Program, information processing apparatus, and information processing method

Abstract

To predict influence on psychological safety felt by an other person with satisfactory accuracy to effectively notify a participant of an advice for improving psychological safety.SOLUTION: A program according to an embodiment of the present invention makes a computer function as a sensibility reading unit, a participant information reading unit, a characteristics reading unit, an influence calculating unit, a selection unit, and a notification unit. The sensibility reading unit reads, from a storage device, sensibility information regarding psychological safety in a communication environment. The participant information reading unit reads, from the storage device, participant information for used in specifying a plurality of participants who participate in a first communication. The behavior characteristics reading unit reads, from the storage device, first behavior characteristics information on each of the participants specified by the participant information. The influence calculating unit calculates influence on each participant given to each other based on the sensibility information regarding the psychological safety and the first behavior characteristics information. The selection unit selects an advice for improving the psychological safety based on the influence. The notification unit notifies the notification targets of the advice.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] An embodiment of the present invention relates to a program, an information processing device, and an information processing method. [Background technology]

[0002] There has been growing interest in psychological safety, which has been reported to be a common feature of highly productive workplaces. For example, there is a technology that adjusts advice for smoothly proceeding with a meeting based on the sensitivity of the participants and notifies them based on their words and actions. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2022-165118 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, with conventional technologies, it has been difficult to more accurately predict the impact on psychological safety felt by others and to more effectively provide advice to improve psychological safety. [Means for solving the problem]

[0005] The program of the embodiment causes a computer to function as a sensitivity reading unit, a participant information reading unit, a characteristic reading unit, an influence calculation unit, a selection unit, and a notification unit. The sensitivity reading unit reads sensitivity information of psychological safety in a communication environment from a storage device. The participant information reading unit reads participant information identifying multiple participants participating in a first communication from the storage device. The behavior characteristic reading unit reads first behavior characteristic information of each participant identified by the participant information from the storage device. The influence calculation unit calculates the influence that each participant has on each other from the psychological safety sensitivity information and the first behavior characteristic information. The selection unit selects advice to improve psychological safety based on the influence. The notification unit notifies a notification target of the advice. [Brief description of the drawings]

[0006] [Figure 1] FIG. 1 is a diagram showing an example of a device configuration of an information processing system according to a first embodiment. [Diagram 2] FIG. 2 is a diagram showing an example of the functional configuration of the information processing apparatus according to the first embodiment. [Diagram 3] FIG. 4 is a diagram showing an example of behavior characteristics of each participant in the first embodiment. [Figure 4] FIG. 2 is a diagram showing an example of sensitivity to psychological safety in the communication environment of the first embodiment. [Diagram 5] 4 is a flowchart showing an example of an information processing method at the start of communication or during communication in the first embodiment. [Figure 6] FIG. 4 is a diagram showing a calculation example of an influence on the surroundings in the first embodiment. [Figure 7] FIG. 4 is a diagram showing an example of calculation of the influence from the surroundings in the first embodiment. [Figure 8] FIG. 4 is a diagram showing example 1 of advice according to the first embodiment. [Figure 9] FIG. 11 is a diagram showing a second example of advice according to the first embodiment. [Figure 10] 5 is a flowchart showing an example of an information processing method after the end of communication in the first embodiment. [Figure 11]FIG. 4 is a diagram showing an example of display information according to the first embodiment. [Figure 12] FIG. 13 is a diagram showing an example of the functional configuration of an information processing apparatus according to a second embodiment. [Figure 13] 13A to 13C are diagrams for explaining a behavior characteristic grasping process according to the second embodiment. [Figure 14] 13 is a flowchart showing an example of an information processing method at the start of communication and during communication in the second embodiment. [Figure 15A] FIG. 11 is a diagram showing an example of usual behavior characteristics of each participant in the second embodiment. [Figure 15B] FIG. 11 is a diagram showing an example of actual behavior characteristics of each participant in the second embodiment. [Figure 16] FIG. 11 is a diagram showing an example of display information according to the second embodiment. [Figure 17] FIG. 13 is a diagram showing an example of the functional configuration of an information processing apparatus according to a third embodiment. [Figure 18] FIG. 13 is a diagram showing an example of the time required for the behavior characteristic of a notification target person to return to the normal fluctuation range in the third embodiment. [Figure 19] FIG. 13 is a diagram showing an example of display information according to the fifth embodiment. [Figure 20] FIG. 1 is a diagram showing an example of a hardware configuration of an information processing apparatus according to first to fifth embodiments. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] Hereinafter, embodiments of a program, an information processing device, and an information processing method will be described in detail with reference to the accompanying drawings.

[0008] (First embodiment) In the first embodiment, an information processing system that operates as a conference support system will be described as an example. Note that this information processing system is not limited to remote conferences and offline conferences, and can be used for any type of communication.

[0009] [Example of device configuration] 1 is a diagram showing an example of a device configuration of an information processing system 100 according to the first embodiment. The information processing system 100 according to the first embodiment includes an information processing device 101 and a plurality of client devices, such as a remote conference terminal 103, a conference room terminal 104, and a room smart speaker 105. The information processing device 101 and the plurality of client devices are connected by a network 102, such as the Internet.

[0010] The communication method of the network 102 may be a wired method or a wireless method, or the network 102 may be configured by combining a wired method and a wireless method.

[0011] The remote conference terminal 103 is, for example, a personal computer on which a remote conference application is installed. The conference room terminal 104 is, for example, a terminal installed in a conference room. The room smart speaker 105 is, for example, a smart speaker that assists with conversations while standing in a room.

