JP6798353B2 - Emotion estimation server and emotion estimation method - Google Patents

Description

The present invention also relates to the emotion estimation server and emotional estimate how.

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

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

Like the technique described in Patent Document 1, there are many existing techniques for estimating the emotion of a "single" person (hereinafter referred to as "individual emotion"). On the other hand, there are few technologies that estimate the emotional atmosphere of a place created by the collaborative activities of "multiple" people (hereinafter referred to as "team emotion") and support the user sharing of the estimated information.

As an example, in Patent Document 2, it is determined whether or not the biometric information received from the biometric sensors of a plurality of individuals is the biometric information whose features have been extracted, and the feature information of the biometric information determined to have been feature extracted is used. A group emotion estimation device that estimates group emotion information based on this has been proposed.

Japanese Unexamined Patent Publication No. 2012-59107 Japanese Unexamined Patent Publication No. 2016-7363

In today's society, where all mechanisms are highly complex, there is a limit to the results that can be produced by the work of one person, and naturally there are many collaborative work by multiple teams. Even in the above-mentioned emotion estimation technique, there will be an increasing need for a method of estimating not only individual emotions but also team emotions cultivated by collaborative activities of multiple people.

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

In order to solve the above problem, according to a certain viewpoint of the present invention, the social relationship information management unit that generates information indicating the social relationship based on the job system data of a plurality of users and the social relationship are shown. Emotion estimation including a team emotion estimation unit that calculates a weighting coefficient based on the information and estimates team emotions based on the sensor data of each of the plurality of users or the information based on the sensor data and the weighting coefficient. A server is provided.

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

In order to solve the above problem, according to a certain viewpoint of the present invention, information indicating social relations is generated based on job system data of a plurality of users, and weighting is performed based on the information indicating social relations. An emotion estimation method is provided that includes calculating a coefficient and estimating team emotions based on the sensor data of each of the plurality of users or information based on the sensor data and the weighting coefficient .

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

It is explanatory drawing which shows an example of the schematic structure of the emotion estimation system which concerns on this embodiment. It is a block diagram which shows an example of the hardware composition of the emotion estimation server, the occupational system DB server, the sensor terminal, and the information presentation terminal which concerns on this embodiment. It is a block diagram which shows an example of the functional structure of the occupational database server which concerns on this embodiment. It is a block diagram which shows an example of the functional structure of the emotion estimation server which concerns on the same embodiment. It is a block diagram which shows an example of the functional structure of the information presenting terminal which concerns on this embodiment. It is explanatory drawing which shows an example of application example of the office system in a certain organization. It is explanatory drawing which shows an example of the job system database in a certain organization. It is explanatory drawing which shows an example of the social relations information based on the occupational system in a certain organization. It is explanatory drawing which shows an example of the information which shows the individual feeling and the information which shows the team feeling in a certain organization. It is explanatory drawing which shows an example of the application screen of an information presenting terminal. It is a flow chart which shows an example of the schematic flow of the information processing of the emotion estimation system which concerns on this embodiment.

Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. In the present specification and the drawings, components having substantially the same functional configuration are designated by the same reference numerals, so that duplicate description will be omitted.

Further, in the present specification and the drawings, a plurality of components having substantially the same or similar functional configurations are distinguished by adding different alphabets after the same reference numerals. However, if it is not necessary to distinguish each of a plurality of components having substantially the same or similar functional configurations, only the same reference numerals are given.

First, the above-mentioned problems of Patent Document 2 will be described. The above-mentioned Patent Document 2 describes a method of estimating group emotional information from individual emotions, but has two major problems described below.

The first problem is that Patent Document 2 does not explain at all how to define and select the constituent persons of the group for which emotions are estimated. For example, in a huge organization with thousands or tens of thousands of people, the number of people who belong to the same organization but have no contact in daily life and do not know their names or faces. Would be far more than the number of acquaintances. Even if the group's emotions are combined and calculated for people who do not interact with each other, the information indicating the team's emotions will have little meaning (because the persons are not a team).

