WO2022137547A1 - Communication assistance system - Google Patents

Communication assistance system Download PDF

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Publication number
WO2022137547A1
WO2022137547A1 PCT/JP2020/048863 JP2020048863W WO2022137547A1 WO 2022137547 A1 WO2022137547 A1 WO 2022137547A1 JP 2020048863 W JP2020048863 W JP 2020048863W WO 2022137547 A1 WO2022137547 A1 WO 2022137547A1
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Prior art keywords
participant
user
output
intimacy
support system
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PCT/JP2020/048863
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French (fr)
Japanese (ja)
Inventor
契 宇都木
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株式会社日立製作所
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Priority to PCT/JP2020/048863 priority Critical patent/WO2022137547A1/en
Publication of WO2022137547A1 publication Critical patent/WO2022137547A1/en

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer

Definitions

  • the present invention relates to a communication support system.
  • remote conferences and remote collaborative creation activities have the problem that communication does not proceed smoothly because it is difficult to understand the real reaction of the other party compared to activities in the actual environment. Therefore, in remote communication involving a large number of people, it is important to provide appropriate feedback on the reactions of participants according to the situation and to support remote communication.
  • Patent Document 1 is known as a background technique of the present invention.
  • speech information is extracted based on voice data collected from participants in a plurality of meetings, activity data in the meeting of the participants is generated, and the dialogue status of the participants is described by the size of a circle or a line.
  • visualizing and displaying using the thickness etc. and by acquiring the voices of multiple participants during the meeting and displaying the ever-changing conversation situation in real time, more active discussions can be held while observing the situation. Techniques that can be induced are disclosed.
  • Patent Document 1 the problems in terms of voice in remote communication involving a large number of people such as remote conferences and remote collaborative creation activities can be solved, but nonverbal communication by visual information such as facial expressions is lacking. The problem of the point to be done has not been solved. Therefore, in remote communication, it is necessary to more appropriately grasp the reaction of each participant.
  • the communication support system of the present invention is a communication support system that supports remote communication performed between a plurality of participants, and includes an input reception unit that receives input from the participants participating in the communication support system, and the above-mentioned.
  • An intimacy estimation unit that estimates the intimacy between the first participant and the other participants based on the information about the first participant and the other participants among the plurality of participants.
  • Output priority calculation that determines the priority of the output contents output from the other participants to the first participant based on the intimacy estimated by the intimacy estimation unit. It has a unit and an output unit that outputs the output content to the first participant based on the output priority calculated by the output priority calculation unit.
  • Configuration of users / devices / networks in a remote communication system Configuration of general information equipment used in FIG.
  • User information stored on the server.
  • a modified example of FIG. Analysis example of user's face image. An example of data showing the judgment value of the analysis of FIG. The whole processing flowchart which concerns on 1st Embodiment. Feedback data sent to the server on a regular basis.
  • FIG. 1 is a configuration of a user, a device, and a network in a remote communication system according to the first embodiment of the present invention.
  • the server 1 is connected to the presenting user 3 and the listening users 6a to 6f via the net line of the general communication network, and analyzes the contents of the remote communication between these users.
  • the presentation user 3 makes a presentation to the listening users 6a to 6f through the information terminal (PC) 2.
  • Each of the listening users 6a to 6f is watching the presentation of the presentation user 3 via the information terminal (PC) 2 and the information terminal (pad) 7.
  • the listening users 6a to 6f are divided into a first group 4 and a second group 5, and this grouping is, for example, a group for each company, a group for each department in the organization, a group for each age, and the like. , It is freely set according to the closeness of the relationship of the group of users who participate in remote communication.
  • each group there is a conversation that is shared only within the group, and the specific content of the conversation, the impression of the presentation content of the presentation user 3, and the content of emotional expression for the presentation are shared by text messages and the like.
  • the concrete conversation content is not transmitted to the outside of each group in principle, and instead, each audit for the presentation of the presentation user 3 is performed between the first group 4 and the second group 5. Only the output contents of emotional expressions such as emoticon icons (non-verbal reactions) representing the reactions of users 6a to 6f are shared.
  • FIG. 2 is a configuration of a general information device used in FIG.
  • the server 1 is composed of a CPU, a main memory for storing program data, and an external storage (device) such as a memory card.
  • the CPU has an input reception unit that accepts input from participants participating in the communication support system, an intimacy estimation unit that estimates the intimacy between users, and an output priority that calculates the output priority based on the intimacy between users. It is equipped with a degree calculation unit, an index calculation unit that calculates an index related to communication between users, and an output unit that determines and outputs output contents based on an output priority and an index related to communication. Details will be described later.
  • the presenting user 3 or the listening users 6a to 6f are output devices (keyboard, mouse, touch panel) such as a display, a camera, a microphone, and an input device (keyboard, mouse, touch panel) connected to a general communication network by an external bus such as USB.
  • the information terminal 2 (PC) or the information terminal 7 (pad) is used to view or transmit audio and video.
  • FIG. 3 is user information stored in the server.
  • FIG. 3A is a data table of user information
  • FIG. 3B is a data table related to the history of FIG. 3A.
  • FIG. 3 (a) profile information about the user who uses the remote communication system is managed.
  • This user information shown in FIG. 3 is an example of an inter-individual distance table from the viewpoint of user A.
  • the items in the data table of FIG. 3A include the group to which the user belongs, the relationship between a certain user A and each user (d is an identification number and has nothing to do with numerical calculation), and the history of text comments by comment number (for details, see FIG. 3 (b)) shows the intimacy coefficient between the user A and another user.
  • This intimacy coefficient is a value indicating the distance between individuals between users, and the intimacy changes depending on the settings, input contents, facial expressions, etc. of each user, which will be described later.
  • the intimacy coefficient shown in FIG. 3A indicates that the smaller the value, the higher the intimacy with the target partner. Further, as shown in FIG. 1, this user information is stored in the server 1 as being common to all users regardless of the presenter or the audience.
  • the intimacy between users can be judged from the contents of the history of text comments in FIG. 3 (b). For example, the number of histories between certain users (number of conversations) and how to convey a message to the other party in a text comment (determined by the frequency of use of a specific positive word) can be used as judgment materials.
  • the intimacy between users can be determined by grasping the relationship between users and the emotions of the other user based on the information set by the screens of FIGS. 4 to 7 described below.
  • the intimacy coefficient set according to the intimacy between the users determined in this way is used in the server 1 to determine the output content for each user, and affects the content output to the user.
  • FIG. 4 is an example of a screen for managing relationships between users.
  • Terminal 2 (7) outputs a screen for managing information about each user.
  • the user of the terminal 2 (7) can select, set, and edit the relationship with each user on the output screen according to the classification (classification of colleagues, customers, friends, acquaintances, etc.) and the degree of familiarity.
  • the familiarity value that can be set for each user is an element for calculating the intimacy coefficient (FIG. 3 (a)).
  • the value of familiarity shown in FIG. 4 indicates that the larger the value, the higher the intimacy. Even if the person is not close, if the other person is an important person (VIP, etc.), setting the familiarity value to a high value can affect the intimacy coefficient (importance coefficient). ..
  • FIG. 5 is an example of a screen for selecting information for the transmission target user.
  • Terminal 2 (7) outputs a screen for setting transmission information.
  • transmission information For example, in FIG. 5, for "colleagues", voice, text, anonymous keywords (specific keywords used without displaying their name to the target user are shared), facial expression information, emotion classification data ( It is set to be able to send (icon related to one's facial expression) and anonymous emotions (only emotions are shared without displaying one's name to the target user), and is not shared for facial expressions.
  • emotion classification data It is set to be able to send (icon related to one's facial expression) and anonymous emotions (only emotions are shared without displaying one's name to the target user), and is not shared for facial expressions.
  • extremely private information such as facial footage
  • the relationship between users is determined by the setting of this transmission information, and a value according to the relationship between users is added to the intimacy in the calculation in the intimacy estimation unit.
  • each information is not sent to the server 1, so that the complete confidentiality of the user information is ensured.
  • FIG. 6 is an example of a screen for setting the feedback amount for each user group.
  • the terminal 2 (7) outputs a screen for setting feedback weighting in order to incorporate highly important opinions and reactions to the group to which the user belongs and to reduce unimportant opinions and reactions as much as possible. There is.
  • the value of this display weighting is an input value that determines how much the reaction of which group is displayed. Therefore, a group in which this value is set to a large value will have a large display on its own information terminal. For example, on the setting screen of FIG. 6, since the display weight of a customer who is in a financial group is 0.9 (maximum value is 1), comments and reactions are greatly displayed to the user of this terminal. The presence on the screen of the terminal becomes large. However, since the display weighting of the group of subordinates of the company is set to 0.3, the comments and reactions on this terminal are displayed small, and the presence on the screen becomes small. In this way, the relationship between users is determined by the display weighting, and the intimacy estimation unit adds a value corresponding to this relationship to the intimacy.
  • FIG. 7 is an example of a screen for setting the amount of feedback regarding emotional expression.
  • Terminal 2 (7) outputs a screen for setting the aggregation of the emotions of the other user.
  • This is a screen for inputting and setting what kind of reaction is important. For example, as shown in FIG. 7, when you want to aggregate positive emotions, you can select a positive item in the emotion group to relate to positive emotions.
  • display weighting values can be set for each of facial expressions, voices, languages, and inputs. The larger the display weighting value, the greater the influence on the calculation result of the intimacy.
  • the display weighting value can be customized for each group or user, and each user's emotions are parameterized by the facial expressions judged from each user's facial image and the input from the UI on each user's terminal. be able to.
  • the emotional parameterization is performed by the index calculation unit calculating an index related to communication.
  • the familiarity value set on the screen of FIG. 4 indicating the relationship for each user, the type of transmission information set on the screen of FIG. 5, and the display weighting set on the screens of FIGS. 6 and 7, respectively.
  • the value of is used in the calculation of the intimacy of each user performed by the intimacy estimation unit in the server 1 (FIG. 2). That is, in the server 1, the intimacy estimation unit estimates the intimacy according to the relationship between the users by using these setting information.
  • FIG. 8 is an example of a model screen of the communication support system according to the first embodiment.
  • the presentation screen is output and displayed on the terminal 2 (7). Further, on the lower side of the presentation screen, the feedback time transition graph 12 and the video 13 of another user participating are projected.
  • the feedback time transition graph 12 shows the reaction (emotion) of each user to the presentation as parameters, and the graph flows to the left with the passage of time. In this graph, the larger the number (there are many good reactions to the presentation), the higher the graph.
  • the quantified feedback from the feedback time transition graph 12 allows the presenter to visually understand the current excitement of the audience, which allows the presenter to proceed with the conference while feeling a realistic reaction. More specifically, the index calculation unit calculates an index according to the reaction of each user based on the value of the emotion display weighting described with reference to FIG. 7, and the output unit feeds back using the value of this index as a parameter. By determining the display content of the time transition graph 12, the reaction of each user is parameterized and reflected in the feedback time transition graph 12.
  • the facial image 13 of another user is a real image or image of a face taken by a camera, a facial expression reproduction model (CG or virtual model that reproduces a facial expression based on the movement of a real person's facial expression), and a facial expression reproduction icon (existing). Based on the movement of the person's facial expression, an icon with a similar facial expression is displayed). Which display is to be displayed is determined by the server 1 for each user based on the output priority calculated by the output priority calculation unit based on the intimacy between the users. For example, users with higher intimacy and higher output priority display images that are closer to real images and images, and by changing the display so that the lower the output priority, the higher the level of abstraction, intimacy and anonymity. It is possible to display both sexes.
  • Word cloud 18 that aggregates and describes trend words in conversation and a text field 19 that expresses chat shared during the presentation are displayed.
  • Word cloud 18 can display the trending words in a large size by aggregating the comments of the users who are participating in the conference, and what kind of keywords are used by the users who are watching the presentation as a whole. You can visualize what you are doing.
  • the comments of the users who are participants are displayed in the text field 19, some users may not be displayed due to the transmission information setting (FIG. 5) described above.
  • a video 16 displaying one's facial expression and a transmission data 17 indicating transmission information are displayed below the Word cloud 18. Further, a voice ON / OFF button 14 and a video ON / OFF button 15 for setting ON / OFF of one's own voice and facial expression are provided.
  • FIG. 9 is a modified example of FIG.
  • FIG. 9 the Word cloud 18 and the text field 19 in FIG. 8 are replaced with the feedback 2-axis graph 20.
  • the feedback 2-axis graph 20 a plot 21 representing the group importance is displayed based on the definition set in the 2-axis graph.
  • FIG. 9 For example, as shown in FIG. 9, "concentration” (how many listening users are listening without showing away, whether the number of nods to the speaker is high) and “positiveness” (speaker's).
  • There is a two-axis graph (such as inputting a specific keyword that has a favorable impression on the content of the presentation, the time of a smile that can be read from the facial expression of the listening user, etc.).
  • This graph shows the result of totaling the indexes related to communication between users calculated by the index calculation unit for each user, and is based on the output priority calculated by the output priority calculation unit based on the intimacy between users.
  • the display content is determined on the server 1.
  • model screen examples in FIGS. 8 and 9 are drawn assuming a PC terminal, a pad terminal may also be used.
  • FIG. 10 is an analysis example of the user's face image. Further, FIG. 11 is an example of data showing the determination value of the analysis of FIG. Note that FIG. 11A is an example of feature point data to be transmitted as “facial expression information”, and FIG. 11B is an example of data to be transmitted as “emotion classification data”.
  • the output unit By analyzing the facial expression of the user in the index calculation unit of the server 1 using the camera captured image 22, it is possible to determine the emotion of the user corresponding to the facial expression and calculate the index related to communication. Based on the index calculated in this way, the output unit generates a facial expression reproduction model or a facial expression reproduction icon.
  • the analysis method creates a data table by digitizing and extracting a set number of points (feature points) that are characteristic of facial expressions in x-coordinates and y-coordinates. As a result, as shown in FIG. 11A, the coordinate values for each feature point in the feature point extraction image 23 are extracted. Then, the facial expression reproduction model 24 of FIG.
  • the facial expression reproduction model 24 may be generated by changing the facial expression reproduction model 24 according to the user's emotions to further understand the user's emotions.
  • FIG. 11A only four feature points are shown, but in reality, it is determined by 30 or more feature points.
  • the index calculation unit can calculate an index related to communication from the feature point extraction image 23 using a machine learning discriminator, and can determine the facial expression icon 25 based on the calculation result. As shown in FIG. 11B, the facial expression icon 25 is determined by calculating a determination value as an index related to communication for each facial expression item such as a smile or a nod.
  • the machine learning discriminator is, for example, SVM (Support vector machine), NN (Neural Network), or the like.
  • the determination value (index) for each facial expression item calculated when the facial expression icon 25 is determined may be used in the calculation of the intimacy of each user performed by the intimacy estimation unit. For example, among the weighted values of the display for each detailed item set on the screen of FIG. 7, the weighted value related to the facial expression can be determined whether or not to be adopted in the calculation of intimacy based on this determination value.
  • the facial expression reproduction model 24 and the facial expression icon 25 created as described above are images that reproduce the facial expressions of each user based on the index related to communication between users. These are transmitted from the server 1 to the terminal of each user, and are displayed as a video 13 on the model screen shown in FIGS. 8 and 9, for example, to output to each user. Note that FIG. 10 shows the output based on facial expression analysis. Similarly, based on the input from the voice, the sound is fed back by applying the sound to a machine learning classifier or the like based on the recognition of the laughing voice and the volume of the voice. It also has a mechanism to do it.