[0012] An information processing device 101 in the first embodiment provides functions of a conference support system to a remote conference terminal 103, a conference room terminal 104, a room smart speaker 105, and the like through a network 102.

[0013] [Example of functional configuration] 2 is a diagram showing an example of a functional configuration of the information processing device 101 according to the first embodiment. The information processing device 101 according to the first embodiment includes a storage unit 300, a sensitivity reading unit 301, a participant information reading unit 302, a behavior characteristic reading unit 303, an influence calculation unit 304, a selection unit 305, a notification unit 306, a behavior characteristic calculation unit 307, an acquisition unit 308, a sensitivity calculation unit 309, and a display control unit 310.

[0014] The storage unit 300 is a storage device that stores various information. For example, the behavioral characteristics of each user in communication and the sensitivity to psychological safety from the surroundings are stored in advance in the storage unit 300. Also, for example, the storage unit 300 stores behavioral data of participants in past communication. Also, for example, the storage unit 300 stores the psychological safety felt by each participant during communication for each communication such as a meeting.

[0015] The behavior characteristic and the sensitivity are updated, for example, by the behavior characteristic calculation unit 307, the acquisition unit 308, and the sensitivity calculation unit 309 each time a communication in which each user participated ends. Details of the update method will be described later. Also, for example, the behavior characteristic and the sensitivity are set by the user at the time of initial use of the information processing device 101.

[0016] The sensitivity reading unit 301 reads sensitivity information about psychological safety in a communication environment from the storage unit 300. The sensitivity information about psychological safety will be described later.

[0017] The participant information reading unit 302 reads participant information that identifies multiple participants participating in communication from the storage unit 300. For example, when conference A is held and the participants are determined, the participant information reading unit 302 reads participant information from the storage unit 300 that indicates that the user, Suzuki, Yamada, and Sato will participate.

[0018] The behavior characteristic reading unit 303 reads, from the storage unit 300, the behavior characteristic information of each participant specified by the participant information.

[0019] 3 is a diagram showing an example of behavioral characteristics of each participant in the first embodiment. The behavioral characteristics of each participant are represented by information (e.g., a numerical value) that indicates the degree of a corresponding characteristic along with at least one characteristic indicator. For example, indicators of behavioral characteristics include "interrupts conversations," "long speech," "uses many positive keywords," "uses many negative keywords," "gets angry," and "makes interjections."

[0020] In the example of Figure 3, "interrupts," "gets angry," "makes a response," and "uses a lot of positive keywords" are used as indicators. For example, the degree of "interrupts" for person C is expressed as +5, so the degree of "interrupts" is higher than that of the average person (0).

[0021] The behavioral characteristics of each participant may be represented by a logical value (0 or 1) indicating the presence or absence of a corresponding characteristic, rather than a numerical value indicating the degree of strength of the corresponding characteristic.

[0022] Returning to FIG. 2, the influence calculation unit 304 calculates the influence that each participant exerts on others based on the sensitivity to psychological safety in the communication environment and the behavioral characteristics of each participant.

[0023] The selection unit 305 selects advice for improving psychological safety based on the influence calculated by the influence calculation unit 304.

[0024] The notification unit 306 notifies the notification target of the advice selected by the selection unit 305.

[0025] The behavior characteristic calculation unit 307 calculates the behavior characteristic of each participant from the behavior data in the past communication (second communication). The behavior characteristic calculation unit 307 can calculate the behavior characteristic of the participant from the past behavior specified from the behavior data without the user setting the behavior characteristic.

[0026] For example, "interrupting" is quantified by calculating the frequency at which a participant starts speaking while another participant is still speaking (turn-taking frequency) from speech and behavior data during a conference. Specifically, the behavior characteristic calculation unit 307 identifies speaker a from video information, determines whether the speaker is in the middle of speaking or has finished speaking from the intonation and interval of the speech, and records that speaker b interrupted the speaker once when the speaker b starts speaking in the middle of speaking. The behavior characteristic calculation unit 307 similarly counts interrupting events for each speaker and normalizes them by the length of the conference to calculate the frequency at which each speaker interrupts per unit time.

[0027] For example, "long speech duration", which is an index of the length of speech duration, is quantified by using the duration of continuous speech from speech and behavior data during a meeting. Specifically, the behavior characteristic calculation unit 307 measures the speech duration of speaker A from video information, and quantifies the continuous speech duration by measuring the time until speakers other than speaker A start speaking. The behavior characteristic calculation unit 307 calculates the speech ratio per unit meeting by normalizing the quantified continuous speech duration by the length of the meeting.

[0028] For example, "there are many positive keywords" is quantified by the number of times the positive keywords appear per speaking time or per meeting time. Specifically, the behavior characteristic calculation unit 307 applies a speech content recognizer to the speech data during the meeting to convert the content of the remarks into text information and compare it with predetermined positive keywords. This makes it possible to calculate the number of times the positive keywords appear per speaking time or per meeting time.

[0029] Positive keywords are keywords that indicate approval, such as "that's a good comment" and "keep going."

[0030] Similarly, the "high number of negative keywords" can be quantified by measuring the frequency of occurrence of negative keywords.

[0031] Negative keywords are keywords that indicate negation, such as "that's no good" and "please reconsider."

[0032] The indicators of these behavioral characteristics are not limited to the above examples, and any indicator that indicates a manner of communication behavior can be used. Furthermore, any method can be used to quantify the behavioral characteristics.

