System

Abstract

An object of the system according to the embodiment is to allow a user to anonymously express an emotion and receive mental health care without anxiety.SOLUTION: A system according to an embodiment includes an emotion expression unit, a virtual space providing unit, a color scheme customization unit, a history deletion unit, and a mental health service providing unit. The emotion expression unit anonymously expresses an emotion. The virtual space providing unit processes the feeling expressed by the feeling expression unit. The color scheme customizing unit customizes the color scheme of the virtual space provided by the virtual space providing unit. The history deletion part deletes the history of the feeling expressed by the feeling expression part. The mental health service providing unit provides a professional mental health service based on the emotion expressed by the emotion expression 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 technologies have had the problem of making it difficult for users to express their feelings anonymously and receive mental health care with peace of mind.

[0005] The system according to the embodiment aims to enable users to express their feelings anonymously and receive mental health care with peace of mind. [Means for solving the problem]

[0006] The system according to the embodiment includes an emotion expression unit, a virtual space providing unit, a color scheme customization unit, a history deletion unit, and a mental health service providing unit. The emotion expression unit expresses emotions anonymously. The virtual space providing unit processes emotions expressed by the emotion expression unit. The color scheme customization unit customizes the color scheme of the virtual space provided by the virtual space providing unit. The history deletion unit deletes the history of emotions expressed by the emotion expression unit. The mental health service providing unit provides specialized mental health services based on the emotions expressed by the emotion expression unit. [Effects of the Invention]

[0007] The system according to the embodiment allows users to express their feelings anonymously and receive mental health care with peace of mind. [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 "Kokoro Note" system according to an embodiment of the present invention is a system that provides a virtual space in which users can freely and anonymously express their emotions. This allows users to express their emotions with peace of mind and facilitates access to professional mental health services.

[0029] The "Kokoro Note" system according to the embodiment includes an emotion expression unit, a virtual space providing unit, a color scheme customization unit, a history deletion unit, and a mental health service providing unit. The emotion expression unit allows users to anonymously express their emotions. For example, the user inputs their emotions in text, and the generation AI analyzes the emotions and provides appropriate feedback. The emotion expression unit can also accept voice input, understand the emotions through voice analysis, and provide feedback. The virtual space providing unit processes the emotions expressed by the emotion expression unit and provides a virtual space where the user can "vent" their emotions in peace. For example, the generation AI generates a virtual avatar based on the user's emotions to support the expression of emotions. The virtual space providing unit can also automatically change environmental settings based on the user's emotions to promote the expression of emotions. The color scheme customization unit customizes the color scheme of the virtual space provided by the virtual space providing unit. For example, the generation AI suggests a color scheme based on the user's emotions, allowing the user to select a color that matches their emotions. The color scheme customization unit can also refer to the user's past selection history to make more personalized suggestions. The history deletion unit deletes the history of emotions expressed by the emotion expression unit. For example, if a user inputs, "I want to delete the history of past emotional expressions," the generation AI deletes the history according to that instruction. The history deletion unit can also analyze the user's emotion history and notify the user of important information before deletion. The mental health service provision unit provides specialized mental health services based on the emotions expressed by the emotion expression unit. For example, the generation AI can analyze the user's emotion history and recommend the most appropriate mental health professional. The mental health service provision unit can also analyze the user's emotions in real time and immediately contact a professional in an emergency. This allows the "Kokoro Note" system according to the embodiment to allow users to express their emotions with peace of mind and facilitate access to specialized mental health services. For example, users can maintain their mental health by anonymously expressing their daily stresses and worries and receiving feedback on their responses.Additionally, more serious issues can be addressed by accessing specialized mental health services when needed.

