System

Abstract

An object of a system according to an embodiment is to effectively perform mental care for a child.SOLUTION: A system according to an embodiment includes a dialogue unit, an emotion understanding unit, an advice providing unit, and a content providing unit. The communicator has a conversation with the child. The emotion understanding unit analyzes the speech of the child acquired by the dialogue unit and understands an emotion. The advice providing unit provides appropriate advice based on the emotion understood by the emotion understanding unit. The content providing unit provides content for mental care on the basis of the advice provided by the advice providing unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional techniques lack appropriate approaches for providing mental health care to children, and there is room for improvement.

[0005] The system according to the embodiment aims to provide effective mental care for children. [Means for solving the problem]

[0006] The system according to the embodiment includes a dialogue unit, an emotion understanding unit, an advice providing unit, and a content providing unit. The dialogue unit converses with the child. The emotion understanding unit analyzes the child's utterances acquired by the dialogue unit and understands their emotions. The advice providing unit provides appropriate advice based on the emotions understood by the emotion understanding unit. The content providing unit provides content for mental care based on the advice provided by the advice providing unit. [Effects of the Invention]

[0007] The system according to the embodiment can effectively provide mental care for children. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The mental care system according to an embodiment of the present invention is a system that provides mental care by having an AI character installed in a device for children and conversing with the child. This allows the mental care system to understand the child's emotions and feelings and provide appropriate advice and support.

[0029] A mental care system according to an embodiment includes a dialogue unit, an emotion understanding unit, an advice providing unit, and a content providing unit. The dialogue unit converses with a child. For example, the dialogue unit uses voice recognition technology to understand what the child is saying and generate an appropriate response. The dialogue unit can also communicate in text format. The dialogue unit can also communicate with the child through video dialogue. The emotion understanding unit analyzes the child's speech acquired by the dialogue unit to understand the child's emotions. For example, the emotion understanding unit uses voice analysis technology to analyze the tone and speed of the child's voice and estimate the child's emotions. The emotion understanding unit can also analyze the child's facial expressions using facial expression analysis technology to understand the child's emotions. The emotion understanding unit can also analyze the content of the child's speech using text analysis technology to understand the child's emotions. The advice providing unit provides appropriate advice based on the emotions understood by the emotion understanding unit. For example, the advice providing unit can provide words of encouragement if the child is sad. The advice providing unit can also provide specific behavioral instructions if the child is stressed. The advice providing unit can also suggest relaxation methods if the child is anxious. The content providing unit provides content for mental care based on the advice provided by the advice providing unit. For example, the content providing unit provides relaxation music. The content providing unit may also provide a meditation guide. Furthermore, the content providing unit may also provide a game for stress relief. In this way, the mental care system according to the embodiment can effectively provide mental care for children.

[0030] The dialogue unit can refer to past dialogue history to generate more personalized responses. For example, if a child says, "I had a fight with a friend at school today," the generation AI can refer to the past dialogue history and respond, based on previous responses in similar situations, with, "That must have been tough. Something similar happened last time, but what caused the fight this time?" Similarly, if a child says, "I'm feeling sad today," the generation AI can refer to the past dialogue history and respond, based on the reasons the child felt sad in the past and the content of the dialogue, with, "Can you tell me why you're sad? Something similar happened last time, but what happened this time?" Furthermore, if a child says, "I'm tired today," the dialogue unit can refer to the past dialogue history and respond, based on the reasons the child felt tired in the past and the content of the dialogue, with, "Why don't you listen to some relaxing music? You were able to relax by listening to music last time, weren't you?" This personalized response improves the accuracy of children's mental care.

[0031] The dialogue unit can analyze the tone and speed of a child's voice to detect changes in emotion in real time and generate responses accordingly. For example, when a child says, "I had a fight with my friend at school today," the dialogue unit analyzes the tone and speed of the voice to detect changes in emotion. For example, if the child's voice is trembling, the dialogue unit can respond gently, "That must have been hard. Why did you fight?" The dialogue unit can also analyze the tone and speed of the voice when a child says, "I'm feeling sad today," to detect changes in emotion. For example, if the child's voice is low and slow, the dialogue unit can respond empathetically, "Can you tell me why you're sad?" The dialogue unit can also analyze the tone and speed of the voice when a child says, "I'm tired today," to detect changes in emotion. For example, if the child's voice is weak, the dialogue unit can suggest, "Would you like to listen to some relaxing music?" This allows for real-time detection of changes in emotion and generation of appropriate responses.