[0033] FIG. 4 is a diagram showing an example of psychological safety sensitivity in a communication environment of the first embodiment. The psychological safety sensitivity is evaluated based on an index of the behavioral characteristics of the participants in the communication environment, and includes information indicating the degree of increase or decrease in psychological safety in the communication environment. For example, as shown in FIG. 4, the psychological safety sensitivity is calculated by the sensitivity calculation unit 309 from a communication environment index indicating how many attendees exhibited the corresponding behavioral characteristics in a conference that each participant participated in in the past, and information on what kind of psychological safety each participant felt in the conference. Each index for evaluating the communication environment is quantified by the total value of each index of the behavioral characteristics of the participants (e.g., attendees in the conference). As shown in FIG. 4, the psychological safety sensitivity is expressed by a numerical value according to several indexes. Each numerical value indicates the degree to which psychological safety increases or decreases for the corresponding surrounding environment. A positive numerical value indicates the degree to which psychological safety is improved, and a negative numerical value indicates the degree to which psychological safety is reduced.

[0034] The example in Figure 4 shows sensitivity based on the communication environment, which indicates how participants A and B feel the psychological safety of the communication environment. It also shows the total value when participants A and B are present. The total value of the participants' sensitivity quantifies the sensitivity of psychological safety.

[0035] In the example of Figure 4, the indicators of behavioral characteristics used are "being interrupted," "there is an angry person," "there is a lot of backchanneling," and "there is a lot of positive keywords."

[0036] For example, Participant A's index for "there are angry people" was -10, which shows that he is likely to lower his psychological safety when there are angry people around.

[0037] In addition, in the example in Figure 4, the sensitivity of psychological safety when participants A and B are present is quantified by the sum of the sensitivity values ​​of participants A and B.

[0038] As shown in FIG. 4, sensitivity is stored in the memory unit 300 as a numerical value that indicates the degree to which the participant's psychological safety increases or decreases in relation to the surrounding environment in accordance with several indicators.

[0039] Psychological safety is measured by the acquisition unit 308. The acquisition unit 308 acquires the psychological safety felt by each participant during communication, and stores the acquired psychological safety in the storage unit 300 in association with information for identifying the user.

[0040] It is generally believed that psychological safety is fostered in a communication environment from the following perspectives: (1) When I make a mistake in a team, I usually get criticized. (2) Team members can point out challenges and difficult problems to each other. (3) Team members may reject others because they are different. (4) It is safe to take risks with your team. (5) It is difficult to ask other team members for help. (6) No team member will intentionally behave in a way that undermines their work. (7) When working with team members, I feel that my skills and talents are respected and utilized. (Source: Google re:Work-Guide: Understanding what makes an effective team)

[0041] The acquiring unit 308 acquires the psychological safety of each participant by, for example, detecting the contents of (1) to (7) through video recognition, voice recognition, and biometric information recognition. For example, the acquiring unit 308 quantifies item (1) by analyzing the contents of remarks made by attendees after a mistake is reported. In addition, for example, the acquiring unit 308 may acquire the psychological safety of the conference from users through a questionnaire after the conference.

[0042] Also, for example, the acquisition unit 308 may acquire a quantitative value of psychological safety by analyzing the length of speech time, the number of hesitations, and the number of soothing actions such as putting a hand on one's chest by voice recognition, video recognition, or biometric information recognition. Specifically, the acquisition unit 308 determines that psychological safety is low / high when the speech time during the target conference is short / long compared to the average speech time in similar conferences (e.g., regular conferences) that the user has previously participated in.

[0043] The sensitivity calculation unit 309 calculates sensitivity parameters such as "being interrupted," "someone who is angry," "a lot of interjections," and "a lot of positive keywords." These sensitivity parameters are calculated from an index of the communication environment that indicates how many attendees exhibited the corresponding behavioral characteristics in past conferences that each participant participated in, and information on the level of psychological safety felt in the conference.

[0044] For example, after communication is completed, the sensitivity calculation unit 309 calculates psychological safety sensitivity information using a psychological safety model that models the relationship between the psychological safety acquired by the acquisition unit 308, the indicators of the communication environment, and the psychological safety sensitivity information.

[0045] Below, an example will be shown in which the relationship between psychological safety, sensitivity, and the communication environment is modeled using a linear model by a system (for example, the sensitivity calculation unit 309) in the sensitivity calculation unit 309. Note that the system that performs the modeling may be a device separate from the information processing device 101.

[0046] The psychological safety felt by a user in a meeting is expressed as the sensitivity a i and the corresponding communication environment index x i It is estimated by summing the scores obtained by multiplying and for all indicators i∈I used in the modeling (Equation (1) below).

[0047]

number

[0048] The correct value of psychological safety analyzed in past meetings j ∈ J, y ~ j and the system estimated y j The sensitivity a that minimizes the difference between i is adjusted by the following formula (2).

[0049]

number

[0050] In addition, the model showing the relationship between psychological safety, sensitivity, and the communication environment is not limited to a linear model, and may be expressed by any modeling.

[0051] As a variation of the model, for example, the influence of the average behavioral characteristics (workplace culture) of each workplace k, k may be added as a bias for the communication environment. For example, an offset c i For example, an offset d may be added to indicate the degree to which the person feels psychological safety, regardless of the indicator.

[0052] An example of a variation of the model is shown in the following formula (3).

[0053]

number

[0054] In addition, impact b k , offset c i and the offset d may be partially used for modeling.