  • cultural differences can be absorbed by setting conversion rules for each nationality of participating users in the recognition mechanism. For example, it is possible to eliminate the difference by setting different gesture and smile thresholds for each country and reflecting emotions in the parameters.
  • FIG. 12 is an overall processing flowchart according to the first embodiment.
  • the personal client operation is the content operated by the terminal of the PC or the pad.
  • the information logged in in step S2 is also shared with the server (described later in step S104).
  • Steps S3 to S12 are flows (loop processing) that are repeated at regular time intervals, and the loop processing is started in step S3.
  • step S4 the voice information obtained by the microphone recording operation at the time of the user using the terminal is acquired.
  • step S5 the voice information of the user using the terminal is processed by converting the recorded information of the microphone into text and estimating the emotional information from the recorded information and the text.
  • step S6 the user using the terminal acquires the video information obtained by recording the camera at the time.
  • step S7 the facial features obtained from the video information of the user using the terminal are recognized from the image information of the camera acquired in step S6, and the information related to emotions is estimated according to the degree of the features. ..
  • step S8 the input information to be transmitted to the server is acquired based on the information acquired / processed in steps S4 to S7.
  • step S9 Send the input information to the server in step S9.
  • the information to be transmitted is input by the input reception unit of the server.
  • This transmission is an asynchronous communication in which the data transmitted to the buffer is read at the timing of reading the audio / video information and is processed.
  • the transmission of step S9 or the reception of step S10 is periodically transmitted / received each time the loop processing of steps S3 to S12 is performed.
  • step S11 the terminal outputs an image (face image, facial expression reproduction model, facial expression icon) based on the information received from the server.
  • Server 1 is started in step S101.
  • step S102 the personal information database (DB) is read.
  • DB personal information database
  • Steps S103 to S112 are flows (loop processing) that are repeated at regular time intervals, and the loop processing is started in step S103.
  • step S104 in the operation of the individual client, the login information of step S2 is received and a new login is accepted.
  • step S105 the loop process is started for a certain user A among the logged-in users.
  • step S106 the information periodically transmitted from the terminal in step S9 is received.
  • the input receiving unit accepts the input of the terminal.
  • step S107 the inter-individual distance between the user A and a plurality of other users is confirmed, the output content is determined, and the loop process of transmitting to the terminal of the user A is started.
  • step S108 the distance between the individual user A and another user is calculated and confirmed.
  • the index calculation unit calculates the index
  • the intimacy estimation unit calculates the intimacy
  • the output priority calculation unit outputs based on the calculated intimacy. The priority is calculated
  • the output unit determines the output content at the terminal based on the calculated output priority.
  • the output content determined here includes the facial expression reproduction model and display reproduction icon of each user displayed as the video 13 of FIGS. 8 and 9, the display content in Word cloud 18 and the text field 19.
  • step S109 the information of the output content determined in step S108 is transmitted to the terminal of the user A. This transmission is asynchronous communication similar to step S9.
  • step S110 the distance between the individual user A and another user is confirmed, the output content is determined, and the loop process of transmitting to the terminal of the user A is terminated.
  • each user follows the output priority according to the personal distance (intimacy) between the user A and each other user.
  • the output content to be output to the user A is determined, and the information of the output content is transmitted from the server 1 to the terminal of the user A.
  • step S111 the loop process targeting user A is terminated.
  • the loop processing of steps S105 to S111 for each user the output content in the terminal of each user is determined, and the information of the output content is transmitted from the server 1 to the terminal of each user.
  • step S112 the loop processing of steps S103 to S112 is terminated.
  • FIG. 13 is an example of feedback data periodically transmitted to the server according to the first embodiment.
  • the feedback data shown in FIG. 13 is the information transmitted in step S9 of FIG. Each item will be explained.
  • a flag as to whether or not to disclose the voice information of the user A is shown to 12 users other than the user A who are participating in the conference, such as [10010 ...]. ing. In this way, it is determined to whom information about oneself can be disclosed. It is not disclosed to the group whose corresponding flag is 0.
  • the file type is recorded in the voice information data column. Similar to the voice information disclosure flag field, the text information disclosure flag column shows a flag as to whether or not the user A discloses voice information to 12 users other than the user A. In the text information data field, the text content input by the user A is recorded.
  • the face image disclosure flag column is the same as the voice information disclosure flag column and the text information disclosure flag column. Face image data is recorded in the face image data column.
  • the facial expression information disclosure flag column is the same as the facial image disclosure flag column, the voice information disclosure flag column, and the text information disclosure flag column.
  • a coordinate value list is recorded in the facial expression information data column. This is a value used for constructing the above-mentioned facial expression reproduction model (see FIG. 10).
  • the emotional information disclosure flag column is the same as the facial expression information disclosure flag column, the face image disclosure flag column, the voice information disclosure flag column, and the text information disclosure flag column.
  • the determination value for the facial expression icon (see FIG. 10) analyzed from the facial image is recorded.
  • the above feedback data is sent to the server, and the intimacy estimation unit determines the intimacy coefficient, which is information regarding the distance between each user and the user A.
  • the above information of each user is totaled by the display weighted value set on the emotion aggregation setting screen (FIG. 7) in the index calculation unit, and the emotion aggregation value for each user is calculated.
  • This purpose-specific emotion aggregate value is transmitted from the server 1 to each user's terminal, and is used for graph display on the screen as shown in the feedback 2-axis graph 20 of FIG. 9 in each terminal. , Expressed as a plot group as the degree of concentration. Further, the correlation with the reception display side user is calculated and used for the calculation of the sympathy value in the inter-individual distance (described later in FIG. 14).
  • FIG. 14 is a flowchart showing the process of calculating the inter-individual distance according to the first embodiment. The flowchart will be described below.
  • the inter-individual distance table created in FIG. 14 is used in the calculation / confirmation of the inter-individual distance in step S108 of FIG. 12, and is created independently of the flow of FIG.
  • step S20 user A (screen viewer) is selected.
  • step S21 a loop process for determining the distance between individuals with each viewer (user X) participating in the conference is started.
  • step S22 it is confirmed whether or not there is target person information. If this target person information does not exist in the information of user A, it is determined that there is no relationship.
  • step S23 the data of the classification group of the target person is acquired.
  • step S24 the importance information is input for each group acquired in step S23.
  • the importance information referred to here is the display weighting (FIG. 6) in the feedback weighting setting.
  • step S25 a numerical value of "friendliness" preset for each user is input from the management screen of the terminal (FIG. 4).
  • step S26 the intimacy in the conversation is calculated from the number of times the user A has talked with each user. The numerical value and the calculated value input in the flow from step S24 to step S26 are used in the calculation in which the intimacy estimation unit determines the inter-individual distance (intimacy).
  • step S27 the correlation with the emotion data of the user A regarding the user X is calculated, and the sympathy value between the user A and the user X is calculated.
  • the feedback data of FIG. 13 is also used to calculate this sympathy value. If the positive correlation is higher than a certain threshold, the empathy value is added to the calculation of the inter-individual distance.
  • step S28 the output priority calculation unit determines the inter-individual distance between the user A and the user X based on the flow of steps S22 to S27.
  • step S29 the loop processing of steps S21 to S29 is terminated.
  • the data table regarding the inter-individual distance of the user A is completed in the step S30. This inter-personal distance data table is created for each user from a certain user A, and the output is determined based on the aggregated data table.
  • the intimacy between users is estimated from the relationship between users and the state of communication, and based on the estimation result, from the user to other users.
  • Output (comments, utterances) can be prioritized. For example, by clearly indicating or outputting a large comment to a participant who has a high degree of intimacy, the comment that is of high interest to the participant can be output preferentially, so that remote communication with a sense of presence can be realized. Can be done. It also calculates indicators related to communication from the user to other users (for example, agree, disagree, understand), and based on this and output priority, outputs a graph expressing the value of the indicator, or an image based on the indicator. Images (for example, user's face image, facial expression reproduction model, facial expression reproduction icon, etc.) can be output.
  • FIG. 15 is an example of a model screen of the communication support system according to the second embodiment.
  • the point of the communication support system of the second embodiment is for exhibitions on VR (Virtual Reality), and is remote communication performed in VR space.
  • VR Virtual Reality
  • the points common to the first embodiment will be omitted, and the differences will be mainly described.
  • the first exhibit 28 In the VR space image 27 output by the terminal 2 (7), the first exhibit 28, the facial expression reproduction icon 29 of the user who is looking at the first exhibit, and the second exhibit 30 are projected. ..
  • each user (avatar) in the VR space can grasp the direction, position, and distance of the line of sight in the virtual space three-dimensionally on the screen.
  • the screen of the facial expression information 32 of the user who is watching can also be used to visualize the atmosphere of the user who is watching the same object. This makes it possible to understand the facial expressions and atmospheres of the users participating in the VR space.
  • FIG. 16 is feedback data periodically transmitted to the server according to the second embodiment.
  • a column for avatar position operation information and a column for avatar angle operation information have been added to the data table described with reference to FIG.
  • the column of avatar position operation information the position in the VR space by the XYZ coordinates is shown.
  • the column of the avatar angle operation information the numerical value regarding the line-of-sight direction in which the avatar is looking at the object in the VR space is shown. That is, the operation information of the avatar is sent together with the feedback data.
  • FIG. 17 is a calculation of the inter-individual distance according to the second embodiment.
  • step S28A The difference from the calculation of the inter-individual distance of the first embodiment shown in FIG. 14 is step S28A and step S29A.
  • step S28A if the user X sees the same object as the user A, the value of the intimacy according to the relationship between the users is added in the calculation of the interpersonal distance between the user A and the user X. ..
  • step S29A if the user X is within a certain distance from the user A in the VR, the intimacy according to the relationship between the users is calculated in the calculation of the interpersonal distance between the user A and the user X. Add the values. This completes the inter-individual distance table in the VR space (step S32A).
  • FIG. 18 is a configuration example of a model of the communication support system according to the third embodiment.
  • the point in the third embodiment is remote communication via the avatar robot. Similar to the description of the second embodiment, the points common to the first embodiment will be omitted, and the differences will be mainly described.
  • the avatar robot 37 is equipped with an omnidirectional camera 34 and is operated at the presentation site 36 set up in the real space.
  • the omnidirectional image 33 taken by the avatar robot 37 using the omnidirectional camera 34 is a projection of the on-site presenter 35, the on-site presenter 39, and the like existing around the avatar robot 37.
  • the avatar robot 37 transmits and projects the captured omnidirectional image 33 to each user 6aB to 6dB.
  • Each user 6aB to 6dB can view the omnidirectional image 33 by an output terminal such as a PC, a pad, a smartphone, or a VR headset.
  • Each user 6aB to 6dB is watching the omnidirectional video 33, but the user 6bB, the user 6cB, and the user 6dB are watching the same object (object video 33b) in the omnidirectional video 33, and the user 6aB is all. You are looking at another object (object image 33a) in the surrounding image 33. Therefore, in FIG. 18, the user 6aB does not participate in the feedback from the user 6bB to the user 6dB to the site 36.
  • the server creates a facial expression reproduction model, a facial expression icon, etc. from the appearance and reaction of the user 6bB to the user 6dB watching the omnidirectional image 33, and feeds back to the site 36.
  • the output of the feedback content is transmitted as feedback to the screen 38 in front of the on-site presenter 39 and the screen 41 in front of the on-site presenter 35 on the 360-degree four-sided display 40 installed in the avatar robot 37, respectively.
  • the feedback content is, for example, screen 42.
  • the content is, for example, the impression of the user 6 dB on the content of the presentation by the on-site presenter 35.
  • FIG. 19 is a user viewing content, which is an example of a user viewing screen model according to the third embodiment. Similar to the description of FIG. 18, the points common to the first embodiment and the second embodiment will be omitted, and the differences will be mainly described.
  • the difference between the first embodiment (see FIGS. 8 and 9) and the second embodiment (see FIG. 15) is that the user's viewpoint image 46 in the avatar robot is used for the screen of the terminal 2 (7). That is.
  • the user's viewpoint image 46 displays a presenter A39, a user B's avatar 44, a facial expression reproduction icon 45 representing the user B's feedback content, a user C's avatar 48, and a face image icon 47 representing the user C's feedback content.
  • the user's viewpoint image 46 is accompanied by another user's avatar (Avatar 44 in FIG. 19). 48) is coming to appear.
  • the viewing angle of another user moves to a viewing angle deviating from a certain viewing angle of the user, the icon of the other user disappears from the user's screen.
  • FIG. 20 is an example of a model screen of the avatar robot according to the third embodiment.
  • FIG. 20 shows the state of the avatar robot as seen from the presenter A.
  • the emotion icon 45 which is the feedback content of the user B
  • the face image icon 47 which is the feedback content of the user C
  • the facial expression information 49 which is the feedback content of the user A
  • FIG. 21 is feedback data transmitted periodically according to the third embodiment.
  • FIG. 21 shows that the difference between the first embodiment and the second embodiment is that the viewpoint robot selection information and the line-of-sight angle information are included in the items.
  • the viewpoint robot selection information column the identification number of the robot is recorded by selecting one robot from the plurality of robots in the field by the user.
  • the line-of-sight angle information information about the line-of-sight angle currently viewed by the user from the robot having the identification number selected in the viewpoint robot selection information field is recorded.
  • FIG. 22 is a calculation of the inter-individual distance according to the third embodiment.
  • FIG. 22 shows the difference between the first embodiment (see FIG. 14) and the second embodiment (see FIG. 17) in step S28B and step S29B.
  • step S28B when the user X is looking at the camera of the same robot among the plurality of avatar robots having the user A, that is, the avatar robot that outputs the image to be viewed by the user X and the avatar robot visually recognized by the user A.
  • the value of the intimacy according to the relationship between these users is added.
  • step 29B based on step 28B, if the line-of-sight direction of user X is close to the line-of-sight direction of user A, that is, when the line-of-sight direction of user X is within a predetermined error range with the line-of-sight direction of user A, the user.
  • the value of the intimacy according to the relationship between these users is added.
  • the inter-individual distance table is completed by the flow of steps S20B to 32B including this.
  • the server 1 is an input reception unit that receives input from participants participating in the communication support system, and among a plurality of participants.
  • the intimacy estimation unit that estimates the intimacy between the first participant and the other participants based on the information about the first participant and the other participants, and the parent estimated by the intimacy estimation unit.
  • An output priority calculation unit that calculates an output priority that determines the priority of output contents output from other participants to the first participant based on the density, and an output calculated by the output priority calculation unit. It has an output unit that outputs the output contents to the first participant based on the priority.
  • the server 1 has an index calculation unit that calculates an index related to communication between the first participant and other participants.
  • the output unit determines the output content based on the output priority calculated by the output priority calculation unit and the index calculated by the index calculation unit. By doing so, it is possible to give feedback according to the communication situation between the participants to the presenter who is making a presentation to other participants.
  • the output unit is taken as an input received by the input reception unit, for example, with a camera.
  • the image of the face of another participant is output as it is, and if it is lower than the predetermined value, for example, a facial expression reproduction model or a facial expression reproduction icon is output as an image based on an index related to communication.
  • the intimacy estimation unit sets the relationship from the first participant to the other participants by the screen of FIG. 4, and from the first participant to the other participants by the screen of FIG.