[0032] The dialogue unit enables the AI ​​character to converse in multiple languages ​​and accommodate children from different cultures. The dialogue unit allows the AI ​​character to converse in multiple languages, such as English, Japanese, and Spanish, and accommodate children from different cultures. For example, if a child says in English, "I had a fight with my friend at school today," the AI ​​character might respond, "That sounds tough. What happened?" The dialogue unit also generates responses that take into account the cultural background of each language, allowing the AI ​​character to accommodate children from different cultures. For example, if a child says in Japanese, "I had a fight with my friend at school today," the AI ​​character might respond, "That must have been tough. Why did you fight?" Furthermore, the dialogue unit learns the nuances and expressions of each language, allowing the AI ​​character to converse in multiple languages ​​and accommodate children from different cultures. For example, if a child says, "Hey me, I'm going to school," the AI ​​character might respond, "That sounds tough. What happened?" This allows us to cater to children from different cultures.

[0033] The dialogue unit can add a function to visually display the content of the dialogue, making it easier for children to understand. For example, when a child says, "I had a fight with my friend at school today," the dialogue unit can add a function to visually display the content of the dialogue, making it easier for children to understand. For example, a fight scene can be displayed using an illustration. Also, when a child says, "I'm feeling sad today," the dialogue unit can add a function to visually display the content of the dialogue, making it easier for children to understand. For example, a character with a sad expression can be displayed. Furthermore, when a child says, "I'm tired today," the dialogue unit can add a function to visually display the content of the dialogue, making it easier for children to understand. For example, an icon of relaxing music can be displayed. This makes it easier for children to visually understand the content of the dialogue.

[0034] The emotion understanding unit can provide more appropriate advice by combining the content of the child's utterance with the background information. For example, if a child says, "I had a fight with my friend at school today," the emotion understanding unit can provide more appropriate advice by combining the content of the utterance with the background information. For example, based on what happened at school, the emotion understanding unit can respond with, "That must have been tough. Why did you get into a fight?" If a child says, "I'm feeling sad today," the emotion understanding unit can provide more appropriate advice by combining the content of the utterance with the background information. For example, based on the home environment, the emotion understanding unit can respond with, "Can you tell me why you're sad?" If a child says, "I'm tired today," the emotion understanding unit can provide more appropriate advice by combining the content of the utterance with the background information. For example, based on what happened at school, the emotion understanding unit can suggest, "Why don't you listen to some relaxing music?" In this way, more appropriate advice can be provided by combining the content of the utterance with the background information.

[0035] The emotion understanding unit can express emotions through creative activities such as music or art and analyze them. For example, when a child says, "I had a fight with my friend at school today," the emotion understanding unit can have the child express emotions through creative activities such as music or art and analyze them. For example, it can analyze a picture the child draws and understand the emotion. Also, when a child says, "I'm feeling sad today," the emotion understanding unit can have the child express emotions through creative activities such as music or art and analyze them. For example, it can analyze music the child has created and understand the emotion. Furthermore, when a child says, "I'm tired today," the emotion understanding unit can have the child express emotions through creative activities such as music or art and analyze them. For example, it can analyze artwork the child has created and understand the emotion. In this way, emotions can be understood by expressing emotions through creative activities and analyzing them.

[0036] The emotion understanding unit can collect feedback from parents and teachers and use it for analysis. For example, when a child says, "I had a fight with my friend at school today," the emotion understanding unit collects feedback from parents and teachers and uses it for analysis. For example, based on the information from the parents or teachers, it can respond with, "That must have been tough. Why did you fight?" Similarly, when a child says, "I'm feeling sad today," the emotion understanding unit collects feedback from parents and teachers and uses it for analysis. For example, based on the information from the parents or teachers, it can respond with, "Can you tell me why you're sad?" Furthermore, when a child says, "I'm tired today," the emotion understanding unit collects feedback from parents and teachers and uses it for analysis. For example, based on the information from the parents or teachers, it can suggest, "Why don't you listen to some relaxing music?" In this way, by utilizing feedback from parents and teachers for analysis, the accuracy of emotion understanding is improved.

[0037] The content providing unit allows the generating AI to create an individually customized mental care program according to the child's mental state. For example, when a child says, "I had a fight with a friend at school today," the content providing unit allows the generating AI to create an individually customized mental care program, suggesting, for example, music for relaxation or breathing exercises for stress relief. Also, when a child says, "I'm feeling sad today," the content providing unit allows the generating AI to create an individually customized mental care program, suggesting, for example, games to change the mood or music to relax. Furthermore, when a child says, "I'm tired today," the content providing unit allows the generating AI to create an individually customized mental care program, suggesting, for example, music for relaxation or breathing exercises for stress relief. In this way, individually customized mental care programs can be provided.

