WO2021134250A1

WO2021134250A1 - Emotion management method and device, and computer-readable storage medium

Info

Publication number: WO2021134250A1
Application number: PCT/CN2019/130021
Authority: WO
Inventors: 肖岚; 朱永胜
Original assignee: 深圳市易优斯科技有限公司
Priority date: 2019-12-30
Filing date: 2019-12-30
Publication date: 2021-07-08
Also published as: CN111149172B; CN111149172A

Abstract

An emotion management method, an emotion management device and a computer-readable storage medium. The method comprises: acquiring voice feature data and body feature data of a user (S10); processing the voice feature data and the body feature data, and determining a user emotion result (S20); and performing emotion management on the user according to the user emotion result and a preset rule (S30). The method can realize the function of discovering user emotion changes, and can realize the functions of managing and adjusting user emotions.

Description

Emotion management method, equipment and computer readable storage medium

Technical field

This application relates to the field of communication technology, and in particular to emotional management methods, devices, and computer-readable storage media.

Background technique

With the development of society, people’s material life has become more and more abundant. However, people’s happiness has not been continuously improved because of the satisfaction of material life. On the contrary, because of the various pressures brought by social competition, more and more Negative emotions appear in our lives. According to incomplete statistics, there are about 200 million Chinese people with varying degrees of mental illness. A conservative estimate is that 30 million Chinese people suffer from depression. The main reason for these mental illnesses is that people do not pay attention to their own management of their own emotions, and they accumulate over time, eventually leading to relatively serious mental illnesses, and even very bad consequences, such as suicide.

At present, the management of user emotions generally uses a camera to take pictures to obtain the user's facial information, and then uses image recognition to identify the user's facial information from the above-mentioned user's avatar, so as to know the user's emotions, but this recognition method The accuracy of facial expression recognition is low, which in turn leads to inaccurate judgment of user emotions and poor user experience. This user emotion management method cannot achieve the effect of managing and regulating user emotions.

Technical solutions

The main purpose of this application is to propose an emotion management method, device, and computer-readable storage medium, aiming to solve the technical problem that user emotions are not easy to find and user emotions are not easy to manage and adjust.

In order to achieve the above objective, the present application provides an emotion management method, which includes the following steps:

Obtain the user's voice feature data and physical feature data;

Processing the voice feature data and the physical feature data to determine the emotional result of the user;

Emotion management is performed on the user according to the user emotion result and preset rules.

In addition, in order to achieve the above object, the present application also provides a device, the device including: a memory, a processor, and an emotion management program stored on the memory and capable of running on the processor, the emotion management program When executed by the processor, the steps of the emotion management method as described above are realized.

In addition, in order to achieve the above-mentioned object, the present application also provides a computer-readable storage medium having an emotion management program stored on the computer-readable storage medium, and when the emotion management program is executed by a processor, the emotion management as described above is realized. Method steps.

This application provides an emotion management method, system, and computer-readable storage medium to obtain user voice feature data and physical feature data; process the voice feature data and the physical feature data to determine the user's emotional result; The user emotion results and preset rules perform emotion management on the user. Through the above method, the present application can realize the function of discovering the user's mood change, and realize the function of managing and adjusting the user's mood.

Description of the drawings

FIG. 1 is a schematic diagram of a terminal structure of a hardware operating environment involved in a solution of an embodiment of the present application;

2 is a schematic flowchart of the first embodiment of the emotion management method of this application;

FIG. 3 is a schematic flowchart of a second embodiment of the emotion management method of this application;

4 is a schematic flowchart of a third embodiment of the emotion management method of this application;

FIG. 5 is a schematic flowchart of a fourth embodiment of the emotion management method of this application.

The realization, functional characteristics, and advantages of the purpose of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings.

Embodiments of the present invention

It should be understood that the specific embodiments described here are only used to explain the application, and are not used to limit the application.

The main solution of the embodiment of this application is: obtain the user's voice feature data and physical feature data; process the voice feature data and the physical feature data to determine the user's emotional result; according to the user's emotional result and preset The rules perform emotional management on the user.

The existing management methods of user emotions generally use a camera to take pictures to obtain the user's facial information, and then use image recognition to recognize the user's facial information from the above-mentioned user's avatar, thereby knowing the user's emotions, but this recognition The method has low accuracy in facial expression recognition, which in turn leads to inaccurate judgment of user emotions and poor user experience. This user emotion management method cannot achieve the effect of managing and regulating user emotions.