The second problem is that Patent Document 2 does not explain that when calculating the emotions of a group, the estimation process is performed with the "social relationship" between the members of the group as an influential factor. Is. For example, in a large business project in which dozens to hundreds of people are involved at the same time, even if it is a collaborative relationship, there is also a strong social relationship in which colleagues in the same team collaborate every day. If so, there may be a weak social relationship in which the departments to which they belong are different and they have only a few points of contact each month. Naturally, the former person with a strong social relationship has a greater influence on each other in team emotions than the latter case with a weak social relationship, and the influence on the estimation of team emotions. It is considered that setting a large degree contributes to the improvement of estimation accuracy. Patent Document 2 describes a method of using the time and place information from which the feature information of the sensor data is extracted for weighting the emotion calculation of the group, but the above-mentioned reference to the social relationship and its estimation processing There is no description to use it.

In order to solve the above two problems of Patent Document 2 with respect to the team emotion estimation technique, whether or not the constituent persons who are the elements of the team emotion of the group have a social relationship with each other, and further, the social relationship. It is necessary to have a mechanism in which the estimation system uses the information of sexual strength for the estimation processing of team emotions.

Therefore, the present invention relates to a technique related to an estimation process of "team emotion" based on individual emotions, and weights are applied between the constituent persons when selecting the constituent persons of the group which are the elements of the team and calculating the team emotions. It realizes an emotion estimation system that can calculate highly accurate team emotions by processing based on the existence and strength of "social relationships", and further, the social relationships are determined by the constituent persons. Converted from the database of "job system" information of the personnel belonging to the organization on the information infrastructure in the organization to which the organization belongs to the parameter data for estimation calculation based on the data acquired by the "social relationship information management department" of the system. It is an object of the present invention to provide a team emotion estimation system characterized in that the team emotion is estimated.

In particular, the present invention is characterized in that it uses information indicating "formal" social relations called occupational data.

Subsequently, with reference to FIG. 1, a schematic configuration of a team emotion estimation system (hereinafter, “emotion estimation system”) according to the embodiment of the present invention will be described.

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

The job-based DB server 300 does not have to be newly prepared for this emotion estimation system. The job system DB server 300 includes, for example, a storage unit and a communication unit that store a database (DB) related to the job system of the staff members on the existing company information infrastructure existing on the company intranet (or cloud network). The existing server equipment provided may be used.

A plurality of users 900 both belong to an organization and have a social relationship with each other due to their occupational system (details will be described later).

FIG. 2 shows emotion estimation server 100, occupational DB server 300, sensor terminal 200, and information presentation terminal 400 (hereinafter, emotion estimation server 100, occupational DB server 300, sensor terminal 200, and information presentation terminal 400, respectively, according to the present embodiment. It is a block diagram which shows an example of the hardware configuration of (the device which concerns on this embodiment) without distinction. It should be noted that it is not necessary for all of the above devices to be equipped with all of the following hardware configurations (for example, the emotion estimation server 100 does not need to be directly equipped with a sensor), and for each device described later. A hardware module capable of realizing a functional configuration may be provided with an appropriate limitation.

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

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

The 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. Bus 801 includes, for example, a plurality of types of buses.

As an example, bus 801 includes a high-speed bus connecting the CPU 803, ROM 805, and RAM 807, and one or more other buses 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, for example, 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)
Nonvolatile memory such as change Random Access Memory
memory) may be used.

The communication interface 811 is a communication means 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, and in this case, for example, a communication antenna, an RF circuit, and other circuits for communication processing may be included. Further, the communication interface 811 may be an interface for wired communication, and in this case, for example, a LAN terminal, a transmission circuit, and other circuits for communication processing may be included.

The sensor 813 is, for example, a camera, a microphone, other sensors, or a combination thereof. The camera captures a subject and includes, for example, an optical system, an image sensor, and an image processing circuit. A microphone picks up ambient sound, 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, and the like. The display device 817 displays an output image (that is, a display screen) from the device according to the present embodiment, and is, for example, a liquid crystal, an organic EL (Organic Light-Emitting Diode), or a CRT (Cathode).
It can be realized by using Ray Tube) or the like. The speaker 819 outputs voice, converts digital data into an electric signal, and converts the electric signal into voice.

