JP2018138155A - Emotion estimation server device, emotion estimation method, presentation device and emotion estimation system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a technique capable of further accurately estimating team emotion.SOLUTION: An emotion estimation server comprises: a social relationship information management unit which generates information representing social relationship on the basis of office organization data of a plurality of users; and a team emotion estimation unit which estimates team emotion on the basis of sensor data of the users or information based on the sensor data, and the information representing the social relationship.SELECTED DRAWING: Figure 1

Description

  The present invention relates to an emotion estimation server device, an emotion estimation method, a presentation device, and an emotion estimation system.

  2. Description of the Related Art Conventionally, there is a technique for measuring a person's behavior and physiological reaction externally using various sensors and estimating the person's internal psychological state (for example, emotion) from the obtained data. Such emotion estimation technology can be used to improve the performance of human-machine interaction of machines that provide interpersonal services, such as service robots, or in physically separated environments such as telework. It is used to help understand the situation of the other party.

  As an example, Patent Document 1 proposes an emotion estimation device that estimates a person's emotion using a plurality of measurement index data such as a camera, a microphone, and a biological signal.

  There are many existing techniques for estimating the emotion of a “one” person (hereinafter “individual emotion”), such as the technology described in Patent Document 1. On the other hand, there are few techniques for estimating the emotional atmosphere of a place (hereinafter referred to as “team feeling”) fostered by the collaborative activities of “a plurality of” persons and supporting user sharing of the estimated information.

  As an example, Patent Document 2 determines whether or not biometric information received from a plurality of individual biometric sensors is biometric information whose features have been extracted. A group emotion estimation apparatus for estimating group emotion information based on the group emotion has been proposed.

JP 2012-59107 A Japanese Patent Laying-Open No. 2006-7363

  In today's society, where every mechanism is highly complex, there are limits to the results that can be produced only by the work of a single person. Even in the above-described emotion estimation technology, the need for a method for estimating not only individual emotions but also team emotions fostered by collaborative activities of multiple persons will increase.

  Therefore, it is required to provide a technique capable of estimating team feeling with higher accuracy.

  In order to solve the above problem, according to one aspect of the present invention, a social relationship information management unit that generates information indicating social relationships based on the organizational data of a plurality of users, and each of the plurality of users An emotion estimation server is provided, comprising: a team emotion estimation unit that estimates team emotion based on sensor data or information based on the sensor data and information indicating the social relationship.

  The emotion estimation server includes a personal emotion estimation unit that estimates a personal emotion for each user based on sensor data of each of the plurality of users, and the team emotion estimation unit includes the personal emotion as information based on the sensor data. May be obtained.

  The team emotion estimation unit may obtain feature data of sensor data of each of the plurality of users as information based on the sensor data.

  The team emotion estimation unit calculates a weighting coefficient based on the information indicating the social relationship, and estimates the team feeling based on the sensor data or the information based on the sensor data and the weighting coefficient. Good.

  The team emotion estimation unit weights the sensor data or information based on the sensor data with the weighting coefficient, and uses the average value, median value, or mode value of the weighted data as the team emotion. It may be calculated.

  The social relationship information management unit may generate information indicating the social relationship based on the job system data.

  The information indicating the social relationship may include the strength of the relationship between the two users.

  According to another aspect of the present invention, generating information indicating social relations based on the organizational data of a plurality of users, sensor data of each of the plurality of users, or information based on the sensor data, There is provided an emotion estimation method including estimating a team emotion based on the information indicating the social relationship.

  Further, according to another aspect of the present invention, based on information indicating social relationships generated based on a plurality of users 'organizational data, and each of the plurality of users' sensor data or information based on the sensor data. A presentation device is provided that includes a presentation unit that presents information indicating the estimated team emotion.

  The presenting unit may present information indicating the team feeling of each of the plurality of teams in a region closer to the stronger the connection between the teams.

  The presenting unit may present information indicating the team emotion and individual emotions of the plurality of users for each emotion category.

  According to another aspect of the present invention, a social relationship information management unit that generates information indicating social relationships based on job system data of a plurality of users, and each of the sensor data or the sensors of the plurality of users An emotion estimation server comprising: a team emotion estimation unit for estimating team emotion based on information based on data and information indicating the social relationship; and a presentation unit for presenting information indicating the team emotion An emotion estimation system having a presentation device is provided.

  As described above, according to the present invention, it is possible to provide a technique capable of estimating a team emotion with higher accuracy.

It is explanatory drawing which shows an example of a schematic structure of the emotion estimation system which concerns on this embodiment. It is a block diagram which shows an example of the hardware constitutions of the emotion estimation server which concerns on the embodiment, a management DB server, a sensor terminal, and an information presentation terminal. It is a block diagram which shows an example of a function structure of the management system DB server which concerns on the embodiment. It is a block diagram which shows an example of a function structure of the emotion estimation server which concerns on the same embodiment. It is a block diagram which shows an example of a function structure of the information presentation terminal which concerns on the embodiment. It is explanatory drawing which shows an example of the application example of the employment system in a certain organization. It is explanatory drawing which shows an example of the employment system database in a certain organization. It is explanatory drawing which shows an example of the social relationship information based on the employment system in a certain organization. It is explanatory drawing which shows an example of the information which shows the personal emotion and the team emotion in a certain organization. It is explanatory drawing which shows an example of the application screen of an information presentation terminal. It is a flowchart which shows an example of the schematic flow of the information processing of the emotion estimation system which concerns on the embodiment.

