Feedback device and program

Abstract

To provide a feedback device capable of grasping information depending on situation of a meeting in real time, and a program.SOLUTION: A feedback device 1 capable of outputting a list of meetings of participants, comprises: a data acquisition unit 11 that acquires a plurality of meeting data of participants; a determination result acquisition unit 31 that acquires determination results for feature points obtained by analyzing conversation data; an evaluation unit 33 that evaluates the meeting data based on the determination result; and an output unit 22 that outputs the acquired meeting data as a list and outputs an evaluation result for each meeting data.SELECTED DRAWING: Figure 8

Description

Technical Field

[0001] The present disclosure relates to a feedback device and a program.

Background Art

[0002] Conventionally, online interviews and meetings such as conferences have been conducted. By recording and analyzing such online meetings, a system for supporting meetings has been proposed (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, in an online meeting, since participants are connected to each other via a network, there is a problem that it is difficult for participants to grasp the situation of the meeting. For example, since participants need to grasp the reactions of other participants and the atmosphere of the meeting through the screen or voice, there is a problem that it is difficult to grasp the situation.

[0005] In Patent Document 1, for an online meeting, by textifying and evaluating the meeting in real time, the record of the online meeting is capitalized after the meeting. On the other hand, in Patent Document 1, it is not possible to present information corresponding to the situation that changes according to the progress of the meeting. Also, in Patent Document 1, it is not possible to grasp even the quality of the meeting. Therefore, it is preferable if information corresponding to the situation of the meeting can be grasped.

[0006] This invention has been made in view of the above-mentioned conventional circumstances, and aims to provide a feedback device and program that can grasp information according to the situation of a meeting. [Means for solving the problem]

[0007] The present invention relates to a feedback device for providing feedback in an online participant meeting, comprising: a data acquisition unit for acquiring meeting data related to the meeting; a reference information acquisition unit for acquiring feature points extracted from the meeting data and judgment criteria for those feature points as reference information; an extraction unit for extracting feature points included in the acquired meeting data based on the acquired reference information; a comparison unit for comparing the extracted feature points with the judgment criteria; a notification creation unit for creating a notification to the relevant parties involved in the meeting based on the comparison result; and an output unit for outputting the created notification to the relevant parties.

[0008] Furthermore, it is preferable that the notification creation unit creates notifications in real time during online meetings with participants.

[0009] Furthermore, the feedback device further comprises a participant information acquisition unit that acquires participant information indicating the attributes of the participant, and a decision unit that determines judgment criteria to be used for the participant based on the acquired participant information, wherein the comparison unit preferably compares the extracted feature points with the determined judgment criteria.

[0010] Furthermore, the reference information acquisition unit preferably includes specific information that identifies the relevant parties to whom the notification will be output, and the output unit preferably determines the recipients of the output based on the acquired participant information and the acquired specific information.

[0011] Furthermore, the extraction unit extracts predetermined expressions included in the meeting data as feature points, and the comparison unit compares the extracted predetermined expressions with the judgment criteria. The notification creation unit preferably creates a notification that evaluates predetermined expressions based on the judgment result.

[0012] Furthermore, it is preferable that the extraction unit extracts the speech ratio of participants as feature points, the comparison unit compares the extracted speech ratio with the judgment criteria, and the notification creation unit creates a notification encouraging participants to strike a balance based on the judgment results.

[0013] Furthermore, it is preferable that the extraction unit extracts the participant's state as a characteristic point, the comparison unit compares the extracted state with the judgment criteria, and the notification creation unit creates a notification that provides advice based on the judgment result.

[0014] Furthermore, it is preferable that the extraction unit extracts the specific content of the statement as characteristic points, the comparison unit compares the extracted content with the judgment criteria, and the notification creation unit creates a notification regarding the extracted content based on the judgment result.

[0015] Furthermore, it is preferable that the extraction unit extracts characteristics of the participants' communication based on the content of their statements as feature points, the comparison unit compares the extracted content with the judgment criteria, and the notification creation unit creates a notification of a response method to the extracted communication characteristics based on the judgment result.

[0016] Furthermore, it is preferable that the feedback device further includes a modification unit that changes the content of the acquired reference information according to the number and attributes of the participants.

[0017] The present invention also relates to a program for causing a computer to function as a feedback device that performs feedback based on an online meeting of participants, the program causing the computer to function as a data acquisition unit that acquires meeting data regarding a meeting, a reference information acquisition unit that acquires, as reference information, feature points extracted from the meeting data and a judgment criterion for the feature points, an extraction unit that extracts feature points included in the acquired meeting data based on the acquired reference information, a comparison unit that compares the extracted feature points with the judgment criterion, a notification creation unit that creates a notification for a person concerned related to the meeting based on the comparison result, and an output unit that outputs the created notification to the person concerned.

Effect of the Invention

[0018] According to the present disclosure, it is possible to provide a feedback device and a program capable of grasping information according to the situation of a meeting.