This application aims to solve the technical problem that user emotions are not easy to find, and user emotions are not easy to manage and adjust.

As shown in FIG. 1, FIG. 1 is a schematic diagram of a terminal structure of a hardware operating environment involved in a solution of an embodiment of the present application.

The terminal in the embodiment of the present application may be a PC, or a mobile terminal device with a display function, such as a smart phone or a tablet computer.

As shown in FIG. 1, the terminal may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002. Among them, the communication bus 1002 is used to implement connection and communication between these components. The user interface 1003 may include a display screen (Display) and an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 may be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a magnetic disk memory. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

Preferably, the terminal may also include a camera, RF (Radio Frequency (radio frequency) circuits, sensors, audio circuits, WiFi modules, etc. Among them, sensors such as light sensors, motion sensors and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor. The ambient light sensor can adjust the brightness of the display screen according to the brightness of the ambient light, and the proximity sensor can turn off the display screen and/or when the mobile terminal is moved to the ear. Backlight. As a kind of motion sensor, the gravity acceleration sensor can detect the magnitude of acceleration in various directions (usually three axes). It can detect the magnitude and direction of gravity when it is stationary. It can be used for applications that recognize the posture of the mobile terminal (such as horizontal and vertical screen switching, Related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, percussion), etc.; of course, the mobile terminal can also be equipped with other sensors such as gyroscope, barometer, hygrometer, thermometer, infrared sensor, etc. No longer.

Those skilled in the art can understand that the terminal structure shown in FIG. 1 does not constitute a limitation on the terminal, and may include more or less components than shown in the figure, or combine some components, or arrange different components.

As shown in FIG. 1, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an emotion management program.

In the terminal shown in FIG. 1, the network interface 1004 is mainly used to connect to the back-end server and communicate with the back-end server; the user interface 1003 is mainly used to connect to the client (user side) and communicate with the client; and the processor 1001 can be used to call the emotion management program stored in the memory 1005 and perform the following operations:

Acquire voice feature data and physical feature data of the user; process the voice feature data and the physical feature data to determine the user's emotional result; perform emotional management on the user according to the user's emotional result and preset rules.

Further, the processor 1001 may call the emotion management program stored in the memory 1005, and also perform the following operations:

Emotion management is performed on the user according to the user emotion result and preset music rules.

Perform emotional management on the user according to the user emotional result and preset coaching rules.

When the user emotion result is a preset emotion result, sending the user emotion result to an emotion management agency;

Receiving emotional intervention information returned by the emotional management agency according to the user emotional result;

Emotion management is performed on the user according to the emotional intervention information.

Processing the voice feature data to obtain user voice emotion results;

Processing the physical feature data to obtain a result of the user's physical emotions;

The user's voice emotion result is verified according to the user's physical emotion result, and the user's emotion result is determined.

Obtain the emotion-related data of the interlocutor;

Processing the emotion-related data to obtain the emotional result of the interlocutor;

The step of performing emotion management on the user according to the user emotion result and preset rules includes:

Emotion management of the user is performed according to the user emotional result, the interlocutor's emotional result and preset rules.

Sending the voice feature data and the body feature data to a server;

Receiving the user's emotional result returned by the server according to the voice feature data and the physical feature data.

Denoising processing is performed on the voice feature data and the body feature data.

Based on the above hardware structure, an embodiment of the emotion management method of the present application is proposed.

The emotional management method of this application.

Referring to FIG. 2, FIG. 2 is a schematic flowchart of the first embodiment of the emotion management method of this application.

In the embodiment of the present application, the emotion management method is applied to an emotion management device, and the emotion management method includes:

Step S10: Acquire voice feature data and body feature data of the user;