  Exemplary embodiments of the present invention will be described below in detail with reference to the accompanying drawings. In addition, in this specification and drawing, about the component which has the substantially same function structure, duplication description is abbreviate | omitted by attaching | subjecting the same code | symbol.

  In the present specification and drawings, a plurality of constituent elements having substantially the same or similar functional configuration are distinguished by attaching different alphabets after the same reference numerals. However, when it is not necessary to particularly distinguish each of a plurality of constituent elements having substantially the same or similar functional configuration, only the same reference numerals are given.

  First, the problem of Patent Document 2 will be described. The aforementioned Patent Document 2 describes a method for estimating group emotion information from individual emotions, but has the following two major problems.

  The first problem is that Patent Document 2 does not explain at all how to define and select the members of the group whose emotions are to be estimated. For example, in a large organization with thousands or tens of thousands of employees, the number of people who belong to the same organization but do not have contact points in daily life and do not know their names or faces Will be far more than the number of acquaintances. Even if the group emotions are calculated for the persons who do not interact with each other, the information indicating the team feelings will have little meaning (because the persons are not teams).

  The second problem is that Patent Document 2 does not explain that estimation processing including “social relationship” among the members of the group is included in the influence factor when calculating the emotion of the group. It is. For example, in a large business project involving dozens to hundreds of related parties at the same time, even if it is called a collaborative relationship, there is also a strong social relationship where a colleague in the same team collaborates every day. If so, there may be a weak social relationship where the departments they belong to are different and have only a few contacts in a month. Naturally, people with strong social relationships in the former have a greater influence on each other in team emotions than in the case of weak social relationships in the latter, and the effects also on estimation of team emotions It is considered that setting a large degree contributes to improvement in estimation accuracy. Japanese Patent Application Laid-Open No. 2004-228561 describes a method of using time and place information from which sensor data feature information is extracted for weighting of emotions of a group. There is no statement to use.

  Regarding the team emotion estimation technology, in order to solve the above-mentioned two problems of Patent Document 2, whether or not the constituent members of the group team emotion have a social relationship with each other, There is a need for a mechanism that the estimation system uses information on the strength of sex for the team emotion estimation process.

  Therefore, the present invention relates to a technique related to a process of estimating “team emotion” based on individual emotions, and selects a member of a group as a team element and assigns a weight when calculating a team emotion between the members. It realizes an emotion estimation system that can calculate team emotions with high accuracy by processing based on the presence or absence of “social relationship” and its strength. Based on the data acquired by the “social relationship information management department” of the system from the “job system” information database of the organization members on the internal information infrastructure of the organization to which it belongs, converted into parameter data for estimation calculation It is an object to provide a team emotion estimation system characterized in that the team emotion is estimated.

  In particular, the present invention is characterized by the use of information indicating “formal” social relations, such as employment data.

  Then, with reference to FIG. 1, the schematic structure of the team emotion estimation system (henceforth "emotion estimation system") which concerns on embodiment of this invention is demonstrated.

  FIG. 1 is an explanatory diagram showing an example of a schematic configuration of the emotion estimation system according to the present embodiment. Referring to FIG. 1, the emotion estimation system includes an emotion estimation server 100, a job management DB server 300, a plurality of users 900, a plurality of sensor terminals 200, a presentation device (hereinafter also referred to as “information presentation terminal”) 400, a LAN ( Local Area Network) 50.

  The office DB server 300 may not be newly prepared for the emotion estimation system. As the administrative DB server 300, for example, a storage unit and a communication unit that store a database (DB) relating to the organizational structure of the affiliated staff on the existing in-house information infrastructure existing on the in-house intra network (or on the cloud network). Existing server equipment provided may be used.

  A plurality of users 900 belong to a certain organization and have social relations based on their job system (details will be described later).

  FIG. 2 shows the emotion estimation server 100, the job DB server 300, the sensor terminal 200, and the information presentation terminal 400 (hereinafter, the emotion estimation server 100, the job DB server 300, the sensor terminal 200, and the information presentation terminal 400 according to this embodiment. It is a block diagram showing an example of a hardware configuration of “the device according to the present embodiment” without being distinguished. Note that it is not necessary for all of the above-described devices to have all of the following hardware configurations (for example, the emotion estimation server 100 does not have to be directly equipped with a sensor). A hardware module capable of realizing the functional configuration may be appropriately limited and provided.

Referring to FIG. 2, the apparatus according to this embodiment includes a bus 801, a CPU (Central Processing Unit) 803, a ROM (Read Only).
Memory) 805, RAM (Random Access Memory) 807, storage device 809, communication interface 811, sensor 813, input device 815, display device 817, and speaker 819.