  • the intimacy can be estimated based on the type of transmission information set for the subject and the amount of feedback set from the first participant to the group to which the other participants belong from the screen of FIG. .. By doing so, it is possible to estimate the intimacy in consideration of the relationship between users.
  • the image based on the index related to communication includes a facial expression reproduction model 24 which is a model image that reproduces the facial expressions of the participants.
  • the output unit can create a facial expression reproduction model 24 from a camera-photographed image 22 of each participant's face. By doing so, it is possible to create a sense of intimacy while ensuring anonymity for a person who has a certain sense of intimacy.
  • the image based on the index related to communication includes the facial expression reproduction icon 25, which is an icon that reproduces the facial expression of the participant.
  • the output unit can create the facial expression reproduction icon 25 from the camera-captured image 22 of each participant's face. By doing so, it is possible to give feedback by expressing emotions that ensure anonymity to a person who is not acquainted.
  • the intimacy estimation unit is used when the avatars of other participants are looking at the same target as the avatars of the first participant, or other participants.
  • the first When at least one of the avatars of the first participant is within a certain distance from the avatar of the first participant, in the calculation of the intimacy between the first participant and the other participant, the first. Add the values according to the relationship between one participant and other participants. By doing so, the intimacy can be estimated from the user's avatars in the VR space.
  • the intimacy estimation unit visually recognizes the avatar robot that outputs the video to be viewed by other participants and the first participant among the plurality of avatar robots.
  • the first is when at least one of the following is satisfied when the avatar robot is the same as the robot, or when the viewing direction of another participant is within a predetermined error from the viewing direction of the first participant.
  • a value corresponding to the relationship between the first participant and the other participant is added. By doing so, even when the avatar robot is used, it is possible to calculate the inter-individual distance between the users and estimate the intimacy between the users.
  • the present invention is not limited to the above embodiment, and various modifications and other configurations can be combined within a range that does not deviate from the gist thereof. Further, the present invention is not limited to the one including all the configurations described in the above-described embodiment, and includes the one in which a part of the configurations is deleted.
  • Avatar (user) looking at the 1st exhibit Facial expression reproduction icon 30 ... 2nd exhibit 31 ... Feedback information 32 ... Looking at the 1st exhibit User's facial expression information 33 ... All-around image of the avatar robot 33a, 33b ... Object 34 ... All-around camera 35 ... On-site presenter B reflected in the all-around image of the avatar robot 36 ... Site 37 ... Abata (operating) robot 38 ... Screen in front of site presenter A 39 ... Site presenter A 40 ... 360-degree four-sided display 41 ... Screen in front of presenter B on site 42 ... Screen on which the facial expression feedback of the viewing user is reflected 44 ... Avatar 45 of user B ... Facial expression reproduction icon 46 of user B ... User's viewpoint image (Abata robot) ) 47 ... Face image icon of user C 48 ... Avata of user C 49 ... Facial expression reproduction model of user A

Abstract

This communication assistance system is for providing assistance in remote communication to be performed by a plurality of participants. The communication assistance system has: an input reception unit that receives input from the participants who participate in the communication assistance system; an intimacy level estimation unit that estimates an intimacy level between a first participant and another participant among the plurality of participants on the basis of information relating to the first participant and the other participant; an output priority calculation unit that, on the basis of the intimacy level estimated by the intimacy level estimation unit, calculates an output priority for determining the priority of an output content to be outputted from the other participant to the first participant; and an output unit that outputs the output content to the first participant on the basis of the output priority calculated by the output priority calculation unit.

Description

コミュニケーション支援システムCommunication support system
 本発明は、コミュニケーション支援システムに関する。 The present invention relates to a communication support system.
 新型コロナウイルス感染症(COVID-19)対策として、対面でのコミュニケーションが制限される問題を解消するため、各個人・各企業間において、デジタル技術を活用した遠隔会議や遠隔協創活動が拡大している。 As a countermeasure against the new coronavirus infection (COVID-19), in order to solve the problem of restricted face-to-face communication, remote conferences and remote collaborative creation activities using digital technology have expanded between individuals and companies. ing.
 そうした背景で、遠隔会議や遠隔協創活動は、実環境での活動に比べて相手方のリアルな反応がわかりにくいという理由により、コミュニケーションが円滑に進まない場面が多くなるという問題がある。そのため、多人数が関与する遠隔コミュニケーションにおいては、状況に応じた参加者の反応のフィードバックを適切に行い、遠隔でのコミュニケーションを支援する効果が重要である。 Against this background, remote conferences and remote collaborative creation activities have the problem that communication does not proceed smoothly because it is difficult to understand the real reaction of the other party compared to activities in the actual environment. Therefore, in remote communication involving a large number of people, it is important to provide appropriate feedback on the reactions of participants according to the situation and to support remote communication.
 本願発明の背景技術として、下記の特許文献1が知られている。特許文献1には、複数の会議の参加者から収集した音声データに基づいて、発話情報を抽出し、参加者の会議におけるアクティビティデータを生成し、参加者の対話状況を円の大きさや線の太さなどを用いて可視化して表示し、さらに会議中の複数の参加者の音声を取得して刻々と変わる会話状況をリアルタイムに表示することで、状況を観察しながらより積極的な議論を誘発できる技術が開示されている。 The following Patent Document 1 is known as a background technique of the present invention. In Patent Document 1, speech information is extracted based on voice data collected from participants in a plurality of meetings, activity data in the meeting of the participants is generated, and the dialogue status of the participants is described by the size of a circle or a line. By visualizing and displaying using the thickness etc., and by acquiring the voices of multiple participants during the meeting and displaying the ever-changing conversation situation in real time, more active discussions can be held while observing the situation. Techniques that can be induced are disclosed.
特開2008-262046号公報Japanese Unexamined Patent Publication No. 2008-262406
 特許文献1の構成では、遠隔会議や遠隔協創活動のように多人数が関与する遠隔コミュニケーションにおいての音声面での課題は解消できているが、表情などの視覚情報による非言語的コミュニケーションが欠落する点の課題が解消されていない。よって、遠隔コミュニケーションにおいて、各参加者の反応をさらに適切に把握する必要がある。 In the structure of Patent Document 1, the problems in terms of voice in remote communication involving a large number of people such as remote conferences and remote collaborative creation activities can be solved, but nonverbal communication by visual information such as facial expressions is lacking. The problem of the point to be done has not been solved. Therefore, in remote communication, it is necessary to more appropriately grasp the reaction of each participant.
 また、上記の点に関して、遠隔コミュニケーションを促進する手法として、各参加者のコメントや映像を出力するインターフェースを用いて、コミュニケーションの状況の可視化及びフィードバックを行う方法が従来技術には存在する。しかし、多人数が参加する遠隔コミュニケーションにおいて、多数の参加者のコメントや映像が各参加者との関係性を考慮せずにそのまま表示されることで、各参加者にとって重要な情報が適切に可視化されず、かつフィードバックもされない状況が生み出されてしまう。こうした状況は各参加者の臨場感の欠如につながり、円滑なコミュニケーションの支障となる。 Regarding the above points, as a method for promoting remote communication, there is a method in the prior art for visualizing the communication situation and giving feedback using an interface that outputs comments and videos of each participant. However, in remote communication where a large number of participants participate, the comments and videos of many participants are displayed as they are without considering the relationship with each participant, so that important information for each participant can be appropriately visualized. It creates a situation where no feedback is given. Such a situation leads to lack of presence of each participant and hinders smooth communication.
 さらに、これに加えて、多人数が参加する遠隔コミュニケーションにおいては、参加者同士の関係性が近いか遠いかに関係なく自身のコメントや映像を直接表示するため、参加者それぞれの匿名性を確保する必要がある。 Furthermore, in addition to this, in remote communication in which a large number of participants participate, their own comments and videos are directly displayed regardless of whether the relationships between the participants are close or far, ensuring the anonymity of each participant. There is a need.
 以上を鑑みて、本発明では、臨場感の向上と匿名性の確保とを両立させた遠隔コミュニケーションを実現できるコミュニケーション支援システムを提供することが課題である。 In view of the above, it is an object of the present invention to provide a communication support system capable of realizing remote communication that achieves both improvement of presence and ensuring anonymity.
 本発明のコミュニケーション支援システムは、複数の参加者の間で行われる遠隔コミュニケーションを支援するコミュニケーション支援システムであって、前記コミュニケーション支援システムに参加する前記参加者からの入力を受け付ける入力受付部と、前記複数の参加者のうち、第1の参加者と他の参加者とに関する情報に基づいて、前記第1の参加者と前記他の参加者との親密度を推定する、親密度推定部と、前記親密度推定部が推定した前記親密度に基づいて、前記他の参加者から前記第1の参加者に対して出力する出力内容の優先度を決める出力優先度を算出する、出力優先度算出部と、前記出力優先度算出部が算出した前記出力優先度に基づいて、前記出力内容を前記第1の参加者に対して出力する出力部と、を有する。 The communication support system of the present invention is a communication support system that supports remote communication performed between a plurality of participants, and includes an input reception unit that receives input from the participants participating in the communication support system, and the above-mentioned. An intimacy estimation unit that estimates the intimacy between the first participant and the other participants based on the information about the first participant and the other participants among the plurality of participants. Output priority calculation that determines the priority of the output contents output from the other participants to the first participant based on the intimacy estimated by the intimacy estimation unit. It has a unit and an output unit that outputs the output content to the first participant based on the output priority calculated by the output priority calculation unit.
 本発明によれば、臨場感の向上と匿名性の確保とを両立させた遠隔コミュニケーションを実現できるコミュニケーション支援システムを提供できる。 According to the present invention, it is possible to provide a communication support system capable of realizing remote communication that achieves both an improvement in presence and anonymity.
本発明の第1の実施形態に係る、遠隔コミュニケーションシステムにおけるユーザ・機器・ネットワークの構成。Configuration of users / devices / networks in a remote communication system according to the first embodiment of the present invention. 図1で使用される一般情報機器の構成。Configuration of general information equipment used in FIG. サーバに保管されるユーザ情報。User information stored on the server. ユーザ間の関係性を確認する画面の例。An example of a screen to check the relationship between users. 送信対象ユーザへの情報を選択する画面の例。An example of a screen for selecting information for the user to be sent. ユーザ所属グループごとのフィードバック量を設定する画面の例。An example of a screen that sets the amount of feedback for each user group. 感情表現に関するフィードバック量を設定する画面の例。An example of a screen that sets the amount of feedback regarding emotional expression. 第1の実施形態に係る、コミュニケーション支援システムのモデル画面の例。An example of a model screen of a communication support system according to the first embodiment. 図8の変形例。A modified example of FIG. ユーザの顔画像の解析例。Analysis example of user's face image. 図10の解析の判定値を示したデータの例。An example of data showing the judgment value of the analysis of FIG. 第1の実施形態に係る、全体処理フローチャート。The whole processing flowchart which concerns on 1st Embodiment. 定期的にサーバに送信されるフィードバックデータ。Feedback data sent to the server on a regular basis. 第1の実施形態に係る、個人間距離の計算。Calculation of inter-individual distance according to the first embodiment. 第2の実施形態に係る、コミュニケーション支援システムのモデル画面の例。An example of a model screen of a communication support system according to the second embodiment. 第2の実施形態に係る、定期的にサーバに送信されるフィードバックデータ。Feedback data periodically transmitted to the server according to the second embodiment. 第2の実施形態に係る、個人間距離の計算。Calculation of inter-individual distance according to the second embodiment. 第3の実施形態に係る、コミュニケーション支援システムのモデルの構成例。A configuration example of a model of a communication support system according to a third embodiment. 第3の実施形態に係る、ユーザ視聴画面のモデル例。A model example of the user viewing screen according to the third embodiment. 第3の実施形態に係る、アバタロボットのモデル画面の例。An example of a model screen of an avatar robot according to a third embodiment. 第3の実施形態に係る、定期的にサーバに送信されるフィードバックデータ。Feedback data periodically transmitted to the server according to the third embodiment. 第3の実施形態に係る、個人間距離の計算。Calculation of inter-individual distance according to the third embodiment.
 以下、図面を参照して本発明の実施形態を説明する。以下の記載および図面は、本発明を説明するための例示であって、説明の明確化のため、適宜、省略および簡略化がなされている。本発明は、他の種々の形態でも実施する事が可能である。特に限定しない限り、各構成要素は単数でも複数でも構わない。 Hereinafter, embodiments of the present invention will be described with reference to the drawings. The following description and drawings are examples for explaining the present invention, and are appropriately omitted and simplified for the sake of clarification of the description. The present invention can also be implemented in various other forms. Unless otherwise specified, each component may be singular or plural.
 図面において示す各構成要素の位置、大きさ、形状、範囲などは、発明の理解を容易にするため、実際の位置、大きさ、形状、範囲などを表していない場合がある。このため、本発明は、必ずしも、図面に開示された位置、大きさ、形状、範囲などに限定されない。 The position, size, shape, range, etc. of each component shown in the drawings may not represent the actual position, size, shape, range, etc. in order to facilitate understanding of the invention. Therefore, the present invention is not necessarily limited to the position, size, shape, range and the like disclosed in the drawings.
(第1の実施形態およびコミュニケーション支援システムの構成)
 図1は、本発明の第1の実施形態に係る、遠隔コミュニケーションシステムにおけるユーザ・機器・ネットワークの構成である。
(Structure of the first embodiment and the communication support system)
FIG. 1 is a configuration of a user, a device, and a network in a remote communication system according to the first embodiment of the present invention.
 サーバ1は、一般通信網のネット回線を介して発表ユーザ3と聴講ユーザ6a~6fと接続され、これらのユーザ同士の遠隔コミュニケーションの内容を分析している。発表ユーザ3は、情報端末(PC)2を通じて、聴講ユーザ6a~6fに対して発表している。 The server 1 is connected to the presenting user 3 and the listening users 6a to 6f via the net line of the general communication network, and analyzes the contents of the remote communication between these users. The presentation user 3 makes a presentation to the listening users 6a to 6f through the information terminal (PC) 2.
 各聴講ユーザ6a~6fは、発表ユーザ3の発表を情報端末(PC)2や、情報端末(パッド)7を介して視聴している。聴講ユーザ6a~6fは、第1のグループ4と第2のグループ5とに分かれているが、このグループ分けは、例えば、企業ごとのグループ、組織内の部署ごとのグループ、年齢別のグループ等、遠隔コミュニケーションに参加するユーザの集団の関係性の近さなどによって自由に設定される。 Each of the listening users 6a to 6f is watching the presentation of the presentation user 3 via the information terminal (PC) 2 and the information terminal (pad) 7. The listening users 6a to 6f are divided into a first group 4 and a second group 5, and this grouping is, for example, a group for each company, a group for each department in the organization, a group for each age, and the like. , It is freely set according to the closeness of the relationship of the group of users who participate in remote communication.
 各グループ内では、グループ内だけに共有される会話があり、テキストメッセージなどで会話の具体的な内容や、発表ユーザ3の発表内容の感想、発表に対する感情表現の内容が共有される。逆に、それぞれのグループ外には具体的な会話内容は原則として伝達されることはなく、その代わり、第1のグループ4と第2のグループ5との間では発表ユーザ3の発表に対する各聴講ユーザ6a~6fの反応を表す顔文字アイコン(非言語反応)など、感情表現についての出力内容だけが共有される。 Within each group, there is a conversation that is shared only within the group, and the specific content of the conversation, the impression of the presentation content of the presentation user 3, and the content of emotional expression for the presentation are shared by text messages and the like. On the contrary, the concrete conversation content is not transmitted to the outside of each group in principle, and instead, each audit for the presentation of the presentation user 3 is performed between the first group 4 and the second group 5. Only the output contents of emotional expressions such as emoticon icons (non-verbal reactions) representing the reactions of users 6a to 6f are shared.