[0038] The content providing unit can learn a child's preferences and interests and provide optimal mental care content based on that. For example, when a child says, "I had a fight with a friend at school today," the content providing unit's generation AI learns the child's preferences and interests and provides optimal mental care content based on that. For example, it can suggest music that the child likes. Also, when a child says, "I'm feeling sad today," the content providing unit's generation AI learns the child's preferences and interests and provides optimal mental care content based on that. For example, it can suggest a game that the child likes. Furthermore, when a child says, "I'm tired today," the content providing unit's generation AI learns the child's preferences and interests and provides optimal mental care content based on that. For example, it can suggest music that the child likes to relax. This makes it possible to provide optimal mental care content based on a child's preferences and interests.

[0039] The content providing unit can promote mental care for the entire family by including joint activities that can be enjoyed with parents and siblings in the mental care content. For example, when a child says, "I had a fight with a friend at school today," the content providing unit can have the generating AI suggest joint activities that can be enjoyed with parents and siblings, thereby promoting mental care for the entire family. For example, the content providing unit can suggest games that the whole family can enjoy. Furthermore, when a child says, "I'm feeling sad today," the content providing unit can suggest joint activities that can be enjoyed with parents and siblings, thereby promoting mental care for the entire family. For example, the content providing unit can suggest art activities that the whole family can enjoy. Furthermore, when a child says, "I'm tired today," the content providing unit can suggest joint activities that can be enjoyed with parents and siblings, thereby promoting mental care for the entire family. For example, the content providing unit can suggest relaxing music that the whole family can enjoy. This promotes mental care for the entire family.

[0040] The content provider can work with schools and local communities to provide mental care content and strengthen social support. For example, when a child says, "I had a fight with a friend at school today," the content provider can have the generation AI work with schools and local communities to provide mental care content and strengthen social support. For example, the content provider can work with school counselors to provide support. Furthermore, when a child says, "I'm feeling sad today," the content provider can have the generation AI work with schools and local communities to provide mental care content and strengthen social support. For example, the content provider can work with local support groups to provide support. Furthermore, when a child says, "I'm tired today," the content provider can have the generation AI work with schools and local communities to provide mental care content and strengthen social support. For example, the content provider can work with a school's relaxation program to provide support. This allows for strengthening social support through collaboration with schools and local communities.

[0041] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0042] The mental care system may further include a health management unit that monitors the child's health condition. The health management unit may, for example, measure the child's heart rate and body temperature to understand the child's health condition. The health management unit may also monitor the child's sleep patterns and provide appropriate sleep advice. Furthermore, the health management unit may record the child's diet and provide advice on nutritional balance. This allows not only mental care for the child but also overall health management.

[0043] The mental care system can further include a learning support unit that monitors the child's learning situation. The learning support unit can, for example, record the child's homework progress and provide appropriate learning advice. The learning support unit can also analyze the child's learning style and suggest the optimal learning method. Furthermore, the learning support unit can evaluate the child's learning results and provide feedback to increase motivation. This makes it possible to strengthen mental care through learning support for children.

[0044] The mental care system can further include a creative activity support unit for fostering children's creativity. The creative activity support unit supports children's activities such as drawing pictures and making music. The creative activity support unit can also evaluate children's creations and provide feedback. The creative activity support unit can also provide a place where children can share and interact with other children. This allows mental care to be provided while fostering children's creativity.

[0045] The mental care system may further include a social activity support unit for fostering the child's social skills. The social activity support unit may, for example, provide opportunities for the child to play with friends. The social activity support unit may also support the child's participation in local events. The social activity support unit may also encourage the child to participate in volunteer activities and provide feedback to foster the child's social skills. This allows mental care to be provided while fostering the child's social skills.

[0046] The mental care system can further include a self-esteem improvement unit for improving a child's self-esteem. The self-esteem improvement unit, for example, records the child's achievements and provides praising feedback. The self-esteem improvement unit can also suggest ways for the child to discover his or her strengths and make use of them. Furthermore, the self-esteem improvement unit can also provide support for the child to set and achieve his or her own goals. In this way, mental care can be provided while improving the child's self-esteem.

[0047] The processing flow of the first embodiment will be briefly explained below.

[0048] Step 1: The dialogue unit converses with the child. For example, the dialogue unit uses voice recognition technology to understand what the child is saying and generate an appropriate response. The dialogue unit can also communicate in text format or through video conversations with the child. Step 2: The emotion understanding unit analyzes the child's utterances acquired by the dialogue unit and understands the emotions. For example, the emotion understanding unit uses voice analysis technology to analyze the tone and speed of the child's voice and infer the emotions. The emotion understanding unit can also use facial expression analysis technology to analyze the child's facial expressions and understand the emotions. Furthermore, the emotion understanding unit can also use text analysis technology to analyze the content of the child's utterances and understand the emotions. Step 3: The advice providing unit provides appropriate advice based on the emotions understood by the emotion understanding unit. For example, if the child is feeling sad, the advice providing unit provides words of encouragement. If the child is feeling stressed, the advice providing unit can also provide specific instructions for action. Furthermore, if the child is feeling anxious, the advice providing unit can also suggest relaxation methods. Step 4: The content providing unit provides content for mental care based on the advice provided by the advice providing unit. For example, the content providing unit provides relaxation music. The content providing unit may also provide a meditation guide. Furthermore, the content providing unit may also provide a game for stress relief.