Next, an example of the 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 the data acquired by the measurement to the emotion estimation server 100 described later. The behavioral and physiological reaction data measured by the sensor terminal 200 and the sensor 813 are, for example, image data including facial expressions and body postures 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 keyboard, mouse, touch panel, autonomic nervous system activity measured by various biosensors (heartbeat activity, skin electrical activity, blood pressure, sweating, breathing, Includes data on skin / core body temperature, etc.), data on central nervous system activity (brain waves, cerebral blood flow, etc.), and data on gaze movement, pupil diameter, number of blinks, etc. measured by a 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 in the shape of a wristwatch or the like. Further, the sensor terminal 200 may be a smartphone terminal including a camera, a microphone, an acceleration sensor, a communication unit, and the like. It should be noted that the sensor terminal 200 is shown in FIG. 1 so that there is one sensor terminal 200 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 correspondence process of the sensor data and the identification data of the measurement target person for each of the plurality of users 900, and obtains 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, it may be identification data of a person identified by face recognition from an image captured by a camera.

Further, the sensor terminal 200 may include a storage unit for temporarily storing the measured data. Further, since the sensor terminal 200 may perform not only measurement but also simple analysis, it may be provided with a control unit for analysis calculation. Further, the sensor terminal 200 may include a communication unit for transmitting the measured or simple-analyzed data to the emotion estimation server 100. The storage unit may be mounted by the storage device 809, the control unit may be mounted by the CPU 803, ROM 805 and RAM 807, and the communication unit may be mounted by the communication interface 811.

Next, with reference to FIG. 3, an example of the functional configuration of the “job-based DB server 300” according to the present embodiment will be described.

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

The communication unit 310 communicates with another device. For example, the communication unit 310 is directly connected to the LAN 50 and communicates with the emotion estimation server 100 described later. The communication unit 310 may be implemented by the communication interface 811.

The storage unit 320 stores a database relating to the job system of the personnel belonging to the organization that uses this emotion estimation system. The storage unit 320 may be mounted by the storage device 809.

Here, the job system is, for example, a "system related to the division of duties" (Kojien 6th edition, Shinmura Izuru, 2008). In this embodiment, the job system is not only the job content but also the emotion estimation related to this embodiment. It shall also include information on the "position" and "occupation type" of the members of the organization that uses the system.

Hereinafter, the data of the occupational system will be described with reference to FIGS. 6 and 7. FIG. 6 is an explanatory diagram showing an example of an application example of the 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, 900F belong to the team (or section) Z as a job system, and the position of the user 900F is the team manager (or section chief), and the general employees 900A, 900B, 900C. He reports to his boss and has the authority to command and command his subordinates 900A, 900B, and 900C depending on his position. In addition, there is 900H who is in the position of manager as the boss of team manager 900F, and the manager 900H has the command and command authority in the work for team manager 900F depending on the position. Further, under the manager 900H, a team manager 900G and general employees 900D and 900E exist as team Y as in team Z. The above-mentioned users 900A, 900B, 900C, 900D, 900E, 900F, 900G, and 900H all belong to the department X. As shown in FIG. 6, a part W and other parts may exist next to the part X, and the parts W and other parts basically have different numbers of people in each position. It may have the same position structure and function as the part X. Further, although not shown in FIG. 6, there may be a department as a higher rank of the department X and the department W, and a representative director and other officers as the positions of the user 900.

Based on the above-mentioned job system, each user 900 has a formal business relationship such as whether they have a direct supervisor / subordinate relationship, a colleague relationship within the same team, or a different department. It is stipulated. In this embodiment, we propose the rule that the closer the distance is, the stronger the social relationship is within the hierarchical structure of the same hierarchy or one hierarchy and the same or adjacent departments. Of course, transcending the hierarchy, for example, the above-mentioned manager 900H has the command and command authority in business for general employees 900A, 900B, 900C, etc., and it is possible to give command and command directly, but that Since such an act is an exceptional action from the viewpoint of the basic function defined by the original hierarchical structure, in this embodiment, the proximity of the hierarchical structure and the strength of social relations are linked according to the basics. It was. However, the relationship that transcends the above-mentioned hierarchical structure is also an exceptional matter, and if the information is recorded in the job system database described later, it can be used as the processing data according to the present embodiment.

FIG. 7 is an explanatory diagram showing an example of a job system database in a certain organization. FIG. 7 shows a table 321 of the job system database corresponding to an example of the job system of the organization described with reference to FIG. Table 321 of the job system database contains, for example, employee IDs (for example, 900A, 900B, ...) That uniquely identify members of the organization to which the job system is applied, departments to which the members belong, and information indicating the positions of the members. Contains the corresponding data. Table 321 of the job system database shows the stored data related to the job system of the users 900A, 900B, 900C, 900D, 900E, 900F, 900G, 900H described in FIG. 6, and is shown in FIG. 6 based on the data. It is possible to request information that shows the social relationship of such a job system.