 こうしたグループ分けにより、グループごとの秘匿性と親近感を作り出すとともに、自グループ以外のグループあるいは聴講ユーザ6a~6fそれぞれがどのような雰囲気なのかを、共有できる。 By such grouping, it is possible to create confidentiality and familiarity for each group, and to share the atmosphere of each group other than the own group or the listening users 6a to 6f.
 図2は、図1で使用される一般情報機器の構成である。 FIG. 2 is a configuration of a general information device used in FIG.
 サーバ1は、CPU、プログラムデータが入る主メモリ、メモリカードなどの外部記憶(装置)によって構成されている。CPUには、コミュニケーション支援システムに参加する参加者からの入力を受け付ける入力受付部、ユーザ同士の親密度を推定する親密度推定部、ユーザ同士の親密度に基づいて出力優先度を算出する出力優先度算出部、ユーザ同士のコミュニケーションに関する指標を算出する指標算出部、出力優先度やコミュニケーションに関する指標に基づいて出力内容を決定し出力する出力部、が備えられている。詳細は後述する。 The server 1 is composed of a CPU, a main memory for storing program data, and an external storage (device) such as a memory card. The CPU has an input reception unit that accepts input from participants participating in the communication support system, an intimacy estimation unit that estimates the intimacy between users, and an output priority that calculates the output priority based on the intimacy between users. It is equipped with a degree calculation unit, an index calculation unit that calculates an index related to communication between users, and an output unit that determines and outputs output contents based on an output priority and an index related to communication. Details will be described later.
 発表ユーザ3または聴講ユーザ6a~6f(図1)は、USBなどの外部バスで一般通信網と接続されている、ディスプレイ、カメラ、マイク、入力機器(キーボードやマウス、タッチパネル)などの出力機器(情報端末2(PC)または情報端末7(パッド))を使用して、音声映像を視聴もしくは発信している。 The presenting user 3 or the listening users 6a to 6f (FIG. 1) are output devices (keyboard, mouse, touch panel) such as a display, a camera, a microphone, and an input device (keyboard, mouse, touch panel) connected to a general communication network by an external bus such as USB. The information terminal 2 (PC) or the information terminal 7 (pad) is used to view or transmit audio and video.
 図3は、サーバに保管されるユーザ情報である。図3(a)はユーザ情報のデータテーブル、図3(b)は、図3(a)の履歴に関するデータテーブルである。 FIG. 3 is user information stored in the server. FIG. 3A is a data table of user information, and FIG. 3B is a data table related to the history of FIG. 3A.
 サーバ1(図1)の内部では、図3(a)に示すように、遠隔コミュニケーションシステムを利用するユーザについてのプロフィール情報が管理されている。図3に示すこのユーザ情報は、ユーザAからの視点の個人間距離テーブルの例である。図3(a)のデータテーブルの項目には、所属グループ、あるユーザAと各ユーザとの関係性(dは識別番号であり数値計算には無関係)、コメント番号によるテキストコメントの履歴(詳細は図3(b))、ユーザAと他のユーザとの親密度係数が記載されている。この親密度係数は、ユーザ同士の個人間距離を示す値であり、後述する各ユーザの設定、入力内容、表情などにより、親密度が変化する。 Inside the server 1 (FIG. 1), as shown in FIG. 3 (a), profile information about the user who uses the remote communication system is managed. This user information shown in FIG. 3 is an example of an inter-individual distance table from the viewpoint of user A. The items in the data table of FIG. 3A include the group to which the user belongs, the relationship between a certain user A and each user (d is an identification number and has nothing to do with numerical calculation), and the history of text comments by comment number (for details, see FIG. 3 (b)) shows the intimacy coefficient between the user A and another user. This intimacy coefficient is a value indicating the distance between individuals between users, and the intimacy changes depending on the settings, input contents, facial expressions, etc. of each user, which will be described later.
 なお、図3(a)に示す親密度係数は、値が小さいほど、対象相手との親密度が高いことを表している。また、このユーザ情報は、図1のように発表者や聴講者関係なく、ユーザ全員に共通するものとして、サーバ1に保存されている。 The intimacy coefficient shown in FIG. 3A indicates that the smaller the value, the higher the intimacy with the target partner. Further, as shown in FIG. 1, this user information is stored in the server 1 as being common to all users regardless of the presenter or the audience.
 図3(b)のテキストコメントの履歴の内容から、ユーザ同士の親密度を判断できる。例えば、あるユーザ同士の履歴数(会話の回数)、テキストコメント内での相手へのメッセージの伝え方(特定のポジティブなワードの使用頻度などで判断)、が判断材料になる。それ以外にも、以下で説明する図4~図7の画面によりそれぞれ設定される情報に基づき、ユーザ同士の関係性や相手ユーザの感情を把握することで、ユーザ同士の親密度を判断できる。こうして判断されたユーザ同士の親密度に応じて設定される親密度係数は、サーバ1において各ユーザに対する出力内容の決定に用いられ、ユーザに出力される内容に影響する。 The intimacy between users can be judged from the contents of the history of text comments in FIG. 3 (b). For example, the number of histories between certain users (number of conversations) and how to convey a message to the other party in a text comment (determined by the frequency of use of a specific positive word) can be used as judgment materials. In addition to that, the intimacy between users can be determined by grasping the relationship between users and the emotions of the other user based on the information set by the screens of FIGS. 4 to 7 described below. The intimacy coefficient set according to the intimacy between the users determined in this way is used in the server 1 to determine the output content for each user, and affects the content output to the user.
 図4は、ユーザ間の関係性を管理する画面の例である。 FIG. 4 is an example of a screen for managing relationships between users.
 端末2(7)は、各ユーザについての情報を管理する画面を出力している。この端末2(7)のユーザは、各ユーザとの関係性を、区分(同僚、顧客、友人、知人等の区分)や親しさの度合いなどにより、出力画面で選択して設定および編集できる。 Terminal 2 (7) outputs a screen for managing information about each user. The user of the terminal 2 (7) can select, set, and edit the relationship with each user on the output screen according to the classification (classification of colleagues, customers, friends, acquaintances, etc.) and the degree of familiarity.
 各ユーザに設定できる親しさの値は、親密度係数(図3(a))を算出する要素になる。図4に示す親しさの値は、大きいとその分親密度が高いことを表している。なお、親しい場合でなくても、相手が重要な人物(VIPなど)であれば、親しさの値を高い値に設定することで、親密度係数(重要度係数)に影響を及ぼすことができる。このように対象ユーザとの関係性を設定することで、親密度推定部によって個人間距離(=親密度)が推定され、一方のユーザの入力情報に対して他方のユーザに出力される内容が決まる。 The familiarity value that can be set for each user is an element for calculating the intimacy coefficient (FIG. 3 (a)). The value of familiarity shown in FIG. 4 indicates that the larger the value, the higher the intimacy. Even if the person is not close, if the other person is an important person (VIP, etc.), setting the familiarity value to a high value can affect the intimacy coefficient (importance coefficient). .. By setting the relationship with the target user in this way, the distance between individuals (= intimacy) is estimated by the intimacy estimation unit, and the content output to the other user for the input information of one user is It will be decided.
 図5は、送信対象ユーザへの情報を選択する画面の例である。 FIG. 5 is an example of a screen for selecting information for the transmission target user.
 端末2(7)、送信情報を設定する画面を出力している。例えば、図5では「同僚」に対しては、音声、テキスト、匿名キーワード(自分の名前を対象ユーザに表示せずに使用された特定のキーワードが共有される)、表情情報、感情分類データ(自分の表情に関するアイコン)、匿名感情(自分の名前を対象ユーザに表示せずに感情だけが共有される)を送信できるように設定されており、顔映像については共有されない設定である。顔映像などのきわめてプライベートな情報については、友人の項目でのみ設定されているように、親しい間柄でのみ共有または表示するように選択することができる。この送信情報の設定によってユーザ同士の関係性が決まり、親密度推定部においての計算でユーザ同士の関係性に応じた値が親密度に加算される。 Terminal 2 (7) outputs a screen for setting transmission information. For example, in FIG. 5, for "colleagues", voice, text, anonymous keywords (specific keywords used without displaying their name to the target user are shared), facial expression information, emotion classification data ( It is set to be able to send (icon related to one's facial expression) and anonymous emotions (only emotions are shared without displaying one's name to the target user), and is not shared for facial expressions. For extremely private information, such as facial footage, you can choose to share or display only with close relationships, as set only in the Friends section. The relationship between users is determined by the setting of this transmission information, and a value according to the relationship between users is added to the intimacy in the calculation in the intimacy estimation unit.
 なお、どの対象にもチェックがない状態であれば、サーバ1に各情報が送られないため、ユーザ情報の完全な秘匿性が確保される。 If there is no check in any of the targets, each information is not sent to the server 1, so that the complete confidentiality of the user information is ensured.
 図6は、ユーザ所属グループごとのフィードバック量を設定する画面の例である。 FIG. 6 is an example of a screen for setting the feedback amount for each user group.
 端末2(7)は、ユーザが所属するグループに対して、重要度の高い意見や反応を取り入れ、重要でない意見や反応をなるべく少なくするために、フィードバック重みづけの設定をする画面を出力している。 The terminal 2 (7) outputs a screen for setting feedback weighting in order to incorporate highly important opinions and reactions to the group to which the user belongs and to reduce unimportant opinions and reactions as much as possible. There is.
 この表示重みづけの値は、どのグループの反応をどの程度表示するかを決める入力値である。そのため、この値が大きく設定されたグループは、自分の情報端末においての表示が大きくなる。例えば、図6の設定画面で、顧客で金融のグループにいる人の表示重みづけは0.9(最大値が1)であるため、この端末のユーザに対してコメントや反応が大きく表示され、端末の画面上での存在が大きくなる。しかし、自社の部下のグループは、表示重みづけが0.3に設定されているため、この端末でのコメントや反応は小さく表示され、画面上での存在が小さくなる。このように、表示重みづけによってユーザ同士の関係性が決まり、親密度推定部ではこの関係性に応じた値が親密度に加算される。 The value of this display weighting is an input value that determines how much the reaction of which group is displayed. Therefore, a group in which this value is set to a large value will have a large display on its own information terminal. For example, on the setting screen of FIG. 6, since the display weight of a customer who is in a financial group is 0.9 (maximum value is 1), comments and reactions are greatly displayed to the user of this terminal. The presence on the screen of the terminal becomes large. However, since the display weighting of the group of subordinates of the company is set to 0.3, the comments and reactions on this terminal are displayed small, and the presence on the screen becomes small. In this way, the relationship between users is determined by the display weighting, and the intimacy estimation unit adds a value corresponding to this relationship to the intimacy.
 図7は、感情表現に関するフィードバック量を設定する画面の例である。 FIG. 7 is an example of a screen for setting the amount of feedback regarding emotional expression.
 端末2(7)は、相手ユーザの感情を集計の設定を行う画面を出力している。これは、どのような反応を重視するか入力設定する画面であり、例えば、図7のように、ポジティブな感情を集計したいときには、感情グループでポジティブの項目を選択することで、ポジティブな感情に関する詳細項目として、表情、音声、言語、入力のそれぞれごとに、表示の重みづけ値を設定することができる。この表示重みづけ値は、大きければ大きいほど親密度の算出結果に大きく影響する。 Terminal 2 (7) outputs a screen for setting the aggregation of the emotions of the other user. This is a screen for inputting and setting what kind of reaction is important. For example, as shown in FIG. 7, when you want to aggregate positive emotions, you can select a positive item in the emotion group to relate to positive emotions. As detailed items, display weighting values can be set for each of facial expressions, voices, languages, and inputs. The larger the display weighting value, the greater the influence on the calculation result of the intimacy.
 例えば、データ[入力],分類[ボタン:いいね]であれば、1.1という値が設定されている。この項目は、他の項目よりも大きいため、「いいねボタン」が「ポジティブ」の集計結果に大きく影響する。逆に、データ[音声],分類[声質:上機嫌]であれば、0.2という値に設定されているため、「ポジティブ」の集計結果への影響が少ない。このように、個々のグループやユーザごとに表示重みづけ値のカスタマイズができ、各ユーザの顔画像から判断した表情や、各ユーザの端末におけるUIからの入力により、各ユーザの感情をパラメータ化することができる。なお、感情のパラメータ化は、指標算出部がコミュニケーションに関する指標を算出することによって行われる。 For example, in the case of data [input] and classification [button: like], a value of 1.1 is set. Since this item is larger than other items, the "Like button" greatly affects the aggregated results of "Positive". On the contrary, in the case of data [voice] and classification [voice quality: good mood], since the value is set to 0.2, the influence on the total result of "positive" is small. In this way, the display weighting value can be customized for each group or user, and each user's emotions are parameterized by the facial expressions judged from each user's facial image and the input from the UI on each user's terminal. be able to. The emotional parameterization is performed by the index calculation unit calculating an index related to communication.
 図4の画面で設定されたユーザごとの関係性を表す親しさの値や、図5の画面で設定された送信情報の種類や、図6、図7の画面でそれぞれ設定された表示重みづけの値は、サーバ1(図2)において、親密度推定部が行う各ユーザの親密度の計算に用いられる。すなわち、サーバ1において親密度推定部は、これらの設定情報を用いて、ユーザ同士の関係性に応じた親密度を推定する。 The familiarity value set on the screen of FIG. 4 indicating the relationship for each user, the type of transmission information set on the screen of FIG. 5, and the display weighting set on the screens of FIGS. 6 and 7, respectively. The value of is used in the calculation of the intimacy of each user performed by the intimacy estimation unit in the server 1 (FIG. 2). That is, in the server 1, the intimacy estimation unit estimates the intimacy according to the relationship between the users by using these setting information.
 図8は、第1の実施形態に係る、コミュニケーション支援システムのモデル画面の例である。 FIG. 8 is an example of a model screen of the communication support system according to the first embodiment.
 端末2(7)には、プレゼンテーション画面が出力表示されている。また、プレゼンテーション画面の下側には、フィードバック時間遷移グラフ12と参加している他ユーザの映像13が映し出されている。 The presentation screen is output and displayed on the terminal 2 (7). Further, on the lower side of the presentation screen, the feedback time transition graph 12 and the video 13 of another user participating are projected.
 フィードバック時間遷移グラフ12は、プレゼンに対する各ユーザの反応(感情)がパラメータ化されて表されており、時間経過とともにグラフが左側に流れている。このグラフでは、数値が大きくなる(プレゼンに対して良い反応が多い)と、グラフが上昇する。このフィードバック時間遷移グラフ12による数値化されたフィードバックにより、現在の聴講者の盛り上がり具合を発表者は視覚で理解でき、これによりリアルな反応を感じながら会議を進めることができる。より具体的には、図7で説明した感情の表示重みづけの値を基に、指標算出部が各ユーザの反応に応じた指標を算出し、この指標の値をパラメータとして、出力部がフィードバック時間遷移グラフ12の表示内容を決定することによって、各ユーザの反応がパラメータ化されてフィードバック時間遷移グラフ12に反映される。 The feedback time transition graph 12 shows the reaction (emotion) of each user to the presentation as parameters, and the graph flows to the left with the passage of time. In this graph, the larger the number (there are many good reactions to the presentation), the higher the graph. The quantified feedback from the feedback time transition graph 12 allows the presenter to visually understand the current excitement of the audience, which allows the presenter to proceed with the conference while feeling a realistic reaction. More specifically, the index calculation unit calculates an index according to the reaction of each user based on the value of the emotion display weighting described with reference to FIG. 7, and the output unit feeds back using the value of this index as a parameter. By determining the display content of the time transition graph 12, the reaction of each user is parameterized and reflected in the feedback time transition graph 12.