Brief Description of the Drawings

[0019] [Figure 1] It is a schematic diagram showing a feedback system including a feedback device according to a first embodiment of the present invention. [Figure 2] It is a block diagram showing the configuration of the feedback device of the first embodiment. [Figure 3] It is a time chart showing an example of the content compared by the comparison unit of the feedback device of the first embodiment. [Figure 4] It is a time chart showing an example of a notification created by the notification creation unit of the feedback device of the first embodiment. [Figure 5] It is a screen diagram showing an example of a screen output by the output unit of the feedback device of the first embodiment. [Figure 6] It is a flowchart showing the flow of operation of the feedback device of the first embodiment. [Figure 7] It is a block diagram showing the configuration of the feedback device of the second embodiment of the present invention. [Figure 8] It is a screen diagram showing a screen displayed by the feedback device of the second embodiment. [Figure 9] It is a screen diagram showing another screen displayed by the feedback device of the second embodiment. [Figure 10] It is a flowchart showing the flow of operations of the feedback device of the second embodiment.

Mode for Carrying Out the Invention

[0020] Hereinafter, the feedback device 1 and the program according to each embodiment of the present invention will be described with reference to FIGS. 1 to 10. First, an outline of the feedback device 1 according to each embodiment will be described.

[0021] Feedback device 1 is, for example, an information processing device such as a server. Feedback device 1 is, for example, a device that provides feedback in an online meeting of participants. Feedback device 1 extracts, for example, the content of participants' statements, facial expressions, gestures, and speaking ratio, and provides feedback to participants, etc., in accordance with the extracted content. Feedback device 1 outputs notifications not only to meeting participants, but also to meeting administrators and moderators, etc. In this way, feedback device 1 aims to grasp information according to the situation of the meeting. In particular, feedback device 1 in the following embodiment provides feedback from a personnel perspective, such as how the mental state of participants has changed (for example, increased interest in the job in a job interview, increased psychological safety, etc., or increased participant motivation in a workplace setting), or how the relationships between participants have changed (for example, increased favorability towards the interviewer in a job interview, or improved superior-subordinate relationships in a workplace meeting). Furthermore, feedback device 1 also aims to provide feedback from perspectives other than personnel, for example, to facilitate communication in meetings or to support facilitation. Feedback device 1 provides feedback such as, "The other participant seems nervous, so please do an icebreaker," or "I think we should move on to the next agenda item." For the sake of clarity, the following explanation will use a job interview as an example of a meeting.

[0022] In the following embodiments, a case where feedback is provided in real time during a meeting is described. Here, "real-time feedback" includes not only immediate feedback but also feedback on the participants' situation every 5 or 10 minutes. Furthermore, in the following embodiments, feedback may not be limited to real time, but may be provided after multiple meetings have been held over a predetermined period, after a predetermined number of meetings have been held, or when a predetermined number of meetings containing problems have been detected. This increases the number of meetings to be reviewed, thereby improving the accuracy of the feedback. Furthermore, feedback may not be limited to real time, but may be provided after a predetermined period of time following the meeting. This allows feedback to be provided to participants in a calm state.

[0023] Next, the feedback system 200, which includes the feedback device 1, will be described. The feedback system 200 includes a plurality of participant terminals 100 and a feedback device 1, as shown in Figure 1.

[0024] The participant terminal 100 is, for example, an information processing device having a microphone and a camera. A participant terminal 100 may be provided for each participant in the meeting. A participant terminal 100 may also be provided for each interviewer. Furthermore, a participant terminal 100 may be provided for each candidate undergoing an interview. Additionally, a participant terminal 100 may be provided for each administrator who manages the meeting but does not directly participate in it. Details of the feedback device 1 will be described later.

[0025] [First Embodiment] Next, a feedback device 1 according to the first embodiment of the present invention will be described with reference to Figures 1 to 6. The feedback device 1 analyzes the status of meetings conducted using participant terminals 100 and provides feedback, such as notifications, to participants. As shown in Figure 1, the feedback device 1 is connected to multiple participant terminals 100 via a network N. In this embodiment, the feedback device 1 is described as a device that also manages meetings between participant terminals 100. As shown in Figure 2, the feedback device 1 includes a data acquisition unit 11, a participant information storage unit 12, a participant information acquisition unit 13, a meeting implementation unit 14, a meeting storage unit 15, a reference information storage unit 16, a reference information acquisition unit 17, a determination unit 18, an extraction unit 19, a comparison unit 20, a notification creation unit 21, an output unit 22, and a modification unit 23.

[0026] The data acquisition unit 11 is implemented, for example, by the operation of the CPU. The data acquisition unit 11 acquires meeting data related to the meeting. For example, the data acquisition unit 11 acquires audio data and video data transmitted from participant terminals 100 as meeting data. Specifically, the data acquisition unit 11 acquires the audio data and video data of each participant transmitted from each participant terminal 100.

