one embodiment, electroencephalogram data and free description data). The improvement support unit 125 identifies improvement elements required to move from the current acceptance state (for example, see point P1 in FIG. 5) to a target acceptance state (for example, a satisfied acceptance state).

[0039] 2-6. Optimization section 126 The optimization unit 126 is a functional unit that automatically adjusts the content (content data) and generates adjusted content based on the improvement data generated by the improvement support unit 125. The optimization unit 126 operates in cooperation with the large-scale language model server 2, and executes processing to generate adjusted content.

[0040] 2-7. Presentation part 127 The presentation unit 127 is a functional unit that presents the analysis results by the acceptability analysis unit 124, the improvement data by the improvement support unit 125, the content after adjustment by the optimization unit 126, etc., on, for example, the output unit 13 or the output unit of the user terminal 3. The presentation unit 127 can convert various data into a visually easy-to-understand format (for example, a map format as shown in FIG. 4, a graph, a table, etc.) and present it.

[0041] 3. Description of the receptive state The multiple acceptance states in the information processing system 100 include four independent acceptance states classified according to the respective degrees of physiological and psychological indices. Categorizing these four independent acceptance states makes it possible to systematically grasp the quality of the evaluator's acceptance of content along two axes: physiological response (relaxed / stressed) and psychological evaluation (high interest / low interest). This makes it possible to clearly identify complex acceptance states that cannot be captured by a single index and specifically identify areas for improving the content. In addition to the four independent acceptance states, the multiple acceptance states also include an intermediate acceptance state. The intermediate acceptance state corresponds to a transitional state in which the evaluator has not yet reached one of the four independent acceptance states. The intermediate acceptance state corresponds to a transitional state in which the evaluator has not yet reached one of the four independent acceptance states. By providing this intermediate acceptance state, it is possible to properly grasp the borderline state in which the evaluator's acceptance state is not clearly classified, enabling a more precise analysis of the acceptance state. Content judged to be in an intermediate acceptance state is in a state in which the evaluator's acceptance state is unclear, so the content's claims can be considered weak, suggesting that it may be possible to guide the evaluator to a clearer acceptance state, which is useful information for content creators. These five receptive states are described below.

[0042] 3-1. State of acceptance The satisfied acceptance state is a state in which the evaluator shows a high level of recognition and understanding of the content and actively accepts it. This state corresponds to region Rg1 in FIG. 4, and is located in a region where the physiological index (ORP value) indicates the reduction side (low value, strong reduction power) and the psychological index (NPS value) indicates a high value. In one embodiment, the satisfied acceptance state is a range in which the ORP value is equal to or less than a threshold value s1 and the NPS value is equal to or greater than a threshold value t1. Note that, in one embodiment, the satisfied acceptance state may have a specified lower limit, such as an ORP value equal to or greater than a threshold value s2, and an specified upper limit, such as an NPS value equal to or less than a threshold value t2. Of course, these lower and upper limits are not necessary.

[0043] The threshold value s1 (mV) is specifically, for example, 0, -2, -4, -6, -8, -10, -12, -14, -16, -18, -20, -25, -30, -35, -40, -45, or -50, and may be within the range of the two values ​​exemplified here. When the NPS value is quantified on a scale of 1 to 10, the threshold value t1 may be, for example, 8, 9, or 10, and may be within the range of the two values ​​exemplified here. Preferably, the threshold value t1 is 9.

[0044] In a state of convinced acceptance, content is accepted with "understanding" and "convincing," leading to the building of long-term trust and relationships. This state is therefore a highly desirable state of acceptance in a variety of contexts, including education, presentations, medical care, and advertising, and has a significant impact on the rate at which information is retained and behavioral change.

[0045] 3-2. Warning acceptance state The warning acceptance state is a state in which the evaluator is wary of the content but recognizes its importance and necessity. This state corresponds to region Rg2 in FIG. 4, and is located in a region where the physiological index (ORP value) indicates the oxidizing side (high value, weak reducing power) and the psychological index (NPS value) indicates a high value. In one embodiment, the warning acceptance state is a range in which the ORP value is equal to or greater than threshold s3 and the NPS value is equal to or greater than threshold t1. Note that, in one embodiment, the warning acceptance state may have an upper limit specified, such as an ORP value equal to or less than threshold s4, or an NPS value equal to or less than threshold t2. Of course, these upper limits may not be required.

[0046] The threshold value s3 (mV) is higher than the threshold value s1, and specifically may be, for example, 50, 45, 40, 35, 30, 25, 20, 18, 16, 14, 12, 10, 8, 6, 4, 2, or 0, or may be within the range of the two values ​​exemplified here. When the NPS value is quantified on a scale of 1 to 10, the threshold value t1 may be, for example, 8, 9, or 10, and may be within the range of the two values ​​exemplified here. Preferably, the threshold value t1 is 9.

[0047] In the warning acceptance state, the content is accepted with a sense of tension and caution, which is an appropriate state for conveying crisis management information or important warning messages. Note that prolonged exposure to the content may cause fatigue and stress in the evaluator, so it may be necessary to appropriately manage exposure to the content.

[0048] 3-3. Reassuring acceptance state The reassuring acceptance state is a state in which the evaluator is relaxed about the content and accepts it with a sense of security. This state corresponds to region Rg3 in FIG. 4, and is located in a region where the physiological index (ORP value) indicates the reducing side (low value, strong reducing power) and the psychological index (NPS value) indicates a low value. In one embodiment, the reassuring acceptance state is a range in which the ORP value is equal to or less than threshold s1 and the NPS value is equal to or less than threshold t3. Note that, in one embodiment, the reassuring acceptance state may have a specified lower limit, such as an ORP value equal to or greater than threshold s2, or may have a specified lower limit, such as an NPS value equal to or greater than threshold t4. Of course, these lower limits are not necessary.