[0055] In this way, in the first embodiment, even if the user does not set the sensitivity information himself, the sensitivity calculation unit 309 can calculate the sensitivity information of psychological safety using the psychological safety model from the indicators of communication environments (e.g., meetings) in which the user has participated in the past and the psychological safety felt at that time.

[0056] [Examples of information processing methods] 5 is a flowchart showing an example of an information processing method before the start of communication in the first embodiment. First, the participant information reading unit 302 reads participant information that identifies multiple participants who will participate in the communication from the storage unit 300 (step S1).

[0057] Next, the behavior characteristic reading unit 303 reads the behavior characteristic information of each participant specified by the participant information from the storage unit 300 (step S2).

[0058] Next, the sensitivity reading unit 301 reads sensitivity information on psychological safety in the communication environment from the storage unit 300 (step S3).

[0059] Next, the influence calculation unit 304 reads the above-mentioned psychological safety model from the storage unit 300 (step S4).

[0060] Next, the influence calculation unit 304 uses the psychological safety model to calculate the influence that each participant has on others from the sensitivity information to psychological safety in the communication environment and the behavioral characteristic information of each participant (step S5).

[0061] Fig. 6 is a diagram showing an example of calculation of influence on the surroundings in the first embodiment. In the example of Fig. 6, the influence of participants c and d on the surroundings is expressed as a score calculated based on a psychological safety model expressed as a linear model. The sensitivity of the surroundings indicates the sum of the sensitivity of the participants other than c, and corresponds to the sum of the example of sensitivity in Fig. 4 described above. For example, for the indicator of c's behavioral characteristic "interrupted" (+5), c's influence score on the surroundings is (-4) x (+5) = (-20).

[0062] FIG. 7 is a diagram showing an example of calculation of influence from the surroundings in the first embodiment. In the example of FIG. 7, the influence that participants c and d receive from the surroundings is represented by a score. In the example of FIG. 7, the influence that participants c and d receive from the surroundings is represented by a score calculated based on a psychological safety model represented by a linear model. The behavioral characteristics of the surroundings indicate the sum of the behavioral characteristics of the participants other than c. For example, for c's sensitivity index "being interrupted" (-2), the influence score that c receives from the surroundings is (+5) x (-2) = (-10).

[0063] Returning to Fig. 5, next, the selection unit 305 judges whether or not notification to the participants is necessary based on the influence calculated in step S5 (step S6). Specifically, the selection unit 305 refers to the storage unit 310 and selects advice to be notified to the participants based on the influence calculated in step S5. If there is advice to be notified, it is judged that notification to the notification target of the advice is necessary.

[0064] Fig. 8 is a diagram showing an example 1 of advice in the first embodiment. Fig. 9 is a diagram showing an example 2 of advice in the first embodiment. As shown in Figs. 8 and 9, advice is stored in the storage unit 310 according to the degree of influence of various indicators of behavior characteristics.

[0065] In the examples of Figs. 8 and 9, advice is stored in a database divided into three categories (low, medium, and high) according to the magnitude of the impact score (degree of impact). Note that the categories do not have to be three, low, medium, and high, and any other categories such as two or five categories may be set, or there may be no categories at all. Also, advice based on a continuous value N, such as "When you feel like you are about to get angry, try counting N seconds" may be set.

[0066] The advice may be registered by the user or may be distributed by the service provider via a network.

[0067] The selection unit 305 selects one or more pieces of advice from the advice stored in the database. For example, the selection unit 305 selects a participant who has been calculated to have the top one of the scores of influence that the participant receives from other participants as a notification target, and selects advice of a category corresponding to the top one of the influence scores.

[0068] Also, for example, the selection unit 305 may select the participant whose top influence score is calculated among the scores of the influence the participant has on other participants as the notification recipient, and select advice of the category corresponding to the top influence score.

[0069] The advice to be selected is not limited to the advice corresponding to the top score, but may be advice corresponding to the top n scores. Also, advice is not limited to advice for categories corresponding to top scores, but advice for categories corresponding to lower scores may be selected.

[0070] 5, if advice is needed (step S6, Yes), the notification unit 306 notifies one or more notification recipients of the advice (step S7). If advice is not needed (step S6, No), the process ends.

[0071] 10 is a flowchart showing an example of an information processing method after the end of communication in the first embodiment. First, after the end of a communication (e.g., a conference A), the behavior characteristic calculation unit 307 calculates behavior characteristics from the behavior data of each participant in the communication (step S21).

[0072] Next, the acquisition unit 308 reads the psychological safety felt by the participants during the communication from the storage unit 300 (step S22). The psychological safety of the participants is, for example, periodically acquired by the acquisition unit 308 during the communication and stored in the storage unit 301.

[0073] Next, the sensitivity calculation unit 309 calculates sensitivity in the communication from the behavioral characteristics calculated in step S21 and the psychological safety read in step S22 (step S23).

[0074] Next, the storage unit 300 stores the information indicating the behavioral characteristics calculated in step S21 and the information indicating the sensitivity calculated in step S23 together with participant information identifying the participant (step S24).

[0075] Returning to FIG. 2, the display control unit 310 controls the display of the display information on the client device or the like.

[0076] [Example of display information] Fig. 11 is a diagram showing an example of display information in the first embodiment. The example in Fig. 11 shows a case where the above-mentioned advice notification function is incorporated in a UI (User Interface) screen of a schedule management application.

[0077] 11, when a specific event on the schedule screen is clicked, the display control unit 310 displays a details screen. The details screen shows the details of the event and the relationship between the user and the participants who are scheduled to attend the event.