[0027] The participant information storage unit 12 is, for example, a recording medium such as a hard disk. The participant information storage unit 12 stores participant information that indicates the attributes of the participants. For example, the participant information storage unit 12 stores participant information linked to identification information (e.g., an ID) that identifies the participant. For example, the participant information storage unit 12 stores information such as whether the participant is an applicant or an interviewer as participant information. In addition, if the participant is an applicant, the participant information storage unit 12 stores, for example, the applicant's self-introduction video, questionnaire results, gender, educational background, work history, and data obtained from other services (chat tools, engagement measurement tools, etc.) as participant information. Furthermore, the participant information storage unit 12 stores participant information such as, for example, the interviewer's gender, personality, age, year of joining the company, type of employment (new graduate / mid-career), department, position, educational background, previous departments, performance evaluation (including 360-degree evaluation and 360-degree feedback), performance information (sales performance, etc.), leave of absence history, attendance data, communication data (frequency and quality of communication with other members obtained from chat tools, etc., connection trends as seen from the organizational chart (many or few members involved in work, etc.)), data from recruitment activities, and data obtained from healthcare products, etc., when the participant is an interviewer. In this embodiment, the participant information storage unit 12 stores participant information in advance before the meeting is held.

[0028] The participant information acquisition unit 13 is implemented, for example, by the operation of the CPU. The participant information acquisition unit 13 acquires participant information that indicates the attributes of the participants. For example, the participant information acquisition unit 13 acquires participant information linked to identification information that identifies the participant.

[0029] The meeting execution unit 14 is implemented, for example, by the operation of a CPU. The meeting execution unit 14 conducts a meeting using meeting data obtained from participant terminals 100 used by participants who are scheduled to participate in a predetermined meeting.

[0030] The meeting storage unit 15 is, for example, a recording medium such as a hard disk. The meeting storage unit 15 stores the content of the meetings that have been held and the notifications that have been created, which will be described later.

[0031] The reference information storage unit 16 is, for example, a recording medium such as a hard disk. The reference information storage unit 16 stores reference information for determining the status of participants with respect to the acquired meeting data. The reference information storage unit 16 stores metadata such as the start and end times of the meeting, the agenda, and the subject matter related to the meeting as reference information. The reference information storage unit 16 also stores criteria such as elapsed time, the quality of the speaking ratio, the quality of the smiling ratio, and the quality of the conversation speed. Furthermore, the reference information storage unit 16 stores specific information that identifies the relevant parties to whom notifications will be output as reference information. For example, the reference information storage unit 16 stores specific information that specifies that the agenda time should be output to the participant terminals 100 of the interviewer and relevant parties (facilitator, controller, etc.). Furthermore, for example, the reference information storage unit 16 stores specific information that identifies the relevant participants as output destinations for the quality of the speaking ratio, the quality of the smiling ratio, and the quality of the conversation speed.

[0032] Furthermore, the standard information storage unit 16 stores judgment criteria related to predetermined expressions included in the meeting data as standard information. For example, the standard information storage unit 16 stores judgment criteria related to aggressive remarks, negative remarks, and positive remarks as standard information. In addition, the standard information storage unit 16 stores judgment criteria related to the volume of voices corresponding to shouting, and gestures such as banging on the table as standard information. Furthermore, the standard information storage unit 16 stores the state of the participants as judgment criteria. For example, the standard information storage unit 16 stores judgment criteria related to the participants' facial expressions, gestures, tone of voice, and the specific content of their remarks as standard information. Furthermore, the standard information storage unit 16 stores judgment criteria related to the characteristics of communication as standard information. In addition, the standard information storage unit 16 stores result indicators such as the internal state of a person that can be read from their remarks and actions (for example, psychological safety, level of trust, and motivation) as a state. Furthermore, the reference information storage unit 16 stores, as expressions, statements and actions that may cause an influence on the "state" (for example, harassing and intimidating words and actions). In other words, the relationship between expressions and the state is treated, for example, as one example, where the "expression" triggers the creation of the "state".

[0033] The reference information acquisition unit 17 is implemented, for example, by the operation of the CPU. The reference information acquisition unit 17 acquires feature points extracted from meeting data and judgment criteria for those feature points as reference information. The reference information acquisition unit 17 acquires, for example, the reference information stored in the reference information storage unit 16.

[0034] The decision unit 18 is implemented, for example, by the operation of the CPU. The decision unit 18 determines the decision criteria to be used for the participant based on the acquired participant information. The decision unit 18 determines the decision criteria to be used for the participant, for example, based on the identification of the output destination included in the criterion information.

[0035] The extraction unit 19 is implemented, for example, by the operation of the CPU. The extraction unit 19 extracts feature points contained in the acquired meeting data based on the acquired reference information. The extraction unit 19 obtains the elapsed time contained in the acquired meeting data, for example, based on the agenda contained in the reference information. The extraction unit 19 also obtains the speech ratio of participants contained in the acquired meeting data as a feature point, for example, based on the speech ratio contained in the reference information. The extraction unit 19 also obtains the facial feature parts of participants contained in the meeting data, for example, based on the smile ratio contained in the reference information. The extraction unit 19 also obtains the conversation speed of participants contained in the meeting data, for example, based on the conversation speed contained in the reference information. The extraction unit 19 extracts feature points from meeting data during a meeting in real time. The extraction unit 19 extracts elapsed time, speech ratio, smile ratio, and conversation speed in real time, for example, as shown in Figure 3.