[0049] The threshold value s1 (mV) is specifically, for example, 0, -2, -4, -6, -8, -10, -12, -14, -16, -18, -20, -25, -30, -35, -40, -45, -50, and may be within the range of the two values ​​exemplified here. The threshold value t3 is lower than the threshold value t1, and when the NPS value is quantified on a scale of 10, it may be, for example, 4, 5, 6, or 7, or may be within the range of the two values ​​exemplified here. Preferably, the threshold value t3 is 6.

[0050] In a state of secure acceptance, content is received with a calm feeling, which is desirable for information content in waiting rooms at medical institutions or content for users at welfare facilities. This state is optimal for content aimed at stress reduction and relaxation, such as in medical and welfare settings, as well as meditation and mindfulness.

[0051] 3-4. Cognitive rejection acceptance state The cognitive rejection acceptance state is a state in which the evaluator has little interest in the content and is not actively processing the information. This state corresponds to region Rg4 in FIG. 4, and is located in a region where the physiological index (ORP value) indicates the oxidizing side (high value, weak reducing power) and the psychological index (NPS value) indicates a low value. In one embodiment, the cognitive rejection acceptance state is a range in which the ORP value is equal to or greater than threshold s3 and the NPS value is equal to or less than threshold t3. Note that, in one embodiment, the cognitive rejection acceptance state may have an upper limit specified, such as an ORP value equal to or less than threshold s4, and a lower limit specified, such as an NPS value equal to or greater than threshold t4. Of course, these upper and lower limits are not necessary.

[0052] The threshold value s3 (mV) is higher than the threshold value s1, and specifically may be, for example, 50, 45, 40, 35, 30, 25, 20, 18, 16, 14, 12, 10, 8, 6, 4, 2, or 0, or may be within the range of the two values ​​exemplified here. The threshold value t3 is lower than the threshold value t1, and when the NPS value is quantified on a scale of 10, it may be, for example, 4, 5, 6, or 7, or may be within the range of the two values ​​exemplified here. Preferably, the threshold value t3 is 6.

[0053] In the cognitive rejection acceptance state, content is accepted with rejection or indifference, and content creators should generally avoid creating content that leads to this state. When content is evaluated as a state, it can be concluded that a comprehensive review of the content, presentation method, presentation timing, etc. is necessary.

[0054] 3-5. Intermediate Receptive State The intermediate receptive state is a transitional state in which the evaluator is not clearly classified into any of the four independent receptive states. This state corresponds to region Rg5 in Figure 4, and is located in the region where physiological or psychological indices show intermediate values.

[0055] In one embodiment, the intermediate acceptance state can be defined as a region Rg5 where the ORP value is between thresholds s1 and s3, or a region Rg6 where the ORP value is between thresholds t1 and t3.

[0056] The intermediate acceptance state suggests that the evaluator's acceptance state has not yet clearly reached one of the four acceptance states (it is not clearly classified into one of the four acceptance states), and can be evaluated as a transitional state. The content in this intermediate acceptance state may be able to be improved to lead to the desired acceptance state.

[0057] 4. Information Processing by Information Processing System 100 The program of the information processing system 100 according to the embodiment executes each step (information processing method) described below. Each step will be described mainly with reference to FIG.

[0058] <Step S1: Physiological index acquisition step> In the physiological index acquisition step, the physiological index acquisition unit 122 acquires the physiological index (ORP value in one embodiment) of the evaluator from the physiological index measurement device 4A. Specifically, the physiological index acquisition unit 122 collects saliva before, during, or after the evaluator watches the content and acquires the ORP value (oxidation-reduction potential) measured by the physiological index measurement device 4A. The ORP value indicates a more relaxed state of the evaluator as it becomes more reduced (e.g., a negative value), and indicates a more stressed state as it becomes more oxidized (e.g., a positive value). The ORP value, which is one example of a physiological index, is stored in the storage unit 11.

[0059] Here, variations in the method by which the information processing device 1 acquires the physiological index (ORP value) will be described. The configuration may be such that the user visually checks the physiological indexes acquired by the physiological index measuring device 4A, inputs the values ​​of the physiological indexes into the user terminal 3, and transmits them from the user terminal 3 to the information processing device 1. In addition, the physiological index measuring device 4A and the user terminal 3 may be configured to work together, so that the physiological indexes acquired by the physiological index measuring device 4A are automatically imported into the user terminal 3 and transmitted from the user terminal 3 to the information processing device 1. Furthermore, the physiological index measuring device 4A and the information processing device 1 may be configured to cooperate with each other, so that the physiological indexes acquired by the physiological index measuring device 4A are automatically taken into the information processing device 1.

[0060] <Step S2: Psychological index acquisition step> In the psychological index acquisition step, the psychological index acquisition unit 123 acquires the psychological index of the evaluator (in one example of the embodiment, the NPS value) from the psychological index measurement device 4B. Specifically, the psychological index acquisition unit 123 acquires the response results of an NPS questionnaire conducted after the evaluator has viewed the content. In the NPS questionnaire, the evaluator answers questions such as, for example, "How likely are you to recommend this content to your friends or colleagues?" The psychological index measurement device 4B quantifies this response value as an NPS value, and the physiological index acquisition unit 122 acquires this. The NPS value, which is one example of a psychological index, functions as an index that quantitatively represents the evaluator's subjective level of interest and acceptance of the content. The NPS value, which is one example of a psychological index, is also stored in the storage unit 11.

[0061] Here, variations in the method by which the information processing device 1 acquires the psychological index (NPS value) will be described. The configuration may be such that the user visually checks the psychological index acquired by the psychological index measurement device 4B, inputs the value of the psychological index into the user terminal 3, and transmits it from the user terminal 3 to the information processing device 1. In addition, the psychological index measurement device 4B and the user terminal 3 may be configured to work together, so that the psychological index acquired by the psychological index measurement device 4B is automatically imported into the user terminal 3 and transmitted from the user terminal 3 to the information processing device 1. Furthermore, the psychological index measurement device 4B and the information processing device 1 may be configured to cooperate with each other, so that the psychological index acquired by the psychological index measurement device 4B is automatically taken into the information processing device 1.

