Data processing method, device and equipment and readable storage medium

Abstract

The invention discloses a data processing method, device and equipment and a readable storage medium, and belongs to the technical field of electronic equipment. The data processing method comprises the following steps: acquiring emotion analysis data of a user; the emotion analysis data comprises at least one of the following items: electronic equipment use data, physiological data, historical emotion data, schedule information and first interaction information input by a user; and outputting second interaction information according to the emotion analysis data through the artificial intelligence emotion assistant.

Description

Technical Field

[0001] The present application belongs to the technical field of electronic equipment, and specifically relates to a data processing method, apparatus, device and readable storage medium. Background Art

[0002] In modern society, people have more and more psychological problems due to factors such as work, study, interpersonal relationships, economy and family.

[0003] In order to solve psychological problems, people usually seek psychological counseling from others and use psychological counseling to regulate emotions and solve psychological problems. However, since psychological counseling requires appointments, psychological problems cannot be solved in a timely manner, that is, the timeliness of solving psychological problems is poor. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a data processing method, device, equipment and readable storage medium, which can improve the timeliness of solving psychological problems.

[0005] In a first aspect, an embodiment of the present application provides a data processing method, including:

[0006] Acquire the user's emotion analysis data; the emotion analysis data includes at least one of the following: electronic device usage data, physiological data, historical emotion data, schedule information, and first interaction information input by the user;

[0007] The second interactive information is outputted according to the sentiment analysis data by an artificial intelligence (AI) sentiment assistant.

[0008] In a second aspect, an embodiment of the present application provides a data processing device, including:

[0009] An acquisition module, used to acquire the user's emotion analysis data; the emotion analysis data includes at least one of the following: electronic device usage data, physiological data, historical emotion data, schedule information, and first interaction information input by the user;

[0010] The output module is used to output the second interaction information according to the emotion analysis data through the artificial intelligence emotion assistant.

[0011] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the programs or instructions are executed by the processor, the steps of the data processing method provided in the embodiment of the present application are implemented.

[0012] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the data processing method provided in the embodiment of the present application are implemented.

[0013] In a fifth aspect, an embodiment of the present application provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the steps of the data processing method provided in the embodiment of the present application.

[0014] In a sixth aspect, an embodiment of the present application provides a computer program product, which is stored in a storage medium and is executed by at least one processor to implement the steps of the data processing method provided in the embodiment of the present application.

[0015] In the embodiment of the present application, by obtaining the user's emotion analysis data; the emotion analysis data includes at least one of the following: electronic device usage data, physiological data, historical emotion data, schedule information, and first interaction information input by the user; the second interaction information is outputted by the artificial intelligence emotion assistant according to the emotion analysis data. In this way, there is no need to make an appointment for psychological consultation, and the artificial intelligence emotion assistant can output the interaction information in time according to the emotion analysis data, which can improve the timeliness of solving psychological problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flowchart of a data processing method provided in an embodiment of the present application;

[0017] Figure 2 is a schematic diagram of an interactive interface of an artificial intelligence emotion assistant provided in an embodiment of the present application;

[0018] Figure 3 is a schematic diagram of a virtual image provided in an embodiment of the present application;

[0019] Figure 4 is a structural schematic diagram of a data processing device provided in an embodiment of the present application;

[0020] Figure 5 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0021] Figure 6 It is a schematic diagram of the hardware structure of an electronic device implementing an embodiment of the present application. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0023] The terms "first", "second", etc. in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms used in this way are interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0024] The data processing method, apparatus, device and medium provided in the embodiments of the present application are described in detail below with reference to the accompanying drawings through specific embodiments and their application scenarios.

[0025] Figure 1 : is a flow chart of a data processing method provided in an embodiment of the present application. The data processing method may include:

[0026] Step 101: Acquire emotion analysis data of the user; the emotion analysis data includes at least one of the following: electronic device usage data, physiological data, historical emotion data, schedule information, and first interaction information input by the user;

[0027] The electronic device usage data in the embodiments of the present application includes, but is not limited to: content browsed or listened to by the user, the user's social interaction data, etc. The user's social interaction data is not limited to session data, call data, and email data, etc.; the electronic device usage data includes, for example, web pages browsed by the user, songs listened to by the user, chat records, etc.

[0028] The physiological data in the embodiments of the present application include but are not limited to the user's heart rate, blood pressure data, etc.

[0029] The historical emotion data in the embodiment of the present application may be the emotions of the user within a certain period of history.

[0030] The schedule information in the embodiment of the present application may include the user's schedule.