In this embodiment, in order to reduce the influence of the user due to emotional fluctuations or to give the user appropriate emotional adjustment when the user experiences emotional fluctuations, the emotion management device actively acquires the user's voice characteristics at preset time intervals Data and physical characteristics data. Among them, the emotion management device may be a wearable device used by the user, such as smart glasses, smart bracelet or wireless earphones, etc.; the emotion management device may be provided with a microphone for acquiring user voice characteristic data; the emotion management device may also be provided with a human sensor, The human body sensor is used to obtain the user's brain waves, skin conductivity, and heart rate; the emotion management device may also be provided with an acceleration sensor for obtaining whether the user's body is in a weightless state; the emotion management device may also be set with a temperature for obtaining the user's body temperature Sensor; Emotion management equipment can also be a mobile terminal; Emotion management equipment can also be a mobile terminal; Emotion management equipment can also be a device used by an emotion recognition agency to recognize user emotions; Among them, the voice feature data is through the microphone of the emotion management device or other The voice data of the user's speech collected by the microphone of the collection device; wherein the physical feature data can be the data of the physical feature of the user's speech collected by the human body sensor, acceleration sensor and/or temperature sensor of the emotion management device; the physical feature data can also be Data of the user’s speaking body characteristics collected by the human body sensor, acceleration sensor and/or temperature sensor of other collection equipment; the body characteristic data may include: the user’s brain waves, the user’s skin conductivity, the user’s heart rate data, and the user’s body temperature Data, user's blood pressure data, etc. Among them, the preset time interval is set to facilitate timely judgment and detection of user emotions, and can be set to 1s-1min, and specifically can be set to 3s, 4s, 5s, 6s, 10s, etc.

Step S10, after acquiring the user's voice feature data and body feature data, may include:

Step a: Perform denoising processing on the voice feature data and body feature data.

In this embodiment, the emotion management device calculates optimized parameters of the voice feature data and the physical feature data, and the optimized parameters include directivity parameters and gain parameters.

Step S20, processing the voice feature data and the physical feature data to determine the emotional result of the user;

In this embodiment, after the emotion management device obtains the user's voice feature data and physical feature data, the emotion management device processes the user's voice feature data and physical feature data to obtain the user's voice and emotion results. Among them, the user emotion result is obtained after processing and calculating the user's voice feature data and the user's physical feature data.

Step S30: Perform emotional management on the user according to the user emotional result and preset rules.

In this embodiment, after the emotion management device obtains the user emotion result, the emotion management device performs emotion management on the user according to the user emotion result and preset rules.

For example, when the user’s user voice emotion result is happy, the user will not be emotionally managed; when the user’s user voice emotion result is angry, play a beautiful music to the user, or tell the user a fable, transfer The user's attention; when the user's user voice emotion results in sadness, tell a joke to the user.

Step S30 performing emotional management on the user according to the user emotional result and preset rules may include:

Step b: Perform emotional management on the user according to the user emotional result and preset music rules.

In this embodiment, after the emotion management device obtains the user emotion result, the emotion management device performs emotion management on the user according to the user emotion result and preset music rules. Among them, the preset music rule can be a rule that adjusts the user's emotions through music according to the obtained user emotional results. For example, when the user's emotional result is angry, play a beautiful piece of music to the user, or play the user's emotions. The volume of the music is adjusted to achieve the rules that ease the user's emotions.

Step c: Perform emotional management on the user according to the user emotional result and preset coaching rules.

In this embodiment, after the emotion management device obtains the user emotion result, the emotion management device performs emotion management on the user according to the user emotion result and preset coaching rules. Among them, the preset coaching rule can be based on the obtained user emotion results, the emotion management device recommends the coach role corresponding to the user emotion results to the user, and broadcasts a paragraph of language or a paragraph of language story to the user for the attention and environment of professional users. The user's emotions.

Step d1, when the user emotion result is a preset emotion result, sending the user emotion result to an emotion management agency;

Step d2, receiving emotional intervention information returned by the emotional management agency according to the user emotional result;

Step d3: Perform emotional management on the user according to the emotional intervention information.

In this embodiment, when the user emotion result is an extreme emotion result, or when the user emotion result is that the emotion management device cannot handle the emotion result, the emotion management structure sends the user emotion management result to the emotion management organization, so that the emotion management Institutions to judge and provide opinions on emotional management; after the emotional management agency receives the user emotional results sent by the emotional management device, the emotional management agency processes and judges the user emotional results, and obtains emotional intervention information that is intervened by the emotional management device. The emotional management agency sends the emotional intervention information to the emotional management device, and the emotional management device receives the emotional intervention information returned by the emotional management agency and the user’s emotional results. After the emotional management device receives the emotional intervention information, the emotional management device responds to the user based on the emotional intervention information. Emotion management is carried out to regulate the user’s emotions; among them, the emotional intervention information can be information that stimulates the user’s body to regulate the user’s emotions when the user’s emotional results are more serious, and the emotional intervention information can also be when the emotional results are more serious. Recommend the emotion management equipment to the corresponding emotion treatment institution, and recommend to the family of the user to transfer the user to the emotion treatment institution for treatment.