[0062] The method of obtaining the psychological index (NPS value) is not limited to the above, and it is also possible to accept a paper-based questionnaire, have a person process and quantify the questionnaire results, and have the user input the quantified content into the user terminal 3 and send it to the information processing device 1, or to have the user input the quantified content into the information processing device 1 and have it imported into the information processing device 1.

[0063] <Step S3: Supplementary data acquisition step> In the supplemental data acquisition step, the data acquisition unit 121 acquires the electroencephalogram data and free description data of the evaluator as supplemental data. The electroencephalogram data is acquired from an electroencephalogram measuring device (e.g., a simple electroencephalograph) while the evaluator is viewing the content. The electroencephalogram data functions as an objective indicator of the evaluator's level of concentration, interest, emotional changes, etc. For example, by analyzing the power spectral density of each frequency band, such as alpha waves, beta waves, and theta waves, it is possible to quantitatively grasp the state of relaxation, concentration, level of drowsiness, etc. Free-text data is text data such as impressions and opinions written by evaluators after viewing the content. Evaluators freely write their impressions of the content, areas they would like to see improved, and scenes that left a particularly strong impression on them. This supplementary data is combined with the results of the reception analysis to identify more detailed areas for improvement. The acquisition of supplementary data is optional, and the state of reception can be analyzed using only physiological and psychological indices. The acquired supplementary data is stored in the storage unit 11.

[0064] <Step S4: Receptive State Analysis Step> In the acceptance state analysis step, the acceptance level analysis unit 124 determines the acceptance state of the evaluator based on the acquired physiological index (in this embodiment, the ORP value) and psychological index (in this embodiment, the NPS value). Specifically, the acceptance level analysis unit 124 compares each acquired index value with the thresholds stored in the storage unit 11 (thresholds s1, s3, t1, and t3 in FIG. 4).

[0065] In the following, two arbitrary receptor states out of the four independent receptor states will be selected, and the relationship between each receptor state and the ORP value and NPS value will be discussed. The plurality of acceptance states include a consent acceptance state and a recognition rejection acceptance state. As shown in Figure 4, the ORP value in the acceptance state has a greater degree of reduction (stronger reduction power) than the ORP value in the acceptance state. Also, the NPS value in the acceptance state has a greater degree of reduction than the NPS value in the acceptance state. The plurality of acceptance states also includes a relief acceptance state and a warning acceptance state. As shown in Figure 4, the ORP value in the reassuring acceptance state has a greater degree of reduction (stronger reducing power) than the ORP value in the warning acceptance state. Also, the NPS value in the reassuring acceptance state is smaller than the NPS value in the warning acceptance state.

[0066] The plurality of acceptance states includes a cognitive rejection acceptance state and an alert acceptance state. As shown in Figure 4, the ORP value in the cognitive rejection acceptance state and the ORP value in the warning acceptance state are smaller in degree of reduction (weaker reducing power) than threshold s3 (an example of a physiological index threshold). Also, the NPS value in the cognitive rejection acceptance state is smaller in degree than the NPS value in the warning acceptance state. The plurality of acceptance states also includes an assured acceptance state and a satisfied acceptance state. 4, the ORP value in the reassuring acceptance state and the ORP value in the satisfied acceptance state have a greater degree of reduction (stronger reducing power) than a predetermined threshold value s1 (an example of a physiological index threshold). Also, the NPS value in the satisfied acceptance state is greater than the NPS value in the reassuring acceptance state.

[0067] The multiple acceptance states include a cognitive rejection acceptance state and a reassured acceptance state. 4, the NPS value in the cognitive rejection acceptance state and the NPS value in the reassurance acceptance state are smaller than a predetermined threshold t3 (an example of a psychological index threshold). Also, the ORP value in the cognitive rejection acceptance state is smaller in degree of reduction (weaker reducing power) than the ORP value in the reassurance acceptance state. The plurality of acceptance states also includes a warning acceptance state and a consent acceptance state. The NPS value in the warning acceptance state and the NPS value in the satisfaction acceptance state are greater than a predetermined threshold t1 (an example of a psychological index threshold). Also, the ORP value in the satisfaction acceptance state has a greater degree of reduction (stronger reducing power) than the ORP value in the warning acceptance state.

[0068] Each of the four independent acceptance states is defined by two of thresholds s1, s3, t1, and t3. For example, the satisfaction acceptance state is defined by thresholds s1 and t1. The warning acceptance state is defined by thresholds s3 and t1. The relief acceptance state is defined by thresholds s1 and t3. The recognition rejection acceptance state is defined by thresholds s3 and t3. By setting clear boundaries using such thresholds, each receptive state is uniquely determined by the combination of two thresholds: physiological and psychological indices, eliminating ambiguity in judgment and improving the accuracy and reliability of automatic judgment by the system. In addition, by clearly defining intermediate receptive states as ranges between these thresholds, it becomes possible to quantitatively evaluate the possibility of transitioning to the four independent receptive states and the direction of improvement.

[0069] Next, we will discuss the relationship between the ORP value and NPS value for intermediate receipt conditions. The acceptability analysis unit 124 analyzes that if the ORP value or the NPS value is within a predetermined range, it corresponds to an intermediate acceptability state. As shown in FIG. 4, the predetermined range includes a range (corresponding to region Rg5) in which the degree of the ORP value is between threshold s1 (an example of a first physiological index threshold) and threshold s3 (an example of a second physiological index threshold), and a range (corresponding to region Rg6) in which the degree of the NPS value is between threshold t1 (an example of a first psychological index threshold) and threshold t3 (an example of a second psychological index threshold).