  The CPU 803 executes various processes in the apparatus according to the present embodiment. The ROM 805 stores a program and data for causing the CPU 803 to execute processing in the apparatus according to the present embodiment. The RAM 807 temporarily stores programs and data when the CPU 803 executes processing.

  A bus 801 connects the CPU 803, the ROM 805, and the RAM 807 to each other. A storage device 809, a communication interface 811, a sensor 813, an input device 815, a display device 817, and a speaker 819 are further connected to the bus 801. The bus 801 includes a plurality of types of buses, for example.

  As an example, the bus 801 includes a high-speed bus that connects the CPU 803, the ROM 805, and the RAM 807, and one or more other buses that are slower than the high-speed bus.

The storage device 809 stores data to be temporarily or permanently stored in the device according to the present embodiment. The storage device 809 may be a magnetic storage device such as a hard disk or an EEPROM (Electrically
Erasable and Programmable Read Only Memory (flash memory)
memory), MRAM (Magnetoresistive Random Access Memory), FeRAM (Ferroelectric Random Access Memory) and PRAM (Phase
non-volatile memory such as change Random Access Memory
memory).

  The communication interface 811 is a communication unit included in the device according to the present embodiment, and communicates with an external device via a network (or directly). The communication interface 811 may be an interface for wireless communication. In this case, for example, a communication antenna, an RF circuit, and other communication processing circuits may be included. The communication interface 811 may be an interface for wired communication. In this case, for example, a LAN terminal, a transmission circuit, and other communication processing circuits may be included.

  The sensor 813 is, for example, a camera, a microphone, another sensor, or a combination thereof. The camera images a subject and includes, for example, an optical system, an image sensor, and an image processing circuit. The microphone collects ambient sounds, converts the sound into an electric signal, and converts the electric signal into digital data.

The input device 815 is a touch panel, a mouse, a line-of-sight detection device, or the like. The display device 817 displays an output image (that is, a display screen) from the device according to the present embodiment. For example, a liquid crystal, an organic EL (Organic Light-Emitting Diode), a CRT (Cathode) is displayed.
Ray Tube) or the like. The speaker 819 outputs sound, converts digital data into an electric signal, and converts the electric signal into sound.

  Next, an example of a functional configuration of the “sensor terminal 200” according to the present embodiment will be described.

  The sensor terminal 200 externally measures the behavior and physiological reaction of the user 900 and transmits data acquired by the measurement to the emotion estimation server 100 described later. The sensor 813 of the sensor terminal 200 and the data of the behavior and physiological reaction to be measured are, for example, image data including facial expression and body posture state content measured by a camera, voice data measured by a microphone, and measurement by an acceleration sensor. Acceleration data of body movements, device operation data measured by input devices such as keyboards, mice, touch panels, etc., autonomic nervous system activities measured by various biological sensors (heart rate activity, electrical skin activity, blood pressure, sweating, breathing, Data of skin / deep body temperature, etc.), data of central nervous system activity (electroencephalogram, cerebral blood flow, etc.), and data of eye movement, pupil diameter, blink number, etc. measured by eye gaze measuring device.

  The sensor of the sensor terminal 200 may be a non-contact type or a contact type to the user. When the sensor of the sensor terminal 200 is a contact type, for example, the sensor terminal 200 may be a wearable terminal having a shape such as a wristwatch. The sensor terminal 200 may be a smartphone terminal that includes a camera, a microphone, an acceleration sensor, a communication unit, and the like. In FIG. 1, one sensor terminal 200 is shown corresponding to one user 900. However, one sensor terminal 200 may acquire sensor data of a plurality of users 900. In that case, the sensor terminal 200 performs a one-to-one association process between the sensor data and the identification data of the measurement target person for each of the plurality of users 900, and combines each combination of the sensor data and the identification data of the measurement target person. Remember or send. The identification data of the person to be measured may be obtained in any way, and as an example, identification data of a person specified by face recognition from an image captured by a camera may be used.

  The sensor terminal 200 may include a storage unit for temporarily storing measured data. In addition, since the sensor terminal 200 may perform not only measurement but also simple analysis, the sensor terminal 200 may include a control unit for analysis calculation. Further, the sensor terminal 200 may include a communication unit for transmitting data that has been measured or simply analyzed to the emotion estimation server 100. The storage unit can be implemented by a storage device 809, the control unit can be implemented by a CPU 803, a ROM 805, and a RAM 807, and the communication unit can be implemented by a communication interface 811.

  Next, an example of a functional configuration of the “job system DB server 300” according to the present embodiment will be described with reference to FIG.

  FIG. 3 is a block diagram illustrating an example of a functional configuration of the office DB server 300 according to the present embodiment. Referring to FIG. 3, the office DB server 300 includes a communication unit 310, a storage unit 320, and a control unit 330.

  The communication unit 310 communicates with other devices. For example, the communication unit 310 is directly connected to the LAN 50 and communicates with the emotion estimation server 100 described later. Note that the communication unit 310 can be implemented by the communication interface 811.