As illustrated in the data of the user 900H in the 10th row of the table 321 of the job system database, the user 900 may have a plurality of job types and positions, and the job system database records the data corresponding to the data. You may. By having a mechanism for allowing the user to be associated with a plurality of affiliations and positions in this way, the present embodiment also applies to the user 900 who engages in duties that are exceptional for the hierarchical job structure, such as a cross-departmental project. The emotion estimation system related to the above can be dealt with.

As described above, the job system DB server 300 does not need to be newly prepared for the emotion estimation system, and the job system on the in-house information infrastructure already possessed by the organization using the emotion estimation system. The existing data may be used.

The control unit 330 provides various functions of the job database server 300. Further, the control unit 330 obtains data including partial information of the occupational database stored in the above-mentioned 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 a function of transmitting to a communication device. The control unit 330 may be mounted by the CPU 803, the ROM 805, and the RAM 807.

Next, an example of the 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 showing an example of the functional configuration of the emotion estimation server 100 according to the present embodiment. Referring to FIG. 4, the emotion estimation server 100 includes a communication unit 110, a storage unit 120, and a control unit 130.

The communication unit 110 communicates with another device. For example, the communication unit 110 is directly connected to the LAN 50 and communicates with the sensor terminal 200 and the job database server 300. The communication unit 110 may be implemented by the communication interface 811.

The storage unit 120 stores programs and data for the operation of the emotion estimation server 100. The storage unit 120 may be mounted by the storage device 809.

The control unit 130 provides various functions of the emotion estimation server 100. The control unit 130 includes an individual emotion estimation unit 131, a social relationship information management unit 133, and a team emotion estimation unit 135. The control unit 130 may be mounted 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 the 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 showing an example of the functional configuration of the information presentation terminal 400 according to the present embodiment. Referring to FIG. 5, the information presenting 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 another device. 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 team emotions from the emotion estimation server 100. The communication unit 410 may be implemented by the communication interface 811.

The storage unit 420 stores programs and data for the operation of the information presentation terminal 400. For example, the storage unit 420 temporarily stores information indicating team emotions acquired from the emotion estimation server 100 by the communication unit 410. The storage unit 420 may be mounted 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 the 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 may be mounted 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. The operation unit 440 may be mounted by the input device 815.

The presentation unit 450 presents information to the user according to the control by the control unit 430. For example, the presentation unit 450 presents to the user information indicating team emotions visualized by the control unit 430. The presentation unit 450 may be mounted by the display device 817.

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. The personal emotion estimation unit 131 estimates personal emotions by estimating the personal emotions of each user 900 based on the measurement data of behaviors and physiological reactions acquired from the user 900 via the sensor terminal 200 and the communication unit 110. Generate information that indicates personal feelings). In addition, 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 personal emotions estimated from a user 900 in the storage unit 120 in association with the ID of the user 900 (see, for example, FIG. 9 described later). ).

Here, the explanation of personal feelings and their estimation methods is supplemented. Personal emotions are, for example, "evaluative reactions to people, things, events, and the environment among various information processes that people perform in their mental processes" (Ortony et al., 1988; Ohira, 2010). Is defined as. Specific types of emotions include happiness, surprise, fear, anger, disgust, sadness, and psychologist James A. on a basic emotion-based discrete model that corresponds to facial expressions by psychologist Paul Ekman. The quadrants of emotions and sorrows in the emotional dimension-based continuous model of pleasure and alertness by Russel are known. Other continuous models include positive or negative emotions by Watson, 3-axis models by Wundt (pleasure, excitement, tension), and 4-axis models by Plutchik. Other applied / complex emotions include confusion, interest, mental stress, concentration, fatigue, busyness, creativity, relaxation / tension, motivation, empathy, and reliability. Furthermore, the liveliness that is experienced as a group atmosphere in business activities can be said to be a type of higher-level emotion.

The emotions and degree of a person can be determined by, for example, using the questionnaire method, by linguistic reporting of the person's letters, sentences, and symbols. As the questionnaire, "Affect Grid" and the like are well known.

However, since the measurement method using the questionnaire requires answering work, the measurement itself may interfere with the original purpose work in daily life where some other work such as work is performed. is there.