[0070] Next, an example of analysis by the acceptability analysis unit 124 will be described. For example, when the ORP value is −20 mV (less than or equal to the threshold value s1) and the NPS value is 9 (more than or equal to the threshold value t1), the acceptance level analysis unit 124 determines that the state is the satisfactory acceptance state (area Rg1). Also, for example, if the ORP value is +30 mV (above threshold s3) and the NPS value is 3 (below threshold t3), the acceptance level analysis unit 124 determines that the state is the recognition rejection acceptance state (area Rg4). Furthermore, for example, if the ORP value is -5 mV (between thresholds s1 and s3) or if the NPS value is 6 (between thresholds t1 and t3), the acceptance level analysis unit 124 determines that the state is an intermediate acceptance state (region Rg5 or Rg6). The acceptance level analysis unit 124 stores the determination result as acceptance state data in the memory unit 11. This acceptance state data may include, for example, the type of acceptance state determined, specific numerical values ​​of each index, the time of determination, etc.

[0071] <Step S5: Acceptance State Presentation Step> In the acceptance state presentation step, the presentation unit 127 causes the output unit to visually present the analysis results by the acceptance level analysis unit 124. Specifically, the output unit displays a screen on which the acceptance states of the evaluators are plotted on a map as shown in Fig. 4. The output unit may be the output unit 13 (display unit) of the information processing device 1 or the output unit (display unit) of the user terminal 3. See Figure 4. For example, if the current acceptance state is the cognitive rejection acceptance state (area Rg4), the evaluator's data point is displayed at the corresponding position on the map. The presentation unit 127 may also cause the output unit to present the name of the determined acceptance state (e.g., "cognitive rejection acceptance state") together with a description of the characteristics of that state (e.g., "A state in which interest in the content is low and active information processing is not being performed"). Furthermore, the presentation unit 127 may also present specific numerical values ​​of the physiological index (ORP value) and psychological index (NPS value) so that the user can quantitatively and intuitively grasp the state of acceptance of the evaluator. This visual presentation allows the content creator to immediately understand the need for and direction of improvement. The presentation may be made by using audio together with a visual display, or by using only audio without a visual display.

[0072] <Step S6: Decide whether to move to the improvement phase> In this step, the user checks the analysis results of the acceptance state and then selects whether to end the processing or proceed to the improvement phase (information processing from step S7 onwards). Specifically, the user checks the acceptance state presented by the presentation unit 127, and if the result is satisfactory, the processing ends. On the other hand, if the acceptance state has not reached the target state, the user can choose to transition to the improvement phase. The presentation unit 127 causes the output unit 13 or the output unit of the user terminal 3 to present a display for making this selection, and the control unit 12 can accept the input result via the input unit 14 of the information processing device 1 or the input unit of the user terminal 3. If transitioning to the improvement phase is to be made, the process proceeds to the improvement data generation step of step S7. If transitioning to the improvement phase is not to be made, the process shown in FIG. 7 ends. This step enables flexible processing according to the user's needs.

[0073] <Step S7: Improved Data Generation Step> In the improvement data generation step, the improvement support unit 125 generates improvement data for the content based on the analysis results of the acceptance level analysis unit 124 and supplementary data (electroencephalogram data, free description data). The improvement data is data that identifies improvements required for the content from the analysis results of the content in the acceptance level analysis unit 124 in order to reach a target acceptance state, which is one of multiple acceptance states. The improvement support unit 125 analyzes the difference between the current acceptance state and the target acceptance state, and identifies improvements to close the difference. The target acceptance state can be acquired, for example, in step S3 or step S6.

[0074] For example, if the current acceptance state (acceptance state of the analysis results in step S4) is a warning acceptance state (ORP value is on the oxidizing side, NPS value is high) as shown at point P1 in Figure 5, areas that need improvement in elements such as content structure, presentation method, amount of information, and presentation timing are identified. In addition, by identifying areas where the evaluator's concentration is declining from the EEG data and extracting any discomfort or requests for improvement felt by the evaluator from the free-form writing data, it is possible to identify more specific areas for improvement.

[0075] An example of a method for generating improvement data by the improvement support unit 125 will be described. The first method is to identify areas for improvement based on a predefined algorithm. Specifically, the difference vector between the coordinates of the current acceptance state (ORP value, NPS value) and the coordinates of the target acceptance state is calculated, and the priority of improvement is determined based on the direction and magnitude of the difference vector. For example, a rule-based algorithm is applied that suggests adding relaxing elements (calm music, warm colors, slow tempo) if the ORP value needs to be reduced, or suggests clarifying information (adding captions, simplifying the structure) if the NPS value needs to be improved.

[0076] As a second means, the improvement support unit 125 can also generate improvement data in cooperation with the large-scale language model server 2. In this case, the improvement support unit 125 generates an analysis prompt based on the analysis results of the receptive state, the electroencephalogram data, and the free description data, and transmits it to the large-scale language model server 2. The improvement support unit 125 can generate improvement data based on the response results from the large-scale language model server 2.

[0077] The generated improvement data is stored in the storage unit 11 as structured data including information such as the location of improvement of the content (content data), the improvement method, and the priority.

[0078] <Step S8: Improvement Data Presentation Step> In the improvement data presentation step, the presentation unit 127 causes the output unit 13 or the output unit of the user terminal 3 to present the improvement data generated by the improvement support unit 125. For example, it is possible to present a specific improvement suggestion such as "The evaluator's concentration level is decreasing from 3 minutes 20 seconds to 4 minutes 20 seconds of the content, so we recommend adjusting the tempo of this part."