[0036] Furthermore, the extraction unit 19 extracts predetermined expressions included in the meeting data as feature points. For example, the extraction unit 19 extracts aggressive remarks, negative remarks, and positive remarks included in the meeting data. Furthermore, the extraction unit 19 extracts the state of the participants as feature points. Furthermore, the extraction unit 19 extracts the characteristics of the participants' communication based on the content of their remarks as feature points. Furthermore, the extraction unit 19 extracts the content of the participants' responses. Furthermore, the extraction unit 19 extracts, for example, at least one of facial expressions and wording as feature points. For example, the extraction unit 19 determines from the feature points the facial expressions of the participants and how those expressions are perceived by other participants (e.g., furrowed brows).

[0037] The comparison unit 20 is implemented, for example, by the operation of the CPU. The comparison unit 20 compares the extracted feature points with the judgment criteria. The comparison unit 20 compares, for example, the extracted elapsed time, speech ratio, smile ratio, and conversation speed with the judgment criteria included in the reference information. The comparison unit 20 compares the extracted feature points with a predetermined threshold as the judgment criterion. The comparison unit 20 compares the extracted feature points with the determined judgment criteria. The comparison unit 20 compares the extracted feature points with the judgment criteria using, for example, the comparison criteria applied to the participant determined by the determination unit 18. The comparison unit 20 also compares the extracted predetermined expression with the judgment criteria. The comparison unit 20 also compares the extracted state with the judgment criteria.

[0038] The notification creation unit 21 is implemented, for example, by the operation of the CPU. Based on the comparison results, the notification creation unit 21 creates notifications for stakeholders involved in the meeting. For example, the notification creation unit 21 creates notifications that encourage participants to balance their speaking ratios based on the judgment results. The notification creation unit 21 also creates notifications that evaluate predetermined expressions based on the judgment results. For example, as shown in Figure 4, the notification creation unit 21 creates a notification for participants with a low smile ratio saying, "Your expression is stiff, please smile." The notification creation unit 21 also creates a notification for participants with a high smile ratio saying, "That's great!" The notification creation unit 21 also creates a notification for participants whose speaking speed is increasing saying, "Your speaking speed is increasing." The notification creation unit 21 also creates notifications that are judged for each participant. For example, the notification creation unit 21 creates notifications that encourage participants to refrain from making aggressive or negative remarks. The notification creation unit 21 also creates notifications that suggest positive remarks are highly valued. Furthermore, the notification creation unit 21 creates notifications that address the communication characteristics extracted based on the judgment results. For example, the notification creation unit 21 notifies the interviewer of the communication characteristics of the participant during the interview, suggesting appropriate ways to interact with that participant (e.g., whether it is better to listen or take the lead). The notification creation unit 21 also estimates the participant's level of understanding and creates notifications for the interviewer.

[0039] Furthermore, the notification creation unit 21 creates notifications that point out biases in the content of speech, such as when the same terminology is repeated. The notification creation unit 21 also creates notifications that encourage correcting biases or continuing as is, based on the good or bad state of speech ratio, voice quality, and facial expression compared in the comparison unit 20. In addition, the notification creation unit 21 creates notifications that point out biases, such as when the same category of words appears repeatedly. Furthermore, the notification creation unit 21 creates notifications that encourage further exploration depending on the frequency of words related to the agenda. The notification creation unit 21 creates notifications such as, "What is the background to your statement?" or "This is the first time the word XXX has appeared, is it a word that is easy for the other person to understand?" For example, in the case of recruitment, the purpose is to "elicit information from the other person" or "assess the other person's personality, abilities, and qualities," and in the case of workplace use, the purpose is to "encourage introspection and provide insights" or "ease tension," etc. These are prepared for each type of conversation and displayed to the participant(s) during communication. At this time, data obtained from previous videos or other data used (see above) may be used to calculate the content of the advice and the timing of its implementation. In addition, the notification generation unit 21 may analyze the other party's response and notify them of their level of understanding.

[0040] The output unit 22 is implemented, for example, by the operation of the CPU. The output unit 22 outputs the created notification to the relevant parties. The output unit 22 determines the recipient participant based on the acquired participant information and acquired specific information. The output unit 22 outputs, for example, the agenda time to the interviewer and facilitator participant terminals 100. The output unit 22 outputs, for example, notifications regarding the speaking rate, smile rate, and conversation speed to the participant terminal 100 of the relevant participant. The output unit 22 may also use, for example, message notifications, voice (sound), graph display on the screen, a traffic light-like display, or color (change in the color of the window border) to provide notifications. The output unit 22 may use methods other than chat for providing advice (see "Notification Method to HR Department / Individual", "Data Display Method", and "Image Data Pattern" below). The timing of the advice provided by the output unit 22 may be immediate, in batch processing every 5 minutes, or after the conversation has ended.

[0041] The modification unit 23 is implemented, for example, by the operation of the CPU. The modification unit 23 modifies the content of the acquired reference information according to the number and attributes of the participants. The modification unit 23 modifies the reference information (e.g., threshold) regarding the speaking ratio according to the ratio of the number of interviewers to the number of examinees.