[0049] (Example 2) The mental care system according to an embodiment of the present invention is a system that provides mental care by having an AI character installed in a device for children and conversing with the child. This allows the mental care system to understand the child's emotions and feelings and provide appropriate advice and support.

[0050] A mental care system according to an embodiment includes a dialogue unit, an emotion understanding unit, an advice providing unit, and a content providing unit. The dialogue unit converses with a child. For example, the dialogue unit uses voice recognition technology to understand what the child is saying and generate an appropriate response. The dialogue unit can also communicate in text format. The dialogue unit can also communicate with the child through video dialogue. The emotion understanding unit analyzes the child's speech acquired by the dialogue unit to understand the child's emotions. For example, the emotion understanding unit uses voice analysis technology to analyze the tone and speed of the child's voice and estimate the child's emotions. The emotion understanding unit can also analyze the child's facial expressions using facial expression analysis technology to understand the child's emotions. The emotion understanding unit can also analyze the content of the child's speech using text analysis technology to understand the child's emotions. The advice providing unit provides appropriate advice based on the emotions understood by the emotion understanding unit. For example, the advice providing unit can provide words of encouragement if the child is sad. The advice providing unit can also provide specific behavioral instructions if the child is stressed. The advice providing unit can also suggest relaxation methods if the child is anxious. The content providing unit provides content for mental care based on the advice provided by the advice providing unit. For example, the content providing unit provides relaxation music. The content providing unit may also provide a meditation guide. Furthermore, the content providing unit may also provide a game for stress relief. In this way, the mental care system according to the embodiment can effectively provide mental care for children.

[0051] The dialogue unit can refer to past dialogue history to generate more personalized responses. For example, if a child says, "I had a fight with a friend at school today," the generation AI can refer to the past dialogue history and respond, based on previous responses in similar situations, with, "That must have been tough. Something similar happened last time, but what caused the fight this time?" Similarly, if a child says, "I'm feeling sad today," the generation AI can refer to the past dialogue history and respond, based on the reasons the child felt sad in the past and the content of the dialogue, with, "Can you tell me why you're sad? Something similar happened last time, but what happened this time?" Furthermore, if a child says, "I'm tired today," the dialogue unit can refer to the past dialogue history and respond, based on the reasons the child felt tired in the past and the content of the dialogue, with, "Why don't you listen to some relaxing music? You were able to relax by listening to music last time, weren't you?" This personalized response improves the accuracy of children's mental care.

[0052] The dialogue unit can analyze the tone and speed of a child's voice to detect changes in emotion in real time and generate responses accordingly. For example, when a child says, "I had a fight with my friend at school today," the dialogue unit analyzes the tone and speed of the voice to detect changes in emotion. For example, if the child's voice is trembling, the dialogue unit can respond gently, "That must have been hard. Why did you fight?" The dialogue unit can also analyze the tone and speed of the voice when a child says, "I'm feeling sad today," to detect changes in emotion. For example, if the child's voice is low and slow, the dialogue unit can respond empathetically, "Can you tell me why you're sad?" The dialogue unit can also analyze the tone and speed of the voice when a child says, "I'm tired today," to detect changes in emotion. For example, if the child's voice is weak, the dialogue unit can suggest, "Would you like to listen to some relaxing music?" This allows for real-time detection of changes in emotion and generation of appropriate responses.

[0053] The dialogue unit can use the emotion estimation function to estimate the child's emotion and generate a response based on that emotion. For example, when a child says, "I had a fight with my friend at school today," the dialogue unit can use the emotion estimation function to estimate the child's emotion and respond, "That must have been tough. Why did you fight?" Also, when a child says, "I'm feeling sad today," the dialogue unit can use the emotion estimation function to estimate the child's emotion and respond, "Can you tell me why you're sad?" Furthermore, when a child says, "I'm tired today," the dialogue unit can use the emotion estimation function to estimate the child's emotion and suggest, "Would you like to listen to some relaxing music?" In this way, the emotion estimation function can generate a response according to the child's emotion.

[0054] The dialogue unit enables the AI ​​character to converse in multiple languages ​​and accommodate children from different cultures. The dialogue unit allows the AI ​​character to converse in multiple languages, such as English, Japanese, and Spanish, and accommodate children from different cultures. For example, if a child says in English, "I had a fight with my friend at school today," the AI ​​character might respond, "That sounds tough. What happened?" The dialogue unit also generates responses that take into account the cultural background of each language, allowing the AI ​​character to accommodate children from different cultures. For example, if a child says in Japanese, "I had a fight with my friend at school today," the AI ​​character might respond, "That must have been tough. Why did you fight?" Furthermore, the dialogue unit learns the nuances and expressions of each language, allowing the AI ​​character to converse in multiple languages ​​and accommodate children from different cultures. For example, if a child says, "Hey me, I'm going to school," the AI ​​character might respond, "That sounds tough. What happened?" This allows us to cater to children from different cultures.