[0079] <Step S9: Adjustment Data Generation Step> In the adjustment data generation step, the optimization unit 126 generates adjusted content by adjusting the content (content data) based on the improvement data generated by the improvement support unit 125. The optimization unit 126 cooperates with the large-scale language model server 2 to automatically adjust the content (content data) based on information on the improvement points and improvement methods included in the improvement data. For example, in the case of video content, it is possible to automatically perform color correction (changing to warmer colors), audio level adjustment (adjusting the volume of background music), tempo change (fine adjustment of playback speed), addition / correction of subtitles, etc. The generated adjusted content is stored in the storage unit 11.

[0080] <Step S10: Adjusted Content Data Presentation Step> In the adjusted content data presentation step, the presentation unit 127 causes the output unit 13 or the output unit of the user terminal 3 to present the adjusted content generated by the optimization unit 126 . The presentation unit 127 may display the pre-adjustment content and the post-adjustment content side by side, or highlight the adjusted parts, so that the user can easily check the changes.

[0081] 5. Functions and Effects of the Embodiments According to the information processing system 100 of the embodiment, it is possible to evaluate the information acceptance state of content multifacetedly and objectively by integrating and analyzing indices from two different perspectives, namely, the evaluator's physiological index (salivary oxidation-reduction potential) and psychological index (the evaluator's subjective evaluation of the content). In other words, according to the information processing system 100 of the embodiment, it is possible to simultaneously and appropriately grasp the degree of both aspects of the evaluator's cognition and understanding, which could not be captured by conventional evaluations using a single index, and to classify the acceptance state into four independent acceptance states, namely, a convinced acceptance state, a warning acceptance state, a relieved acceptance state, and a cognitive rejection acceptance state, as well as an intermediate acceptance state, thereby making it possible to evaluate the quality of information acceptance of content multifacetedly and objectively.

[0082] In the information processing system 100 according to the embodiment, the ORP value of saliva is used as an example of a physiological index. The ORP value is a physiological index that is non-invasive and can be easily measured, and it can capture physiological responses in real time without placing a burden on the evaluator. By combining this ORP value with the NPS value, it becomes possible to appropriately determine whether the product was accepted and recognized as intended.

[0083] Furthermore, by visually presenting the results using a two-dimensional map such as that shown in Figure 4, users (content creators) can grasp at a glance the difference between the current acceptance state and the target state, and can clearly understand the direction of improvement.

[0084] Furthermore, the information processing system 100 according to the embodiment not only analyzes the reception state, but also has a function for generating improvement data by the improvement support unit 125 and a function for automatically generating adjusted content by the optimization unit 126, thereby making it possible to provide content creators with specific and feasible improvement measures.

[0085] The information processing system 100 according to the embodiment is effective not only for productions such as video data, but also for measuring and optimizing the effectiveness of live events (e.g., corporate events). For example, in an in-house award ceremony, physiological and psychological indices can be acquired from multiple participants, and the receptive state can be analyzed for each segment of the event (opening, award ceremony, award speech, top message, etc.) to optimize the event structure. Furthermore, in a top message presentation, physiological and psychological indices can be measured during a rehearsal to understand the receptive state in advance and adjust the presentation method for the actual event. For example, if the rehearsal measurement indicates a warning receptive state, adjusting the tone and expressions to be more gentle and friendly can lead to the target acceptable receptive state.

[0086] 6. Other embodiments The physiological index acquisition unit 122 may acquire physiological indices for each part of the content, the psychological index acquisition unit 123 may acquire psychological indices for each part of the content, and the acceptance level analysis unit 124 may analyze whether each part of the content corresponds to one of a plurality of predetermined acceptance states. For example, if the content is a short video, the ORP value may be measured immediately after the start and end of the content, and if the content is a long event, the ORP value may be measured for each part such as the opening, presentation, and closing. Note that psychological indices are also acquired for each part in the same way. This makes it possible to track changes in the acceptance state throughout the content.

[0087] The large-scale language model server 2 may be a combination of closed AI and open AI. For example, when the improvement support unit 125 generates data in cooperation with the large-scale language model server 2, first, the closed AI (a dedicated AI that operates in a private environment) of the large-scale language model server 2 analyzes the analysis results of the evaluator's electroencephalogram data, descriptive data, and receptive state using a deep learning algorithm, and extracts points for improving the content. The open AI (AI that operates in a public environment) on the large-scale language model server 2 then performs a reanalysis that takes into account social evaluations and trend information, generating comprehensive improvement data that takes market acceptability into account. Note that this step-by-step process is just one example, and the processing order and type of AI used can be changed as appropriate depending on the type of content and purpose.

[0088] In the embodiment, an NPS questionnaire is used as a psychological index, but the present invention is not limited to this, and other indices that can quantify the evaluator's subjective evaluation of the content may be used. For example, a Likert scale (5- to 7-point scale) can be used to measure multidimensional aspects such as "satisfaction," "understanding," and "trust." The Likert scale is commonly used in the medical and educational fields, and allows for analysis along multiple evaluation axes. Alternatively, a visual analogue scale (VAS) may be used to express the evaluator's sense of comfort and immersion with a continuous value ranging from 0 to 100. VAS is widely used in psychology and clinical evaluations, and is capable of capturing subtle changes in psychological states. Furthermore, the Semantic Differential (SD) method can be used to quantify the impression of content using pairs of polar adjectives such as "fun-boring" or "reassuring-anxious." The SD method is widely used in advertising and UX research, and is suitable for evaluating the emotional aspects of content. In addition, a behavioral preference test (multiple choice evaluation) may be configured to use multiple choice questions such as "Which content would you like to watch again?". Similar to NPS, a behavioral preference test is useful as an index that reflects the actual behavioral intentions of the evaluator. These psychological indices may be used alone or in combination to evaluate a multifaceted psychological state.