  The memory | storage part 320 memorize | stores the database regarding the organization system of the member of the organization using this emotion estimation system. Note that the storage unit 320 can be implemented by the storage device 809.

  Here, the job system is, for example, the “system related to job assignment” (Kojien 6th edition, edited by Niimura, 2008). In this embodiment, the job system includes not only job content but also emotion estimation according to this embodiment. It also includes information on the “position” and “job type” of the members of the organization using the system.

  In the following, explanation regarding the data of the job system will be given with reference to FIG. 6 and FIG. FIG. 6 is an explanatory diagram illustrating an example of an application example of a job system in a certain organization. FIG. 6 shows a plurality of users 900 belonging to an organization that uses the emotion estimation system. Here, the users 900A, 900B, 900C, and 900F belong to the team (or section) Z as a job system, and the position of the user 900F is a team manager (or section manager), who is a general employee, 900A, 900B, and 900C. Directly supervising the company, he has the command and command right in the business to the subordinates 900A, 900B, 900C. In addition, there is 900H in the position of the general manager as the boss of the team manager 900F, and the general manager 900H has the command to command the team manager 900F in accordance with the job system. Further, under the manager 900H, as with team Z, team manager 900G and general employees 900D and 900E exist as team Y. The above-described users 900A, 900B, 900C, 900D, 900E, 900F, 900G, and 900H all belong to the part X. As shown in FIG. 6, there may be a part W or other part next to the part X. The part W or other part basically has a different number of people in each position. It may have the same organizational structure and functions as part X. Further, although not shown in FIG. 6, there may be a department as a higher rank of the department X or the department W, or a representative director or other officer as a position of the user 900.

  Based on the above-mentioned system, each user 900 has a formal social relationship in business such as whether it is a direct supervisor / subordinate relationship, a colleague relationship within the same team, or another division. It is prescribed. In the present embodiment, a law is proposed that the closer the distance is within the hierarchical structure of the organizational structure in which the departments are the same or adjacent in the same hierarchy or one hierarchy, the stronger the social relationship. Of course, the transcendence of the hierarchy, for example, the above-mentioned general manager 900H has the command right to command the general employees 900A, 900B, 900C, etc., and although it is possible to directly give the command, Such actions are exceptional when viewed from the basic work defined by the original hierarchical organizational structure, so in this embodiment, the closeness of the hierarchical structure and the strength of social relationships are linked according to the basics. It was. However, if the relationship that transcends the hierarchical structure described above is recorded as an exceptional matter in an organizational database that will be described later, it can be used as processing data according to the present embodiment.

  FIG. 7 is an explanatory diagram showing an example of a management system database in a certain organization. FIG. 7 shows a table 321 of an organization database corresponding to an example of the organization organization described in FIG. The table 321 of the organization database includes, for example, information indicating an employee ID (for example, 900A, 900B,...) That uniquely identifies a member of an organization to which the organization is applied, a department to which the member belongs, and a position of the member. Contains the corresponding data. The table 321 of the organization database shows storage data related to the organization of the users 900A, 900B, 900C, 900D, 900E, 900F, 900G, and 900H described in FIG. 6, and the data shown in FIG. It is possible to obtain information indicating social relationships of such occupational systems.

  As exemplified in the data of the user 900H on the 10th line of the table 321 of the job system database, the user 900 may have a plurality of job types and positions, and the job database records data corresponding to them. May be. In this way, this embodiment is also applied to a user 900 who is engaged in a job that is exceptional for a hierarchical job structure, such as a cross-departmental project, by allowing a user to associate a plurality of affiliations and positions. The emotion estimation system according to can respond.

  As described above, the job system DB server 300 does not have to be newly prepared for the emotion estimation system, and is based on the in-house information infrastructure that the organization using the emotion estimation system already has. Such existing data may be used.

  The control unit 330 provides various functions of the office DB server 300. In addition, the control unit 330 receives data including partial information of the organization database stored in the storage unit 320 in response to a request from another communication device, for example, the emotion estimation server 100, via the communication unit 310. It has the function to transmit to a communication apparatus. The control unit 330 can be implemented by the CPU 803, the ROM 805, and the RAM 807.

  Next, an example of a functional configuration of the “emotion estimation server 100” according to the present embodiment will be described with reference to FIG. FIG. 4 is a block diagram illustrating an example of a functional configuration of the emotion estimation server 100 according to the present embodiment. Referring to FIG. 4, emotion estimation server 100 includes a communication unit 110, a storage unit 120, and a control unit 130.

  The communication unit 110 communicates with other devices. For example, the communication unit 110 is directly connected to the LAN 50 and communicates with the sensor terminal 200 and the office DB server 300. Note that the communication unit 110 can be implemented by the communication interface 811.

  The storage unit 120 stores a program and data for the operation of the emotion estimation server 100. Note that the storage unit 120 can be implemented by the storage device 809.