[0078] The example of FIG. 11 shows a case where four participants (the user, Suzuki, Yamada, and Sato) take part in a communication. The arrows on the details screen show the influence they have on each other. When the influence exceeds a predetermined level, the display control unit 310 displays on the display device display information (first display information) on which an icon emphasizing the notification is superimposed. In the example of FIG. 11, for relationships that have an influence of a certain level or more, the arrow is emphasized by an exclamation mark icon. By hovering the mouse over the arrow emphasized by the exclamation mark, corresponding advice is displayed. This makes it possible to emphasize the notification so that it catches the user's eye when special attention is required.

[0079] The form of communication is not limited to a meeting, but may be one-on-one, a regular meeting, a presentation, a conversation, a phone call, etc. The scale of communication may be arbitrary. The communication may be conducted online, or may be a hybrid meeting including a user who participates online and a user who participates face-to-face.

[0080] As described above, in the information processing device 101 of the first embodiment, the sensitivity reading unit 301 reads sensitivity information on psychological safety in a communication environment from a storage device (the storage unit 300 in the first embodiment). The participant information reading unit 302 reads participant information identifying multiple participants participating in the first communication from the storage device. The behavior characteristic reading unit 303 reads first behavior characteristic information of each participant identified by the participant information from the storage device. The influence calculation unit 304 calculates the influence that each participant has on each other from the psychological safety sensitivity information and the first behavior characteristic information. The selection unit selects advice to improve psychological safety based on the influence. Then, the notification unit 306 notifies the notification target of the advice.

[0081] As a result, according to the first embodiment, the impact on psychological safety felt by others can be predicted with higher accuracy, and advice to improve psychological safety can be more effectively notified. For example, the impact on each participant in a communication such as a meeting can be predicted in advance based on the behavioral characteristic information of each participant and the psychological safety sensitivity information. Specifically, advice can be given to participants who feel psychologically unsafe before they fall into an unsafe situation, and a relaxed response can be encouraged. In addition, advice can be given in advance to perpetrators who drive those around them into unsafe situations with a calm mind. This has the effect of providing an opportunity to efficiently review communication.

[0082] In addition, in conventional technology, for example, advice is determined based on behavior data and advice rules, so there is no adjustment based on the combination of participants in the same room. In other words, it was not possible to give appropriate advice to participants based on the sensitivity of each participant's psychological safety, such as "how did the participant feel after receiving the behavior?"

[0083] On the other hand, according to the first embodiment, by modeling the behavioral characteristics of participants and the psychological safety sensitivity based on the behavior of those around them, it is also possible to give advice at a predetermined timing when the participant information is fixed. In other words, advice can be given before a psychologically unsafe situation occurs, allowing time for advance mental preparation. In addition, advice can be given in advance to perpetrators who drive those around them into unsafe situations in a calm state of mind, and it is possible to encourage efficient review of behavioral characteristics.

[0084] Second embodiment Next, a second embodiment will be described. In the description of the second embodiment, the same description as in the first embodiment will be omitted, and only the differences from the first embodiment will be described. The difference between the second embodiment and the first embodiment is that the second embodiment further includes a function of grasping actual behavior characteristics based on information during communication.

[0085] [Example of functional configuration] 12 is a diagram showing an example of the functional configuration of an information processing device 101-2 according to the second embodiment. The information processing device 101-2 according to the second embodiment further includes a grasping unit 401 in addition to the configuration of the information processing device 101 according to the first embodiment.

[0086] The grasping unit 401 grasps the behavior characteristics (second behavior characteristic information) of participants during communication (for example, during a conference) from the appearance of the participants during communication. While the behavior characteristic calculation unit 307 of the first embodiment calculates the behavior characteristics (first behavior characteristic information) from the action data of each participant in a past conference, the grasping unit 401 of the second embodiment calculates the behavior characteristics at a certain frequency or all the time without waiting for the end of the conference.

[0087] 13 is a diagram for explaining the behavior characteristic grasping process of the second embodiment. A period 411 from the conference start time to the conference end time indicates a target period for which the behavior characteristic calculation unit 307 calculates the behavior characteristics of the participants.

[0088] The grasping unit 401 extracts a time period for grasping the behavior of the participants by using a sliding window with a certain time width 412 before the current time as an input window, and calculates the behavior characteristics of the participants during the extracted time period. This makes it possible to grasp the behavior characteristics of the participants without waiting for the end of the conference.

[0089] The method of calculating the behavior characteristic by the grasping unit 401 may be different from the method of calculating the behavior characteristic by the behavior characteristic calculation unit 307. For example, the models and coefficients used in the calculation of the behavior characteristic by the grasping unit 401 and the behavior characteristic calculation unit 307 may be different.

[0090] [Examples of information processing methods] 14 is a flowchart showing an example of a method for processing information at the start of communication and during communication in the second embodiment. First, the participant information reading unit 302, the behavior characteristic reading unit 303, the sensitivity reading unit 301, and the influence calculation unit 304 read participant information, behavior characteristic information, sensitivity information on psychological safety, and a psychological safety model in advance (step S31).

[0091] Next, the grasping unit 401 grasps the behavior characteristics of the participants from the appearance of the participants during communication (for example, during a conference) (step S32).

[0092] Next, the influence calculation unit 304 uses the psychological safety model to calculate the influence that each participant has on each other based on the psychological safety sensitivity information in the communication environment and the behavioral characteristic information of each participant grasped in step S32 (step S33).