[0055] The dialogue unit can add a function to visually display the content of the dialogue, making it easier for children to understand. For example, when a child says, "I had a fight with my friend at school today," the dialogue unit can add a function to visually display the content of the dialogue, making it easier for children to understand. For example, a fight scene can be displayed using an illustration. Also, when a child says, "I'm feeling sad today," the dialogue unit can add a function to visually display the content of the dialogue, making it easier for children to understand. For example, a character with a sad expression can be displayed. Furthermore, when a child says, "I'm tired today," the dialogue unit can add a function to visually display the content of the dialogue, making it easier for children to understand. For example, an icon of relaxing music can be displayed. This makes it easier for children to visually understand the content of the dialogue.

[0056] The dialogue unit uses the emotion estimation function to automatically generate a dialogue scenario according to the child's emotions, thereby providing a wider variety of dialogues. For example, when a child says, "I had a fight with my friends at school today," the dialogue unit uses the emotion estimation function to automatically generate a dialogue scenario according to the child's emotions, and responds, "That must have been tough. Why did you fight?" Furthermore, when a child says, "I'm feeling sad today," the dialogue unit can use the emotion estimation function to automatically generate a dialogue scenario according to the child's emotions, and respond, "Can you tell me why you're sad?" Furthermore, when a child says, "I'm tired today," the dialogue unit can use the emotion estimation function to automatically generate a dialogue scenario according to the child's emotions, and suggest, "Why don't you listen to some relaxing music?" This makes it possible to provide a wider variety of dialogues according to emotions.

[0057] The emotion understanding unit analyzes a child's facial expressions and gestures using a camera, and is able to understand emotions more accurately. For example, when a child says, "I had a fight with my friend at school today," the emotion understanding unit analyzes the child's facial expressions and gestures using a camera, and is able to understand emotions more accurately. For example, if the child's face is red, it is estimated that the child is feeling angry. The emotion understanding unit also analyzes the child's facial expressions and gestures using a camera when the child says, "I'm feeling sad today," and is able to understand emotions more accurately. For example, if the child is crying, it is able to estimate that the child is feeling sad. The emotion understanding unit also analyzes the child's facial expressions and gestures using a camera when the child says, "I'm tired today," and is able to understand emotions more accurately. For example, if the child is rubbing their eyes, it is able to estimate that the child is feeling tired. In this way, emotions can be understood more accurately by analyzing facial expressions and gestures.

[0058] The emotion understanding unit can provide more appropriate advice by combining the content of the child's utterance with the background information. For example, if a child says, "I had a fight with my friend at school today," the emotion understanding unit can provide more appropriate advice by combining the content of the utterance with the background information. For example, based on what happened at school, the emotion understanding unit can respond with, "That must have been tough. Why did you get into a fight?" If a child says, "I'm feeling sad today," the emotion understanding unit can provide more appropriate advice by combining the content of the utterance with the background information. For example, based on the home environment, the emotion understanding unit can respond with, "Can you tell me why you're sad?" If a child says, "I'm tired today," the emotion understanding unit can provide more appropriate advice by combining the content of the utterance with the background information. For example, based on what happened at school, the emotion understanding unit can suggest, "Why don't you listen to some relaxing music?" In this way, more appropriate advice can be provided by combining the content of the utterance with the background information.

[0059] The emotion understanding unit can monitor a child's emotions in real time using the emotion estimation function and provide advice according to changes in emotions. For example, when a child says, "I had a fight with my friend at school today," the emotion understanding unit can monitor the child's emotions in real time using the emotion estimation function and respond with, "That must have been tough. Why did you fight?" Also, when a child says, "I'm feeling sad today," the emotion understanding unit can monitor the child's emotions in real time using the emotion estimation function and respond with, "Can you tell me why you're sad?" Furthermore, when a child says, "I'm tired today," the emotion understanding unit can monitor the child's emotions in real time using the emotion estimation function and suggest, "Why don't you listen to some relaxing music?" This makes it possible to provide advice according to changes in emotions in real time.