  The control unit 130 provides various functions of the emotion estimation server 100. The control unit 130 includes a personal emotion estimation unit 131, a social relationship information management unit 133, and a team emotion estimation unit 135. The control unit 130 can be implemented by the CPU 803, the ROM 805, and the RAM 807. The functions of the individual emotion estimation unit 131, the social relationship information management unit 133, and the team emotion estimation unit 135 will be described later.

  Next, an example of a functional configuration of the “information presentation terminal 400” according to the present embodiment will be described with reference to FIG. FIG. 5 is a block diagram illustrating an example of a functional configuration of the information presentation terminal 400 according to the present embodiment. Referring to FIG. 5, the information presentation terminal 400 includes a communication unit 410, a storage unit 420, a control unit 430, an operation unit 440, and a presentation unit 450.

  The communication unit 410 communicates with other devices. For example, the communication unit 410 is directly connected to the LAN 50 and communicates with the emotion estimation server 100. For example, the communication unit 410 acquires information indicating the team emotion from the emotion estimation server 100. Note that the communication unit 410 can be implemented by the communication interface 811.

  The storage unit 420 stores a program and data for the operation of the information presentation terminal 400. For example, the storage unit 420 temporarily stores information indicating the team emotion acquired from the emotion estimation server 100 by the communication unit 410. Note that the storage unit 420 can be implemented by the storage device 809.

  The control unit 430 provides various functions of the information presentation terminal 400. For example, the control unit 430 visualizes information indicating the team emotion, and controls the presentation unit 450 so that the information indicating the team emotion is presented by the presentation unit 450. The control unit 430 can be implemented by the CPU 803, the ROM 805, and the RAM 807.

  The operation unit 440 receives an operation input from the user. When the operation unit 440 outputs the received operation to the control unit 430, the operation is used for various operations by the control unit 430. Note that the operation unit 440 can be implemented by the input device 815.

  The presentation unit 450 presents information to the user according to control by the control unit 430. For example, the presentation unit 450 presents information indicating the team emotion visualized by the control unit 430 to the user. Note that the presentation unit 450 can be implemented by the display device 817.

  Functions of the individual emotion estimation unit 131, the social relationship information management unit 133, and the team emotion estimation unit 135 will be described. The personal emotion estimation unit 131 estimates the personal emotion for each user 900 based on the behavioral and physiological response measurement data acquired from the user 900 via the sensor terminal 200 and the communication unit 110, thereby estimating personal emotion estimation data ( Information indicating personal feelings). Further, the personal emotion estimation unit 131 has a function of storing the generated data in the storage unit 120. In particular, the personal emotion estimation unit 131 may store information indicating the personal emotion estimated from a certain user 900 in the storage unit 120 in association with the ID of the user 900 (for example, see FIG. 9 described later). ).

  Here, a supplementary explanation of personal emotion and its estimation method is provided. As an example, personal feelings are “evaluative responses about people, things, events, and environments among various information processes that people perform in their mental processes” (Ortony et al., 1988; Ohira, 2010). It is defined as Specific types of emotions include happiness, surprise, fear, anger, disgust, sadness on the basic emotion-based discrete model corresponding to facial expressions by psychologist Paul Ekman, psychologist James A. et al. There are known quadrants of emotion, etc. in a continuous model based on the emotion dimension based on the degree of pleasure and arousal by Russell. Other continuous models include a positive or negative emotion by Watson, a 3-axis model by Wundt (pleasure, excitement, and tension), and a 4-axis model by Plutik. Other examples of applied / complex emotions include confusion, interest, mental stress, concentration, fatigue, busyness, creativity, relaxation / tension, motivation, co-sensitivity, and reliability. Furthermore, it can be said that a lively feeling as a group atmosphere in business activities is a kind of higher-level emotion.

  The emotion and level of a person can be determined by linguistic reports using characters, sentences, and symbols of the person by using, for example, a questionnaire. As the questionnaire, “Affect Grid” is well known.

  However, since the measurement method using a questionnaire requires an answering work, the measurement itself may interfere with the original purpose work in everyday life where something is different. is there.

  Therefore, in this emotion estimation system, the personal emotion estimation unit 131 mechanically estimates an emotion (obtained by the questionnaire method or the like) based on the behavior or physiological response data measured by the sensor terminal 200 described above. . In order to perform the estimation processing, emotion estimation model data generated in advance by learning processing is required. The emotion estimation model is generated, for example, from a group of data in which the behavioral and physiological reaction data at a certain time point / situation is associated with learning data composed of answer data of the questionnaire. For example, ask questions about the user's subjective emotions and behavioral / physiological data such as facial expressions, voice, heart rate activity, and electrodermal activity measured by countless cameras and microphones and wearable activity meters embedded in the office. The correct answer data that is answered on paper is associated with the learning data. The behavior / physiology data may be feature data for learning processing in which a measurement value from a sensor is converted.

  The feature amount data may be a position of a representative feature point of the face, a distance of a straight line connecting each two points, or an angle formed. Alternatively, the feature amount data may be the maximum value and standard deviation of the fundamental frequency, power, average speech rate, and primary cepstrum coefficient of speech. Alternatively, the feature amount data may be an average value, standard deviation, or heart rate variability of a heart rate or a beat interval. Alternatively, the feature amount data may be an average value, standard deviation, increase / decrease rate, etc. of the skin conductance level. These feature amount data may be used in any way, may be used as an absolute value at a certain time point, or may be used as a relative change rate between two time points.