[0093] Next, the selection unit 305 determines whether or not notification to the participants is necessary based on the influence calculated in step S33 (step S34). In the second embodiment, the timing for determining that notification is necessary (timing of notifying the notification target) may be changed in consideration of the influence based on the behavior characteristics during communication.

[0094] Specifically, the selection unit 305 determines the timing of notification to the notification target from the usual behavior characteristics and the behavior characteristics during communication, and selects advice at the notification timing. For example, the selection unit 305 selects advice when the second behavior characteristic information indicates a change exceeding a threshold determined based on the first behavior characteristic information.

[0095] 15A is a diagram showing an example of the usual behavior characteristics of each participant in the second embodiment. In the example of FIG. 15A, the usual behavior characteristics are represented by the average behavior characteristic value and variance. For example, for the index of "angry," the usual behavior characteristics of person C are represented by the average behavior characteristic value 0 and the variance ±1.

[0096] FIG. 15B is a diagram showing an example of actual behavior characteristics (behavior characteristics acquired during communication) of each participant in the second embodiment. The selection unit 305 selects advice when the behavior characteristics acquired during communication show a change exceeding a threshold determined based on the usual behavior characteristics. The threshold is determined, for example, taking into consideration the variance of the usual behavior characteristics. For example, the threshold in the case of person c is 1 because the usual behavior characteristics are 0±1. In the example of FIG. 15B, the actual behavior characteristic of person c is +2, which exceeds the threshold=1. Therefore, the selection unit 305 selects advice for person c.

[0097] This allows for advice to be given earlier to a person who often gets angry (in the example of Figure 15A, Mr. d) when he / she is about to get angry, and also to a person who does not usually get angry very often (in the example of Figure 15A, Mr. c) when he / she is about to get angry.

[0098] Returning to FIG. 14, if advice is needed (Yes at step S6), the notification unit 306 notifies one or more notification targets of the advice (step S35).

[0099] If advice is not required (step S6, No), the grasping unit 401 judges whether the communication has ended (step S36). If the communication has not ended (step S36, No), the process of steps S32 to S36 is repeated at a predetermined interval. If the communication has ended (step S36, Yes), the process ends.

[0100] [Example of display information] Fig. 16 is a diagram showing an example of display information in the second embodiment. The example in Fig. 16 shows a case where the above-mentioned advice notification function is incorporated in the UI screen of a schedule management application. In the details screen in the second embodiment, the degree of improvement or deterioration is displayed with an up arrow or a down arrow for a person whose behavior characteristic has been updated during communication.

[0101] The influences on each other are displayed with arrows, as in the first embodiment. For relationships that have a certain degree of influence or more, the arrows are highlighted with an exclamation mark. By hovering the mouse over the arrow, corresponding advice is displayed.

[0102] As described above, according to the second embodiment, it is possible to notify advice in a more timely manner based on the behavior characteristics of the participants estimated from past behavior tendencies and the behavior characteristics calculated from the behavior in the current communication (behavior characteristics more in line with the actual situation). In other words, advice can be notified in a more timely manner based not only on the behavior characteristics set in advance and past tendencies, but also on the actual situation of the behavior characteristics during the actual communication and the sensitivity of the surroundings.

[0103] Third embodiment Next, a third embodiment will be described. In the description of the third embodiment, the same description as in the first embodiment will be omitted, and only the differences from the first embodiment will be described. The difference between the third embodiment and the second embodiment is that the third embodiment further includes a function of adjusting the advice stored in the storage unit 300 based on whether or not a change has occurred in the behavior characteristic before and after the notified advice.

[0104] [Example of functional configuration] 17 is a diagram illustrating an example of a functional configuration of an information processing device 101-3 according to the third embodiment. The information processing device 101-3 according to the third embodiment further includes an adjustment unit 501 in addition to the configuration of the information processing device 101 according to the first embodiment.

[0105] The adjustment unit 501 adjusts the advice to be notified to the notification target based on whether or not a change has occurred in the behavior characteristics of the notification target before and after the notified advice. For example, the adjustment unit 501 adjusts the strength of the advice based on the length of time until the advice notified by the notification unit 306 takes effect. Specifically, the adjustment unit 501 adjusts the strength of the advice to be notified when the notification target satisfies the same advice condition from the next time onwards, based on the length of time required for the behavior characteristics of the notification target to return to the normal behavior characteristic fluctuation range of the notification target (see FIG. 18 ).

[0106] FIG. 18 is a diagram showing an example of the time required for the notification target to return to the normal behavior characteristic variation range in the third embodiment. The adjustment is performed by changing the advice to one or more adjacent categories in the above-mentioned FIG. 8 and FIG. 9. For example, even if the notification target has a medium influence on other participants (or the notification target is influenced by other participants), if the time required for the effect to be brought about is longer than the predetermined time, the adjustment unit 501 performs adjustment to give high advice. Conversely, even if the notification target has a medium influence on other participants (or the notification target is influenced by other participants), if the time required for the effect to be brought about is shorter than the predetermined time, the adjustment unit 501 performs adjustment to give low advice.

[0107] According to the third embodiment, the strength of advice can be adjusted for each user (e.g., a participant in a conference) depending on whether or not there is a change in behavior in response to the advice, thereby preventing excessive or insufficient feedback from being given through advice.

[0108] (Fourth embodiment) Next, the fourth embodiment will be described. In the description of the fourth embodiment, the description of the same as the first embodiment will be omitted, and only the difference from the first embodiment will be described. The difference between the fourth embodiment and the first embodiment is that a conditional behavior characteristic and a conditional sensitivity are used.