[0060] The emotion understanding unit can express emotions through creative activities such as music or art and analyze them. For example, when a child says, "I had a fight with my friend at school today," the emotion understanding unit can have the child express emotions through creative activities such as music or art and analyze them. For example, it can analyze a picture the child draws and understand the emotion. Also, when a child says, "I'm feeling sad today," the emotion understanding unit can have the child express emotions through creative activities such as music or art and analyze them. For example, it can analyze music the child has created and understand the emotion. Furthermore, when a child says, "I'm tired today," the emotion understanding unit can have the child express emotions through creative activities such as music or art and analyze them. For example, it can analyze artwork the child has created and understand the emotion. In this way, emotions can be understood by expressing emotions through creative activities and analyzing them.

[0061] The emotion understanding unit can collect feedback from parents and teachers and use it for analysis. For example, when a child says, "I had a fight with my friend at school today," the emotion understanding unit collects feedback from parents and teachers and uses it for analysis. For example, based on the information from the parents or teachers, it can respond with, "That must have been tough. Why did you fight?" Similarly, when a child says, "I'm feeling sad today," the emotion understanding unit collects feedback from parents and teachers and uses it for analysis. For example, based on the information from the parents or teachers, it can respond with, "Can you tell me why you're sad?" Furthermore, when a child says, "I'm tired today," the emotion understanding unit collects feedback from parents and teachers and uses it for analysis. For example, based on the information from the parents or teachers, it can suggest, "Why don't you listen to some relaxing music?" In this way, by utilizing feedback from parents and teachers for analysis, the accuracy of emotion understanding is improved.

[0062] The emotion understanding unit can use the emotion estimation function to provide advice to parents and teachers based on the child's emotions, thereby enhancing support for the child. For example, when a child says, "I had a fight with my friend at school today," the emotion understanding unit can use the emotion estimation function to provide advice based on the child's emotions to parents and teachers, responding, "That must have been tough. Why did you fight?" Furthermore, when a child says, "I'm feeling sad today," the emotion understanding unit can use the emotion estimation function to provide advice based on the child's emotions to parents and teachers, responding, "Can you tell me why you're sad?" Furthermore, when a child says, "I'm tired today," the emotion understanding unit can use the emotion estimation function to provide advice based on the child's emotions to parents and teachers, suggesting, "Why don't you listen to some relaxing music?" This allows for enhanced support for the child by providing advice to parents and teachers as well.

[0063] The content providing unit allows the generating AI to create an individually customized mental care program according to the child's mental state. For example, when a child says, "I had a fight with a friend at school today," the content providing unit allows the generating AI to create an individually customized mental care program, suggesting, for example, music for relaxation or breathing exercises for stress relief. Also, when a child says, "I'm feeling sad today," the content providing unit allows the generating AI to create an individually customized mental care program, suggesting, for example, games to change the mood or music to relax. Furthermore, when a child says, "I'm tired today," the content providing unit allows the generating AI to create an individually customized mental care program, suggesting, for example, music for relaxation or breathing exercises for stress relief. In this way, individually customized mental care programs can be provided.

[0064] The content providing unit can learn a child's preferences and interests and provide optimal mental care content based on that. For example, when a child says, "I had a fight with a friend at school today," the content providing unit's generation AI learns the child's preferences and interests and provides optimal mental care content based on that. For example, it can suggest music that the child likes. Also, when a child says, "I'm feeling sad today," the content providing unit's generation AI learns the child's preferences and interests and provides optimal mental care content based on that. For example, it can suggest a game that the child likes. Furthermore, when a child says, "I'm tired today," the content providing unit's generation AI learns the child's preferences and interests and provides optimal mental care content based on that. For example, it can suggest music that the child likes to relax. This makes it possible to provide optimal mental care content based on a child's preferences and interests.

[0065] The content providing unit can use the emotion estimation function to provide mental care content in real time that corresponds to the child's emotions. For example, when a child says, "I had a fight with a friend at school today," the content providing unit can use the emotion estimation function to provide mental care content in real time that corresponds to the child's emotions. For example, music for relaxation can be suggested. Furthermore, when a child says, "I'm feeling sad today," the content providing unit can use the emotion estimation function to provide mental care content in real time that corresponds to the child's emotions. For example, a game that will help change the child's mood can be suggested. Furthermore, when a child says, "I'm tired today," the content providing unit can use the emotion estimation function to provide mental care content in real time that corresponds to the child's emotions. For example, music for relaxation can be suggested. In this way, mental care content that corresponds to the child's emotions can be provided in real time.

[0066] The content providing unit can promote mental care for the entire family by including joint activities that can be enjoyed with parents and siblings in the mental care content. For example, when a child says, "I had a fight with a friend at school today," the content providing unit can have the generating AI suggest joint activities that can be enjoyed with parents and siblings, thereby promoting mental care for the entire family. For example, the content providing unit can suggest games that the whole family can enjoy. Furthermore, when a child says, "I'm feeling sad today," the content providing unit can suggest joint activities that can be enjoyed with parents and siblings, thereby promoting mental care for the entire family. For example, the content providing unit can suggest art activities that the whole family can enjoy. Furthermore, when a child says, "I'm tired today," the content providing unit can suggest joint activities that can be enjoyed with parents and siblings, thereby promoting mental care for the entire family. For example, the content providing unit can suggest relaxing music that the whole family can enjoy. This promotes mental care for the entire family.