[0031] The first interaction information in the embodiment of the present application may be information input to the artificial intelligence emotion assistant when the user interacts with the artificial intelligence emotion assistant.

[0032] Step 102: Output second interaction information according to the emotion analysis data through the artificial intelligence emotion assistant.

[0033] In some possible implementations of the embodiments of the present application, in step 102, the emotion analysis data may be input into the artificial intelligence emotion assistant, and the artificial intelligence emotion assistant outputs interaction information corresponding to the emotion analysis data. It is understandable that the interaction information corresponding to the emotion analysis data input into the artificial intelligence emotion assistant is the second interaction information.

[0034] The second interactive information in the embodiment of the present application includes but is not limited to: emotion regulation information, recommendation information of emotion regulation courses. The emotion regulation information in the embodiment of the present application includes but is not limited to: recommendation information of emotion regulation behavior and emotion relief information.

[0035] In the embodiment of the present application, the emotion analysis data of the user is obtained; the emotion analysis data includes at least one of the following: electronic device usage data, physiological data, historical emotion data, schedule information, and first interaction information input by the user; the second interaction information is outputted by the artificial intelligence emotion assistant according to the emotion analysis data. In this way, there is no need to make an appointment for psychological consultation, and the interaction information can be outputted according to the emotion analysis data by the artificial intelligence emotion assistant, which can improve the timeliness of solving psychological problems.

[0036] In some possible implementations of the embodiments of the present application, when the second interaction information includes emotion regulation information, before step 102, the data processing method provided by the embodiments of the present application may also include: determining the emotion type based on the emotion analysis data; and determining the emotion regulation information based on the emotion type.

[0037] In some possible implementations of the embodiments of the present application, an emotion category recognition model for identifying emotion types may be pre-trained, and emotion regulation information corresponding to different emotion types may be set, and the emotion category recognition model may be configured in an artificial intelligence emotion assistant, wherein the emotion types include but are not limited to happiness, anger, sadness, fear, anxiety, depression, tension, etc. After the acquired emotion analysis data is input into the emotion category recognition model in the artificial intelligence emotion assistant, the emotion category recognition model outputs the emotion type corresponding to the emotion analysis data, and then determines the emotion regulation information corresponding to the emotion type output by the emotion category recognition model according to the pre-set emotion type and emotion regulation information, and then outputs the emotion regulation information.

[0038] For example, when it is determined that the user is anxious, the user may be recommended to do outdoor exercise or take several deep breaths.

[0039] In some possible implementations of the embodiments of the present application, the emotion types corresponding to the sample data used to train the emotion category recognition model can be marked, and the sample data and the marked emotion types can be input into the emotion category recognition model to train the emotion category recognition model until the training termination conditions are met, wherein the training termination conditions include but are not limited to the loss value of the loss function of the emotion category recognition model no longer decreasing, the accuracy of the emotion category recognition model is greater than the preset accuracy, the precision of the emotion category recognition model is greater than the preset accuracy, and the like.

[0040] In some possible implementations of the embodiments of the present application, when the second interaction information includes emotion regulation information, before step 102, the data processing method provided by the embodiments of the present application may also include: determining the urgency of emotion regulation based on the emotion analysis data; determining the emotion regulation information based on the urgency of emotion regulation.

[0041] In some possible implementations of the embodiments of the present application, an emotion regulation urgency recognition model for identifying the urgency of regulation may be pre-trained, and emotion regulation information corresponding to emotions with different emotion regulation urgency may be set, and the emotion regulation urgency recognition model may be configured in an artificial intelligence emotion assistant, wherein the emotion regulation urgency includes but is not limited to particularly, very, quite, slightly, etc. After the acquired emotion analysis data is input into the emotion regulation urgency recognition model in the artificial intelligence emotion assistant, the emotion regulation urgency recognition model outputs the emotion regulation urgency corresponding to the emotion analysis data, and then determines the emotion regulation information corresponding to the emotion regulation urgency output by the emotion regulation urgency recognition model according to the preset emotion regulation urgency and emotion regulation information, and then outputs the emotion regulation information.

[0042] For example, when it is determined that the user is particularly anxious, the user may be recommended to see a doctor and take medication as prescribed by the doctor to relieve the anxiety; when it is determined that the user is slightly anxious, the user may be recommended to do outdoor exercise or take multiple deep breaths.