[0030] The emotion expression unit can refer to the user's past emotional history and provide more personalized feedback. For example, when a user expresses an emotion, the generation AI refers to the user's past emotional history and provides advice based on past feedback for similar emotional states. For example, it may re-suggest ways to deal with stress in the past. The emotion expression unit also analyzes the user's past emotional history, finds specific patterns, and provides feedback based on those patterns. For example, it may identify regular times when stress is felt and suggest preventative measures. The emotion expression unit also analyzes emotional changes and trends based on the user's past emotional history and provides long-term advice. For example, it may predict emotional ups and downs and suggest appropriate ways to deal with the situation. This allows the generation AI to provide more appropriate feedback to the user.

[0031] The emotion expression unit can generate art and graphics that visually express the user's emotions. For example, when a user inputs an emotion, the generation AI generates abstract art based on that emotion to visually express the emotion. For example, it generates a red spiral to represent anger or a blue teardrop to represent sadness. The emotion expression unit also analyzes the user's emotion and generates graphics that match that emotion. For example, it generates bright flowers to represent joy or dark clouds to represent stress. When a user inputs an emotion, the generation AI generates dynamic animations based on that emotion to visually express changes in emotion. For example, it generates wave movements to represent rising emotions or a tranquil landscape to represent calming emotions. This visual representation of the user's emotions allows for a deeper understanding of emotions.

[0032] The emotion expression unit can analyze the user's emotions in real time and provide feedback according to changes in emotions. For example, when a user inputs an emotion, the emotion expression unit allows the generation AI to analyze the emotion in real time and provide feedback according to changes in emotion. For example, if emotions change suddenly, it will suggest ways to relax. The emotion expression unit also allows the generation AI to analyze the user's emotions in real time and adjust the feedback according to changes in emotion. For example, if emotions start to calm down, it will suggest positive action as the next step. The emotion expression unit also allows the generation AI to analyze the emotion in real time when a user inputs an emotion and provide advice according to changes in emotion. For example, if emotions are heightened, it will suggest deep breathing or meditation. This makes it possible to provide feedback that responds immediately to changes in the user's emotions.

[0033] The emotion expression unit can accept voice input, understand emotions through voice analysis, and provide feedback. For example, when a user expresses emotions through voice, the generation AI analyzes the voice to understand the emotions and provide feedback. For example, it analyzes the tone and speed of the voice and suggests ways to relax if the user is feeling stressed. The emotion expression unit also accepts voice input, understands emotions through voice analysis, and provides appropriate feedback. For example, it analyzes the intonation and strength of the voice to detect heightened emotions and provide advice. The emotion expression unit also accepts voice input, understands emotions, and provides feedback. For example, it checks whether the content of the voice matches the emotions and suggests specific ways to deal with the situation. This makes it possible to understand the user's emotions through voice input and provide appropriate feedback.

[0034] The emotion expression unit generates poetry or lyrics from the user's emotions, thereby diversifying the ways in which emotions can be expressed. For example, when a user inputs an emotion, the emotion expression unit allows the generation AI to generate poetry based on that emotion to express that emotion. For example, it generates poetry that expresses sadness or poetry that expresses joy. The emotion expression unit also allows the generation AI to analyze the user's emotions and generate lyrics based on those emotions. For example, when the user is feeling stressed, it generates lyrics that encourage relaxation. The emotion expression unit also allows the generation AI to generate poetry or lyrics based on the user's emotions, thereby diversifying the ways in which emotions can be expressed. For example, it generates poetry that expresses heightened emotions or lyrics that express calming emotions. In this way, the ways in which emotions can be expressed can be diversified by expressing the user's emotions as poetry or lyrics.

[0035] The emotion expression unit can automatically generate background music according to the user's emotion and emphasize the emotional atmosphere. For example, when a user inputs an emotion, the emotion expression unit has the generation AI automatically generate background music based on that emotion to emphasize the emotional atmosphere. For example, if the user wants to relax, it generates calm music. The emotion expression unit also analyzes the user's emotion and automatically generates background music that matches that emotion. For example, if the user is feeling stressed, it generates music that has a relaxing effect. The emotion expression unit also inputs an emotion, and the emotion expression unit automatically generates background music based on that emotion to emphasize the emotional atmosphere. For example, it generates intense music that represents heightened emotions and quiet music that represents calmed emotions. In this way, the emotional atmosphere can be emphasized by generating background music according to the user's emotion.