 他ユーザの顔の映像13は、カメラで撮影した顔の実映像または実画像、表情再現モデル(実在の人物の表情の動きを基に表情を再現するCGやバーチャルモデル)、表情再現アイコン(実在の人物の表情の動きを基にそれに近い表情のアイコンが表記される)のいずれかが表示される。いずれの表示とするかは、サーバ1により、各ユーザ同士の親密度に基づいて出力優先度算出部が算出する出力優先度を基に、ユーザごとに決定される。例えば、親密度が高くて出力優先度が高いユーザほど実映像や実画像に近いものを表示し、出力優先度が低くなるほど抽象度が高くなるように表示を変化させることで、親近感と匿名性を両立させた表示とすることができる。 The facial image 13 of another user is a real image or image of a face taken by a camera, a facial expression reproduction model (CG or virtual model that reproduces a facial expression based on the movement of a real person's facial expression), and a facial expression reproduction icon (existing). Based on the movement of the person's facial expression, an icon with a similar facial expression is displayed). Which display is to be displayed is determined by the server 1 for each user based on the output priority calculated by the output priority calculation unit based on the intimacy between the users. For example, users with higher intimacy and higher output priority display images that are closer to real images and images, and by changing the display so that the lower the output priority, the higher the level of abstraction, intimacy and anonymity. It is possible to display both sexes.
 プレゼンテーション画面の右側には、会話内のトレンド単語を集計して表記するWord cloud18や、プレゼンテーション中に共有されるチャットを表記するテキスト欄19が表示されている。Word cloud18は、会議に参加しているユーザのコメントを集計することで、トレンドとなっている単語を大きく表示することができ、プレゼンを視聴しているユーザが、全体としてどのようなキーワードを使っているかを視覚化できている。テキスト欄19には参加者であるユーザのコメントが表示されるが、前述した送信情報の設定(図5)によって、表示されないユーザもいる。 On the right side of the presentation screen, Word cloud 18 that aggregates and describes trend words in conversation and a text field 19 that expresses chat shared during the presentation are displayed. Word cloud 18 can display the trending words in a large size by aggregating the comments of the users who are participating in the conference, and what kind of keywords are used by the users who are watching the presentation as a whole. You can visualize what you are doing. Although the comments of the users who are participants are displayed in the text field 19, some users may not be displayed due to the transmission information setting (FIG. 5) described above.
 Word cloud18の下側には、自分の表情を表示する映像16と送信情報を表記する送信データ17が表示されている。さらに、自分の音声や表情のON/OFFを設定する音声ON/OFFボタン14、映像ON/OFFボタン15が備えられている。 Below the Word cloud 18, a video 16 displaying one's facial expression and a transmission data 17 indicating transmission information are displayed. Further, a voice ON / OFF button 14 and a video ON / OFF button 15 for setting ON / OFF of one's own voice and facial expression are provided.
 図9は、図8の変形例である。 FIG. 9 is a modified example of FIG.
 図9は、図8のWord cloud18や、テキスト欄19が、フィードバック2軸グラフ20に置きかわっている。フィードバック2軸グラフ20の中には、2軸グラフに設定された定義に基づいて、グループ重要度を表すプロット21が表示されている。 In FIG. 9, the Word cloud 18 and the text field 19 in FIG. 8 are replaced with the feedback 2-axis graph 20. In the feedback 2-axis graph 20, a plot 21 representing the group importance is displayed based on the definition set in the 2-axis graph.
 例えば図9に示すように、「集中度」(どれだけの聴講ユーザがよそ見せずに話を聞いているか、話者にたいしてのうなずきの回数が多いかどうか)と「ポジティブ度」(話者のプレゼン内容に対しての好感のある特定のキーワードの入力、聴講ユーザの表情から読み取れる笑顔の時間など)の2軸グラフがある。このグラフは、指標算出部により算出されたユーザ同士のコミュニケーションに関する指標をユーザごとに集計した結果を示しており、出力優先度算出部によってユーザ同士の親密度に基づき算出される出力優先度を基に、サーバ1においてその表示内容が決定される。これにより、発表ユーザに対して、タイムリーにプレゼンを視聴するユーザの傾聴状況、あるいは心理状況を伝えることができる。この2軸の項目は自由に設定することができ、例えば「ネガティブ度」「チャット数(時間当たり)」などの設定でも、同様に発表ユーザに会議の臨場感を伝えることができる。 For example, as shown in FIG. 9, "concentration" (how many listening users are listening without showing away, whether the number of nods to the speaker is high) and "positiveness" (speaker's). There is a two-axis graph (such as inputting a specific keyword that has a favorable impression on the content of the presentation, the time of a smile that can be read from the facial expression of the listening user, etc.). This graph shows the result of totaling the indexes related to communication between users calculated by the index calculation unit for each user, and is based on the output priority calculated by the output priority calculation unit based on the intimacy between users. The display content is determined on the server 1. As a result, it is possible to inform the presenting user of the listening status or the psychological status of the user who watches the presentation in a timely manner. These two-axis items can be freely set. For example, even with settings such as "negative degree" and "number of chats (per hour)", it is possible to convey the presence of the conference to the presenting user in the same manner.
 また、グループ重要度を表すプロット21に色の設定をすることで、3軸のグラフにすることもできる。例えば、「ポジティブ度」「集中度」以外に「チャット数」を加えた場合、「チャット数」の多さに応じて、色を明るい色に変えたりすることで、3つの要素を視覚表現できる。このように、視覚化されたフィードバックにより、全体分布や重要分布がわかりやすくなる。 It is also possible to create a 3-axis graph by setting a color for the plot 21 that represents the group importance. For example, if you add "number of chats" in addition to "degree of positiveness" and "degree of concentration", you can visually express three elements by changing the color to a brighter color according to the number of "number of chats". .. In this way, the visualized feedback makes it easier to understand the overall distribution and important distribution.
 さらに、このフィードバックグラフのプロットに、知り合いや重要者のデータのアイコンをプロットすることで、さらに理解しやすくすることができる。また、どれかの項目が大きくなったら歓声が聞こえるような設定もできる。 Furthermore, by plotting the data icons of acquaintances and important people on the plot of this feedback graph, it can be made easier to understand. You can also set it so that you can hear cheers when any of the items get bigger.
 なお、図8および9のモデル画面例はPCの端末を想定して描かれているが、パッドによる端末でもよい。 Although the model screen examples in FIGS. 8 and 9 are drawn assuming a PC terminal, a pad terminal may also be used.
 図10は、ユーザの顔画像の解析例である。また、図11は、図10の解析の判定値を示したデータの例である。なお、図11(a)は「表情情報」として送信対象となる特徴点データの例であり、図11(b)は、「感情分類データ」として送信対象となるデータの例である。 FIG. 10 is an analysis example of the user's face image. Further, FIG. 11 is an example of data showing the determination value of the analysis of FIG. Note that FIG. 11A is an example of feature point data to be transmitted as “facial expression information”, and FIG. 11B is an example of data to be transmitted as “emotion classification data”.
 カメラ撮影画像22により、サーバ1の指標算出部にてユーザの表情を分析することで、その表情に対応するユーザの感情を判断し、コミュニケーションに関する指標を算出することができる。こうして算出された指標を基に、出力部で表情再現モデルまたは表情再現アイコンを生成する。分析方法は、特徴点抽出画像23に示すように、表情の特徴となるポイント(特徴点)を設定されている数だけx座標とy座標で数値化して抽出し、データテーブルを作成する。これにより、図11(a)に示すように、特徴点抽出画像23における特徴点ごとの座標値が抽出される。そして、各特徴点の座標値を顔の特定部位にそれぞれ対応付けたモデル画像を生成することにより、図10の表情再現モデル24が完成する。こうして完成した表情再現モデル24からユーザの表情を判別することで、ユーザの感情を判断することができる。このとき、ユーザの感情に応じて表情再現モデル24に変化を加えることで、ユーザの感情をより一層分かりやすく表現した表情再現モデル24を生成してもよい。なお、図11(a)では4つの特徴点だけで表記されているが、実際には30以上の特徴点によって判断される。 By analyzing the facial expression of the user in the index calculation unit of the server 1 using the camera captured image 22, it is possible to determine the emotion of the user corresponding to the facial expression and calculate the index related to communication. Based on the index calculated in this way, the output unit generates a facial expression reproduction model or a facial expression reproduction icon. As shown in the feature point extraction image 23, the analysis method creates a data table by digitizing and extracting a set number of points (feature points) that are characteristic of facial expressions in x-coordinates and y-coordinates. As a result, as shown in FIG. 11A, the coordinate values for each feature point in the feature point extraction image 23 are extracted. Then, the facial expression reproduction model 24 of FIG. 10 is completed by generating a model image in which the coordinate values of the feature points are associated with the specific parts of the face. By discriminating the user's facial expression from the facial expression reproduction model 24 completed in this way, the user's emotion can be determined. At this time, the facial expression reproduction model 24 may be generated by changing the facial expression reproduction model 24 according to the user's emotions to further understand the user's emotions. In FIG. 11A, only four feature points are shown, but in reality, it is determined by 30 or more feature points.
 また、指標算出部は、機械学習判別機を利用して特徴点抽出画像23からコミュニケーションに関する指標を算出し、その算出結果に基づいて、表情アイコン25を決定できる。これは図11(b)に示すように、笑顔や頷き具合などの表情項目ごとに、コミュニケーションに関する指標としての判定値を算出することにより、表情アイコン25が決まる。機械学習判別機は、例えばSVM(Support vector machine)や、NN(Neural Network)などである。 Further, the index calculation unit can calculate an index related to communication from the feature point extraction image 23 using a machine learning discriminator, and can determine the facial expression icon 25 based on the calculation result. As shown in FIG. 11B, the facial expression icon 25 is determined by calculating a determination value as an index related to communication for each facial expression item such as a smile or a nod. The machine learning discriminator is, for example, SVM (Support vector machine), NN (Neural Network), or the like.
 なお、表情アイコン25を決定する際に算出した表情項目ごとの判定値(指標)は、親密度推定部が行う各ユーザの親密度の計算において利用してもよい。例えば、図7の画面で設定された詳細項目ごとの表示の重み付け値のうち、表情に関する重み付け値については、この判定値に基づいて親密度の計算における採用の可否を決定することができる。 The determination value (index) for each facial expression item calculated when the facial expression icon 25 is determined may be used in the calculation of the intimacy of each user performed by the intimacy estimation unit. For example, among the weighted values of the display for each detailed item set on the screen of FIG. 7, the weighted value related to the facial expression can be determined whether or not to be adopted in the calculation of intimacy based on this determination value.
 上記のようにして作成された表情再現モデル24や表情アイコン25は、ユーザ同士のコミュニケーションに関する指標に基づいて各ユーザの表情を再現した画像である。これらはサーバ1から各ユーザの端末へと送信され、例えば図8、9に示したモデル画面において映像13として表示されることで、各ユーザに対する出力が行われる。なお、図10は、表情の分析による出力だが、同様に音声からの入力を基にして笑い声の認識、声の声量などで、音を機械学習の分類機などにかけて感情パラメータを生成することでフィードバックする機構も備えている。 The facial expression reproduction model 24 and the facial expression icon 25 created as described above are images that reproduce the facial expressions of each user based on the index related to communication between users. These are transmitted from the server 1 to the terminal of each user, and are displayed as a video 13 on the model screen shown in FIGS. 8 and 9, for example, to output to each user. Note that FIG. 10 shows the output based on facial expression analysis. Similarly, based on the input from the voice, the sound is fed back by applying the sound to a machine learning classifier or the like based on the recognition of the laughing voice and the volume of the voice. It also has a mechanism to do it.
 また、認識機構において参加ユーザの国籍ごとに変換ルールを設定することで、文化差異を吸収することもできる。例えば、国ごとに異なるジェスチャや笑顔の閾値を設定し、感情をパラメータに反映することで差異をなくすことができる。 In addition, cultural differences can be absorbed by setting conversion rules for each nationality of participating users in the recognition mechanism. For example, it is possible to eliminate the difference by setting different gesture and smile thresholds for each country and reflecting emotions in the parameters.
 図12は、第1の実施形態に係る、全体処理フローチャートである。 FIG. 12 is an overall processing flowchart according to the first embodiment.
 まず、端末上での個人クライアント動作についてのフローを説明する。個人クライアント動作は、PCやパッドの端末により操作された内容である。ステップS1で端末の情報設定をする。ステップS2で端末にログインをする。ステップS2でログインした情報は、サーバにも共有される(ステップS104で後述)。 First, the flow of personal client operation on the terminal will be explained. The personal client operation is the content operated by the terminal of the PC or the pad. Set the terminal information in step S1. Log in to the terminal in step S2. The information logged in in step S2 is also shared with the server (described later in step S104).
 ステップS3~ステップS12は、ある一定時間ごとの繰り返すフロー(ループ処理)であり、ステップS3でループ処理を開始する。ステップS4で、端末を使用しているユーザの当該時刻におけるマイク録音操作によって得られる音声情報を取得する。ステップS5で、マイクの録音情報をテキストに変換し、録音情報とテキストから感情情報を推定することで、端末を使用しているユーザの音声情報を処理している。ステップS6で、端末を使用しているユーザが当該時刻においてカメラを録画操作することで得られる映像情報を取得する。ステップS7で、ステップS6で取得したカメラの画像情報から、端末を使用しているユーザの映像情報で得られる顔の特徴を認識し、その特徴の度合いによって感情に関する情報を推定することで処理する。ステップS8で、ステップS4~ステップS7で取得・処理された情報を基に、サーバに送信する入力情報を取得する。 Steps S3 to S12 are flows (loop processing) that are repeated at regular time intervals, and the loop processing is started in step S3. In step S4, the voice information obtained by the microphone recording operation at the time of the user using the terminal is acquired. In step S5, the voice information of the user using the terminal is processed by converting the recorded information of the microphone into text and estimating the emotional information from the recorded information and the text. In step S6, the user using the terminal acquires the video information obtained by recording the camera at the time. In step S7, the facial features obtained from the video information of the user using the terminal are recognized from the image information of the camera acquired in step S6, and the information related to emotions is estimated according to the degree of the features. .. In step S8, the input information to be transmitted to the server is acquired based on the information acquired / processed in steps S4 to S7.