  For the generation of the emotion estimation model using the learning data, for example, a known SVM (Support Vector Machine) or deep learning (Deep Learning) method may be used as a learning method, or a simple regression analysis method may be used. May be used. A learning model may be generated for each individual user, or a model common to humans may be generated using learning data of a plurality of users. The personal emotion estimation unit 131 can estimate the personal emotion from the behavior / physiology data of a certain person by using the obtained emotion estimation model data.

  The emotion estimation server 100 and the personal emotion estimation unit 131 may have a function of generating learning data for the above-described personal emotion estimation processing and the emotion estimation model itself. Further, the generation of the feature amount data for the learning data is performed by the sensor terminal 200 instead of the emotion estimation server 100, and the sensor terminal 200 transmits the feature amount data to the emotion estimation server 100. May be.

  The social relationship information management unit 133 is information necessary for the team emotion estimation unit 135 (to be described later) to estimate the team emotion and indicates the social relationship based on the above-described organizational structure (hereinafter also referred to as “social relationship information”). Is generated. For this purpose, the social relationship information management unit 133 acquires data including information on the above-described organizational system database from the organizational system DB server 300 via the communication unit 110, generates information indicating the social relationship based on the organizational system, It has a function of storing the generated information in the storage unit 120.

  FIG. 8 is an explanatory diagram showing an example of social relationship information based on a job system in a certain organization. FIG. 8 shows a table 121 of social relationship information based on a management system corresponding to an example of the organizational management system described with reference to FIGS. 6 and 7. The table 121 of social relationship information based on the organization system includes, for example, an employee ID 1 that uniquely identifies a member of an organization to which the organization system is applied, an employee ID 2 of a member other than the member, and the social relationship of both Includes data indicating strength. It should be noted that the strength of social relationship is derived from the law that, as described above, the closer the distance is within the hierarchical structure of the organization, the stronger the social relationship. In the example of FIG. 8, the user 900A belongs to the same team Z and is directly related to the team manager 900F who is the superior and the colleagues 900B and 900C in the same hierarchy, the social relationship is “strong”, and the manager who is the superior who is separated by two levels. Social relationship is “medium” with 900H, social relationship “weak” with general employee 900E of another team, and social relationship “-” (none) with employee 900I of another department W who has no contact in daily life Is recorded in the table 121.

  In the example of FIG. 8, the strength of the social relationship is four levels of “strong”, “medium”, “weak”, and “none”, but naturally the number of strength categories may be more or less than this. Of course, it may be continuous quantitative data. In addition, for example, the classification threshold may be arbitrarily set by the administrator of the emotion estimation system in advance, for example, the case where three or more hierarchies are separated is classified as social relationship “medium”, and the setting parameter is stored in advance 120 may be stored.

  The team emotion estimation unit 135 is based on the information indicating the personal emotion generated by the personal emotion estimation unit 131 and the information indicating the social relationship based on the job system generated by the social relationship information management unit 133. Generate information that indicates team emotions. The team emotion estimation unit 135 has a function of storing information indicating the calculated team emotion in the storage unit 120.

  Here, the team emotion is, for example, a representative value obtained by weighting the information indicating the individual emotion for each member in a preset group of users by the strength of social relationship with the group, for example, “average value” Calculated as “median” and “mode”. As an example, when the information indicating the personal emotion is quantitative data and the average value is adopted as the representative value, the team emotion estimation unit 135 sets the team emotion value as an example of the information indicating the team emotion (Formula 1 ).

・・・（数式１）

... (Formula 1)

  Where TE: team emotion value, m: number of combinations of two users targeted in the group, QR: weighting coefficient corresponding to the strength of social relationship between the two users, RE: the two users A representative value (for example, “average value”, “median value”, “mode value”) obtained from each individual emotion value of the user is used. In this case, the group of users for which the team emotion value is calculated may be team Z, team Y, the whole part X, or only users 900F, 900G, and 900H in the example of FIG. Thus, it may be limited to executive employees, or may be limited to general employees in the department X such as only the users 900A, 900B, 900C, 900D, and 900E. With the above-described calculation method, if there is a base personal emotion value and job system data, a team emotion value can be obtained for an arbitrarily set group. Further, the number of combinations of the aforementioned users is not necessarily two, and may be a combination of three or more.

  Here, the value of the weighting coefficient corresponding to the strength of each social relationship is not limited. For example, the weighting coefficient may be larger as the social relationship is stronger. More specifically, the weighting coefficient corresponding to the social relationship strength “strong” may be larger than the weighting coefficient corresponding to the social relationship strength “medium”. The weighting coefficient corresponding to the social relationship strength “medium” may be larger than the weighting coefficient corresponding to the social relationship strength “weak”. In addition, the weighting coefficient corresponding to the social relationship strength “weak” may be larger than the weighting coefficient corresponding to the social relationship strength “none”.