[0036] The virtual space providing unit generates a virtual avatar according to the user's emotions and can support the expression of emotions. For example, when a user inputs an emotion, the virtual space providing unit has the generation AI generate a virtual avatar according to that emotion and support the expression of emotions. For example, if the user is feeling sad, it generates an avatar that is shedding tears. The virtual space providing unit also has the generation AI analyze the user's emotions and generate a virtual avatar that matches that emotion. For example, if the user is feeling happy, it generates an avatar that is smiling. The virtual space providing unit also has the user input an emotion, and the generation AI generates a virtual avatar according to that emotion and supports the expression of emotions. For example, if the user is feeling stressed, it generates an avatar with a tired expression. In this way, the expression of emotions can be supported by generating a virtual avatar according to the user's emotions.

[0037] The virtual space providing unit automatically changes the environmental settings according to the user's emotions, thereby promoting emotional expression. For example, when a user inputs an emotion, the virtual space providing unit causes the generation AI to automatically change the environmental settings according to that emotion. For example, if the user wants to relax, the generation AI sets a calm landscape or sunny weather. The virtual space providing unit also analyzes the user's emotions and automatically changes the environmental settings to match that emotion. For example, if the user is feeling stressed, the generation AI sets a quiet forest or ocean landscape. The virtual space providing unit also automatically changes the environmental settings according to that emotion, promoting emotional expression. For example, stormy weather is set to represent heightened emotions, or a calm sunset is set to represent calming emotions. In this way, changing the environmental settings according to the user's emotions can promote emotional expression.

[0038] The virtual space providing unit generates an interactive story according to the user's emotions, thereby deepening the expression of emotions. For example, when a user inputs an emotion, the virtual space providing unit has the generation AI generate an interactive story based on that emotion, thereby deepening the expression of emotions. For example, it generates an adventure story that expresses heightened emotions, or a healing story that expresses calming emotions. In addition, the virtual space providing unit has the generation AI analyze the user's emotions and generate an interactive story that matches those emotions. For example, if the user is feeling stressed, it generates a story that has a relaxing effect. In addition, when a user inputs an emotion, the virtual space providing unit has the generation AI generate an interactive story based on that emotion, thereby deepening the expression of emotions. For example, it generates a dynamic story in which the story progresses according to changes in emotions. In this way, it is possible to deepen the expression of emotions by generating an interactive story according to the user's emotions.

[0039] The virtual space providing unit can provide a virtual pet that corresponds to the user's emotions and support the expression of emotions. For example, when a user inputs an emotion, the virtual space providing unit causes the generation AI to provide a virtual pet that corresponds to that emotion and support the expression of emotions. For example, if the user wants to relax, the virtual space providing unit can provide a pet that moves gently. The virtual space providing unit can also analyze the user's emotions and provide a virtual pet that matches that emotion. For example, if the user is feeling stressed, the virtual space providing unit can provide a pet that has a soothing effect. When a user inputs an emotion, the virtual space providing unit causes the generation AI to provide a virtual pet that corresponds to that emotion and support the expression of emotions. For example, the virtual space providing unit can provide an active pet that represents heightened emotions or a quiet pet that represents calmed emotions. In this way, the virtual space providing unit can support the expression of emotions by providing a virtual pet that corresponds to the user's emotions.