 ステップS9でサーバに入力情報を送信する。送信される情報は、サーバの入力受付部で入力が受け付けられる。この送信は音声・映像情報を読み取るタイミングで、バッファに送信されているデータを読み込み、処理対象としている非同期の通信である。ステップS10でサーバから配信された情報を受信する。このステップS9の送信またはステップS10の受信は、ステップS3~ステップS12のループ処理のたびに定期的に送信・受信される。ステップS11で、サーバから受信した情報を基に、端末で画像(顔映像、表情再現モデル、表情アイコン)を出力する。ステップS13でログアウトによって、個人クライアント動作のフローは終了する。 Send the input information to the server in step S9. The information to be transmitted is input by the input reception unit of the server. This transmission is an asynchronous communication in which the data transmitted to the buffer is read at the timing of reading the audio / video information and is processed. Receive the information delivered from the server in step S10. The transmission of step S9 or the reception of step S10 is periodically transmitted / received each time the loop processing of steps S3 to S12 is performed. In step S11, the terminal outputs an image (face image, facial expression reproduction model, facial expression icon) based on the information received from the server. By logging out in step S13, the flow of individual client operation ends.
 続いて、サーバ動作についてのフローを説明する。ステップS101でサーバ1を起動する。ステップS102で個人情報データベース(DB)の読み取りを行う。 Next, the flow of server operation will be explained. Server 1 is started in step S101. In step S102, the personal information database (DB) is read.
 ステップS103~ステップS112は、ある一定時間ごとの繰り返すフロー(ループ処理)であり、ステップS103でループ処理を開始する。ステップS104で、個人クライアント動作において、ステップS2のログインの情報を受けて、新規ログイン受付をする。ステップS105で、ログイン中のユーザのうち、あるユーザAを対象にループ処理を開始する。 Steps S103 to S112 are flows (loop processing) that are repeated at regular time intervals, and the loop processing is started in step S103. In step S104, in the operation of the individual client, the login information of step S2 is received and a new login is accepted. In step S105, the loop process is started for a certain user A among the logged-in users.
 ステップS106で、ステップS9において端末から定期送信される情報を受信する。具体的には、入力受付部が端末の入力を受け付けている。ステップS107で、ユーザAとその他の複数のユーザとの個人間距離を確認して出力内容を決定し、ユーザAの端末へ送信するループ処理を開始する。ステップS108でユーザAとある他のユーザとの個人間距離を計算・確認する。具体的には、ステップS107とステップS108のフローで、指標算出部による指標の算出を行い、親密度推定部による親密度の算出を行い、算出した親密度に基づいて出力優先度算出部が出力優先度を算出し、算出した出力優先度に基づき、出力部が端末での出力内容を決定する。ここで決定される出力内容には、図8、9の映像13として表示される各ユーザの表情再現モデルや表示再現アイコン、Word cloud18やテキスト欄19における表示内容などが含まれる。ステップS109では、ステップS108で決定した出力内容の情報をユーザAの端末に送信する。この送信は、ステップS9と同様の非同期通信である。 In step S106, the information periodically transmitted from the terminal in step S9 is received. Specifically, the input receiving unit accepts the input of the terminal. In step S107, the inter-individual distance between the user A and a plurality of other users is confirmed, the output content is determined, and the loop process of transmitting to the terminal of the user A is started. In step S108, the distance between the individual user A and another user is calculated and confirmed. Specifically, in the flow of step S107 and step S108, the index calculation unit calculates the index, the intimacy estimation unit calculates the intimacy, and the output priority calculation unit outputs based on the calculated intimacy. The priority is calculated, and the output unit determines the output content at the terminal based on the calculated output priority. The output content determined here includes the facial expression reproduction model and display reproduction icon of each user displayed as the video 13 of FIGS. 8 and 9, the display content in Word cloud 18 and the text field 19. In step S109, the information of the output content determined in step S108 is transmitted to the terminal of the user A. This transmission is asynchronous communication similar to step S9.
 ステップS110でユーザAとある他のユーザとの個人間距離を確認して出力内容を決定し、ユーザAの端末へ送信するループ処理を終了する。このステップS107~S110のループ処理がユーザAを除いた各ユーザについてそれぞれ実行されることにより、ユーザAと他の各ユーザとの個人間距離(親密度)に応じた出力優先度に従って、各ユーザからユーザAに対して出力する出力内容が決定され、その出力内容の情報がサーバ1からユーザAの端末へと送信される。 In step S110, the distance between the individual user A and another user is confirmed, the output content is determined, and the loop process of transmitting to the terminal of the user A is terminated. By executing the loop processing of steps S107 to S110 for each user excluding the user A, each user follows the output priority according to the personal distance (intimacy) between the user A and each other user. The output content to be output to the user A is determined, and the information of the output content is transmitted from the server 1 to the terminal of the user A.
 ステップS111でユーザAを対象とするループ処理を終了する。このステップS105~S111のループ処理が各ユーザについてそれぞれ実行されることにより、各ユーザの端末における出力内容が決定され、その出力内容の情報がサーバ1から各ユーザの端末へと送信される。ステップS112でステップS103~ステップS112のループ処理を終了する。 In step S111, the loop process targeting user A is terminated. By executing the loop processing of steps S105 to S111 for each user, the output content in the terminal of each user is determined, and the information of the output content is transmitted from the server 1 to the terminal of each user. In step S112, the loop processing of steps S103 to S112 is terminated.
 図13は、第1の実施形態に係る、定期的にサーバに送信されるフィードバックデータの例である。 FIG. 13 is an example of feedback data periodically transmitted to the server according to the first embodiment.
 図13に示すフィードバックデータは、図12のステップS9で送信される情報である。それぞれの項目について説明する。音声情報開示フラグの欄には、[10010…]というように会議に参加しているユーザA以外の12人分のユーザに対して、ユーザAの音声情報を開示するかどうかのフラグが示されている。これにより、だれに対して自分に関する情報を公開してよいか判別している。対応フラグが0であるグループには開示がされない。 The feedback data shown in FIG. 13 is the information transmitted in step S9 of FIG. Each item will be explained. In the voice information disclosure flag column, a flag as to whether or not to disclose the voice information of the user A is shown to 12 users other than the user A who are participating in the conference, such as [10010 ...]. ing. In this way, it is determined to whom information about oneself can be disclosed. It is not disclosed to the group whose corresponding flag is 0.
 音声情報データの欄には、ファイルの種類が記録される。テキスト情報開示フラグの欄には、音声情報開示フラグの欄と同様に、ユーザA以外の12人分のユーザに対して、ユーザAが音声情報を開示するかどうかのフラグが示されている。テキスト情報データの欄は、ユーザAが入力したテキスト内容が記録されている。顔画像開示フラグの欄は、音声情報開示フラグの欄、テキスト情報開示フラグの欄と同様である。顔画像データの欄は、顔画像データが記録されている。表情情報開示フラグの欄は、顔画像開示フラグの欄、音声情報開示フラグの欄、テキスト情報開示フラグの欄と同様である。 The file type is recorded in the voice information data column. Similar to the voice information disclosure flag field, the text information disclosure flag column shows a flag as to whether or not the user A discloses voice information to 12 users other than the user A. In the text information data field, the text content input by the user A is recorded. The face image disclosure flag column is the same as the voice information disclosure flag column and the text information disclosure flag column. Face image data is recorded in the face image data column. The facial expression information disclosure flag column is the same as the facial image disclosure flag column, the voice information disclosure flag column, and the text information disclosure flag column.
 表情情報データの欄は、座標値リストが記録されている。これは、前述した表情再現モデルの構築(図10参照)に用いられる値である。感情情報開示フラグの欄は、表情情報開示フラグの欄、顔画像開示フラグの欄、音声情報開示フラグの欄、テキスト情報開示フラグの欄と同様である。感情情報データの欄は、顔映像から分析した表情アイコン(図10参照)についての判定値が記録されている。 A coordinate value list is recorded in the facial expression information data column. This is a value used for constructing the above-mentioned facial expression reproduction model (see FIG. 10). The emotional information disclosure flag column is the same as the facial expression information disclosure flag column, the face image disclosure flag column, the voice information disclosure flag column, and the text information disclosure flag column. In the emotion information data column, the determination value for the facial expression icon (see FIG. 10) analyzed from the facial image is recorded.
 上記のフィードバックデータがサーバに送られ、親密度推定部によって各ユーザとユーザAとの個人間距離に関する情報である親密度係数が決定される。また、それぞれのユーザの上記の情報は、指標算出部において、感情集計設定画面(図7)で設定された表示重みづけ値で合計されて、各ユーザの目的別感情集計値が算出される。この目的別感情集計値は、サーバ1から各ユーザの端末へと送信され、各端末において図9のフィードバック2軸グラフ20のような画面上のグラフ表示に用いられ、例えば目的設定として、ポジティブ度、集中度としてプロット集団で表現される。また、受信表示側ユーザとの相関を計算して、個人間距離における共感値の計算に用いられる(図14で後述)。 The above feedback data is sent to the server, and the intimacy estimation unit determines the intimacy coefficient, which is information regarding the distance between each user and the user A. In addition, the above information of each user is totaled by the display weighted value set on the emotion aggregation setting screen (FIG. 7) in the index calculation unit, and the emotion aggregation value for each user is calculated. This purpose-specific emotion aggregate value is transmitted from the server 1 to each user's terminal, and is used for graph display on the screen as shown in the feedback 2-axis graph 20 of FIG. 9 in each terminal. , Expressed as a plot group as the degree of concentration. Further, the correlation with the reception display side user is calculated and used for the calculation of the sympathy value in the inter-individual distance (described later in FIG. 14).
 図14は、第1の実施形態に係る、個人間距離の計算の処理を示すフローチャートである。以下、フローチャートを説明する。 FIG. 14 is a flowchart showing the process of calculating the inter-individual distance according to the first embodiment. The flowchart will be described below.
 図14で作成される個人間距離テーブルは、図12のステップS108での個人間距離の計算・確認で使用され、図12のフローとは別に独立して作成される。まず、ステップS20で、ユーザA(画面閲覧者)を選択する。ステップS21で、会議に参加している各視聴者(ユーザX)との個人間距離に関する決定を行うループ処理を開始する。ステップS22では、対象者情報があるどうかの確認をする。この対象者情報がユーザAの情報に無ければ関係性がないと判定される。ステップS23では、対象者の分類グループのデータを取得する。 The inter-individual distance table created in FIG. 14 is used in the calculation / confirmation of the inter-individual distance in step S108 of FIG. 12, and is created independently of the flow of FIG. First, in step S20, user A (screen viewer) is selected. In step S21, a loop process for determining the distance between individuals with each viewer (user X) participating in the conference is started. In step S22, it is confirmed whether or not there is target person information. If this target person information does not exist in the information of user A, it is determined that there is no relationship. In step S23, the data of the classification group of the target person is acquired.
 ステップS24では、ステップS23で取得したグループごとに重要度情報を入力する。ここでいう重要度情報とは、フィードバックの重みづけの設定での表示重みづけ(図6)のことである。ステップS25では、端末の管理画面からそれぞれのユーザに対して予め設定された「親しさ」の数値を入力する(図4)。ステップS26では、ユーザAがそれぞれのユーザと会話した履歴の回数から、会話での親密さを算出する。ステップS24からステップS26のフローで入力された数値および算出された値は、親密度推定部が個人間距離(親密度)を決める計算で使用される。 In step S24, the importance information is input for each group acquired in step S23. The importance information referred to here is the display weighting (FIG. 6) in the feedback weighting setting. In step S25, a numerical value of "friendliness" preset for each user is input from the management screen of the terminal (FIG. 4). In step S26, the intimacy in the conversation is calculated from the number of times the user A has talked with each user. The numerical value and the calculated value input in the flow from step S24 to step S26 are used in the calculation in which the intimacy estimation unit determines the inter-individual distance (intimacy).
 ステップS27で、ユーザXに関するユーザAの感情データとの相関を計算して、ユーザAとユーザXの共感値を算出する。この共感値の算出には、図13のフィードバックデータも用いられる。正の相関がある一定の閾値より高い場合には、共感値が個人間距離の計算に加算される。 In step S27, the correlation with the emotion data of the user A regarding the user X is calculated, and the sympathy value between the user A and the user X is calculated. The feedback data of FIG. 13 is also used to calculate this sympathy value. If the positive correlation is higher than a certain threshold, the empathy value is added to the calculation of the inter-individual distance.
 ステップS28で、出力優先度算出部により、ステップS22~ステップS27のフローに基づいてユーザAとユーザXとの個人間距離を決定する。ステップS29でステップS21~ステップS29のループ処理を終了する。このステップS21~S29のループ処理がユーザA以外の各ユーザについてそれぞれ実行されることにより、ステップS30でユーザAの個人間距離についてのデータテーブルが完成する。この個人間距離データテーブルは、あるユーザAから各ユーザに対して作成され、集計されたデータテーブルをもとに出力が決まる。 In step S28, the output priority calculation unit determines the inter-individual distance between the user A and the user X based on the flow of steps S22 to S27. In step S29, the loop processing of steps S21 to S29 is terminated. By executing the loop processing of steps S21 to S29 for each user other than the user A, the data table regarding the inter-individual distance of the user A is completed in the step S30. This inter-personal distance data table is created for each user from a certain user A, and the output is determined based on the aggregated data table.
 以上のように個人間距離に関するデータテーブルを作成することによって、ユーザ同士の関係性やコミュニケーションの様子から、ユーザ同士の親密度を推定し、その推定結果に基づいて、ユーザから他のユーザへの出力(コメント、発話)の優先度付けを行うことができる。例えば、親密度が高い参加者にはコメントを明示したり大きく出力したりすることで、当該参加者にとって関心度が高いコメントを優先的に出力できるため、臨場感のある遠隔コミュニケーションを実現することができる。また、ユーザから他のユーザへのコミュニケーションに関する指標(たとえば賛成、反対、理解)も算出し、これと出力優先度に基づいて、指標の値を表現したグラフを出力したり、指標に基づく画像や映像(たとえばユーザの顔の映像、表情再現モデル、表情再現アイコンなど)を出力したりすることができる。 By creating a data table related to the distance between individuals as described above, the intimacy between users is estimated from the relationship between users and the state of communication, and based on the estimation result, from the user to other users. Output (comments, utterances) can be prioritized. For example, by clearly indicating or outputting a large comment to a participant who has a high degree of intimacy, the comment that is of high interest to the participant can be output preferentially, so that remote communication with a sense of presence can be realized. Can be done. It also calculates indicators related to communication from the user to other users (for example, agree, disagree, understand), and based on this and output priority, outputs a graph expressing the value of the indicator, or an image based on the indicator. Images (for example, user's face image, facial expression reproduction model, facial expression reproduction icon, etc.) can be output.
(第2の実施形態)
 図15は、第2の実施形態に係る、コミュニケーション支援システムのモデル画面の例である。
(Second embodiment)
FIG. 15 is an example of a model screen of the communication support system according to the second embodiment.
 第2の実施形態のコミュニケーション支援システムでのポイントは、VR(Virtual Reality)上での展示会を対象にしたもので、VR空間で行われる遠隔コミュニケーションである。第1の実施形態と共通する点は省略し、異なる点を中心に説明していく。 The point of the communication support system of the second embodiment is for exhibitions on VR (Virtual Reality), and is remote communication performed in VR space. The points common to the first embodiment will be omitted, and the differences will be mainly described.
 端末2(7)が出力するVR空間の映像27には、第1の展示物28、第1の展示物を見ているユーザの表情再現アイコン29、第2の展示物30が映し出されている。VR空間の映像27に示す通り、VR空間内で各ユーザ(アバタ)が仮想空間において視線の方向、位置、対象物との距離、を画面上で立体的に把握することができる。 In the VR space image 27 output by the terminal 2 (7), the first exhibit 28, the facial expression reproduction icon 29 of the user who is looking at the first exhibit, and the second exhibit 30 are projected. .. As shown in the image 27 of the VR space, each user (avatar) in the VR space can grasp the direction, position, and distance of the line of sight in the virtual space three-dimensionally on the screen.