[0067] The content provider can work with schools and local communities to provide mental care content and strengthen social support. For example, when a child says, "I had a fight with a friend at school today," the content provider can have the generation AI work with schools and local communities to provide mental care content and strengthen social support. For example, the content provider can work with school counselors to provide support. Furthermore, when a child says, "I'm feeling sad today," the content provider can have the generation AI work with schools and local communities to provide mental care content and strengthen social support. For example, the content provider can work with local support groups to provide support. Furthermore, when a child says, "I'm tired today," the content provider can have the generation AI work with schools and local communities to provide mental care content and strengthen social support. For example, the content provider can work with a school's relaxation program to provide support. This allows for strengthening social support through collaboration with schools and local communities.

[0068] The content providing unit uses the emotion estimation function to periodically update mental care content based on the child's emotions, thereby always providing new content. For example, when a child says, "I had a fight with my friend at school today," the content providing unit uses the emotion estimation function to periodically update mental care content based on the child's emotions, thereby always providing new content. For example, new music for relaxation can be suggested. Furthermore, when a child says, "I'm feeling sad today," the content providing unit uses the emotion estimation function to periodically update mental care content based on the child's emotions, thereby always providing new content. For example, a new game that will help change the mood can be suggested. Furthermore, when a child says, "I'm tired today," the content providing unit uses the emotion estimation function to periodically update mental care content based on the child's emotions, thereby always providing new content. For example, new music for relaxation can be suggested. In this way, the emotion-based mental care content can be periodically updated, thereby always providing new content.

[0069] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0070] The mental care system may further include a health management unit that monitors the child's health condition. The health management unit may, for example, measure the child's heart rate and body temperature to understand the child's health condition. The health management unit may also monitor the child's sleep patterns and provide appropriate sleep advice. Furthermore, the health management unit may record the child's diet and provide advice on nutritional balance. This allows not only mental care for the child but also overall health management.

[0071] The mental care system can further include a learning support unit that monitors the child's learning situation. The learning support unit can, for example, record the child's homework progress and provide appropriate learning advice. The learning support unit can also analyze the child's learning style and suggest the optimal learning method. Furthermore, the learning support unit can evaluate the child's learning results and provide feedback to increase motivation. This makes it possible to strengthen mental care through learning support for children.

[0072] The mental care system can further include a creative activity support unit for fostering children's creativity. The creative activity support unit supports children's activities such as drawing pictures and making music. The creative activity support unit can also evaluate children's creations and provide feedback. The creative activity support unit can also provide a place where children can share and interact with other children. This allows mental care to be provided while fostering children's creativity.

[0073] The mental care system may further include a social activity support unit for fostering the child's social skills. The social activity support unit may, for example, provide opportunities for the child to play with friends. The social activity support unit may also support the child's participation in local events. The social activity support unit may also encourage the child to participate in volunteer activities and provide feedback to foster the child's social skills. This allows mental care to be provided while fostering the child's social skills.

[0074] The mental care system can further include a self-esteem improvement unit for improving a child's self-esteem. The self-esteem improvement unit, for example, records the child's achievements and provides praising feedback. The self-esteem improvement unit can also suggest ways for the child to discover his or her strengths and make use of them. Furthermore, the self-esteem improvement unit can also provide support for the child to set and achieve his or her own goals. In this way, mental care can be provided while improving the child's self-esteem.

[0075] The mental care system can further include an emotion feedback unit that estimates the child's emotion and provides appropriate feedback based on the emotion. For example, when a child says, "I had a fight with my friend at school today," the emotion feedback unit estimates the child's emotion and responds, "That must have been tough. Why did you fight?" When a child says, "I'm feeling sad today," the emotion feedback unit can estimate the child's emotion and respond, "Can you tell me why you're sad?" When a child says, "I'm tired today," the emotion feedback unit can estimate the child's emotion and suggest, "Why don't you listen to some relaxing music?" This makes it possible to provide appropriate feedback based on the child's emotion.

[0076] The mental care system may further include an emotional activity suggestion unit that estimates a child's emotion and suggests an appropriate activity based on the emotion. For example, when a child says, "I had a fight with my friend at school today," the emotional activity suggestion unit estimates the emotion and responds, "That must have been tough. Why did you fight?" When a child says, "I'm feeling sad today," the emotional activity suggestion unit can estimate the emotion and respond, "Can you tell me why you're sad?" When a child says, "I'm tired today," the emotional activity suggestion unit can estimate the emotion and suggest, "Why don't you listen to some relaxing music?" This allows appropriate activities to be suggested based on the emotion.