[0040] The virtual space providing unit generates a virtual garden according to the user's emotions, thereby promoting the expression of emotions. For example, when a user inputs an emotion, the virtual space providing unit has the generation AI generate a virtual garden according to that emotion, thereby promoting the expression of emotions. For example, if the user wants to relax, the generation AI generates a garden with a tranquil landscape. The virtual space providing unit also analyzes the user's emotions and generates a virtual garden that matches those emotions. For example, if the user is feeling stressed, the generation AI generates a garden that has a soothing effect. The virtual space providing unit also generates a virtual garden according to the emotion, thereby promoting the expression of emotions. For example, it generates a colorful garden that represents heightened emotions or a tranquil garden that represents calmed emotions. In this way, the generation of a virtual garden according to the user's emotions can be promoted.

[0041] The virtual space providing unit can hold a virtual event according to the user's emotions, thereby deepening the expression of the emotion. For example, when a user inputs an emotion, the virtual space providing unit causes the generation AI to hold a virtual event according to that emotion, thereby deepening the expression of the emotion. For example, if the user wants to relax, the generation AI can hold a calming music concert. The virtual space providing unit also analyzes the user's emotions and holds a virtual event that matches that emotion. For example, if the user is feeling stressed, the generation AI can hold an exhibition that has a soothing effect. The virtual space providing unit also inputs an emotion, and the generation AI can hold a virtual event according to that emotion, thereby deepening the expression of the emotion. For example, the generation AI can hold an energetic concert that represents heightened emotions or a quiet exhibition that represents calming emotions. In this way, the expression of the emotion can be deepened by holding a virtual event according to the user's emotions.

[0042] The color scheme customization unit can refer to the user's past selection history to make more personalized suggestions. For example, when a user customizes a color scheme, the generation AI refers to the user's past selection history to suggest colors chosen in similar situations. For example, the color scheme customization unit re-suggests colors chosen in the past when the user wanted to relax. The color scheme customization unit also analyzes the user's past color scheme selection history, finds specific patterns, and makes suggestions based on those patterns. For example, it suggests colors chosen for specific emotional states. Furthermore, when a user customizes a color scheme, the generation AI analyzes emotional changes and trends based on the user's past selection history to make long-term suggestions. For example, it suggests color schemes that correspond to emotional ups and downs. In this way, by referring to the user's past selection history, more appropriate color schemes can be suggested.

[0043] The color scheme customization unit can add animation effects according to the user's emotions to enhance emotional expression. For example, when a user customizes a color scheme, the color scheme customization unit has the generation AI analyze the emotion and add animation effects according to that emotion. For example, if the user wants to relax, a gentle animation is added. The color scheme customization unit also has the generation AI analyze the user's emotions and add animation effects that match the emotion. For example, if the user is feeling stressed, an animation with a soothing effect is added. The color scheme customization unit also has the generation AI analyze the emotion when a user customizes a color scheme and add animation effects according to the emotion. For example, a dynamic animation that represents an increase in emotion or a calm animation that represents a decrease in emotion is added. In this way, by adding animation effects according to the user's emotions, emotional expression can be enhanced.

[0044] The color scheme customization unit can analyze a user's emotions in real time and suggest a color scheme that corresponds to changes in emotions. For example, when a user customizes a color scheme, the color scheme customization unit uses the generation AI to analyze emotions in real time and suggest a color scheme that corresponds to changes in emotions. For example, if there is a sudden change in emotions, the generation AI suggests an appropriate color. The color scheme customization unit also analyzes a user's emotions in real time and adjusts the color scheme according to changes in emotions. For example, if emotions are calming down, the generation AI suggests a color that has a relaxing effect. When a user customizes a color scheme, the generation AI also analyzes emotions in real time and suggests a color scheme that corresponds to changes in emotions. For example, it suggests bright colors that represent heightened emotions and calm colors that represent calmed emotions. This makes it possible to optimize the expression of emotions by suggesting color schemes that correspond to changes in the user's emotions.