  In this embodiment, first, it is assumed that the personal emotion estimation unit 131 estimates the personal emotion and then the team emotion estimation unit 135 estimates the team emotion as the collective data thereof. However, the team emotion estimation unit 135 may estimate the team emotion directly from the sensor data of a plurality of persons who are the targets of the team. In this case, the team emotion estimation unit 135 may perform a weighting calculation process corresponding to the strength of the above-described social relationship on the sensor data value itself or the feature value data (converted value).

  At this time, the value of the sensor data itself or the feature amount data is not particularly limited. As an example, the feature amount data of the sensor data may be a rate of change of the heart rate after being converted from the pulse detected by the pulse sensor. For example, the rate of change of heart rate may be the rate of change of heart rate, for example, the ratio of the current heart rate to the previous heart rate (eg, “heart rate increased 20%”, “heart rate Etc.) ”. The sensor data value itself or its feature value data may be used in place of information indicating individual emotion when estimating the team emotion.

  FIG. 9 is an explanatory diagram illustrating an example of information indicating personal feelings and information indicating team feelings in a certain organization. FIG. 9 shows a table 122 of information indicating personal feelings and information indicating team feelings corresponding to an example of the organizational structure described in FIG. Here, the positive degree of quantitative data is illustrated as an example of information indicating personal feeling and information indicating team feeling.

  Next, an example of a functional configuration of the “information presentation terminal 400” according to the present embodiment will be described. In the information presentation terminal 400, the control unit 430 acquires information indicating the team emotion estimated by the emotion estimation server 100 and information indicating the personal emotion via the communication unit 410, visualizes them, and displays the information via the presentation unit 450. Present it to the user. The user may be the user 900 whose team feeling or personal feeling is estimated, or a person different from the user 900 whose team feeling or personal feeling is estimated (for example, an industrial physician in charge of mental health management of a certain organization). Etc.).

  In addition, when the control unit 430 visualizes and presents the information indicating the team emotion and the information indicating the personal emotion, the control unit 430 uses the information indicating the social relationship based on the above-described job system so that the user can easily understand the information. The information indicating the team feeling or the information indicating the personal feeling may be “categorized” and presented. For example, when the control unit 430 displays information indicating the team emotion of a certain team on the screen, the control unit 430 presents information indicating the individual emotion of the team member together with the vicinity region of the information indicating the team emotion. You may present via. Thereby, the user of the information presentation terminal 400 can intuitively grasp the information indicating the team feeling and the information indicating the personal feeling that is the calculation element.

  In addition, for example, when the control unit 430 displays information indicating a plurality of team emotions by a plurality of teams on the screen, based on the information indicating the social relationship, the teams that are more closely related in terms of duties are closer to the region. Information indicating each other's team feelings may be presented via the presentation unit 450. Thereby, when the user of the information presentation terminal 400 confirms the information indicating the team feelings of a plurality of teams, the user can efficiently view the display based on the strength of the business relationship between the teams.

  FIG. 10 is an explanatory diagram illustrating an example of an application screen of the information presentation terminal 400. Referring to FIG. 10, information indicating a certain team emotion of a certain team (positive degree of team T1) and information indicating a personal feeling as a calculation element thereof (positive degrees of users U11 to U14 belonging to team T1) are close to each other. Information indicating another team emotion of the same team (the fatigue level of the team T1) and information indicating the individual emotions that are the calculation elements (the fatigue levels of the users U11 to U14 belonging to the team T1) It is displayed in the nearby area. As described above, the presentation unit 450 presents the information indicating the team emotion and the information indicating the personal emotion for each emotion category, thereby making it easier to grasp the team emotion and the personal emotion for each category.

  As shown in FIG. 10, the control unit 430 may present the past estimated information of the team emotion and the personal emotion as a history, and may present the information in a time series graph form (FIG. 10 shows a graph). The right side of the line segment is shown as the current estimated information of the team feeling and the personal feeling, and the estimated information traced back to the past from the right end to the left is shown).

  Next, an example of information processing according to the present embodiment will be described with reference to FIG. FIG. 11 is a flowchart showing an example of a schematic flow of information processing of the emotion estimation system according to the present embodiment. In step S101, the emotion estimation server 100 is set by the administrator of the emotion estimation system, the team to be estimated for the team emotion, the parameters of the constituent members, the type of team emotion to be estimated (for example, the positive degree, Parameters of negativeness, confusion, etc., and team emotion calculation methods (for example, selection of mean / median / mode as representative values, number of social strength categories, social strength) The weighting coefficient values, etc.) are stored in the storage unit 120.

  Note that the above parameters may be set in advance by the administrator before the information processing, the setting parameters at the time of the previous information processing may be used, or the initial setting parameters may be used as they are. Good. In that case, the execution of step S101 may be omitted.

  In step S <b> 103, in the emotion estimation server 100, the communication unit 110 acquires sensor data of the behavior and physiological reaction of the user 900 who is a member of the team whose target team emotion is estimated via the sensor terminal 200. .