Therefore, in this emotion estimation system, the personal emotion estimation unit 131 mechanically estimates and processes emotions (obtained by the questionnaire method or the like) based on the behavioral and physiological reaction data measured by the sensor terminal 200 described above. .. In order to perform the estimation process, the data of the emotion estimation model generated by the learning process in advance is required. The emotion estimation model is generated from, for example, a group of data in which the data of the behavior or physiological reaction at a certain time point / situation is associated with the learning data consisting of the answer data of the questionnaire. For example, ask questions about the user's facial expression, voice, heartbeat activity, skin electrical activity, and other behavioral / physiological data measured from countless cameras, microphones, and wearable activity meters embedded in the office, and the user's subjective emotions. The correct answer data that was answered on paper is associated with the data for learning. The behavior / physiological data may be feature data for learning processing in which the measured values from the sensors are converted.

The feature amount data may be the position of a representative feature point of the face, the distance of a straight line connecting each of the two points, or the angle formed. Alternatively, the feature data may be the fundamental frequency, power, average speech speed, maximum value and standard deviation of the first-order cepstrum coefficient of speech. Alternatively, the feature amount data may be the average value of the heart rate or the beat interval, the standard deviation, or the heart rate variability. Alternatively, the feature amount data may be an average value of the skin conductance level, a standard deviation, an increase / decrease rate, or the like. These feature data may be used in any way, as an absolute value at a certain time point, or as a relative rate of change 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 method may be used as a learning method, or a simple regression analysis method may be used. May be used. Further, the learning model may be generated for each individual user, or a model common to humans may be generated using the learning data of a plurality of users. The individual emotion estimation unit 131 can estimate individual emotions from the behavior / physiological 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-mentioned personal emotion estimation process and the emotion estimation model itself. Further, the above-mentioned feature amount data for the learning data is generated not by the emotion estimation server 100 but by the sensor terminal 200, and the sensor terminal 200 transmits the feature amount data to the emotion estimation server 100. You may.

The social relations information management unit 133 is information indicating the social relations based on the above-mentioned occupational system, which is necessary for the team emotion estimation unit 135, which will be described later, to estimate and process the team emotions (hereinafter, also referred to as “social relations information”). To generate. Therefore, the social relations information management unit 133 acquires data including the above-mentioned job system database information from the job system DB server 300 via the communication unit 110, and generates information indicating the social relationship based on the job 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 relations information based on the occupational system in a certain organization. FIG. 8 shows a table 121 of social relations information based on the job system corresponding to an example of the job system of the organization described with reference to FIGS. 6 and 7. The table 121 of the social relationship information based on the job system shows, for example, an employee ID 1 that uniquely identifies a member of the organization to which the job system is applied, an employee ID 2 of a member other than the member, and the social relationship between the two. Contains data showing strength. As mentioned above, the strength of social relations is derived from the rule that the closer the distance is within the hierarchical structure of the occupational system, the stronger the social relations. In the example of FIG. 8, the user 900A belongs to the same team Z and has a “strong” social relationship with the team manager 900F, who reports directly to him, and his colleagues 900B and 900C, who are two levels apart. 900H is social relationship "medium", general employee of another team 900E is social relationship "weak", and employee 900I of another department W who has no contact in daily life is social relationship "-" (none) Is recorded in the table 121.

In the example of FIG. 8, the strength of social relations is divided into four stages of "strong", "medium", "weak", and "none", but the number of strength classifications is naturally greater or less than this. It does not matter, and it may be continuous quantitative data. In addition, for example, when three or more layers are separated from each other, the threshold value for the classification may be arbitrarily set in advance by the administrator of the emotion estimation system, and the setting parameter is stored in advance in the storage unit. It may be stored in 120.

The team emotion estimation unit 135 is based on the information indicating the above-mentioned individual emotions generated by the individual emotion estimation unit 131 and the information indicating the social relations based on the above-mentioned occupational system generated by the social relations information management unit 133. Generate information that indicates team emotions. Further, the team emotion estimation unit 135 has a function of storing the calculated information indicating the team emotion in the storage unit 120.

Here, the team feeling is, for example, a representative value in which information indicating individual feelings for each member in a preset group of users is weighted by the strength of social relation to the group, for example, "mean value". It is calculated as "median" and "mode". As an example, when the information indicating individual emotions is quantitative data and the average value is adopted as the representative value, the team emotion estimation unit 135 uses the following team emotion values as an example of the information indicating team emotions (Formula 1). ) Can be obtained.