[0042] Next, the operation flow of the feedback device 1 will be explained with reference to the flowchart in Figure 6. First, the standard information acquisition unit 17 acquires standard information (step S1). Next, the participant information acquisition unit 13 acquires participant information (step S2). The modification unit 23 then modifies the content of the acquired standard information according to the number and attributes of the participants. Next, the data acquisition unit 11 acquires meeting data (step S3).

[0043] Next, the meeting implementation unit 14 conducts the meeting (step S4). Next, the decision unit 18 determines the decision criteria to be used for the participants (step S5). Next, the extraction unit 19 extracts feature points included in the meeting data (step S6). Next, the comparison unit 20 compares the extracted features with the decision criteria (step S7).

[0044] Next, the notification creation unit 21 creates a notification based on the comparison results (step S8). Then, the output unit 22 outputs the created notification to the relevant participants (step S9).

[0045] Next, it is determined whether the meeting will end or not (step S10). If the meeting ends (step S10: YES), the process in this flow ends. On the other hand, if the meeting continues (step S10: NO), the process returns to step S6.

[0046] Next, I will explain the program. Each component included in the feedback device 1 can be implemented by hardware, software, or a combination thereof. Here, implementation by software means that it is implemented by a computer loading and executing a program.

[0047] Programs can be stored and supplied to a computer using various types of non-transitory computer-readable media. Non-transitory computer-readable media include various types of tangible storage media. Examples of non-transitory computer-readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROMs (Read Only Memory), CD-Rs, CD-R / Ws, and semiconductor memory (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, and RAMs (random access memory)). Display programs may also be supplied to a computer using various types of transient computer-readable media. Examples of transient computer-readable media include electrical signals, optical signals, and electromagnetic waves. Transitory computer-readable media can be supplied to a computer via wired communication channels such as electric wires and optical fibers, or via wireless communication channels.

[0048] As described above, the feedback device 1 and program according to this embodiment provide the following effects. (1) A feedback device 1 that provides real-time feedback to participants in an online meeting, comprising: a data acquisition unit 11 that acquires meeting data related to the meeting; a reference information acquisition unit 17 that acquires reference information such as feature points extracted from the meeting data and judgment criteria for those feature points; an extraction unit 19 that extracts feature points included in the acquired meeting data based on the acquired reference information; a comparison unit 20 that compares the extracted feature points with the judgment criteria; a notification creation unit 21 that creates a notification for stakeholders involved in the meeting based on the comparison result; and an output unit 22 that outputs the created notification to the stakeholders. This allows for real-time information to be grasped according to the status of the meeting. (2) The feedback device 1 further comprises a participant information acquisition unit 13 that acquires participant information indicating the attributes of the participants, and a decision unit 18 that determines the judgment criteria to be used for the participants based on the acquired participant information, and the comparison unit 20 compares the extracted feature points with the determined judgment criteria. This makes it possible to change the judgment criteria for each participant, thereby improving flexibility.

[0049] (3) The reference information acquisition unit 17 further includes specific information that identifies the relevant parties to whom the notification will be output, and the output unit 22 determines the recipients of the output based on the acquired participant information and the acquired specific information. This allows the content of the feedback to be changed for each participant, thereby improving flexibility.

[0050] (4) The extraction unit 19 extracts the specific content of the statements as characteristic points, the comparison unit 20 compares the extracted content with the judgment criteria, and the notification creation unit 21 creates a notification for the extracted content based on the judgment result. This makes it possible to create a notification indicating the quality of each participant's statement, thereby improving flexibility.

[0051] (5) The extraction unit 19 extracts the characteristics of the participants' communication based on the content of their statements as feature points, the comparison unit 20 compares the extracted content with the judgment criteria, and the notification creation unit 21 creates a notification of the response method to the extracted communication characteristics based on the judgment result. This makes it possible to notify participants of the preferred way of communicating, thereby improving flexibility.

[0052] (6) The feedback device 1 further includes a modification unit 23 that modifies the content of the acquired standard information according to the number and attributes of the participants. This allows the judgment criteria to be flexibly changed according to the circumstances of the participants.

[0053] [Second Embodiment] Next, the feedback device 1 and program according to the second embodiment of the present invention will be described with reference to Figures 7 to 10. In describing the second embodiment, the same reference numerals are used for identical components, and their descriptions are omitted or simplified.

[0054] The feedback device 1 and program according to the second embodiment output a list of participants' meetings. In particular, the feedback device 1 according to the second embodiment aims to obtain information that can be used to improve meetings by displaying a list of judgments and accumulated information regarding completed meeting data.

[0055] The feedback device 1 according to the second embodiment differs from the first embodiment in that, as shown in Figure 7, it comprises a judgment result acquisition unit 31, a detection target setting unit 32, an evaluation unit 33, a trend judgment unit 34, a change acquisition unit 35, and an input acquisition unit 36. Furthermore, the feedback device 1 according to the second embodiment differs from the first embodiment in that the data acquisition unit 11 acquires multiple sets of already completed meeting data. In addition, the feedback device 1 according to the second embodiment differs from the first embodiment in that the output unit 22 outputs the acquired meeting data as a list and outputs evaluation results for each set of meeting data.