  In step S <b> 105, in the emotion estimation server 100, the personal emotion estimation unit 131 performs a personal emotion estimation process from the sensor data of the user 900. In the present embodiment, the process in which the personal emotion estimation unit 131 first estimates the personal emotion and then the team emotion estimation unit 135 estimates the team emotion as the collective data has been described as an example. However, as described above, the team emotion estimation unit 135 may estimate the team emotion directly from the sensor data of a plurality of persons to be a team target. In that case, the team emotion estimation unit 135 may perform a weighting calculation process corresponding to the strength of the above-described social relationship on the sensor data value itself or the feature amount data thereof. In that case, the execution of step S105 may be omitted.

  In step S <b> 107, in the emotion estimation server 100, the communication unit 110 acquires the organization data of the user 900 who is a member of the team for which the team emotion is estimated from the organization DB server 300, and the social relationship information The management unit 133 generates the above-described social NW information based on the organizational data acquired by the communication unit 110, and calculates the social relationship information based on the generated social NW information.

  In step S109, the team emotion estimation unit 135 estimates the team emotion of the team set in step S101 from the information indicating the personal emotion and the social relationship information. In step S111, in the information presentation terminal 400, the control unit 430 causes the presentation unit 450 to present information indicating the team emotion acquired from the emotion estimation server 100 and information indicating the personal emotion that is a calculation element thereof. If information indicating the estimated team feeling is not presented by the information presentation terminal 400, the execution of step S111 may be omitted.

  As described above, according to the embodiment of the present invention, it is possible to automatically and accurately estimate the team feeling based on the personal feeling by using the information indicating the “formal” social relationship such as the office data.

  The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to such examples. It is obvious that a person having ordinary knowledge in the technical field to which the present invention pertains can come up with various changes or modifications within the scope of the technical idea described in the claims. Of course, it is understood that these also belong to the technical scope of the present invention.

  For example, in the above description, the example in which the control unit 430 of the information presentation terminal 400 determines the layout of various information presented by the presentation unit 450 has been mainly described. However, the layout of various information presented by the presentation unit 450 may be determined by another device (for example, the emotion estimation server 100). At this time, the emotion estimation server 100 may determine the layout of various information presented by the presentation unit 450 for each type of user viewing the information presentation terminal 400 (for example, the user's job title).

DESCRIPTION OF SYMBOLS 100 Emotion estimation server 110 Communication part 120 Storage part 130 Control part 131 Personal emotion estimation part 133 Social relationship information management part 135 Team emotion estimation part 200 Sensor terminal 300 Job management DB server 310 Communication part 320 Storage part 330 Control part 400 Information presentation terminal 410 communication unit 420 storage unit 430 control unit 440 operation unit 450 presentation unit

Claims (12)

A social relationship information management unit that generates information indicating social relationships based on the organizational data of multiple users;
Team emotion estimation unit for estimating team emotion based on sensor data of each of the plurality of users or information indicating the social relationship and information indicating the social relationship;
An emotion estimation server comprising: The emotion estimation server
Based on sensor data of each of the plurality of users, a personal emotion estimation unit that estimates personal emotion for each user,
The team emotion estimation unit obtains information indicating the personal emotion as information based on the sensor data.
The emotion estimation server according to claim 1. The team emotion estimation unit obtains feature data of sensor data of each of the plurality of users as information based on the sensor data.
The emotion estimation server according to claim 1. The team emotion estimation unit calculates a weighting coefficient based on the information indicating the social relationship, and estimates the team feeling based on the sensor data or the information based on the sensor data and the weighting coefficient.
The emotion estimation server according to claim 1. The team emotion estimation unit weights the sensor data or information based on the sensor data with the weighting coefficient, and uses the average value, median value, or mode value of the weighted data as the team emotion. calculate,
The emotion estimation server according to claim 4. The social relationship information management unit generates information indicating the social relationship based on the job system data.
The emotion estimation server according to claim 1. The information indicating the social relationship includes the strength of the relationship between the two users.
The emotion estimation server according to claim 6. Generating social relationships based on the organizational data of multiple users,
Estimating team feelings based on sensor data of each of the plurality of users or information based on the sensor data and information indicating the social relationship;
Emotion estimation method including Presenting information indicating the estimated team feeling based on information indicating social relationships generated based on the organizational data of a plurality of users and sensor data of each of the plurality of users or information based on the sensor data Presenting part,
A presentation device comprising: The presenting unit presents information indicating the team feeling of each of a plurality of teams in a region closer to the stronger the connection between the teams,
The presentation device according to claim 9. The presenting unit presents information indicating the team emotion and individual emotions of each of the plurality of users for each emotion category,
The presentation device according to claim 9. A social relationship information management unit that generates information indicating social relationships based on the organizational data of multiple users;
Team emotion estimation unit for estimating team emotion based on sensor data of each of the plurality of users or information indicating the social relationship and information indicating the social relationship;
An emotion estimation server comprising:
A presentation unit for presenting information indicating the team feeling;
A presentation device comprising:
Emotion estimation system.

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