・・・（数式１）

... (Formula 1)

However, TE: team emotion value, m: number of combinations of two users targeted in the group, QR: weighting coefficient corresponding to the strength of social relations of the two users, RE: of the two users. It is a representative value (for example, "mean value", "median value", "mode value") obtained from each individual emotion value of the user. At this time, the group of users to be calculated for the team emotion value may be team Z, team Y, or the entire department X in the example of FIG. 6, and only users 900F, 900G, and 900H. It may be limited to executive employees, or it may be limited to general employees in department X, such as only users 900A, 900B, 900C, 900D, 900E. According to the above-mentioned calculation method, if there is data on the underlying individual emotional value and the occupational system, the team emotional value can be obtained for an arbitrarily set group. Further, the number of combinations of the above-mentioned users does not necessarily have to be 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 stronger the social relationship, the larger the value of the weighting coefficient may be. More specifically, the weighting coefficient corresponding to the strength "strong" of social relations may be larger than the weighting coefficient corresponding to the strength "medium" of social relations. Further, the weighting coefficient corresponding to the strength of social relation "medium" may be larger than the weighting coefficient corresponding to the strength of social relation "weak". Further, the weighting coefficient corresponding to the strength of social relation "weak" may be larger than the weighting coefficient corresponding to the strength of social relation "none".

In the present embodiment, it is mainly assumed that the individual emotion estimation unit 131 first estimates the individual emotion, and then the team emotion estimation unit 135 estimates the team emotion as a collective data thereof. However, the team emotion estimation unit 135 may estimate the team emotion directly from the sensor data of a plurality of people targeted by the team. In that case, the team emotion estimation unit 135 may perform a weighting calculation process corresponding to the above-mentioned strength of social relations on the sensor data value itself or its feature amount data (converted value).

At this time, the value of the sensor data itself or the feature amount data thereof is not particularly limited. As an example, the feature amount data of the sensor data may be the rate of change of the heart rate after being converted from the pulse detected by the pulse sensor. For example, the rate of change in heart rate can be the rate of change in heart rate, for example, the ratio of the current heart rate to the previous heart rate (eg, "heart rate increased by 20%", "heart rate increased". It may be represented by "10% decrease" etc.). The value of the sensor data itself or the feature amount data thereof may be used instead of the information indicating the individual emotion in estimating the team emotion.

FIG. 9 is an explanatory diagram showing an example of information showing individual feelings and information showing team feelings in a certain organization. FIG. 9 illustrates a table 122 of information indicating individual emotions and information indicating team emotions corresponding to an example of the organizational structure described with reference to FIG. 7. Here, the positiveness of quantitative data is illustrated as an example of information indicating individual emotions and information indicating team emotions.

Next, an example of the 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 team emotions and personal emotions estimated by the emotion estimation server 100 via the communication unit 410, visualizes them, and uses the presentation unit 450. And present it to the user. The user may be a user 900 whose team emotions and individual emotions are estimated, or a person different from the user 900 whose team emotions and individual emotions are estimated (for example, an industrial physician in charge of mental health management of an organization). Etc.).

In addition, when the control unit 430 visualizes and presents the information indicating the team emotion and the information indicating the individual emotion, the control unit 430 makes it easy for the user to understand the information by using the information indicating the social relationship based on the above-mentioned occupational system. Information indicating team emotions and information indicating individual emotions may be "categorized" and presented. For example, when the control unit 430 displays information indicating the team emotions of a certain team on the screen, the control unit 430 combines the information indicating the individual emotions of the members of the team with the information in the vicinity of the information indicating the team emotions, and the presentation unit 450. May be presented via. As a result, the user of the information presentation terminal 400 can intuitively grasp the information indicating the team emotion and the information indicating the individual emotion that is the calculation element thereof.

Further, for example, when the control unit 430 displays information indicating a plurality of team emotions by a plurality of teams on the screen, the teams having a stronger job relationship are closer to each other based on the information indicating the social relationship. Information indicating each other's team feelings may be presented via the presentation unit 450. As a result, the user of the information presenting terminal 400 can efficiently view the information indicating the team emotions of a plurality of teams based on the strength of the relationship of duties between the teams.