[0056] The decision result acquisition unit 31 is implemented, for example, by the operation of the CPU. The decision result acquisition unit 31 acquires decision results for feature points obtained by analyzing meeting data. The decision result acquisition unit 31 acquires, for example, the results compared by the comparison unit 20 of the first embodiment as decision results. The decision result acquisition unit 31 also acquires notifications created by the notification creation unit 21 of the first embodiment as decision results.

[0057] The detection target setting unit 32 is implemented, for example, by the operation of the CPU. The detection target setting unit 32 sets important features contained in the meeting data as detection targets. For example, the detection target setting unit 32 sets predetermined negative statements and predetermined positive statements as detection targets.

[0058] The evaluation unit 33 is implemented, for example, by the operation of a CPU. The evaluation unit 33 evaluates the meeting data based on the judgment results. For example, the evaluation unit 33 evaluates meeting data with many judgment results indicating a positive trend as good meeting data. Also, the evaluation unit 33 evaluates meeting data as problematic if, for example, it is determined that the interview contains inappropriate remarks, etc.

[0059] The trend determination unit 34 is implemented, for example, by the operation of the CPU. The trend determination unit 34 determines the trend of the acquired judgment results. For example, the trend determination unit 34 determines the trend of the judgment results for each participating interviewer. Specifically, the trend determination unit 34 determines the speaking tendencies of each participating interviewer.

[0060] The change acquisition unit 35 is implemented, for example, by the operation of the CPU. The change acquisition unit 35 acquires the participant's changes in feature points for each acquired judgment result. For example, the change acquisition unit 35 acquires the participant's rate of change in relation to smiling. The change acquisition unit 35 also acquires, for example, the participant's changes in the utterance ratio.

[0061] The input acquisition unit 36 ​​is implemented, for example, by the operation of the CPU. The input acquisition unit 36 ​​acquires text, etc., entered by participants, etc., during or after a meeting. For example, the input acquisition unit 36 ​​acquires text such as notes taken by participants during the meeting, or comments on an interview entered by participants or related parties after the meeting.

[0062] As shown in Figure 8, the output unit 22 outputs a list of meeting data. The output unit 22 outputs evaluation results, trends, changes, and input content along with the list of meeting data. For example, the output unit 22 outputs information such as the date and time of the meeting, participant names, and meeting content, along with the evaluation results, trends, changes, and input content of the meeting data. In addition, as shown in Figure 9, the output unit 22 outputs details of the content of the meeting data selected from the list. The output unit 22 may also detect problematic interviews and output this information to the interview manager, etc. This allows the output unit 22 to understand the communication trends of participants or groups including participants.

[0063] Next, the operation of the feedback device 1 will be explained with reference to the flowchart in Figure 10.

[0064] First, the data acquisition unit 11 acquires meeting data (step S11). Next, the judgment result acquisition unit 31 acquires the judgment result (step S12). Then, the detection target acquisition unit acquires the detection target (step S13).

[0065] Next, the evaluation unit 33 evaluates the meeting data (step S14). Next, the trend determination unit 34 determines the trend in the meeting data (step S15). Next, the change acquisition unit 35 acquires changes in participants in the meeting data (step S16). Next, the input acquisition unit 36 ​​acquires input data such as text (step S17). Next, the output unit 22 outputs an overview of the meeting data along with the evaluation results, trends, changes, and input data (step S18).

[0066] Next, it is determined whether or not to terminate the evaluation (step S19). If there is no meeting data to evaluate (step S19: YES), the process in this flow terminates. On the other hand, if there is still meeting data to evaluate (step S19: NO), the process returns to step S1.

[0067] As described above, the feedback device 1 and program according to this embodiment provide the following effects. (7) A feedback device 1 capable of outputting a list of participants' meetings, comprising: a data acquisition unit 11 that acquires multiple participant meeting data; a judgment result acquisition unit 31 that acquires judgment results for feature points obtained by analyzing conversation data; an evaluation unit 33 that evaluates the meeting data based on the judgment results; and an output unit 22 that outputs the acquired meeting data as a list and outputs the evaluation results for each meeting data. By displaying a list of judgments and accumulated information regarding completed meeting data, information that can be used to improve meetings can be obtained.

[0068] (8) The evaluation unit 33 detects important features in the meeting data, and the output unit 22 outputs the detected important features along with the meeting data. This allows for the output of features that deserve particular attention, making it possible to identify meeting data that deserves more attention.

[0069] (9) The feedback device 1 further includes a trend determination unit 34 that determines the trend of the acquired judgment results, and the output unit 22 outputs the determined trend. This makes it possible to grasp the trends in the content of participants' statements, and to obtain information that can be used to improve meetings.

[0070] (10) The feedback device 1 further includes a change acquisition unit 35 that acquires changes in the participant with respect to characteristic points for each acquired judgment result, and an evaluation unit 33 evaluates the acquired changes in the participant. This makes it easier to grasp the detailed changes in the participant's state.

[0071] (11) The evaluation unit 33 evaluates the content of the meeting for each participant included in the meeting data, and the output unit 22 outputs the evaluation result for each participant along with the meeting data. This makes it easy to obtain different evaluation results for meeting data for each participant.