This embodiment obtains the user’s voice feature data and physical feature data through the above-mentioned solution; processes the voice feature data and the physical feature data to determine the user’s emotional result; and compares all users according to the user’s emotional result and preset rules. The user performs emotional management. As a result, the function of discovering the user's mood changes in time is realized, and the function of managing and adjusting the user's mood is realized.

Further, referring to FIG. 3, FIG. 3 is a schematic flowchart of a second embodiment of the emotion management method of this application. Based on the embodiment shown in FIG. 2 above, the step S20 to process the voice feature data and the physical feature data to determine the emotional result of the user may include:

Step S21, processing the voice feature data to obtain a voice emotion result of the user;

In this embodiment, after the emotion management device obtains the voice feature data of the user, the emotion management device processes the voice feature data of the user to obtain the voice emotion result of the user. Among them, the user's voice emotion result is obtained after processing and calculating the user's voice feature data.

Step e1: Recognizing keyword information and intonation information included in the voice feature data;

In this embodiment, the emotion management device extracts keyword information and intonation information from the voice feature data, where the intonation information includes at least one of the volume, speech rate, pitch, and respective change trends of the voice data. Exemplarily, the word segmentation database can be used to remove meaningless words in the semantic content, and at the same time extract keyword information that can indicate the user's emotion; for the recognized intonation, filter out the intonation information that meets the preset conditions, exemplary, The volume exceeds the maximum preset threshold and the minimum preset threshold is filtered out as a target intonation, or the speech rate exceeds a certain preset threshold is also used as intonation information.

Step e2: Generate a voice emotion model according to the keyword information and the intonation information, and match the voice emotion model with the voice standard emotion model in the emotion model library to generate a user voice emotion result.

In this embodiment, the emotion management device generates a voice emotion model according to the keyword information and intonation information, and matches the voice emotion model with the voice standard emotion model in the emotion model library to generate a user voice emotion result.

Step e2, generating a voice emotion model based on the keyword information and the intonation information, and matching the voice emotion model with the voice standard emotion model in the emotion model library to generate a user voice emotion result, which may include:

Step e21: Determine voice feature points according to the keyword information and the intonation information;

In this embodiment, the recognized keyword information and intonation information are further analyzed and screened, and keywords and intonations that can clearly indicate the user's emotions are determined as voice feature points. The voice feature points include keyword feature points and intonation. Feature points. Exemplarily, the keyword information can be screened through the emotionally sensitive word database established in advance, and the filtered keyword information can be determined as the keyword feature points. The emotionally sensitive word database includes the user's various emotions. Frequently said vocabulary. Since the intonation information is usually displayed in the form of a waveform graph, the points with a more obvious change trend can be used as the characteristic points of intonation, such as the point where the speech speed suddenly increases.

Step e22: Generate a voice emotion model according to the voice feature points, and calibrate the voice feature points in the voice emotion model;

In this embodiment, a voice emotion model is generated according to the determined voice feature points, so as to analyze user emotions according to the voice emotion model. The voice feature points are calibrated on the voice emotion model, where the voice feature points can be the more prominent part of the voice feature points determined in, thereby realizing further screening of the user's emotional characteristics, making the user's emotional characteristics more obvious .

Step e23: Match the voice emotion model with the voice standard emotion model in the emotion model library to adjust the calibrated voice feature points on the voice emotion model, and record the voice feature change data of the voice feature points ；

In this embodiment, the emotion management device matches the voice emotion model with the voice standard emotion model in the emotion model library to adjust the calibrated voice feature points on the voice emotion model for fine-tuning, and record the voice features of the voice feature points Change data. The voice standard emotion model can be established based on the user's daily voice data and the expression corresponding to the daily voice data.

Step e22: Match the voice feature change data with the intonation feature data and the psychological behavior feature data in the emotion model library, and generate a user voice emotion result according to the matching result.

In this embodiment, according to the matching result of the voice feature change data of the voice feature point with the intonation feature data and the mental behavior feature data in the emotion model library, the user's emotion or emotion change data is output.