 さらに、出力画面のユーザの視線対象を判定する第1の展示物への反応フィードバック情報31により、前述した数値化されたフィードバック(2軸グラフ)20のグループ重要度21、また第1の展示物を見ているユーザの表情情報32の画面も併せて、同じ対象物を見ているユーザの雰囲気を視覚化できる。これにより、そのVR空間の場に参加しているユーザの表情や雰囲気を理解することができる。 Further, the group importance 21 of the above-mentioned quantified feedback (2-axis graph) 20 and the first exhibit by the reaction feedback information 31 to the first exhibit for determining the user's line-of-sight target on the output screen. The screen of the facial expression information 32 of the user who is watching can also be used to visualize the atmosphere of the user who is watching the same object. This makes it possible to understand the facial expressions and atmospheres of the users participating in the VR space.
 例えば、知り合いのユーザがある展示物に対して音声でコメントを言うと、同じ展示物を見ている他のユーザはリアルタイムでその知り合いユーザの音声を聞くことができる。これは、コメント欄に表示される知り合いのユーザが文章でコメントした場合も同様で、そのまま文章として表示される。しかし、同じ展示を見ている一般ユーザ(関係性がない)の意見は単語レベルでWord cloud18で表示される。 For example, if an acquaintance user makes a voice comment on an exhibit, other users who are looking at the same exhibit can hear the acquaintance user's voice in real time. This also applies when an acquaintance user displayed in the comment field makes a comment in a sentence, and the user is displayed as a sentence as it is. However, the opinions of general users (not related) who are viewing the same exhibition are displayed in Word cloud 18 at the word level.
 図16は、第2の実施形態に係る、定期的にサーバに送信されるフィードバックデータである。 FIG. 16 is feedback data periodically transmitted to the server according to the second embodiment.
 図13で説明したデータテーブルに、アバタ位置操作情報の欄、アバタ角度操作情報の欄が追加されている。アバタ位置操作情報の欄には、XYZ座標によるVR空間での位置が示されている。アバタ角度操作情報の欄には、アバタがVR空間内で対象物を見ている視線方向に関する数値が示されている。つまりフィードバックデータには、アバタの操作情報が一緒に送られる。 A column for avatar position operation information and a column for avatar angle operation information have been added to the data table described with reference to FIG. In the column of avatar position operation information, the position in the VR space by the XYZ coordinates is shown. In the column of the avatar angle operation information, the numerical value regarding the line-of-sight direction in which the avatar is looking at the object in the VR space is shown. That is, the operation information of the avatar is sent together with the feedback data.
 図17は、第2の実施形態に係る、個人間距離の計算である。 FIG. 17 is a calculation of the inter-individual distance according to the second embodiment.
 図14に示した第1の実施形態の個人間距離の計算と異なる点は、ステップS28AとステップS29Aである。ステップS28Aでは、ユーザXがユーザAと同一の対象を見ているなら、ユーザAとユーザXとの個人間距離の計算において、これらのユーザ間の関係性に応じた親密度の値を加算する。ステップS29Aでは、VR内でユーザXがユーザAから一定の距離の範囲内にいれば、ユーザAとユーザXとの個人間距離の計算において、これらのユーザ間の関係性に応じた親密度の値を加算する。これによりVR空間での個人間距離テーブルが完成する(ステップS32A)。 The difference from the calculation of the inter-individual distance of the first embodiment shown in FIG. 14 is step S28A and step S29A. In step S28A, if the user X sees the same object as the user A, the value of the intimacy according to the relationship between the users is added in the calculation of the interpersonal distance between the user A and the user X. .. In step S29A, if the user X is within a certain distance from the user A in the VR, the intimacy according to the relationship between the users is calculated in the calculation of the interpersonal distance between the user A and the user X. Add the values. This completes the inter-individual distance table in the VR space (step S32A).
(第3の実施形態)
 図18は、第3の実施形態に係る、コミュニケーション支援システムのモデルの構成例である。
(Third embodiment)
FIG. 18 is a configuration example of a model of the communication support system according to the third embodiment.
 第3の実施形態でのポイントは、アバタロボットを経由した遠隔コミュニケーションである。第2の実施形態の説明と同様に、第1の実施形態と共通する点は省略し、異なる点を中心に説明していく。 The point in the third embodiment is remote communication via the avatar robot. Similar to the description of the second embodiment, the points common to the first embodiment will be omitted, and the differences will be mainly described.
 アバタロボット37は、全周囲カメラ34を備えており、実空間上に設営された発表現場36において稼働される。アバタロボット37が全周囲カメラ34を用いて撮影した全周囲映像33は、アバタロボット37の周囲に存在する現場発表者35、現場発表者39等を映し出したものである。 The avatar robot 37 is equipped with an omnidirectional camera 34 and is operated at the presentation site 36 set up in the real space. The omnidirectional image 33 taken by the avatar robot 37 using the omnidirectional camera 34 is a projection of the on-site presenter 35, the on-site presenter 39, and the like existing around the avatar robot 37.
 アバタロボット37は、撮影した全周囲映像33を各ユーザ6aB~6dBに送信して映し出す。各ユーザ6aB~6dBは、PC、パッド、スマートフォン、VR用ヘッドセットなどの出力端末によって全周囲映像33を見ることができる。 The avatar robot 37 transmits and projects the captured omnidirectional image 33 to each user 6aB to 6dB. Each user 6aB to 6dB can view the omnidirectional image 33 by an output terminal such as a PC, a pad, a smartphone, or a VR headset.
 各ユーザ6aB~6dBが全周囲映像33を視聴しているが、ユーザ6bBとユーザ6cBとユーザ6dBは全周囲映像33の中の同じ対象(対象物映像33b)を見ていて、ユーザ6aBは全周囲映像33の中の別の対象(対象物映像33a)を見ている。よって図18では、ユーザ6aBは、ユーザ6bB~ユーザ6dBの現場36へのフィードバックには加わらない。 Each user 6aB to 6dB is watching the omnidirectional video 33, but the user 6bB, the user 6cB, and the user 6dB are watching the same object (object video 33b) in the omnidirectional video 33, and the user 6aB is all. You are looking at another object (object image 33a) in the surrounding image 33. Therefore, in FIG. 18, the user 6aB does not participate in the feedback from the user 6bB to the user 6dB to the site 36.
 ユーザ6bB~ユーザ6dBが全周囲映像33を視聴している様子や反応から、表情再現モデルや表情アイコンなどを作成して現場36に対してサーバがフィードバックする。フィードバック内容の出力は、アバタロボット37に設置された360度4面ディスプレイ40において、現場発表者39の前の画面38や、現場発表者35の前の画面41、にフィードバックとしてそれぞれ送信される。フィードバック内容は、例えば画面42である。その内容は具体的には、例えば現場発表者35の発表内容に対するユーザ6dBの感想である。 The server creates a facial expression reproduction model, a facial expression icon, etc. from the appearance and reaction of the user 6bB to the user 6dB watching the omnidirectional image 33, and feeds back to the site 36. The output of the feedback content is transmitted as feedback to the screen 38 in front of the on-site presenter 39 and the screen 41 in front of the on-site presenter 35 on the 360-degree four-sided display 40 installed in the avatar robot 37, respectively. The feedback content is, for example, screen 42. Specifically, the content is, for example, the impression of the user 6 dB on the content of the presentation by the on-site presenter 35.
 図19は、第3の実施形態に係る、ユーザ視聴画面のモデル例である、ユーザの視聴内容である。図18の説明と同様に、第1の実施形態および第2の実施形態と共通する点は省略し、異なる点を中心に説明していく。 FIG. 19 is a user viewing content, which is an example of a user viewing screen model according to the third embodiment. Similar to the description of FIG. 18, the points common to the first embodiment and the second embodiment will be omitted, and the differences will be mainly described.
 第1の実施形態(図8、図9参照)および第2の実施形態(図15参照)との違いは、アバタロボットにおけるユーザの視点映像46を端末2(7)の画面に使用していることである。ユーザの視点映像46には、発表者A39、ユーザBのアバタ44、ユーザBのフィードバック内容を表す表情再現アイコン45、ユーザCのアバタ48、ユーザCのフィードバック内容を表す顔画像アイコン47、が表示されている。これは、ユーザが発表者Aに視線を合わせている時、他のユーザも同様に視線を発表者Aに合わせていると、ユーザの視点映像46に他ユーザのアバタ(図19ではアバタ44、48)が登場するようになっている。逆に、ユーザの一定の視聴角度から外れた視聴角度に他のユーザの視聴角度が移動すると、ユーザの画面から他ユーザのアイコンが消える。 The difference between the first embodiment (see FIGS. 8 and 9) and the second embodiment (see FIG. 15) is that the user's viewpoint image 46 in the avatar robot is used for the screen of the terminal 2 (7). That is. The user's viewpoint image 46 displays a presenter A39, a user B's avatar 44, a facial expression reproduction icon 45 representing the user B's feedback content, a user C's avatar 48, and a face image icon 47 representing the user C's feedback content. Has been done. This is because when the user is looking at the presenter A, the other user is also looking at the presenter A, and the user's viewpoint image 46 is accompanied by another user's avatar (Avatar 44 in FIG. 19). 48) is coming to appear. On the contrary, when the viewing angle of another user moves to a viewing angle deviating from a certain viewing angle of the user, the icon of the other user disappears from the user's screen.
 図20は、第3の実施形態に係るアバタロボットのモデル画面の例である。 FIG. 20 is an example of a model screen of the avatar robot according to the third embodiment.
 図20は、発表者Aから見たアバタロボットの様子である。アバタロボットの360度4面ディスプレイ40には、ユーザBのフィードバック内容である感情アイコン45、ユーザCのフィードバック内容である顔画像アイコン47、ユーザAのフィードバック内容である表情情報49、が映し出されている。現場にはアバタロボットだけがいる状態と仮定すると、これを見ることで、発表者Aは自分のプレゼンテーション内容に対しての反応を視覚的に理解することができる。 FIG. 20 shows the state of the avatar robot as seen from the presenter A. The emotion icon 45, which is the feedback content of the user B, the face image icon 47, which is the feedback content of the user C, and the facial expression information 49, which is the feedback content of the user A, are projected on the 360-degree four-sided display 40 of the avatar robot. There is. Assuming that there is only an avatar robot in the field, the presenter A can visually understand the reaction to the content of his presentation by seeing this.
 図21は、第3の実施形態に係る、定期的に送信されるフィードバックデータである。 FIG. 21 is feedback data transmitted periodically according to the third embodiment.
 図21は、第1の実施形態および第2の実施形態との違いは、視点ロボット選択情報、視線角度情報、が項目にあることである。視点ロボット選択情報の欄は、ユーザが現場にいる複数のロボットのうち、1つのロボットを選択することで、ロボットの識別番号が記録される。また、視線角度情報は視点ロボット選択情報の欄で選んだ識別番号のロボットからユーザが現在見ている視線の角度についての情報が記録される。 FIG. 21 shows that the difference between the first embodiment and the second embodiment is that the viewpoint robot selection information and the line-of-sight angle information are included in the items. In the viewpoint robot selection information column, the identification number of the robot is recorded by selecting one robot from the plurality of robots in the field by the user. Further, as the line-of-sight angle information, information about the line-of-sight angle currently viewed by the user from the robot having the identification number selected in the viewpoint robot selection information field is recorded.
 図22は、第3の実施形態に係る、個人間距離の計算である。 FIG. 22 is a calculation of the inter-individual distance according to the third embodiment.
 図22は、第1の実施形態(図14参照)および第2の実施形態(図17参照)との違いは、ステップS28BとステップS29Bである。ステップS28Bでは、ユーザXがユーザAと複数あるアバタロボットのうち同一ロボットのカメラを見ていると、すなわち、ユーザXが視聴する映像を出力するアバタロボットとユーザAが視認しているアバタロボットとが同一のときに、ユーザAとユーザXとの個人間距離の計算において、これらのユーザ間の関係性に応じた親密度の値を加算する。 FIG. 22 shows the difference between the first embodiment (see FIG. 14) and the second embodiment (see FIG. 17) in step S28B and step S29B. In step S28B, when the user X is looking at the camera of the same robot among the plurality of avatar robots having the user A, that is, the avatar robot that outputs the image to be viewed by the user X and the avatar robot visually recognized by the user A. Are the same, in the calculation of the distance between the individuals of the user A and the user X, the value of the intimacy according to the relationship between these users is added.
 ステップ29Bではステップ28Bを踏まえて、ユーザXの視線方向がユーザAの視線方向と近いのであれば、すなわち、ユーザXの視線方向がユーザAの視線方向と所定の誤差範囲内のときに、ユーザAとユーザXとの個人間距離の計算において、これらのユーザ間の関係性に応じた親密度の値を加算する。これを含んだステップS20B~ステップ32Bのフローにより、個人間距離テーブルが完成される。 In step 29B, based on step 28B, if the line-of-sight direction of user X is close to the line-of-sight direction of user A, that is, when the line-of-sight direction of user X is within a predetermined error range with the line-of-sight direction of user A, the user. In the calculation of the inter-individual distance between A and the user X, the value of the intimacy according to the relationship between these users is added. The inter-individual distance table is completed by the flow of steps S20B to 32B including this.
 以上説明した本発明の第1~第3の実施形態によれば、以下の作用効果を奏する。 According to the first to third embodiments of the present invention described above, the following effects are exhibited.
(1)複数の参加者の間で行われる遠隔コミュニケーションを支援するコミュニケーション支援システムにおいて、サーバ1は、コミュニケーション支援システムに参加する参加者からの入力を受け付ける入力受付部と、複数の参加者のうち、第1の参加者と他の参加者とに関する情報に基づいて、第1の参加者と他の参加者との親密度を推定する、親密度推定部と、親密度推定部が推定した親密度に基づいて、他の参加者から第1の参加者に対して出力する出力内容の優先度を決める出力優先度を算出する、出力優先度算出部と、出力優先度算出部が算出した出力優先度に基づいて、その出力内容を第1の参加者に対して出力する出力部と、を有する。このようにしたことで、臨場感の向上と匿名性の確保とを両立させた遠隔コミュニケーションを実現できるコミュニケーション支援システムを提供できる。 (1) In a communication support system that supports remote communication performed among a plurality of participants, the server 1 is an input reception unit that receives input from participants participating in the communication support system, and among a plurality of participants. , The intimacy estimation unit that estimates the intimacy between the first participant and the other participants based on the information about the first participant and the other participants, and the parent estimated by the intimacy estimation unit. An output priority calculation unit that calculates an output priority that determines the priority of output contents output from other participants to the first participant based on the density, and an output calculated by the output priority calculation unit. It has an output unit that outputs the output contents to the first participant based on the priority. By doing so, it is possible to provide a communication support system that can realize remote communication that achieves both an improvement in presence and anonymity.
(2)コミュニケーション支援システムにおいて、サーバ1は、第1の参加者と他の参加者についてのコミュニケーションに関する指標を算出する指標算出部を有する。出力部は、出力優先度算出部が算出した出力優先度と、指標算出部が算出した指標と、に基づいて出力内容を決定する。このようにしたことで、他の参加者への発表を行っている発表者に対して、参加者同士のコミュニケーション状況に応じたフィードバックを行うことができる。 (2) In the communication support system, the server 1 has an index calculation unit that calculates an index related to communication between the first participant and other participants. The output unit determines the output content based on the output priority calculated by the output priority calculation unit and the index calculated by the index calculation unit. By doing so, it is possible to give feedback according to the communication situation between the participants to the presenter who is making a presentation to other participants.