[0089] Furthermore, the information processing system 100 may be configured to record the analysis results of the acceptance state and the history of the improvement process in cooperation with blockchain technology. That is, the control unit 12 may further include a recording unit (not shown in FIG. 3) that records information processed by the information processing device 1, such as the analysis results of the acceptance level analysis unit 124, in the blockchain. For example, for content that receives a high rating, such as a satisfactory acceptance state, in the initial acceptance state analysis, the quality of the content can be proven by recording the evaluation results on the blockchain. In addition, by recording on the blockchain the history of generating adjusted content using the large-scale language model server 2 and the entire improvement process from the improvement data to the adjusted content, it is possible to ensure traceability of content improvements. In this way, by collaborating with blockchain technology, it is possible to ensure transparency in the value of content and the improvement process.

[0090] The information processing system 100 may be configured to further include a learning unit. The learning unit may be included in the information processing device 1, or may be included in a server external to the information processing device 1. The learning unit is a functional unit that predicts physiological indices and psychological indices from content data. The learning unit is configured to input content into a learning model and output physiological indices and psychological indices from the learning model. In other words, the learning unit has a pre-constructed learning model, and is configured to input content (content data) into this learning model so as to output physiological indices (predicted ORP values) and psychological indices (predicted NPS values) for the content. The learning model is constructed by machine learning using, for example, a plurality of contents stored in the past and a data set of corresponding actually measured physiological indices and psychological indices. In a configuration including a learning unit, the physiological index acquisition unit 122 acquires predicted physiological indices from the learning unit, and the psychological index acquisition unit 123 acquires predicted psychological indices from the learning unit. This makes it possible to analyze the reception state from content data alone, without performing actual measurements using the physiological index measurement device 4A and the psychological index measurement device 4B. The information processing system 100 can also be implemented as a web service that accepts content data from an external system via an API (Application Programming Interface) and returns the acceptance status. For example, when a content production company uploads content data in production via the API, the learning unit predicts physiological and psychological indices for the content, and the acceptance level analysis unit 124 analyzes the acceptance status based on these predicted values ​​and returns the analysis results as an API response. Such an API service enables faster and smoother content evaluation and automatic evaluation of large amounts of content. Furthermore, since ORP value measurements require a certain amount of processing time after saliva collection and NPS values ​​are obtained through a questionnaire after the event has ended, continuous real-time monitoring during the event is not easy, but by utilizing a learning model as in this case, it is possible to obtain predicted ORP and NSP values ​​by analyzing content such as video and audio data from the event venue in real time. This makes it possible to estimate reception status in real time, and is expected to have the effect of making real-time improvement suggestions during a presentation, such as "Please speak a little more slowly."

[0091] Furthermore, with regard to the information processing system 100 according to the embodiment, there are various methods for using physiological indices. For example, as described in the embodiment, the ORP value may be measured after the evaluator has come into contact with the content or each part of the content to be evaluated, and the measured ORP value may be used as the physiological index. Alternatively, the ORP value may be measured before the evaluator has come into contact with the content and then measured again after the evaluator has come into contact with the content, and the difference between the measured ORP values ​​may be used as the physiological index. This difference allows for a more accurate understanding of the effect of the content on the evaluator's physiological state, enabling an evaluation that corrects for individual differences.