Step S22, processing the physical feature data to obtain a result of the user's physical emotions;

In this embodiment, after the emotion management device obtains the physical feature data of the user, the emotion management device processes the physical feature data of the user to obtain the result of the user's physical emotion. Among them, the result of the user's physical emotion is obtained after processing and calculating the user's physical feature data.

Step S23, verifying the user's voice emotion result according to the user's physical emotion result, and determining the user's emotion result;

In this embodiment, the emotion management device compares the user's physical emotion result and the user's voice emotion result respectively at the same time point. If the user's physical emotion result at a time point is different from the user voice emotion result, the time point is deleted If the user’s physical emotion result at a time point is the same as the user’s voice emotion result, the user’s voice emotion result at that time point will be retained; when the emotion management device compares the user’s voice emotion result within the preset time interval to After the physical feature time information is all compared one by one, the user voice emotion results after the user voice emotion results with different comparison results are deleted, and the user voice emotion results are searched.

This embodiment obtains the user’s voice feature data and physical feature data through the above solution; processes the voice feature data to obtain the user’s voice emotion results; processes the physical feature data to obtain the user’s physical emotion results; The result of the user's body emotion verifies the result of the user's voice emotion, and determines the result of the user's emotion; and the emotion management of the user is performed according to the result of the user's emotion and preset rules. As a result, the function of discovering the user's mood changes in time is realized, and the function of managing and adjusting the user's mood is realized.

Further, referring to FIG. 4, FIG. 4 is a schematic flowchart of a third embodiment of the emotion management method of this application. In order to manage the user's emotions more accurately, based on the embodiment shown in FIG. 3 above, after obtaining the user's voice feature data and physical feature data in step S10, it may include:

Step S40: Obtain emotion-related data of the interlocutor;

In this embodiment, after the emotion management device obtains the user's voice feature data and physical feature data, the emotion management device can obtain the emotion-related data of the interlocutor with the user; wherein the emotion-related data may be the interlocutor's voice data, which can be It is the face data of the conversation person, and it can also be the special diagnosis data of the conversation person's body; among them, the emotion management device can be equipped with a camera for obtaining the face data of the conversation person; among them, the voice feature data of the conversation person's face data is through the emotion management device The voice data of the user's speech collected by the microphone of the microphone or the microphone of other collection devices; wherein the voice feature data of the face data of the conversation person is the face data of the conversation person collected through the camera of the emotion management device or the head of the other collecting device.

Step S50, processing the emotion-related data to obtain the emotion result of the interlocutor;

In this embodiment, after the emotion management device obtains the emotion-related data of the interlocutor, the emotion management device processes the emotion-related data to obtain the emotion result of the interlocutor. Among them, the emotion result of the interlocutor is obtained after processing and calculating the emotion-related data of the interlocutor.

Step S40 obtains the emotion-related data of the interlocutor, which may include:

Step f1: Obtain the interlocutor's voice data and interlocutor's face data of the interlocutor;

In this embodiment, after the emotion management device obtains the voice feature data and physical feature data of the user, the emotion management device can obtain the voice data of the conversation person and the face data of the conversation person with the user.

Step S50, the processing the emotion-related data to obtain the result of determining the emotion of the interlocutor may include:

Step g1, processing the voice data of the interlocutor to obtain the result of the interlocutor's voice emotion;

In this embodiment, after the emotion management device obtains the interlocutor's voice data of the interlocutor, the emotion management device processes the interlocutor's voice data of the interlocutor to obtain the result of the interlocutor's voice emotion. Among them, the voice emotion result of the interlocutor is obtained after processing and calculating the voice data of the interlocutor.

Step g2, processing the face data of the conversation person to obtain the face emotion result of the conversation person;

In this embodiment, after the emotion management device obtains the face data of the conversation person, the emotion management device processes the face data of the conversation person to obtain the face emotion result of the conversation person. Among them, the face emotion result of the conversation person is obtained after processing and calculating the face data of the conversation person.

Step g2 processes the face data of the conversation person to obtain the emotion result of the conversation person's face, which may include:

Step g21: Recognizing the face image information of the conversation person included in the face data of the conversation person;

In this embodiment, the emotion management device extracts the face image information of the conversation person from the face data of the conversation person; wherein the face image information of the conversation person may be used for image information representing the expression of the conversation person, for example, representing the conversation person A happy image, an image that expresses the sadness of the interlocutor, and an image that expresses the anger of the interlocutor; the emotion management device can be used to remove images without user facial expressions in the facial image information of the interlocutor or the facial expressions of the interlocutor due to the rapid rotation or movement of the interlocutor Unclear face image.