FIG. 10 is an explanatory diagram showing an example of an application screen of the information presentation terminal 400. Referring to FIG. 10, information indicating a certain team emotion (positive degree of team T1) of a certain team and information indicating individual emotion (positive degree of users U11 to U14 belonging to team T1) which is a calculation factor thereof are close to each other. Information indicating another team emotion of the same team (team T1 fatigue level) and information indicating individual emotions (fatigue level of users U11 to U14 belonging to team T1) displayed in the area of It is displayed in the nearby area. In this way, by presenting the information indicating the team emotion and the information indicating the individual emotion for each emotion category, the presentation unit 450 makes it easy to grasp the team emotion and the individual emotion for each category.

As shown in FIG. 10, the control unit 430 may have the past estimated information of team emotions and individual emotions presented as a history and present the information in a time-series graph (graph in FIG. 10). The right line segment of is shown as the current estimated information of team emotions and individual emotions, and the estimated information that goes back to the past is shown from the right end to the left).

Subsequently, an example of information processing according to the present embodiment will be described with reference to FIG. FIG. 11 is a flow chart 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 sets the parameters of the team to which the team emotion is estimated and its constituents, and the type of the estimated team emotion (for example, positiveness,) set by the administrator of the emotion estimation system. Corresponds to parameters of negativeness, confusion, etc., calculation method of team emotions (for example, selection of mean / median / mode as representative values, number of classifications of strength of social relations, strength of social relations) The parameters of the weighting coefficient value, etc.) are stored in the storage unit 120.

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 diverted, or the initial setting parameters may be used as they are. Good. In that case, the execution of this step S101 may be omitted.

In step S103, 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 for which the team emotion is estimated, via the sensor terminal 200. ..

In step S105, in the emotion estimation server 100, the individual emotion estimation unit 131 performs an individual emotion estimation process from the sensor data of the user 900. In the present embodiment, the process in which the individual emotion estimation unit 131 first estimates the individual emotion and then the team emotion estimation unit 135 estimates the team emotion as collective data of them 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 people targeted by the team. In that case, the team emotion estimation unit 135 may perform a weighting calculation process corresponding to the above-mentioned strength of social relations on the sensor data value itself or its feature amount data. In that case, the execution of this step S105 may be omitted.

In step S107, in the emotion estimation server 100, the communication unit 110 acquires the job system data of the user 900 who is a member of the team for which the team emotion is estimated from the job system DB server 300, and social relationship information. The management unit 133 generates the above-mentioned social NW information based on the job system 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 individual 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 the information indicating the team emotion acquired from the emotion estimation server 100 and the information indicating the individual emotion as the calculation element thereof. If the information presenting terminal 400 does not present the estimated team emotion information, the execution of this step S111 may be omitted.

As described above, according to the embodiment of the present invention, it is possible to automatically and highly accurately estimate team emotions based on individual emotions by using information indicating "formal" social relationships such as occupational data.

Although the preferred embodiments of the present invention have been described in detail with reference to the accompanying drawings, the present invention is not limited to such examples. It is clear that a person having ordinary knowledge in the field of technology to which the present invention belongs can come up with various modifications or modifications within the scope of the technical ideas described in the claims. , These are also naturally understood to belong to the technical scope of the present invention.

For example, in the above, an 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 (for example, the job title of the user) who visually recognizes the information presentation terminal 400.

100 Emotion estimation server 110 Communication unit 120 Storage unit 130 Control unit 131 Individual emotion estimation unit 133 Social relations information management department 135 Team emotion estimation unit 200 Sensor terminal 300 Occupational DB server 310 Communication unit 320 Storage unit 330 Control unit 400 Information presentation terminal 410 Communication unit 420 Storage unit 430 Control unit 440 Operation unit 450 Presentation unit

Claims (3)

The Social Relations Information Management Department, which generates information indicating social relations based on the job system data of multiple users,
A team emotion estimation unit that calculates a weighting coefficient based on the information indicating the social relationship and estimates the team emotion based on the sensor data of each of the plurality of users or the information based on the sensor data and the weighting coefficient. ,
Emotion estimation server. The team emotion estimation unit weights the sensor data or information based on the sensor data by the weighting coefficient, and sets the average value, median value, or mode value of the weighted data as the team emotion. calculate,
The emotion estimation server according to claim 1 . To generate information showing social relationships based on the job system data of multiple users,
To calculate the weighting coefficient based on the information indicating the social relationship,
Estimating team emotions based on the sensor data of each of the plurality of users or the information based on the sensor data and the weighting coefficient .
Emotion estimation methods, including.

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