[0043] In some possible implementations of the embodiments of the present application, the emotion regulation urgency corresponding to the sample data used to train the emotion regulation urgency recognition model can be marked, and the sample data and the marked emotion regulation urgency can be input into the emotion regulation urgency recognition model to train the emotion regulation urgency recognition model until the training termination conditions are met, wherein the training termination conditions include but are not limited to the loss value of the loss function of the emotion regulation urgency recognition model no longer decreasing, the accuracy of the emotion regulation urgency recognition model is greater than the preset accuracy, the accuracy of the emotion regulation urgency recognition model is greater than the preset accuracy, and the like.

[0044] In some possible implementations of the embodiments of the present application, when the second interaction information includes recommendation information for an emotion regulation course, before step 102, the data processing method provided by the embodiments of the present application may further include: determining the emotion regulation course based on the emotion analysis data.

[0045] In some possible implementations of the embodiments of the present application, the emotion regulation courses in the embodiments of the present application include, but are not limited to, emotion transfer method courses, rational thinking method courses, Morita therapy courses, and music therapy courses. Among them, different emotion types can correspond to different courses in the emotion regulation course. After the user's emotion type is determined based on the emotion analysis data, the course corresponding to the user's emotion type in the emotion regulation course is fed back to the user.

[0046] In some possible implementations of the embodiments of the present application, the second interaction information in the embodiments of the present application may be an emotion regulation task, wherein the emotion regulation task is used to remind the user to regulate the user's emotions in the manner indicated by the emotion regulation task.

[0047] In some possible implementations of the embodiments of the present application, different emotion types correspond to different emotion regulation tasks. After the emotion type of the user is determined, the emotion regulation task corresponding to the emotion type is fed back to the user.

[0048] For example, when a user does not operate an electronic device for a long time, frequently switches applications, or stays in a certain application for a long time, it is inferred that the user's emotion may be in an anxious state, and an emotion regulation task such as deep breathing or meditation is pushed to the user.

[0049] As another example, based on the usage data of the user's electronic device, it can be inferred that the user is in a high-stress state, and an emotion regulation task such as listening to music to relax or doing outdoor activities can be pushed to the user.

[0050] In some possible implementations of the embodiments of the present application, the data processing method provided by the embodiments of the present application may further include: adjusting the emotion regulation task according to the execution results and feedback information of the user on the historical emotion regulation task.

[0051] In some possible implementations of the embodiments of the present application, an emotion regulation task list may be generated based on the emotion regulation tasks, and the emotion regulation tasks may be added to the emotion regulation task list.

[0052] The execution results and feedback information of the user on the historical emotion regulation tasks in the emotion regulation task list are obtained, and the content of the subsequent emotion regulation tasks in the emotion regulation task list is adaptively adjusted according to the user's feedback information and the execution results of the emotion regulation tasks.

[0053] For example, the user's historical feedback information for the emotion regulation task "listen to music to relax and engage in outdoor activities" is that he does not like outdoor activities, and the execution result of the emotion regulation task "listen to music to relax and engage in outdoor activities" is starting a music program to listen to music, then the subsequent emotion regulation task "listen to music to relax and engage in outdoor activities" can be adjusted to "listen to music to relax".

[0054] In some possible implementations of the embodiments of the present application, when the emotion analysis data includes first interaction information input by a user, step 101 may include: obtaining the first interaction information input by the user through the interaction interface of the artificial intelligence emotion assistant; accordingly, step 102 may include: outputting second interaction information through the interaction interface of the artificial intelligence emotion assistant.

[0055] For example, the interactive interface of the artificial intelligence emotion assistant is as follows: Figure 2 As shown, Figure 2 It is a schematic diagram of the interactive interface of the artificial intelligence emotion assistant provided in the embodiment of the present application.

[0056] In some possible implementations of the embodiments of the present application, the data processing method provided by the embodiments of the present application may also include: determining the image of the artificial intelligence emotion assistant based on image reference information; the image reference information includes at least one of the following: user information, user emotion information, user setting information, and environmental information.

[0057] In some possible implementations of the embodiments of the present application, user information includes but is not limited to the user's age, gender, occupation, etc.; user setting information is information set by the user according to his or her preferences for creating the image of an artificial intelligence emotional assistant; environmental information is but is not limited to the sound and brightness of the environment in which the electronic device is located.

[0058] In some possible implementations of the embodiments of the present application, the image of the artificial intelligence emotional assistant in the embodiments of the present application may include a first virtual image corresponding to the user and a second virtual image that interacts with the first virtual image for psychological counseling.