Step g22: Generate a face emotion model of the conversation person according to the face image information of the conversation person, and match the face emotion model of the conversation person with the standard emotion model of the face in the emotion model library to generate a face emotion result of the conversation person.

In this embodiment, the emotion management device generates a dialogue face emotion model based on the face image information of the dialogue person, and matches the dialogue face emotion model with the standard emotion model of the face in the emotion model library to generate the dialogue face emotion result.

Step g22 generates a face emotion model of the dialogue person according to the face image information of the dialogue person, and matches the face emotion model of the dialogue person with the standard emotion model of the face in the emotion model library to generate a face emotion result of the dialogue person. include:

Step g221: Determine the facial emotion feature points of the conversation person according to the face image information of the conversation person;

In this embodiment, the emotion management device further analyzes and filters the recognized face image information of the conversation person to determine the face image of the conversation person that can clearly show the expression of the conversation person, that is, determine the face emotion characteristics of the conversation person point.

Step g222, generating a facial emotion model of the dialogue person according to the facial emotion feature points of the dialogue person, and marking the facial emotion feature points of the dialogue person on the facial emotion model of the dialogue person;

In this embodiment, the emotion management device generates a facial emotion model of the dialogue person according to the determined facial emotion feature points of the dialogue person, so as to analyze the emotion of the dialogue person according to the facial emotion model of the dialogue person. The face emotion feature points of the dialogue person are calibrated on the face emotion model of the dialogue person. Among them, the face emotion feature points of the dialogue person can be a more prominent part of the facial emotion feature points determined in The further screening of emotional characteristics makes the emotional characteristics of the interlocutor more obvious.

Step g223: Match the face emotion model of the dialog person with the standard emotion model of the face in the emotion model library to adjust the calibrated emotional feature points of the face of the dialog person on the emotion model of the dialog person, and record all The face change data of the dialogue person describing the emotional feature points of the dialogue person's face;

In this embodiment, the emotion management device will match the facial emotion model of the dialogue person with the standard emotion model of the face in the emotion model library to adjust the calibrated facial emotion feature points of the dialogue person’s facial emotion model. And record the face feature change data of the dialogue person's facial emotion feature points.

Step g224 matches the face feature change data of the conversation person with the facial expression feature data in the emotion model library and the psychological behavior feature data, and generates a face emotion result of the conversation person according to the matching result.

In this embodiment, the emotion management device outputs the facial emotion result of the dialogue person according to the matching result of the dialogue person's facial feature change data of the dialogue person's facial feature points and the expression feature data and mental behavior characteristic data in the emotion model library.

Step g3, verifying the voice emotion result of the interlocutor according to the facial emotion result of the interlocutor, and determining the emotion result of the interlocutor.

In this embodiment, the emotion management device compares the facial emotion result of the conversation person and the speech emotion result of the conversation person at the same time point. If the facial emotion result of the conversation person at a time point is different from the voice emotion result of the conversation person , Delete the conversational person’s voice emotion result at that time point; if the conversational person’s facial emotion result at a time point is the same as the conversation person’s voice emotion result, the conversational person’s voice emotion result at that time point will be retained; The voice emotion results of the interlocutor within the preset time interval and the physical feature time information are all compared one by one, the interlocutor’s voice emotion results after the different interlocutor’s voice emotion results will be deleted and the interlocutor’s voice emotion results will be searched. .

In step S30, performing emotional management on the user according to the user emotional result and preset rules may include:

Step S31: Perform emotional management on the user according to the emotional result of the user, the emotional result of the interlocutor and preset rules.

In this embodiment, after the emotion management device obtains the emotion result of the conversation person and the emotion result of the user, the emotion management device performs emotion management on the user according to the emotion result of the user, the emotion result of the conversation person, and preset rules.

This embodiment obtains the user’s voice feature data and physical feature data through the above solution; obtains the emotion-related data of the conversation person; processes the emotion-related data to obtain the emotion result of the conversation person; compares the voice feature data and the The physical feature data is processed to determine the emotional result of the user; the emotional management of the user is performed according to the emotional result of the user, the emotional result of the interlocutor and preset rules. As a result, the function of discovering the user's mood changes in time is realized, and the function of managing and adjusting the user's mood is realized.