[0092] 7. Additional Notes Various embodiments are exemplified below, and the embodiments shown below can be combined with each other. [Appendix 1] An information processing system for analyzing content, comprising: The device includes a physiological index acquisition unit, a psychological index acquisition unit, an acceptance analysis unit, and a presentation unit, the physiological index acquisition unit is configured to acquire a physiological index; the physiological index corresponds to a potential indicating an oxidation-reduction state of saliva of the evaluator who has come into contact with the content; the psychological index acquisition unit is configured to acquire a psychological index, the psychological index is data quantifying an evaluation of the evaluator's interest in the content, the acceptability analysis unit is configured to analyze whether the physiological index and the psychological index correspond to a plurality of predetermined acceptability states, Each of the acceptance states is a state indicating how the evaluator who has come into contact with the content has accepted the content, The presentation unit causes an output unit to present the analysis result of the acceptance analysis unit. [Appendix 2] 10. The information processing system of claim 1, An information processing system, wherein the plurality of receptive states include four independent receptive states classified according to the respective degrees of the physiological index and the psychological index. [Appendix 3] 10. The information processing system according to claim 2, the plurality of accepting states includes, in addition to the four independent accepting states, an intermediate accepting state; An information processing system, wherein the intermediate acceptance state corresponds to a transitional state in which the evaluator has not yet reached one of the four independent acceptance states. [Appendix 4] 4. The information processing system according to claim 3, the acceptance level analysis unit analyzes that the physiological index or the psychological index falls within a predetermined range as corresponding to the intermediate acceptance state; the predetermined range includes a range in which the degree of the physiological index is between a first physiological index threshold and a second physiological index threshold, and a range in which the degree of the psychological index is between a first psychological index threshold and a second psychological index threshold, An information processing system, wherein each of the four independent acceptance states is defined by two of the first physiological index threshold, the second physiological index threshold, the first psychological index threshold, and the second psychological index threshold. [Appendix 5] An information processing system according to any one of Supplementary Note 2 to Supplementary Note 4, The plurality of acceptance states include a consent acceptance state and a recognition rejection acceptance state, The physiological index in the consent acceptance state has a greater degree of reduction than the physiological index in the recognition rejection acceptance state, An information processing system, wherein the psychological index in the assent acceptance state is greater in degree than the psychological index in the cognitive rejection acceptance state. [Appendix 6] An information processing system according to any one of Supplementary Note 2 to Supplementary Note 5, The plurality of acceptance states include a relief acceptance state and a warning acceptance state, The physiological index in the relief acceptance state has a greater degree of reduction than the physiological index in the warning acceptance state, An information processing system, wherein the psychological index in the relief acceptance state is smaller in magnitude than the psychological index in the warning acceptance state. [Appendix 7] An information processing system according to any one of Supplementary Note 2 to Supplementary Note 6, the plurality of acceptance states include a recognition rejection acceptance state and a warning acceptance state; The physiological index in the cognitive rejection acceptance state and the physiological index in the warning acceptance state have a degree of reduction smaller than a physiological index threshold; An information processing system, wherein the psychological indicator in the cognitive rejection acceptance state is smaller in magnitude than the psychological indicator in the warning acceptance state. [Appendix 8] An information processing system according to any one of Supplementary Note 2 to Supplementary Note 7, The plurality of acceptance states include a relief acceptance state and a satisfaction acceptance state, The physiological index in the relieved acceptance state and the physiological index in the satisfied acceptance state have a degree of reduction greater than a predetermined physiological index threshold value, An information processing system, wherein the psychological index in the convinced acceptance state is greater in degree than the psychological index in the relieved acceptance state. [Appendix 9] An information processing system according to any one of Supplementary Note 2 to Supplementary Note 8, The plurality of acceptance states include a cognitive rejection acceptance state and a reassured acceptance state, The psychological index in the cognitive rejection acceptance state and the psychological index in the relief acceptance state are smaller in degree than a predetermined psychological index threshold, An information processing system, wherein the physiological index in the cognitive rejection acceptance state has a smaller degree of reduction than the physiological index in the relief acceptance state. [Appendix 10] An information processing system according to any one of Supplementary Note 2 to Supplementary Note 9, The plurality of acceptance states include a warning acceptance state and a consent acceptance state, The psychological index in the warning acceptance state and the psychological index in the satisfaction acceptance state are greater in degree than a predetermined psychological index threshold value, An information processing system, wherein the physiological index in the satisfaction acceptance state has a greater degree of reduction than the physiological index in the warning acceptance state. [Appendix 11] An information processing system according to any one of Supplementary Note 1 to Supplementary Note 10, Further equipped with an improvement support department, the improvement support unit is configured to generate improvement data based on the supplemental data; the supplemental data includes at least one of electroencephalogram data of the evaluator and free description data of the evaluator; the improvement data is data that identifies improvements that are required for the content to reach a target acceptance state, which is one of the plurality of acceptance states, based on the analysis result of the content by the acceptance level analysis unit; The presentation unit causes the output unit to present the improvement data. [Appendix 12] 12. The information processing system of claim 11, further comprising an optimization unit; the optimization unit is configured to generate adjusted content by adjusting the content based on the improvement data; The presentation unit causes the output unit to present the adjusted content. [Appendix 13] An information processing system according to any one of Supplementary Note 1 to Supplementary Note 12, An information processing system, wherein the content is image data, video data, audio data, a live event, or interactive content. [Appendix 14] An information processing system according to any one of Supplementary Note 1 to Supplementary Note 13, the physiological index acquisition unit acquires the physiological index for each part of the content, the psychological index acquisition unit acquires the psychological index for each part of the content, The information processing system, wherein the acceptance level analysis unit analyzes whether each part of the content corresponds to one of the plurality of predetermined acceptance states. [Appendix 15] An information processing system according to any one of Supplementary Note 1 to Supplementary Note 14, Further comprising a recording unit, The recording unit is configured to record the analysis result of the acceptance analysis unit in a blockchain. [Appendix 16] An information processing system according to any one of Supplementary Note 1 to Supplementary Note 15, Further equipped with a learning section, the learning unit is configured to input the content into a learning model and output the physiological index and the psychological index from the learning model; An information processing system, wherein the physiological index acquisition unit acquires the physiological index from the learning unit, and the psychological index acquisition unit acquires the psychological index from the learning unit. [Appendix 17] 1. An information processing method for analyzing content, comprising: The method includes a physiological index acquisition step, a psychological index acquisition step, a receptive state analysis step, and a receptive state presentation step, In the physiological index acquisition step, a physiological index is acquired, the physiological index corresponds to a potential indicating an oxidation-reduction state of saliva of the evaluator who has come into contact with the content; In the psychological index acquisition step, a psychological index is acquired, the psychological index is data quantifying an evaluation of the evaluator's interest in the content, In the receptive state analysis step, it is analyzed whether the physiological index and the psychological index correspond to a plurality of predetermined receptive states, Each of the acceptance states is a state indicating how the evaluator who has come into contact with the content has accepted the content, In the acceptance state presenting step, an output unit is caused to present the analysis result of the acceptance state analyzing step. [Appendix 18] A program that causes a computer to execute the information processing method described in Appendix 17.

[0093] Although the embodiments have been described above, they are presented as examples and are not intended to limit the scope of the invention. The novel embodiments can be embodied in various other forms, and various omissions, substitutions, and modifications can be made. The embodiments and their modifications are included within the scope and spirit of the invention, and are also included in the scope of the invention and its equivalents as defined in the claims. [Explanation of symbols]

[0094] 100: Information Processing Systems 1: Information processing equipment 10: Communications Department 11: Storage section 12: Control section 121: Data acquisition section 122: Physiological index acquisition section 123: Psychological index acquisition department 124: Acceptance Analysis Section 125: Improvement Support Department 126: Optimization section 127:Presentation part 13: Output section 14: Input section 15: Communication bus 2: Large-scale language model server 3: User terminal 4: Indicator measuring device 4A: Physiological index measuring device 4AT: Electrode mechanism 22: Cotton swabs 23: Cotton part 24: Base part 25: Part 26: Indicator electrode 27: Part 28: Lead wire 29: Bottom 29A: Sample tank 30: Liquid junction 31: Part 32:Reference electrode 33: Tank lid 34:KCl solution 35: Measuring part 36: Physiological index measuring device body 37: Measurement result print button 38: Start measurement button 39: Display section 40: Display section 41: Printing section 42:Measurement box 4B: Psychological index measuring device 5: Communication network