[0045] The color scheme customization unit suggests textures and patterns according to the user's emotions, thereby diversifying the expression of emotions. For example, when a user customizes a color scheme, the color scheme customization unit uses the generation AI to analyze the user's emotions and suggest textures and patterns according to that emotion. For example, if the user wants to relax, it suggests a calm texture. The color scheme customization unit also analyzes the user's emotions and suggests textures and patterns that match that emotion. For example, if the user is feeling stressed, it suggests a pattern that has a soothing effect. The color scheme customization unit also analyzes the user's emotions when a user customizes a color scheme, and suggests textures and patterns according to that emotion. For example, it suggests a dynamic pattern that represents heightened emotions and a calm texture that represents calmed emotions. In this way, by suggesting textures and patterns according to the user's emotions, it is possible to diversify the expression of emotions.

[0046] The color scheme customization unit can suggest light intensity and shadow effects according to the user's emotions, thereby enhancing emotional expression. For example, when a user customizes a color scheme, the generation AI analyzes the user's emotions and suggests light intensity and shadow effects according to that emotion. For example, if the user wants to relax, a gentle light intensity is suggested. The color scheme customization unit can also analyze the user's emotions and suggest light intensity and shadow effects that match that emotion. For example, if the user is feeling stressed, a shadow effect with a soothing effect is suggested. When a user customizes a color scheme, the generation AI analyzes the user's emotions and suggests light intensity and shadow effects according to that emotion. For example, a strong light that represents heightened emotions and a soft shadow that represents calmed emotions are suggested. This makes it possible to enhance emotional expression by suggesting light intensity and shadow effects according to the user's emotions.

[0047] The color scheme customization unit generates virtual art according to the user's emotions, thereby deepening the expression of emotions. For example, when a user customizes a color scheme, the color scheme customization unit uses a generation AI to analyze the user's emotions and generate virtual art according to those emotions. For example, if the user wants to relax, the color scheme customization unit generates art with calming colors. The color scheme customization unit also analyzes the user's emotions and generates virtual art that matches those emotions. For example, if the user is feeling stressed, the color scheme customization unit generates art that has a soothing effect. The color scheme customization unit also analyzes the user's emotions when a user customizes a color scheme, the color scheme customization unit uses a generation AI to analyze the user's emotions and generate virtual art according to those emotions. For example, the color scheme customization unit generates dynamic art that represents heightened emotions or tranquil art that represents calmed emotions. This allows the user to deepen their emotional expression by generating virtual art according to their emotions.

[0048] The history deletion unit can analyze the user's emotional history and notify the user of important information before deletion. For example, when the user deletes the history, the generation AI analyzes the emotional history and notifies the user of important information. For example, it notifies the user of past emotional changes and trends. The history deletion unit also analyzes the user's emotional history and notifies the user of important information before deletion. For example, it notifies the user of how to deal with a particular emotional state. The history deletion unit also analyzes the emotional history and notifies the user of important information when the user deletes the history. For example, it predicts emotional ups and downs and notifies the user of appropriate ways to deal with the situation. In this way, by notifying the user of important information before deleting the emotional history, the user does not lose necessary information.

[0049] The history deletion unit can back up the user's emotion history and enable it to be restored as needed. For example, when the user deletes the history, the history deletion unit enables the generation AI to back up the emotion history and restore it as needed. For example, past changes and trends in emotions are restored. The history deletion unit also enables the generation AI to back up the user's emotion history and restore it as needed. For example, it restores countermeasures for specific emotional states. The history deletion unit also enables the generation AI to back up the emotion history and restore it as needed when the user deletes the history. For example, it predicts emotional ups and downs and restores appropriate countermeasures. In this way, by backing up the emotion history and enabling it to be restored as needed, the user does not lose important information.

[0050] The history deletion unit can analyze the user's emotions, predict emotional changes after deletion, and provide feedback. For example, when a user deletes history, the generation AI in the history deletion unit analyzes the user's emotions, predicts emotional changes after deletion, and provides feedback. For example, if emotions change suddenly, the generation AI suggests an appropriate way to deal with the situation. The history deletion unit also analyzes the user's emotions, predicts emotional changes after deletion, and provides feedback. For example, if emotions begin to calm down, the generation AI suggests a way to deal with emotions that has a relaxing effect. The history deletion unit also analyzes the user's emotions, predicts emotional changes after deletion, and provides feedback. For example, it suggests a way to deal with emotions that indicates an increase in emotions or a way to calm emotions. In this way, the generation AI can predict emotional changes after deleting emotional history and provide appropriate feedback, thereby stabilizing the user's emotions.