[0059] In some possible implementations of the embodiments of the present application, the user's first virtual image can be emotionally mapped based on the user's real physical state, can be dynamically adjusted as the user's emotions and state change, and has environmental adaptability. For example, when the user is in different scenes such as a quiet room or outdoors, the user's virtual image will show corresponding emotions and states, which are more in line with the current scene. The user's virtual image can not only synchronize the user's emotions and states in real time, but also dynamically adjust according to the user's device usage habits and physiological feedback to achieve a real-time mapping effect with the user's physical world.

[0060] In some possible implementations of the embodiments of the present application, the user's personalized preference characteristics can be extracted from the user's historical usage data of the electronic device, and a virtual image corresponding to the personalized preference characteristics can be created to meet the user's personalized needs, wherein the user's historical usage data of the electronic device includes but is not limited to: chat records, web browsing records, product browsing records, shopping records, etc.

[0061] For example, assuming that the user's avatar is a cartoon character, the user often browses web pages or commodities related to the cartoon character, and the user purchases items related to the cartoon character many times, the user's virtual image is created as a cartoon character.

[0062] In some possible implementations of the embodiments of the present application, after creating a first virtual image corresponding to the user, the user can adjust the appearance features of the first virtual image, for example, adjusting the hairstyle or color of the hair of the first virtual image.

[0063] In some possible implementations of the embodiments of the present application, after creating a first virtual image corresponding to the user, the first virtual image can be dynamically adjusted according to various real-time data such as the user's physical data, environmental data, and usage data of the user's electronic device.

[0064] In some possible implementations of the embodiments of the present application, the expression, tone and interaction method of the first virtual image can be adjusted in real time according to the user's emotions, so as to achieve instant feedback of the user's emotions through the virtual image. For example, the user's expression can be captured in real time by the camera of the electronic device, and the user's emotions can be identified through the expression, thereby achieving mirror feedback of the virtual image, providing the user with instant feedback that is more in line with the user's psychological state.

[0065] In some possible implementations of the embodiments of the present application, when a user is receiving psychological consultation through the first virtual image, the first virtual image can provide the user with appropriate suggestions based on the information in the electronic device to enhance the naturalness of the interaction. For example, if the user has consulted about stress relief in the past, the suggestion "You have consulted about stress relief before, would you like to consult about stress relief again" can be provided.

[0066] In some possible implementations of the embodiments of the present application, a second virtual image that meets the user's preferences and is easy to accept can be automatically generated based on the image characteristics of the first virtual image. The appearance and interaction style of the second virtual image are customized based on the user's preferences so as to establish a sense of trust more naturally. The second virtual image interacts with the first virtual image and acts as a medium for psychological consultation for the user.

[0067] Exemplarily, assuming that the first virtual image corresponding to the user is a cartoon character, the second virtual image can also be a cartoon character; another exemplary embodiment, assuming that the first virtual image corresponding to the user is a specific cartoon character, the second virtual image can be a friend of the specific cartoon character; another exemplary embodiment, assuming that the first virtual image corresponding to the user is a specific cartoon character, the second virtual image can be a friend of the specific cartoon character; another exemplary embodiment, assuming that the first virtual image corresponding to the user is a student, the second virtual image can be a teacher.

[0068] For example, Figure 3 As shown, Figure 3 It is a schematic diagram of a virtual image provided in an embodiment of the present application. Figure 3 The virtual image 301 corresponding to the user and the virtual image 302 that interacts with the virtual image 301 for psychological consultation are included. Figure 3 In the embodiment, the virtual image corresponding to the user is a lock, and the virtual image that interacts with the virtual image corresponding to the user for psychological consultation is a key.

[0069] In some possible implementations of the embodiments of the present application, the data processing method provided by the embodiments of the present application may also include: determining the interaction method between the second virtual image and the first virtual image based on the usage data and environmental information of the user's use of the electronic device; controlling the second virtual image to feedback the emotion regulation task to the first virtual image in the determined interaction method.

[0070] In some possible implementations of the embodiments of the present application, electronic device usage data includes but is not limited to application usage frequency, social media interaction, etc., and environmental data includes but is not limited to: noise, lighting changes, etc.

[0071] For example, when the user is in dim light, the user may provide feedback on the first emotion regulation task to the first virtual image in a comforting conversational style.

[0072] As another example, if it is detected based on the user's usage data and environmental information of the electronic device that the user tends to give high-frequency emotional feedback in a short period of time, the interaction frequency can be increased, and the emotion regulation task can be fed back to the user multiple times in a short period of time.

[0073] In some possible implementations of the embodiments of the present application, the data processing method provided by the embodiments of the present application may also include: updating the emotion category recognition model according to the execution results and feedback information of the user on the emotion regulation task.