Further, referring to FIG. 5, FIG. 5 is a schematic flowchart of a fourth embodiment of the emotion management method of this application. Based on the embodiment shown in FIG. 2 above, after obtaining the user's voice feature data and body feature data in step S20, it may further include:

Step S24, sending the voice feature data and the body feature data to a server;

Step S25: Receive a user emotional result returned by the server according to the voice feature data and the physical feature data.

In this embodiment, after the emotion management device obtains the user's voice feature data and physical feature data, the emotion management device can send the user's voice feature data and physical feature data to the cloud server for processing; so that the cloud server can receive the voice After the feature data and physical feature data, the cloud server processes the voice feature data and physical feature data. The cloud server obtains the user's emotional results based on the voice feature data and physical feature data, and the cloud server sends the obtained user emotional results to the emotional management device. The emotion management device receives the user emotion result returned by the cloud server according to the voice feature data and the physical feature data.

This embodiment obtains the voice feature data and physical feature data of the user through the above-mentioned solution; sends the voice feature data and the physical feature data to the server; receives the server according to the voice feature data and the physical feature data Returned user emotional results; emotional management of the user according to the user emotional results and preset rules. As a result, the function of discovering the user's mood changes in time is realized, and the function of managing and adjusting the user's mood is realized.

The application also provides an emotion management device.

The emotion management device of the present application includes: a memory, a processor, and an emotion management program stored on the memory and capable of running on the processor, and the emotion management program is executed by the processor to realize the emotions described above Steps of the management method.

For the method implemented when the emotion management program running on the processor is executed, please refer to each embodiment of the emotion management method of the present application, which will not be repeated here.

The application also provides a computer-readable storage medium.

An emotion management program is stored on the computer-readable storage medium of the present application, and when the emotion management program is executed by a processor, the steps of the above-mentioned emotion management method are realized.

It should be noted that in this article, the terms "include", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements not only includes those elements, It also includes other elements that are not explicitly listed, or elements inherent to the process, method, article, or system. If there are no more restrictions, the element defined by the sentence "including a..." does not exclude the existence of other identical elements in the process, method, article, or system that includes the element.

The serial numbers of the foregoing embodiments of the present application are for description only, and do not represent the advantages and disadvantages of the embodiments.

Through the description of the above implementation manners, those skilled in the art can clearly understand that the above-mentioned embodiment method can be implemented by means of software plus the necessary general hardware platform, of course, it can also be implemented by hardware, but in many cases the former is better.的实施方式。 Based on this understanding, the technical solution of this application essentially or the part that contributes to the existing technology can be embodied in the form of a software product, and the computer software product is stored in a storage medium (such as ROM/RAM) as described above. , Magnetic disks, optical disks), including several instructions to make a terminal device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) execute the method described in each embodiment of the present application.

The above are only the preferred embodiments of the application, and do not limit the scope of the patent for this application. Any equivalent structure or equivalent process transformation made using the content of the description and drawings of the application, or directly or indirectly applied to other related technical fields , The same reason is included in the scope of patent protection of this application.

Claims

An emotion management method, wherein the emotion management method includes the following steps:

Obtain the user's voice feature data and physical feature data;

Processing the voice feature data and the physical feature data to determine the emotional result of the user;

Emotion management is performed on the user according to the user emotion result and preset rules.
5. The emotion management method according to claim 1, wherein the step of performing emotion management on the user according to the user emotion result and preset rules comprises:

Emotion management is performed on the user according to the user emotion result and preset music rules.
5. The emotion management method according to claim 1, wherein the step of performing emotion management on the user according to the user emotion result and preset rules comprises:

Perform emotional management on the user according to the user emotional result and preset coaching rules.
5. The emotion management method according to claim 1, wherein the step of performing emotion management on the user according to the user emotion result and preset rules comprises:

When the user emotion result is a preset emotion result, sending the user emotion result to an emotion management agency;

Receiving emotional intervention information returned by the emotional management agency according to the user emotional result;

Emotion management is performed on the user according to the emotional intervention information.
8. The emotion management method according to claim 1, wherein the step of processing the voice feature data and the physical feature data to determine the emotional result of the user comprises:

Processing the voice feature data to obtain user voice emotion results;