[0109] The behavior characteristic reading unit 303 of the fourth embodiment reads conditional behavior characteristics in addition to the behavior characteristics of individual participants. Even for the same participant, the behavior characteristics may change depending on the combination with other participants (e.g., participants who are also present at a conference). The conditional behavior characteristics are behavior characteristics based on the combination of participants participating in communication.

[0110] The conditional behavioral characteristics may include behavioral characteristics that differ depending on a combination with a specific person, as well as a combination with a specific attribute (for example, a superior, a subordinate, a new employee, an older person, a gender, etc.).

[0111] The behavior characteristic in the first embodiment is calculated from behavior in past communication situations. On the other hand, the conditional behavior characteristic is calculated by aggregating behavior characteristics in communication situations that satisfy a predetermined condition (for example, a combination of participants attending a meeting) based on the participant information and behavior characteristic information stored in the storage unit 300. That is, in the fourth embodiment, the behavior characteristic calculation unit 307 calculates a conditional behavior characteristic for each communication situation that satisfies a predetermined condition.

[0112] Similarly, the sensitivity reading unit 301 of the fourth embodiment also reads conditional sensitivity. Even for the same participant, the sensitivity may change depending on the combination with other participants. The conditional sensitivity is sensitivity based on the combination of participants participating in the communication.

[0113] Like the conditional behavior characteristic, the conditional sensitivity is calculated from information on a communication situation that satisfies a predetermined condition. That is, in the fourth embodiment, the sensitivity calculation unit 309 calculates the conditional sensitivity by modeling the relationship between psychological safety, sensitivity, and the communication environment for each communication situation that satisfies a predetermined condition. Then, the influence calculation unit 304 calculates the influence that each participant has on each other from the conditional sensitivity information and the conditional behavior characteristic information.

[0114] According to the fourth embodiment, more appropriate advice can be given based on more detailed conditions (conditional behavior characteristics and conditional sensitivities that differ depending on the combination of participants, etc.) than in the first embodiment.

[0115] Fifth embodiment Next, a fifth embodiment will be described. In the description of the fifth embodiment, the same description as in the fourth embodiment will be omitted, and only the differences from the fourth embodiment will be described. The fifth embodiment differs from the fourth embodiment in that it further includes a function of displaying past notifications to participants and their subsequent behavioral characteristics. That is, the display control unit 310 further displays, on the display device, display information (second display information) including the relationship between changes in the behavioral characteristics of each participant and advice notified in the past.

[0116] [Example of display information] Fig. 19 is a diagram showing an example of display information in the fifth embodiment. Fig. 19 shows an example of a management screen referenced by a person (e.g., an administrator) who has the authority to check communication information of each member of the group. The management screen provides a function for viewing the behavior characteristics of each member of the group and advice notified by the notification unit 306.

[0117] The history of advice recorded in the storage unit 300 is displayed as an arrow, and details are displayed by hovering the mouse over or clicking on the arrow.

[0118] Behavior characteristics 1 and 2 in Figure 19 indicate two different conditional behavior characteristics. Similarly, Susceptibility 1 and 2 indicate two different conditional susceptibility.

[0119] In addition, the management screen in Fig. 19 may have a function of detecting trend changes in various indices and raising an alert. In order to detect trend changes, a setting screen may be further provided that accepts detection conditions from the user, such as a drop to a predetermined rate or less compared to the previous day.

[0120] According to the fifth embodiment, for example, the communication situation of a group can be more easily understood. Specifically, the manager or the like can check advice given by the notification unit 306 so far and the change in behavior when the advice was received. This allows early detection of changes in the trend of psychological safety felt by each member and members who have repeatedly received advice.

[0121] Finally, an example of the hardware configuration of the information processing apparatus 101 (101-2, 101-3) according to the first to fifth embodiments will be described.

[0122] [Example of hardware configuration] 20 is a diagram showing an example of a hardware configuration of the information processing device 101 (101-2, 101-3) according to the first to fifth embodiments. The information processing device 101 (101-2, 101-3) includes a processor 601, a main storage device 602, an auxiliary storage device 603, a display device 604, an input device 605, and a communication device 606. The processor 601, the main storage device 602, the auxiliary storage device 603, the display device 604, the input device 605, and the communication device 606 are connected via a bus 610.

[0123] The information processing device 101 (101-2, 101-3) may not include some of the above configurations. For example, if the information processing device 101 (101-2, 101-3) can use the input function and display function of an external device, the information processing device 101 (101-2, 101-3) may not include the display device 604 and the input device 605.

[0124] The processor 601 executes a program read from the auxiliary storage device 603 to the main storage device 602. The main storage device 602 is a memory such as a read only memory (ROM) and a random access memory (RAM). The auxiliary storage device 603 is a hard disk drive (HDD), a memory card, or the like.

[0125] The display device 604 is, for example, a liquid crystal display. The input device 605 is an interface for operating the information processing device 101 (101-2, 101-3). The display device 604 and the input device 605 may be realized by a touch panel having a display function and an input function. The communication device 606 is an interface for communicating with other devices.

[0126] For example, the program executed by the information processing device 101 (101-2, 101-3) is provided as a computer program product in the form of a file in an installable or executable format, recorded on a computer-readable storage medium such as a memory card, a hard disk, a CD-RW, a CD-ROM, a CD-R, a DVD-RAM, or a DVD-R.

[0127] Also, for example, the programs executed by the information processing devices 101 (101-2, 101-3) may be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network.