[0051] The history deletion unit can anonymize the user's emotional history so that it can be used for data analysis. For example, when a user deletes their history, the history deletion unit allows the generation AI to anonymize the emotional history so that it can be used for data analysis. For example, it anonymizes and analyzes emotional changes and trends. The history deletion unit also anonymizes the user's emotional history so that it can be used for data analysis. For example, it anonymizes and analyzes ways to deal with specific emotional states. The history deletion unit also anonymizes the emotional history so that it can be used for data analysis when a user deletes their history. For example, it anonymizes and analyzes emotional ups and downs and suggests appropriate ways to deal with them. In this way, by anonymizing the emotional history and using it for data analysis, it is possible to effectively utilize data while protecting the user's privacy.

[0052] The history deletion unit can compress the user's emotional history and enable partial deletion as needed. For example, when a user deletes the history, the history deletion unit enables the generation AI to compress the emotional history and enable partial deletion as needed. For example, it compresses and saves emotional history for a specific period of time. The history deletion unit also enables the generation AI to compress the user's emotional history and enable partial deletion as needed. For example, it compresses and saves ways to deal with specific emotional states. The history deletion unit also enables the generation AI to compress the emotional history and enable partial deletion as needed when a user deletes the history. For example, it compresses and saves emotional ups and downs and suggests appropriate ways to deal with them. In this way, by compressing the emotional history and enabling partial deletion as needed, data management is made easier while protecting the user's privacy.

[0053] The history deletion unit can analyze the user's emotions and monitor emotional changes after deletion in real time. For example, when a user deletes history, the generation AI in the history deletion unit analyzes the user's emotions and monitors emotional changes after deletion in real time. For example, if there is a sudden change in emotions, it proposes an appropriate response. The history deletion unit also analyzes the user's emotions and monitors emotional changes after deletion in real time. For example, if the emotions begin to calm down, it proposes a response that has a relaxing effect. The history deletion unit also analyzes the user's emotions when a user deletes history, and monitors emotional changes after deletion in real time. For example, it proposes a response that indicates an increase in emotions or a response that indicates a calming of emotions. In this way, by monitoring emotional changes in real time after deleting emotional history, it is possible to stabilize the user's emotions.

[0054] The mental health service provision unit can analyze the user's emotional history and recommend the most appropriate mental health specialist. For example, when the user inputs their emotions, the mental health service provision unit has the generation AI analyze the emotional history and recommend the most appropriate mental health specialist. For example, it recommends a specialist for a specific emotional state. The mental health service provision unit also has the generation AI analyze the user's emotional history and recommend the most appropriate mental health specialist. For example, it recommends an appropriate specialist based on past emotional history. The mental health service provision unit also has the generation AI analyze the user's emotional history and recommend the most appropriate mental health specialist. For example, it analyzes emotional changes and trends and recommends an appropriate specialist. In this way, by analyzing the emotional history and recommending the most appropriate mental health specialist, the user can receive appropriate support.

[0055] The mental health service provision unit can automatically make a reservation for a specialized mental health service based on the user's emotional history. For example, when a user inputs their emotions, the mental health service provision unit has a generation AI automatically make a reservation for a specialized mental health service based on the emotional history. For example, it reserves a service for a specific emotional state. In addition, the mental health service provision unit has a generation AI analyze the user's emotional history and automatically make a reservation for a specialized mental health service. For example, it reserves an appropriate service based on past emotional history. In addition, when a user inputs their emotions, the generation AI automatically makes a reservation for a specialized mental health service based on the emotional history. For example, it analyzes emotional changes and trends and reserves an appropriate service. In this way, by automatically making a reservation for a specialized mental health service based on the emotional history, the user can receive support quickly.