[0074] In some possible implementations of the embodiments of the present application, the response to emotion regulation tasks can be detected over a long period of time, and the emotion category recognition model can be continuously updated to ensure that the user's emotions can be accurately judged and the emotion regulation tasks can be accurately pushed, thereby more adaptively meeting the user's emotional support needs.

[0075] In some possible implementations of the embodiments of the present application, the emotion regulation information in the embodiments of the present application may also include problem insight information, personalized emotion suggestion information, emotion review information, emotion warning information, etc.

[0076] In some possible implementations of the embodiments of the present application, multidimensional data can be analyzed, and the artificial intelligence emotion assistant can provide feedback on the user's recent emotional fluctuations and potential sources of stress, where the multidimensional data includes but is not limited to user physiological data, schedule data, electronic device usage data, etc.

[0077] For example, if it is detected that the user has worked for a long time, concentrated on replying to important emails, or continuously browsed work-related content in recent days, the user can proactively ask: "I noticed that you have been working very intensively recently. Are you a little tired? Maybe we can see if there are some small relaxation techniques to help you find balance in your busy life."

[0078] As another example, by identifying subtle changes in a user's emotions after browsing a mental health topic, the user can be reminded: "I noticed that you've been paying attention to some mental health content recently. I'm here to provide you with support and advice at any time, or help you further vent your emotions."

[0079] In some possible implementations of the embodiments of the present application, suggestions that meet the user's actual emotional needs can be provided based on emotional data, environment, and user behavior patterns.

[0080] For example, if it is detected that the user has opened a relaxation application after a high-load task, the system can proactively suggest: "It looks like you have just finished an important task. Why not try a deep breathing relaxation exercise or listen to some soothing music to relax yourself."

[0081] As another example, if it is detected that the user has recently browsed a large amount of anxiety-related content and has a lot of meetings scheduled in the near future, you can proactively propose: "Your schedule next week is quite full, which may bring some pressure. I can help you prepare some short meditation or breathing exercises so that you can relieve anxiety at any time."

[0082] In some possible implementations of the embodiments of the present application, after the user's daily events and tasks are completed, the user can be guided to review his emotions to help the user deeply understand the causes of emotions and improve emotion management skills.

[0083] For example, after a user completes an important project, an emotional follow-up can be conducted: "Last week's project seemed very important to you. Did you feel any special sense of accomplishment or pressure? We can review the process of completing the project together to see which aspects are worthy of recognition and which aspects can be improved."

[0084] For another example, if it is detected that the user has emotional fluctuations such as insomnia and changes in appetite after a project, guidance can be provided at an appropriate time: "I noticed that your mood seems to be affected after completing the project. We can review the challenges brought about by this project and explore some effective relaxation methods."

[0085] In some possible implementations of the embodiments of the present application, the emotional information of multiple user interactions can be sorted out to ensure the consistency of the conversation content and the continuity of support.

[0086] For example, if the user has mentioned that a certain method is effective for mood regulation, such as morning walks, the user can be reminded in similar situations: "You once said that morning walks are helpful for mood. If you have time tomorrow, you can arrange a short morning activity, which may make you feel better."

[0087] As another example, if you find that certain schedules or tasks continue to cause increased stress, you can propose an emotional relief plan: "I have noticed that you have felt more stressed every time you have to review a project in the past few months. We can work together to design a phased review plan that will help you cope with it more calmly."

[0088] In some possible implementations of the embodiments of the present application, early warning and intervention can be performed before emotional fluctuations appear.

[0089] For example, if the user is found to have persistent signs of insomnia and has used an electronic device to view stress management-related content multiple times, a gentle reminder can be issued: "It seems that your sleep quality has not been ideal recently. Can you arrange a soothing bedtime meditation? I can recommend some tips for falling asleep."

[0090] As another example, after discovering that there are some contents in the user's social interactions or message records that are likely to cause emotional fluctuations, psychological counseling suggestions will be provided in advance to help the user reduce the risk of emotional intensification.

[0091] In the embodiments of the present application, through problem insight, emotional review and long-term tracking support, users can be provided with emotional management anytime and anywhere in their daily lives, allowing users to feel intimate accompanying support and high-frequency emotional care.

[0092] In some possible implementations of the embodiments of the present application, the data during the user's psychological consultation process can be encrypted to prevent the user's private data from being leaked and to protect the user's privacy.

[0093] In some possible implementations of the embodiments of the present application, access rights to the data of the user during the psychological counseling process can be monitored, and any unauthorized access will be prohibited to ensure the security of the user's privacy data.