[0128] Also, for example, the programs executed by the information processing devices 101 (101-2, 101-3) may be provided via a network such as the Internet without being downloaded. Specifically, for example, the programs may be configured as an ASP (Application Service Provider) type cloud service.

[0129] Also, for example, the programs for the information processing devices 101 (101-2, 101-3) may be provided by being pre-installed in a ROM or the like.

[0130] The programs executed by the information processing devices 101 (101-2, 101-3) are modularized to include functions that can be realized by the programs among the functional configurations described above. As for each function, the processor 601 reads out the program from a storage medium and executes it, and the above-mentioned functional blocks are loaded onto the main storage device 602 as actual hardware. In other words, the above-mentioned functional blocks are generated on the main storage device 602.

[0131] Note that some or all of the above-described functions may be realized by hardware such as an integrated circuit (IC) instead of by software.

[0132] Furthermore, each function may be realized using a plurality of processors 601. In this case, each processor 601 may realize one of the functions, or may realize two or more of the functions.

[0133] Although some embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and spirit of the invention, and are included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0134] 100 Information Processing Systems 101 Information processing device 102 Network 103 Remote conference terminal 104 Conference Room Terminals 105 Smart speaker in living room 300 Storage section 301 Sensitivity Reader 302 Participant information reading unit 303 Behavior characteristic reading part 304 Impact Calculation Unit 305 Selection Section 306 Notification Department 307 Behavior characteristic calculation unit 308 Acquisition Department 309 Sensitivity calculation section 310 Display control unit 401 Grasping part 501 Adjustment section 601 Processor 602 Main storage 603 Auxiliary storage device 604 Display device 605 Input Device 606 Communication Equipment 610 Bus

Claims

1. Computer, A sensitivity reading unit that reads sensitivity information of psychological safety in a communication environment from a storage device; a participant information reading unit that reads participant information that identifies a plurality of participants participating in the first communication from the storage device; a behavior characteristic reading unit that reads, from the storage device, first behavior characteristic information of each participant identified by the participant information; an influence calculation unit that calculates the influence that each participant has on each other based on the psychological safety sensitivity information and the first behavioral characteristic information; A selection unit that selects advice for improving psychological safety based on the influence; a notification unit that notifies a notification target of the advice; A program to function as a

2. The first behavior characteristic information includes information representing a degree of a behavior characteristic for at least one indicator of the behavior characteristic. The program according to claim 1.

3. The psychological safety sensitivity information is evaluated based on an indicator of the nature of the behavior of the participants in the communication environment, and includes information indicating the degree of increase or decrease in psychological safety in the communication environment. The program according to claim 2.

4. The computer, and further functioning as a behavior characteristic calculation unit that calculates the first behavior characteristic information of each participant from behavior data in a second communication that has been conducted in the past. The program according to any one of claims 1 to 3.

5. The computer, an acquisition unit that acquires the psychological safety felt by each participant during the first communication and stores the acquired psychological safety in the storage device; After the first communication is completed, the device further functions as a sensitivity calculation unit that calculates the sensitivity information of psychological safety using a psychological safety model in which the relationship between the psychological safety acquired by the acquisition unit, the indicators of the communication environment, and the sensitivity information of psychological safety is modeled. The program according to any one of claims 1 to 3.

6. The computer, and further functioning as an ascertaining unit that ascertains second behavior characteristic information indicating behavior characteristics of each participant during the first communication from the appearance of the participants during the first communication; the selection unit selects advice when the second behavior characteristic information shows a change exceeding a threshold value determined based on the first behavior characteristic information. The program according to any one of claims 1 to 3.

7. The computer, and further functioning as an adjustment unit that adjusts the advice to be notified to the notification target based on whether or not a change has occurred in the behavioral characteristics of the notification target before and after the notified advice. The program according to any one of claims 1 to 3.

8. The behavior characteristic reading unit reads conditional behavior characteristic information based on a combination of participants participating in the first communication; The sensitivity reading unit reads conditional sensitivity information based on a combination of participants participating in the first communication; The influence calculation unit calculates influences of each participant on each other based on the conditional sensitivity information and the conditional behavior characteristic information. The program according to any one of claims 1 to 3.

9. The computer, and when the influence exceeds a predetermined level, further functioning as a display control unit that displays, on a display device, first display information on which an icon emphasizing the notification is superimposed. The program according to any one of claims 1 to 3.

10. the display control unit further displays, on the display device, second display information including a relationship between a change in the behavior characteristic of each participant and advice notified in the past. The program according to claim 9.

11. A sensitivity reading unit that reads sensitivity information of psychological safety in a communication environment from a storage device; a participant information reading unit that reads participant information that identifies a plurality of participants participating in the first communication from the storage device; a behavior characteristic reading unit that reads, from the storage device, first behavior characteristic information of each participant identified by the participant information; an influence calculation unit that calculates the influence that each participant has on each other based on the psychological safety sensitivity information and the first behavioral characteristic information; A selection unit that selects advice for improving psychological safety based on the influence; A notification unit that notifies a notification target of the advice; An information processing device comprising:

12. An information processing device reads sensitivity information of psychological safety in a communication environment from a storage device; The information processing device reads participant information that identifies a plurality of participants participating in a first communication from the storage device; The information processing device reads, from the storage device, first behavior characteristic information of each participant identified by the participant information; A step of calculating an influence that each participant has on each other from the psychological safety sensitivity information and the first behavioral characteristic information by the information processing device; The information processing device selects advice for improving psychological safety based on the influence; a step of notifying a notification target person of the advice by the information processing device; An information processing method comprising:

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