Claims

1. An information processing system for analyzing content, comprising: The device includes a physiological index acquisition unit, a psychological index acquisition unit, an acceptance analysis unit, and a presentation unit, the physiological index acquisition unit is configured to acquire a physiological index; the physiological index corresponds to a potential indicating an oxidation-reduction state of saliva of the evaluator who has come into contact with the content; the psychological index acquisition unit is configured to acquire a psychological index, the psychological index is data quantifying an evaluation of the evaluator's interest in the content, the acceptability analysis unit is configured to analyze whether the physiological index and the psychological index correspond to a plurality of predetermined acceptability states, Each of the acceptance states is a state indicating how the evaluator who has come into contact with the content has accepted the content, the plurality of receptive states include independent first to fourth receptive states classified according to the respective degrees of the physiological index and the psychological index, and an intermediate receptive state; The intermediate acceptance state corresponds to a transitional state in which the evaluator has not yet reached one of the first to fourth acceptance states, The physiological index in the first receptive state and the third receptive state has a greater degree of reduction than the physiological index in the second receptive state and the fourth receptive state; the psychological index in the first acceptance state and the second acceptance state is higher in degree than the psychological index in the third acceptance state and the fourth acceptance state; The physiological index in the intermediate receptive state has a smaller degree of reduction than the physiological index in the first receptive state and the third receptive state, and has a larger degree of reduction than the physiological index in the second receptive state and the fourth receptive state, the psychological index in the intermediate accepting state is smaller in degree than the psychological index in the first accepting state and the second accepting state, and is larger in degree than the psychological index in the third accepting state and the fourth accepting state; The presentation unit causes an output unit to present the analysis result of the acceptance analysis unit.

2. An information processing system according to claim 1, The first acceptance state is a convincing acceptance state in which the evaluator recognizes and understands the content and actively accepts it; the second receptive state is a warning receptive state in which the rater is wary of the content; the third acceptance state is a relaxed acceptance state in which the evaluator is relaxed and accepting of the content; An information processing system, wherein the fourth acceptance state is a cognitive rejection acceptance state in which the evaluator has little interest in the content and is not actively processing information.

3. 3. The information processing system according to claim 2, the acceptance level analysis unit analyzes that the physiological index or the psychological index falls within a predetermined range as corresponding to the intermediate acceptance state; the predetermined range includes a range in which the degree of the physiological index is between a first physiological index threshold and a second physiological index threshold, and a range in which the degree of the psychological index is between a first psychological index threshold and a second psychological index threshold, An information processing system, wherein each of the four independent acceptance states is defined by two of the first physiological index threshold, the second physiological index threshold, the first psychological index threshold, and the second psychological index threshold.

4. An information processing system according to any one of claims 1 to 3, Further equipped with an improvement support department, the improvement support unit is configured to generate improvement data based on the supplemental data; the supplemental data includes at least one of electroencephalogram data of the evaluator and free description data of the evaluator; the improvement data is data that identifies improvements that are required for the content to reach a target acceptance state, which is one of the plurality of acceptance states, based on the analysis result of the content by the acceptance level analysis unit; The presentation unit causes the output unit to present the improvement data.

5. 5. The information processing system according to claim 4, further comprising an optimization unit; the optimization unit is configured to generate adjusted content by adjusting the content based on the improvement data; The presentation unit causes the output unit to present the adjusted content.

6. An information processing system according to any one of claims 1 to 3, An information processing system, wherein the content is image data, video data, audio data, a live event, or interactive content.

7. An information processing system according to any one of claims 1 to 3, the physiological index acquisition unit acquires the physiological index for each part of the content, the psychological index acquisition unit acquires the psychological index for each part of the content, The information processing system, wherein the acceptance level analysis unit analyzes whether each part of the content corresponds to one of the plurality of predetermined acceptance states.

8. An information processing system according to any one of claims 1 to 3, Further comprising a recording unit, The recording unit is configured to record the analysis result of the acceptance analysis unit in a blockchain.

9. An information processing system according to any one of claims 1 to 3, Further equipped with a learning section, the learning unit is configured to input the content into a learning model and output the physiological index and the psychological index from the learning model; An information processing system, wherein the physiological index acquisition unit acquires the physiological index from the learning unit, and the psychological index acquisition unit acquires the psychological index from the learning unit.

10. A computer-implemented information processing method for analyzing content, comprising: The method includes a physiological index acquisition step, a psychological index acquisition step, a receptive state analysis step, and a receptive state presentation step, In the physiological index acquisition step, a physiological index is acquired, the physiological index corresponds to a potential indicating an oxidation-reduction state of saliva of the evaluator who has come into contact with the content; In the psychological index acquisition step, a psychological index is acquired, the psychological index is data quantifying an evaluation of the evaluator's interest in the content, In the receptive state analysis step, it is analyzed whether the physiological index and the psychological index correspond to a plurality of predetermined receptive states, Each of the acceptance states is a state indicating how the evaluator who has come into contact with the content has accepted the content, the plurality of receptive states include independent first to fourth receptive states classified according to the respective degrees of the physiological index and the psychological index, and an intermediate receptive state; The intermediate acceptance state corresponds to a transitional state in which the evaluator has not yet reached one of the first to fourth acceptance states, The physiological index in the first receptive state and the third receptive state has a greater degree of reduction than the physiological index in the second receptive state and the fourth receptive state; the psychological index in the first acceptance state and the second acceptance state is higher in degree than the psychological index in the third acceptance state and the fourth acceptance state; The physiological index in the intermediate receptive state has a smaller degree of reduction than the physiological index in the first receptive state and the third receptive state, and has a larger degree of reduction than the physiological index in the second receptive state and the fourth receptive state, the psychological index in the intermediate accepting state is smaller in degree than the psychological index in the first accepting state and the second accepting state, and is larger in degree than the psychological index in the third accepting state and the fourth accepting state; In the acceptance state presenting step, an output unit is caused to present the analysis result of the acceptance state analyzing step.

11. A program causing a computer to execute the information processing method according to claim 10.

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