[0094] The data processing method provided in the embodiments of the present application can be applied to professionals, students, people who travel frequently, people with active digital social interaction, and groups with a high degree of dependence on electronic devices.

[0095] For professionals, it can monitor and analyze user emotion-related activity information during work, such as meeting schedules, email content, and instant messaging communications, and help users cope with heavy work pressure through real-time emotional feedback. When emotional fluctuations are detected, it can timely suggest users to conduct short relaxation exercises or emotional review, and provide personalized emotional counseling solutions to help users improve their mental health and work efficiency.

[0096] For students, it can collect and analyze data about users in learning applications, social media, schedules, etc. to help identify academic or social events that may affect emotions. When it detects that a user is depressed or stressed, it can proactively suggest meditation, mood diary or other relaxation activities to help users manage emotions and improve psychological resilience.

[0097] For frequent business travelers, it can help alleviate loneliness, fatigue or anxiety caused by travel by combining the user's itinerary information, flight schedule and schedule. By analyzing factors such as the user's schedule changes and mobile environment, psychological support and stress relief suggestions can be provided at the appropriate time. For example, it can recommend relaxation training when the schedule is tight, or recommend rest and adjustment in leisure time to help users maintain a good mental state.

[0098] For people who are active in digital social networking, we can capture their emotional changes in real time by analyzing the frequency of users' interactions and emotional expressions on social media. When we identify that users may have anxiety or negative emotions due to social activities, we can actively guide them through appropriate communication styles, or suggest that they appropriately reduce the use of social platforms, to help users establish healthy social habits.

[0099] For those who are highly dependent on electronic devices, we can help identify emotional problems caused by excessive use of electronic devices by analyzing their application usage behavior and browsing habits. When users feel anxious due to long-term use of electronic devices or frequent reception of information, we can actively suggest that users temporarily leave the electronic devices or participate in beneficial emotion management activities, thereby improving their ability to regulate their own emotions.

[0100] In the embodiment of the present application, by allowing the user to use the virtual image for emotional mapping and adjusting the expression and interaction mode of the virtual image, it is possible to provide the user with more appropriate emotional feedback, effectively increasing the credibility and comfort of emotional management. It is also possible to predict the user's emotional fluctuation trend in advance, provide emotional support and intervention at an early stage, effectively reduce the user's emotional fluctuation, and improve the effectiveness of mental health management.

[0101] The data processing method provided in the embodiment of the present application can be executed by a data processing device. In the embodiment of the present application, the data processing device provided in the embodiment of the present application is described by taking the data processing method executed by the data processing device as an example.

[0102] Figure 4 400 is a schematic diagram of the structure of a data processing device provided in an embodiment of the present application. The data processing device 400 may include:

[0103] The acquisition module 401 is used to acquire the emotion analysis data of the user; the emotion analysis data includes at least one of the following: electronic device usage data, physiological data, historical emotion data, schedule information, and first interaction information input by the user;

[0104] The output module 402 is used to output the second interaction information according to the emotion analysis data through the artificial intelligence emotion assistant.

[0105] In the embodiment of the present application, the emotion analysis data of the user is obtained; the emotion analysis data includes at least one of the following: electronic device usage data, physiological data, historical emotion data, schedule information, and first interaction information input by the user; the second interaction information is outputted by the artificial intelligence emotion assistant according to the emotion analysis data. In this way, there is no need to make an appointment for psychological consultation, and the interaction information can be outputted according to the emotion analysis data by the artificial intelligence emotion assistant, which can improve the timeliness of solving psychological problems.

[0106] In some possible implementations of the embodiment of the present application, the second interaction information includes emotion regulation information; the data processing device 400 provided in the embodiment of the present application further includes:

[0107] A first determination module, used to determine the emotion type according to the emotion analysis data;

[0108] The second determination module is used to determine emotion regulation information according to the emotion type.

[0109] In some possible implementations of the embodiment of the present application, the second interaction information includes emotion regulation information; the data processing device 400 provided in the embodiment of the present application further includes:

[0110] A third determination module is used to determine the urgency of emotion regulation based on the emotion analysis data;

[0111] The fourth determination module is used to determine the emotion regulation information according to the urgency of the emotion regulation.

[0112] In some possible implementations of the embodiments of the present application, the second interaction information includes emotion regulation information, and the emotion regulation information includes recommendation information of emotion regulation behavior and emotion relief information.

[0113] In some possible implementations of the embodiment of the present application, the second interaction information includes recommendation information of an emotion regulation course; the data processing device 400 provided in the embodiment of the present application further includes:

[0114] The fifth determination module is used to determine the emotion regulation course according to the emotion analysis data.