[0072] (12) The feedback device 1 further includes an input acquisition unit 36 ​​that acquires input for meeting data, and the output unit 22 outputs the acquired input content along with the meeting data. This makes it easier to obtain detailed information such as the status of the meeting.

[0073] Although preferred embodiments of the feedback device and program of the present invention have been described above, this disclosure is not limited to the embodiments described above and can be modified as appropriate.

[0074] For example, in the above embodiment, the meeting data may include only audio data, only video data, or both.

[0075] Furthermore, although the above embodiment uses interviews as an example of a meeting, it is not limited to this. Meetings can include various types of meetings, such as internal company meetings (1-on-1, group meetings), business negotiations with other companies, etc. Meetings can also include entrance examinations (university entrance examinations, etc.) and career counseling in employment placement businesses, etc.

[0076] Furthermore, in the above embodiment, the meeting is not limited to a one-on-one meeting, but may be a meeting with multiple participants. Also, the notification creation unit 21 and output unit 22 may create and output a notification to other participants with the aim of stopping one participant from talking too much. The notification creation unit 21 may also create a notification to the facilitator with the aim of stopping the talk. In addition, the notification creation unit 21 may issue notifications not limited to stopping talk, but aimed at ensuring the smooth progress of the meeting. For example, the notification creation unit 21 may issue a notification encouraging smiles if there are few smiles. The notification creation unit 21 may also issue a notification suggesting taking a break if concentration is waning, or a notification prompting other participants who look dissatisfied with what another participant has said to speak up.

[0077] Furthermore, in the second embodiment described above, the output unit 22 may output a list of meeting data that can be sorted and searched based on the participant, date and time, attribute, tags attached to the meeting data, etc.

[0078] Furthermore, in the above embodiment, the extraction unit 19 may extract features such as tone of voice, facial expressions other than smiles (sadness, surprise, relaxation, anger, and embarrassment, etc.), number of interruptions, quality of timing, quality of speech content, gestures, and quality of body language.

[0079] Furthermore, in the above embodiment, participants are not limited to those who are actually attending the meeting. Participants may include, for example, administrators who manage the meeting but do not attend it, or viewers who view the meeting content without attending (including department managers and individuals who give instructions to participants from outside). In this case, it is not necessary for notifications to be fed back from the video or verbal actions of administrators or viewers.

[0080] Furthermore, in the second embodiment described above, the evaluation unit 33 may create tags indicating the trends of the meeting. The evaluation unit 33 may create tags indicating the trends of the meeting, such as whether the conversation was lively, whether the participants' personalities and workplace issues were explored in depth, or whether the participants' mental state (such as their desire to work for the company, their motivation for work, and their level of trust in others) improved. For example, the evaluation unit 33 may use "meeting trends," "participant characteristics," and "characteristics of relationships between participants" as targets for tagging. For example, the evaluation unit 33 may tag whether the meeting trends are good or bad, whether there is a relationship of trust, and whether there is a tendency towards harassment. The evaluation unit 33 may also create tags indicating the characteristics of the participants. For example, the evaluation unit 33 may extract participant characteristics depending on the type of meeting. For example, if the meeting is an interview, the evaluation unit 33 may extract characteristics such as "English ability," "volunteering," "studying abroad," "New York," and "TOEFL" from the participants' statements during the meeting and use them as tags. Furthermore, the evaluation unit 33 may create tags for participants' characteristics such as speaking tendencies, personality traits (bright or dark), amount of conversation, sociability, frequency of smiles, influence on others, and likeability. The evaluation unit 33 may also enable matching participants with departments or interviewers that are a good match for them.

[0081] Furthermore, in the second embodiment described above, the output unit 22 may sort and display the meeting data. The output unit 22 may sort the meeting data, for example, by participant, by date and time, by participant attributes, or by participant tags.

[0082] Furthermore, in the second embodiment described above, the output unit 22 may output the contents of the meeting data in the form of a pie chart (including a donut chart), a table / heatmap (including a pivot table), a bar graph (including a stacked bar graph), a line graph, a scatter plot, a bubble chart, a band graph, a funnel (particularly useful for representing the yield rate of the hiring process), a histogram, a gauge (like a car's meter), an area graph, a box plot, a radar chart, a Pareto chart, a slope graph, contour lines, a Sankey diagram, a waterfall chart, or a map to an organizational chart / network diagram. The output unit 22 may also output using message notifications, audio (sound), a graph display on the screen, a display mimicking a traffic light, or screen color (display with colored edges on the window).

[0083] In the second embodiment, the output unit 22 may use the progress time of the meeting data, the time of implementation, various scores, or communication status as the axes of the graph. The evaluation unit 33 may also analyze the meeting data and extract highlights. The evaluation unit 33 may link the time at which the following occurred in the meeting data: points of score increase and decrease, inappropriate remarks, and remarks related to changes in emotion. The evaluation unit 33 may also enable playback of the corresponding part of a video from the link. The evaluation unit 33 may also create a highlight video that includes these highlights. The output unit 22 may display the following in the graph: each score and its progression within a single meeting; multiple meetings conducted with the same participants are displayed in comparison; or participants are displayed in comparison. For example, "a comparison of interviews conducted by interviewer A with student B / student C on the same graph," or "a comparison of meetings conducted by supervisor D with subordinate E / subordinate F on the same graph."