[0077] The mental care system may further include an emotional relaxation suggestion unit that estimates a child's emotions and suggests an appropriate relaxation method based on the emotions. For example, when a child says, "I had a fight with my friend at school today," the emotional relaxation suggestion unit estimates the child's emotions and responds, "That must have been tough. Why did you fight?" When a child says, "I'm feeling sad today," the emotional relaxation suggestion unit can estimate the child's emotions and respond, "Can you tell me why you're sad?" When a child says, "I'm tired today," the emotional relaxation suggestion unit can estimate the child's emotions and suggest, "Why don't you listen to some relaxing music?" This allows appropriate relaxation methods to be suggested based on the child's emotions.

[0078] The mental care system may further include an emotion-based mental care program creation unit that estimates a child's emotion and creates an appropriate mental care program based on that emotion. For example, when a child says, "I had a fight with my friend at school today," the emotion-based mental care program creation unit estimates the child's emotion and responds, "That must have been tough. Why did you fight?" When a child says, "I'm feeling sad today," the emotion-based mental care program creation unit can estimate the child's emotion and respond, "Can you tell me why you're sad?" When a child says, "I'm tired today," the emotion-based mental care program creation unit can estimate the child's emotion and suggest, "Would you like to listen to some relaxing music?" This allows an appropriate mental care program to be created based on emotions.

[0079] The mental care system can further include an emotional mental care content providing unit that estimates a child's emotions and provides appropriate mental care content based on the emotions. For example, when a child says, "I had a fight with my friend at school today," the emotional mental care content providing unit estimates the child's emotions and responds, "That must have been tough. Why did you fight?" When a child says, "I'm feeling sad today," the emotional mental care content providing unit can estimate the child's emotions and respond, "Can you tell me why you're sad?" When a child says, "I'm tired today," the emotional mental care content providing unit can estimate the child's emotions and suggest, "Why don't you listen to some relaxing music?" This allows appropriate mental care content to be provided based on emotions.

[0080] The processing flow of the second embodiment will be briefly explained below.

[0081] Step 1: The dialogue unit converses with the child. For example, the dialogue unit uses voice recognition technology to understand what the child is saying and generate an appropriate response. The dialogue unit can also communicate in text format or through video conversations with the child. Step 2: The emotion understanding unit analyzes the child's utterances acquired by the dialogue unit and understands the emotions. For example, the emotion understanding unit uses voice analysis technology to analyze the tone and speed of the child's voice and infer the emotions. The emotion understanding unit can also use facial expression analysis technology to analyze the child's facial expressions and understand the emotions. Furthermore, the emotion understanding unit can also use text analysis technology to analyze the content of the child's utterances and understand the emotions. Step 3: The advice providing unit provides appropriate advice based on the emotions understood by the emotion understanding unit. For example, if the child is feeling sad, the advice providing unit provides words of encouragement. If the child is feeling stressed, the advice providing unit can also provide specific instructions for action. Furthermore, if the child is feeling anxious, the advice providing unit can also suggest relaxation methods. Step 4: The content providing unit provides content for mental care based on the advice provided by the advice providing unit. For example, the content providing unit provides relaxation music. The content providing unit may also provide a meditation guide. Furthermore, the content providing unit may also provide a game for stress relief.

[0082] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0083] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0084] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0085] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0086] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0087] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0088] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0089] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0090] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0091] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0092] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0093] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0094] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0095] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0096] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0097] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0098] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0099] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0100] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0101] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0102] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0103] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0104] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0105] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0106] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0107] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0108] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0109] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0110] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0111] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0112] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0113] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0114] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0115] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0116] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0117] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0118] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0119] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0120] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0121] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0122] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0123] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0124] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0125] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0126] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0127] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0128] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0129] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0130] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0131] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0132] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0133] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0134] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0135] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0136] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0137] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0138] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0139] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0140] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0141] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0142] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0143] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0144] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0145] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0146] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0147] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0148] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0149] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A dialogue section that talks with children, an emotion understanding unit that analyzes the child's utterances acquired by the dialogue unit and understands their emotions; an advice providing unit that provides appropriate advice based on the emotion understood by the emotion understanding unit; a content providing unit that provides content for mental care based on the advice provided by the advice providing unit. A system characterized by:

2. The dialogue unit Reference past interaction history to generate more personalized responses 2. The system of claim 1.

3. The dialogue unit Analyzing the tone and rate of the child's voice to detect changes in the child's emotions in real time and generating a response accordingly 2. The system of claim 1.

4. The dialogue unit Inferring the child's emotion and generating a response based on the emotion.

2. The system of claim 1.

5. The dialogue unit To enable communication in multiple languages ​​and accommodate children from different cultures 2. The system of claim 1.

Images