[0115] In some possible implementations of the embodiments of the present application, the sentiment analysis data includes first interaction information input by a user; and the acquisition module 401 is specifically used to:

[0116] Acquire first interaction information input by a user through an interaction interface of an artificial intelligence emotion assistant;

[0117] Accordingly, the output module 402 is specifically used for:

[0118] The second interaction information is output through the interaction interface of the artificial intelligence emotion assistant.

[0119] In some possible implementations of the embodiments of the present application, the data processing device 400 provided in the embodiments of the present application further includes:

[0120] The sixth determination module is used to determine the image of the artificial intelligence emotional assistant based on the image reference information; the image reference information includes at least one of the following: user information, user emotional information, user setting information, and environmental information.

[0121] The data processing device in the embodiment of the present application can be an electronic device, or a component in the electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal, or other devices other than a terminal. Exemplarily, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, a vehicle-mounted electronic device, a mobile Internet device (Mobile Internet Device, MID), an augmented reality (augmented reality, AR) / virtual reality (virtual reality, VR) device, a robot, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), etc., and can also be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), a television (television, TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

[0122] The data processing device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0123] The data processing device provided in the embodiment of the present application can realize Figures 1 to 3 To avoid repetition, the various processes implemented in the data processing method embodiment will not be described here.

[0124] Alternatively, if Figure 5 As shown, an embodiment of the present application also provides an electronic device 500, including a processor 501 and a memory 502, wherein the memory 502 stores programs or instructions that can be executed on the processor 501, and when the program or instructions are executed by the processor 501, the various steps of the data processing method embodiment provided in the embodiment of the present application are implemented, and the same technical effect can be achieved. To avoid repetition, they are not described here.

[0125] Figure 6 It is a schematic diagram of the hardware structure of an electronic device implementing an embodiment of the present application.

[0126] The electronic device 600 includes but is not limited to: a radio frequency unit 601, a network module 602, an audio output unit 603, an input unit 604, a sensor 605, a display unit 606, a user input unit 607, an interface unit 608, a memory 609, and a processor 610.

[0127] Those skilled in the art will appreciate that the electronic device 600 may also include a power source (such as a battery) for supplying power to each component, and the power source may be logically connected to the processor 610 through a power management system, thereby implementing functions such as managing charging, discharging, and power consumption management through the power management system. Figure 6 The electronic device structure shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be described in detail here.

[0128] Among them, the processor 610 is used to: obtain the user's emotion analysis data; the emotion analysis data includes at least one of the following: electronic device usage data, physiological data, historical emotion data, schedule information, and first interaction information input by the user; output second interaction information based on the emotion analysis data through an artificial intelligence emotion assistant.

[0129] In the embodiment of the present application, the emotion analysis data of the user is obtained; the emotion analysis data includes at least one of the following: electronic device usage data, physiological data, historical emotion data, schedule information, and first interaction information input by the user; the second interaction information is outputted by the artificial intelligence emotion assistant according to the emotion analysis data. In this way, there is no need to make an appointment for psychological consultation, and the interaction information can be outputted according to the emotion analysis data by the artificial intelligence emotion assistant, which can improve the timeliness of solving psychological problems.

[0130] In some possible implementations of the embodiments of the present application, the second interaction information includes emotion regulation information; the processor 610 is further used to: determine the emotion type according to the emotion analysis data; and determine the emotion regulation information according to the emotion type.

[0131] In some possible implementations of the embodiments of the present application, the second interaction information includes emotion regulation information; the processor 610 is further used to: determine the urgency of emotion regulation according to the emotion analysis data; and determine the emotion regulation information according to the urgency of emotion regulation.

[0132] In some possible implementations of the embodiments of the present application, the second interaction information includes emotion regulation information, and the emotion regulation information includes recommendation information of emotion regulation behavior and emotion relief information.

[0133] In some possible implementations of the embodiments of the present application, the second interaction information includes recommendation information of an emotion regulation course; the processor 610 is further used to: determine the emotion regulation course according to the emotion analysis data.

[0134] In some possible implementations of the embodiments of the present application, the sentiment analysis data includes first interaction information input by a user; and the processor 610 is specifically configured to:

[0135] Acquire first interaction information input by a user through an interaction interface of an artificial intelligence emotion assistant;

[0136] The second interaction information is output through the interaction interface of the artificial intelligence emotion assistant.