[0084] Furthermore, in the first embodiment described above, the notification creation unit 21 may create a notification immediately or retrospectively if it detects an interview with an extremely low communication analysis score. In the second embodiment, the evaluation unit 33 may, for example, in the evening of that day, list any interviews conducted that day with extremely low levels of smiling and send an email notification to the HR department. The evaluation unit 33 may also discover and suggest pairs of (interviewers) that have a complementary relationship in terms of communication quality, thereby contributing to the improvement of the overall quality of the interviews. In the first embodiment described above, the comparison unit 20 may compare the power balance of participants in communication. The output unit 22 may output this comparison result.

[0085] Furthermore, in the above embodiment, the feedback device 1 can be used in conjunction with both recruitment interviews and workplace interviews. For example, the feedback device 1 may store the wording used in a participant's recruitment interview as participant information and use the stored judgment information to make decisions in interviews with the same participant in the workplace.

[0086] Furthermore, in the second embodiment described above, the evaluation unit 33 may analyze the manner and content of the participants' (job seekers and interviewers) statements and convert them into evaluation indicators. The evaluation unit 33 may also evaluate the job seekers' situations based on the differences in the participants' reactions to the interviewers' statements. The evaluation unit 33 may also evaluate which agenda items the participants spoke about more appropriately. The evaluation unit 33 may also analyze the degree of self-confidence in the statements and whether the participants provided rich answers, and assign scores to them. This allows the evaluation unit 33 to stabilize the evaluation system for participants.

[0087] Furthermore, in the above embodiment, the output unit 22 may notify the output content via chat, dashboard, report, email, or call (telephone, etc.). Also, when the output unit 22 outputs data as an image, it may output it by color-coding, marking, blinking, enclosing (dashed lines, wavy lines, dotted lines, etc.), adding animation, including a pop-up message (including a character), or notifying with sound.

[0088] Furthermore, in the above embodiment, the feedback device 1 is used to determine the optimal assignment of interviewers. The feedback device 1 may also analyze and profile the participant's personality. The feedback device 1 may also reflect this in the participant's future activities (for example, notifying the manager that it may be desirable to avoid assigning the participant to a lively department because a quiet personality was detected during the interview). [Explanation of Symbols]

[0089] 1. Feedback device 11 Data Acquisition Unit 13 Participant information acquisition department 17 Standard information acquisition section 18. Decision Section 19 Extraction part 20 Comparison Section 21 Notification Creation Department 22 Output section 23 Changes 31 Judgment result acquisition part 33 Evaluation Department 34 Trend Judgment Department 35 Change Acquisition Unit 36 Input acquisition unit

Claims

1. An output device capable of outputting a list of participants' meetings, A data acquisition unit that acquires multiple meeting data for the same participant in multiple meetings, A judgment result acquisition unit that acquires judgment results for feature points obtained by analyzing the aforementioned meeting data, Based on the aforementioned determination results, an evaluation unit evaluates the characteristics of participant communication in the meeting data for each of the multiple meetings, For each of the aforementioned multiple meetings, an output unit outputs the acquired meeting data as a list, and also outputs the evaluation results for each of the said multiple meetings. A feedback device equipped with the following features.

2. The evaluation unit detects important features in the meeting data for each of the multiple meetings, The feedback device according to claim 1, wherein the output unit outputs the detected important features together with the meeting data for each of the plurality of meetings.

3. It further includes a trend determination unit that determines the trend of the acquired judgment results, The feedback device according to claim 1 or 2, wherein the output unit outputs the determined trend.

4. The system further includes a change acquisition unit that acquires changes in the participant's characteristics for each acquired judgment result. The evaluation unit evaluates the acquired changes in the participant, according to any one of claims 1 to 3.

5. The evaluation unit evaluates the content of each of the multiple meetings for each participant included in the meeting data. The feedback device according to any one of claims 1 to 4, wherein the output unit outputs the evaluation results for each participant along with the meeting data for each of the plurality of meetings.

6. The invention further comprises an input acquisition unit that acquires input for the meeting data for each of the plurality of meetings, The feedback device according to any one of claims 1 to 5, wherein the output unit outputs the acquired input content together with the meeting data for each of the plurality of meetings.

7. A program that makes a computer function as an output device capable of outputting a list of participants' meetings, The aforementioned computer, A data acquisition unit that acquires multiple meeting data for the same participant in multiple meetings. A judgment result acquisition unit that acquires judgment results for feature points obtained by analyzing the aforementioned meeting data. Based on the aforementioned determination, an evaluation unit evaluates the characteristics of participant communication in the meeting data for each of the multiple meetings. For each of the aforementioned multiple meetings, the output unit outputs the acquired meeting data as a list, and also outputs the evaluation results for each of the said multiple meetings. A program that makes it function as such.

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