(3)出力部は、第1の参加者に対して、出力優先度算出部が算出した出力優先度が所定よりも高い場合は、入力受付部で受け付けた入力として、たとえばカメラで撮影された他の参加者の顔の画像をそのまま出力し、所定よりも低い場合は、コミュニケーションに関する指標に基づく画像として、たとえば表情再現モデルや表情再現アイコンを出力する。このようにしたことで、重要度の高いフィードバックを逃さず、かつ匿名性が担保されたフィードバックもできる。 (3) When the output priority calculated by the output priority calculation unit is higher than the predetermined value for the first participant, the output unit is taken as an input received by the input reception unit, for example, with a camera. The image of the face of another participant is output as it is, and if it is lower than the predetermined value, for example, a facial expression reproduction model or a facial expression reproduction icon is output as an image based on an index related to communication. By doing so, it is possible to provide feedback that guarantees anonymity without missing important feedback.
(4)親密度推定部は、図4の画面により第1の参加者から他の参加者に対して設定される関係性と、図5の画面により第1の参加者から他の参加者に対して設定される送信情報の種類と、図6の画面により第1の参加者から他の参加者の所属グループに対して設定されるフィードバック量と、に基づいて親密度を推定することができる。このようにしたことで、ユーザ同士の関係性に配慮した親密度を推定できる。 (4) The intimacy estimation unit sets the relationship from the first participant to the other participants by the screen of FIG. 4, and from the first participant to the other participants by the screen of FIG. The intimacy can be estimated based on the type of transmission information set for the subject and the amount of feedback set from the first participant to the group to which the other participants belong from the screen of FIG. .. By doing so, it is possible to estimate the intimacy in consideration of the relationship between users.
(5)コミュニケーションに関する指標に基づく画像は、参加者の表情を再現したモデル画像である表情再現モデル24を含む。出力部は、それぞれの参加者の顔を撮影したカメラ撮影画像22から、表情再現モデル24を作成することができる。このようにしたことで、一定の親近感がある相手にたいして、匿名性を確保しつつ親近感も生み出すことができる。 (5) The image based on the index related to communication includes a facial expression reproduction model 24 which is a model image that reproduces the facial expressions of the participants. The output unit can create a facial expression reproduction model 24 from a camera-photographed image 22 of each participant's face. By doing so, it is possible to create a sense of intimacy while ensuring anonymity for a person who has a certain sense of intimacy.
(6)コミュニケーションに関する指標に基づく画像は、参加者の表情を再現したアイコンである表情再現アイコン25を含む。出力部は、それぞれの参加者の顔を撮影したカメラ撮影画像22から、表情再現アイコン25を作成することができる。このようにしたことで、知り合いでない相手に対して、匿名性を確保した感情表現によるフィードバックができる。 (6) The image based on the index related to communication includes the facial expression reproduction icon 25, which is an icon that reproduces the facial expression of the participant. The output unit can create the facial expression reproduction icon 25 from the camera-captured image 22 of each participant's face. By doing so, it is possible to give feedback by expressing emotions that ensure anonymity to a person who is not acquainted.
(7)VR空間を用いて遠隔コミュニケーションを行う場面において、親密度推定部は、他の参加者のアバタが第1の参加者のアバタと同じ対象を見ている時、あるいは、他の参加者のアバタが第1の参加者のアバタから一定の距離の範囲内にいる時、の少なくとも一方が満たされる場合に、第1の参加者と当該他の参加者との親密度の計算において、第1の参加者と他の参加者との関係性に応じた値を加算する。このようにしたことで、VR空間上でのユーザのアバタ同士から親密度を推定することができる。 (7) In the scene of remote communication using the VR space, the intimacy estimation unit is used when the avatars of other participants are looking at the same target as the avatars of the first participant, or other participants. When at least one of the avatars of the first participant is within a certain distance from the avatar of the first participant, in the calculation of the intimacy between the first participant and the other participant, the first. Add the values according to the relationship between one participant and other participants. By doing so, the intimacy can be estimated from the user's avatars in the VR space.
(8)アバタロボットを用いて遠隔コミュニケーションを行う場面において、親密度推定部は、複数のアバタロボットのうち、他の参加者が視聴する映像を出力するアバタロボットと第1の参加者の視認しているアバタロボットとが同一の時、あるいは、他の参加者の視聴方向が第1の参加者の視聴方向と所定の誤差の範囲内の時、の少なくとも一方が満たされる場合に、第1の参加者と他の参加者との親密度の計算において、第1の参加者と他の参加者との関係性に応じた値を加算する。このようにしたことで、アバタロボットを利用した場合でもユーザ同士の個人間距離を算出し、ユーザ同士の親密度を推定することができる。 (8) In the scene of remote communication using the avatar robot, the intimacy estimation unit visually recognizes the avatar robot that outputs the video to be viewed by other participants and the first participant among the plurality of avatar robots. The first is when at least one of the following is satisfied when the avatar robot is the same as the robot, or when the viewing direction of another participant is within a predetermined error from the viewing direction of the first participant. In the calculation of the intimacy between a participant and another participant, a value corresponding to the relationship between the first participant and the other participant is added. By doing so, even when the avatar robot is used, it is possible to calculate the inter-individual distance between the users and estimate the intimacy between the users.
 なお、本発明は上記の実施形態に限定されるものではなく、その要旨を逸脱しない範囲内で様々な変形や他の構成を組み合わせることができる。また本発明は、上記の実施形態で説明した全ての構成を備えるものに限定されず、その構成の一部を削除したものも含まれる。 The present invention is not limited to the above embodiment, and various modifications and other configurations can be combined within a range that does not deviate from the gist thereof. Further, the present invention is not limited to the one including all the configurations described in the above-described embodiment, and includes the one in which a part of the configurations is deleted.
1…サーバ
2…情報端末(PC)
3…発表ユーザ
4…第1のグループ
5…第2のグループ
6a~6c…聴講ユーザ
7…情報端末(パッド)
12…フィードバック時間遷移グラフ
13…他ユーザの映像
14…音声ON/OFFボタン
15…映像ON/OFFボタン
16…自分の表情を表示する映像
17…送信データ
18…Word cloud
19…テキスト欄
20…フィードバック2軸グラフ
21…グループ重要度を表すプロット
22…カメラ撮影画像
23…特徴点抽出画像
24…表情再現モデル
25…表情再現アイコン
26…第1展示物を見ているアバタ
27…VR空間の映像
28…第1展示物
29…第1展示物を見ているアバタ(ユーザ)の表情再現アイコン
30…第2展示物
31…フィードバック情報
32…第1展示物を見ているユーザの表情情報
33…アバタロボットの全周囲映像
33a,33b…アバタロボットの全周囲映像の中に映る対象物
34…全周囲カメラ
35…現場発表者B
36…現場
37…アバタ(稼働)ロボット
38…現場発表者Aの前の画面
39…現場発表者A
40…360度4面ディスプレイ
41…現場発表者Bの前の画面
42…視聴ユーザの表情フィードバックが映る画面
44…ユーザBのアバタ
45…ユーザBの表情再現アイコン
46…ユーザの視点映像(アバタロボット)
47…ユーザCの顔画像アイコン
48…ユーザCのアバタ
49…ユーザAの表情再現モデル
1 ... Server 2 ... Information terminal (PC)
3 ... Announcement user 4 ... First group 5 ... Second group 6a-6c ... Auditing user 7 ... Information terminal (pad)
12 ... Feedback time transition graph 13 ... Video of another user 14 ... Voice ON / OFF button 15 ... Video ON / OFF button 16 ... Video displaying one's facial expression 17 ... Transmission data 18 ... Word cloud
19 ... Text field 20 ... Feedback 2-axis graph 21 ... Plot showing group importance 22 ... Camera shot image 23 ... Feature point extraction image 24 ... Facial expression reproduction model 25 ... Facial expression reproduction icon 26 ... Abata looking at the first exhibit 27 ... VR space image 28 ... 1st exhibit 29 ... Avatar (user) looking at the 1st exhibit Facial expression reproduction icon 30 ... 2nd exhibit 31 ... Feedback information 32 ... Looking at the 1st exhibit User's facial expression information 33 ... All-around image of the avatar robot 33a, 33b ... Object 34 ... All-around camera 35 ... On-site presenter B reflected in the all-around image of the avatar robot
36 ... Site 37 ... Abata (operating) robot 38 ... Screen in front of site presenter A 39 ... Site presenter A
40 ... 360-degree four-sided display 41 ... Screen in front of presenter B on site 42 ... Screen on which the facial expression feedback of the viewing user is reflected 44 ... Avatar 45 of user B ... Facial expression reproduction icon 46 of user B ... User's viewpoint image (Abata robot) )
47 ... Face image icon of user C 48 ... Avata of user C 49 ... Facial expression reproduction model of user A

Claims (8)

  1.  複数の参加者の間で行われる遠隔コミュニケーションを支援するコミュニケーション支援システムであって、
     前記コミュニケーション支援システムに参加する前記参加者からの入力を受け付ける入力受付部と、
     前記複数の参加者のうち、第1の参加者と他の参加者とに関する情報に基づいて、前記第1の参加者と前記他の参加者との親密度を推定する、親密度推定部と、
     前記親密度推定部が推定した前記親密度に基づいて、前記他の参加者から前記第1の参加者に対して出力する出力内容の優先度を決める出力優先度を算出する、出力優先度算出部と、
     前記出力優先度算出部が算出した前記出力優先度に基づいて、前記出力内容を前記第1の参加者に対して出力する出力部と、を有する
     コミュニケーション支援システム。
    A communication support system that supports remote communication between multiple participants.
    An input reception unit that accepts input from the participants who participate in the communication support system, and
    An intimacy estimation unit that estimates the intimacy between the first participant and the other participants based on the information about the first participant and the other participants among the plurality of participants. ,
    Output priority calculation that determines the priority of the output content output from the other participant to the first participant based on the intimacy estimated by the intimacy estimation unit. Department and
    A communication support system including an output unit that outputs the output contents to the first participant based on the output priority calculated by the output priority calculation unit.
  2.  請求項1に記載のコミュニケーション支援システムであって、
     前記第1の参加者と前記他の参加者についてのコミュニケーションに関する指標を算出する指標算出部を有し、
     前記出力部は、前記出力優先度算出部が算出した前記出力優先度と、前記指標算出部が算出した前記指標と、に基づいて、前記出力内容を決定する
     コミュニケーション支援システム。
    The communication support system according to claim 1.
    It has an index calculation unit that calculates an index related to communication between the first participant and the other participants.
    The output unit is a communication support system that determines the output content based on the output priority calculated by the output priority calculation unit and the index calculated by the index calculation unit.
  3.  請求項2に記載のコミュニケーション支援システムであって、
     前記出力部は、前記第1の参加者に対して、前記出力優先度算出部が算出した前記出力優先度が所定よりも高い場合は、前記入力受付部で受け付けた前記入力を出力し、所定よりも低い場合は、前記指標に基づく画像を出力する
     コミュニケーション支援システム。
    The communication support system according to claim 2.
    When the output priority calculated by the output priority calculation unit is higher than the predetermined value, the output unit outputs the input received by the input reception unit to the first participant, and determines the output. If it is lower than, a communication support system that outputs an image based on the above index.
  4.  請求項1に記載のコミュニケーション支援システムであって、
     前記親密度推定部は、前記第1の参加者から前記他の参加者に対して設定される関係性と、前記第1の参加者から前記他の参加者に対して設定される送信情報の種類と、前記第1の参加者から前記他の参加者の所属グループに対して設定されるフィードバック量と、に基づいて前記親密度を推定する
     コミュニケーション支援システム。
    The communication support system according to claim 1.
    The intimacy estimation unit is of the relationship set from the first participant to the other participant and the transmission information set from the first participant to the other participant. A communication support system that estimates the intimacy based on the type and the amount of feedback set from the first participant to the group to which the other participant belongs.
  5.  請求項3に記載のコミュニケーション支援システムであって、
     前記指標に基づく画像は、前記参加者の表情を再現したモデル画像である表情再現モデルを含み、
     前記出力部は、それぞれの前記参加者の顔を撮影した画像から、前記表情再現モデルを作成して出力する
     コミュニケーション支援システム。
    The communication support system according to claim 3.
    The image based on the index includes a facial expression reproduction model which is a model image that reproduces the facial expression of the participant.
    The output unit is a communication support system that creates and outputs the facial expression reproduction model from images of the faces of the participants.
  6.  請求項2に記載のコミュニケーション支援システムであって、
     前記指標に基づく画像は、前記参加者の表情を再現したアイコンである表情再現アイコンを含み、
     前記出力部は、それぞれの前記参加者の顔を撮影した画像から、前記表情再現アイコンを作成して出力する
     コミュニケーション支援システム。
    The communication support system according to claim 2.
    The image based on the index includes a facial expression reproduction icon which is an icon that reproduces the facial expression of the participant.
    The output unit is a communication support system that creates and outputs the facial expression reproduction icon from an image of each participant's face.
  7.  請求項1に記載のコミュニケーション支援システムであって、
     VR空間を用いて前記遠隔コミュニケーションを行う場面において、
     前記親密度推定部は、前記他の参加者のアバタが前記第1の参加者のアバタと同じ対象を見ている時、あるいは、前記他の参加者のアバタが前記第1の参加者のアバタから一定の距離の範囲内にいる時、の少なくとも一方が満たされる場合に、前記第1の参加者と前記他の参加者との前記親密度の計算において、前記第1の参加者と前記他の参加者との関係性に応じた値を加算する
     コミュニケーション支援システム。
    The communication support system according to claim 1.
    In the scene where the remote communication is performed using the VR space,
    In the intimacy estimation unit, when the avatar of the other participant is looking at the same target as the avatar of the first participant, or the avatar of the other participant is the avatar of the first participant. The first participant and the other in the calculation of the intimacy between the first participant and the other participant when at least one of them is satisfied when they are within a certain distance from. A communication support system that adds values according to the relationship with the participants.
  8.  請求項1に記載のコミュニケーション支援システムであって、
     アバタロボットを用いて前記遠隔コミュニケーションを行う場面において、
     前記親密度推定部は、複数の前記アバタロボットのうち、前記他の参加者が視聴する映像を出力するアバタロボットと前記第1の参加者が視認しているアバタロボットとが同一の時、あるいは、前記他の参加者の視線方向が前記第1の参加者の視線方向と所定の誤差範囲内の時、の少なくとも一方が満たされる場合に、前記第1の参加者と前記他の参加者との前記親密度の計算において、前記第1の参加者と前記他の参加者との関係性に応じた値を加算する
     コミュニケーション支援システム。
    The communication support system according to claim 1.
    In the scene where the remote communication is performed using the avatar robot
    The intimacy estimation unit is used when, among the plurality of the avatar robots, the avatar robot that outputs the video viewed by the other participant and the avatar robot visually recognized by the first participant are the same, or When at least one of the line-of-sight direction of the other participant is within a predetermined error range from the line-of-sight direction of the first participant, the first participant and the other participant A communication support system that adds values according to the relationship between the first participant and the other participants in the calculation of the intimacy.
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