[0137] In some possible implementations of the embodiments of the present application, the processor 610 is further configured to:

[0138] The image of the artificial intelligence emotion assistant is determined based on the image reference information; the image reference information includes at least one of the following: user information, user emotion information, user setting information, and environmental information.

[0139] It should be understood that in the embodiment of the present application, the input unit 604 may include a graphics processor (GPU) 6041 and a microphone 6042, and the graphics processor 6041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 606 may include a display panel 6061, and the display panel 6061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 607 includes a touch panel 6071 and at least one of other input devices 6072. The touch panel 6071 is also called a touch screen. The touch panel 6071 may include two parts: a touch detection device and a touch controller. Other input devices 6072 may include, but are not limited to, a physical keyboard, function keys (such as a volume control button, a switch button, etc.), a trackball, a mouse, and a joystick, which will not be repeated here.

[0140] The memory 609 can be used to store software programs and various data. The memory 609 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, an application program or instructions required for at least one function (such as a sound playback function, an image playback function, etc.), etc. In addition, the memory 609 may include a volatile memory or a non-volatile memory, or the memory 609 may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM) and a direct memory bus random access memory (DRRAM). The memory 609 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0141] The processor 610 may include one or more processing units; optionally, the processor 610 integrates an application processor and a modem processor, wherein the application processor mainly processes operations related to an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communication signals, such as a baseband processor. It is understandable that the modem processor may not be integrated into the processor 610.

[0142] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the data processing method embodiment provided in the embodiment of the present application are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0143] The processor is a processor in the electronic device described in the above embodiment. The readable storage medium includes a computer-readable storage medium, and examples of computer-readable storage media include non-transitory computer-readable media, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0144] An embodiment of the present application also provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the data processing method embodiment provided in the embodiment of the present application, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0145] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0146] The embodiment of the present application also provides a computer program product, which is stored in a storage medium. The program product is executed by at least one processor to implement the various processes of the data processing method embodiment provided in the embodiment of the present application, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0147] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0148] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0149] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A data processing method, characterized in that: The method comprises: Acquire the user's emotion analysis data; the emotion analysis data includes at least one of the following: electronic device usage data, physiological data, historical emotion data, schedule information, and first interaction information input by the user; The second interaction information is outputted according to the emotion analysis data by the artificial intelligence emotion assistant.

2. The method according to claim 1, characterized in that The second interaction information includes emotion regulation information; Before the step of outputting the second interaction information according to the emotion analysis data by the artificial intelligence emotion assistant, the method further includes: Determining an emotion type based on the emotion analysis data; Emotion regulation information is determined according to the emotion type.

3. The method according to claim 1, characterized in that The second interaction information includes emotion regulation information; Before the step of outputting the second interaction information according to the emotion analysis data by the artificial intelligence emotion assistant, the method further includes: determining an emotion regulation urgency based on the emotion analysis data; Emotion regulation information is determined according to the emotion regulation urgency.

4. The method according to claim 1, characterized in that: The second interaction information includes emotion regulation information, and the emotion regulation information includes recommendation information of emotion regulation behavior and emotion relief information.

5. The method according to claim 1, characterized in that The second interactive information includes recommendation information of emotion regulation courses; Before the step of outputting the second interaction information according to the emotion analysis data by the artificial intelligence emotion assistant, the method further includes: An emotion regulation course is determined based on the emotion analysis data.

6. The method according to claim 1, characterized in that The sentiment analysis data includes first interaction information input by a user; The obtaining of the user's emotion analysis data includes: Acquire the first interaction information input by the user through the interaction interface of the artificial intelligence emotion assistant; The outputting the second interaction information according to the emotion analysis data by the artificial intelligence emotion assistant includes: The second interaction information is output through the interaction interface of the artificial intelligence emotion assistant.

7. The method according to claim 1, characterized in that The method further comprises: The image of the artificial intelligence emotion assistant is determined based on image reference information; the image reference information includes at least one of the following: user information, user emotion information, user setting information, and environmental information.

8. A data processing device, characterized in that: The device comprises: An acquisition module, used to acquire emotion analysis data of the user; the emotion analysis data includes at least one of the following: electronic device usage data, physiological data, historical emotion data, schedule information, and first interaction information input by the user; An output module is used to output second interaction information according to the emotion analysis data through an artificial intelligence emotion assistant.

9. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the programs or instructions are executed by the processor, the steps of the data processing method according to any one of claims 1 to 7 are implemented.

10. A readable storage medium, characterized in that: The readable storage medium stores programs or instructions, and when the programs or instructions are executed by the processor, the steps of the data processing method according to any one of claims 1 to 7 are implemented.

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