Processing the physical feature data to obtain a result of the user's physical emotions;

The user's voice emotion result is verified according to the user's physical emotion result, and the user's emotion result is determined.
5. The emotion management method according to claim 5, wherein after the step of obtaining the user's voice feature data and physical feature data, the method comprises:

Obtain the emotion-related data of the interlocutor;

Processing the emotion-related data to obtain the emotional result of the interlocutor;

The step of performing emotion management on the user according to the user emotion result and preset rules includes:

Emotion management of the user is performed according to the user emotional result, the interlocutor's emotional result and preset rules.
8. The emotion management method according to claim 1, wherein the step of processing the voice feature data and the physical feature data to determine the emotional result of the user comprises:

Sending the voice feature data and the body feature data to a server;

Receiving the user's emotional result returned by the server according to the voice feature data and the physical feature data.
5. The emotion management method according to claim 1, wherein the step of obtaining the user's voice feature data and body feature data includes:

Denoising processing is performed on the voice feature data and the body feature data.
An emotion management device, wherein the emotion management device includes a memory, a processor, and an emotion management program stored in the memory and running on the processor, and the emotion management program is executed by the processor When implementing the following steps:

Obtain the user's voice feature data and physical feature data;

Processing the voice feature data and the physical feature data to determine the emotional result of the user;

Emotion management is performed on the user according to the user emotion result and preset rules.
9. The emotion management device of claim 9, wherein the following steps are implemented when the emotion management program is executed by the processor:

Emotion management is performed on the user according to the user emotion result and preset music rules.
9. The emotion management device of claim 9, wherein the following steps are implemented when the emotion management program is executed by the processor:

Perform emotional management on the user according to the user emotional result and preset coaching rules.
9. The emotion management device of claim 9, wherein the following steps are implemented when the emotion management program is executed by the processor:

When the user emotion result is a preset emotion result, sending the user emotion result to an emotion management agency;

Receiving emotional intervention information returned by the emotional management agency according to the user emotional result;

Emotion management is performed on the user according to the emotional intervention information.
9. The emotion management device of claim 9, wherein the following steps are implemented when the emotion management program is executed by the processor:

Processing the voice feature data to obtain user voice emotion results;

Processing the physical feature data to obtain a result of the user's physical emotions;

The user's voice emotion result is verified according to the user's physical emotion result, and the user's emotion result is determined.
The emotion management device according to claim 13, wherein the following steps are implemented when the emotion management program is executed by the processor:

Obtain the emotion-related data of the interlocutor;

Processing the emotion-related data to obtain the emotional result of the interlocutor;

The step of performing emotion management on the user according to the user emotion result and preset rules includes:

Emotion management of the user is performed according to the user emotional result, the interlocutor's emotional result and preset rules.
9. The emotion management device of claim 9, wherein the following steps are implemented when the emotion management program is executed by the processor:

Sending the voice feature data and the body feature data to a server;

Receiving the user's emotional result returned by the server according to the voice feature data and the physical feature data.
9. The emotion management device of claim 9, wherein the emotion management program is executed by the processor to implement the following steps:

Denoising processing is performed on the voice feature data and the body feature data.
A computer-readable storage medium, wherein an emotion management program is stored on the computer-readable storage medium, and when the emotion management program is executed by a processor, the following steps are implemented:

Obtain the user's voice feature data and physical feature data;

Processing the voice feature data and the physical feature data to determine the emotional result of the user;

Emotion management is performed on the user according to the user emotion result and preset rules.
17. The computer-readable storage medium of claim 17, wherein the emotion management program implements the following steps when being executed by the processor:

Emotion management is performed on the user according to the user emotion result and preset music rules.
17. The computer-readable storage medium of claim 17, wherein the emotion management program implements the following steps when being executed by the processor:

Processing the voice feature data to obtain user voice emotion results;

Processing the physical feature data to obtain a result of the user's physical emotions;

The user's voice emotion result is verified according to the user's physical emotion result, and the user's emotion result is determined.
The computer-readable storage medium of claim 19, wherein the emotion management program implements the following steps when being executed by the processor:

Obtain the emotion-related data of the interlocutor;

Processing the emotion-related data to obtain the emotional result of the interlocutor;

The step of performing emotion management on the user according to the user emotion result and preset rules includes:

Emotion management of the user is performed according to the user emotional result, the interlocutor's emotional result and preset rules.