[0056] The mental health service provision unit analyzes the user's emotions in real time and can immediately contact a specialist in an emergency. For example, when a user inputs their emotions, the mental health service provision unit has the generation AI analyze the emotions in real time and immediately contact a specialist in an emergency. For example, a specialist will be contacted if there is a sudden change in emotions. The mental health service provision unit also analyzes the user's emotions in real time and immediately contacts a specialist in an emergency. For example, if the emotions begin to calm down, it will suggest a coping method that has a relaxing effect. The mental health service provision unit also analyzes the user's emotions in real time and immediately contacts a specialist in an emergency. For example, it will suggest a coping method that represents an increase in emotions and a coping method that represents a calming emotion. In this way, emotions are analyzed in real time and a specialist is immediately contacted in an emergency, allowing the user to receive prompt and appropriate support.

[0057] The mental health service providing unit can analyze the user's emotional history and suggest online counseling or support groups. For example, when a user inputs their emotions, the mental health service providing unit has the generation AI analyze the emotional history and suggest online counseling or support groups. For example, it suggests counseling for a specific emotional state. The mental health service providing unit also has the generation AI analyze the user's emotional history and suggest online counseling or support groups. For example, it suggests appropriate counseling based on past emotional history. The mental health service providing unit also has the generation AI analyze the user's emotional history and suggest online counseling or support groups. For example, it analyzes emotional changes and trends and suggests appropriate counseling. In this way, by analyzing the emotional history and suggesting online counseling or support groups, the user can receive appropriate support.

[0058] The mental health service providing unit can provide self-care resources based on the user's emotional history. For example, when the user inputs their emotions, the generation AI provides self-care resources based on the emotional history. For example, it may provide a meditation guide for a specific emotional state. In addition, the mental health service providing unit analyzes the user's emotional history and provides self-care resources. For example, it may provide appropriate relaxation techniques based on past emotional history. In addition, when the user inputs their emotions, the generation AI provides self-care resources based on the emotional history. For example, it may analyze emotional changes and trends and provide appropriate self-care resources. In this way, providing self-care resources based on emotional history makes it easier for the user to manage themselves.

[0059] The mental health service providing unit can analyze a user's emotions in real time and provide mental health resources corresponding to the emotions in real time. For example, when a user inputs an emotion, the mental health service providing unit has the generation AI analyze the emotion in real time and provide mental health resources corresponding to the emotion. For example, if an emotion suddenly changes, an appropriate resource is provided. The mental health service providing unit also has the generation AI analyze a user's emotions in real time and provide mental health resources corresponding to the emotion. For example, if an emotion is calming down, a resource with a relaxing effect is provided. The mental health service providing unit also has the generation AI analyze a user's emotions in real time and provide mental health resources corresponding to the emotion. For example, a resource representing an increase in emotion or a resource representing a calming emotion is provided. In this way, emotions are analyzed in real time and mental health resources corresponding to the emotion are provided in real time, allowing the user to receive appropriate support quickly.

[0060] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0061] The emotion expression unit can also generate poems or lyrics based on the user's emotions. For example, if the user is feeling sad, it can generate soothing poetry. The emotion expression unit can also suggest lyrics that have a relaxing effect or lyrics that boost energy, depending on the user's emotions. Furthermore, the emotion expression unit can dynamically update poems or lyrics according to changes in the user's emotions, always providing the most appropriate expression.

[0062] The virtual space providing unit can also generate a virtual garden based on the user's emotions, encouraging emotional expression. For example, if the user wants to relax, it can generate a garden with a tranquil landscape. The virtual space providing unit can also change the garden's environment and the types of plants depending on the user's emotions. Furthermore, when the user inputs their emotions, the generating AI can suggest actions for the garden that correspond to those emotions, deepening the emotional expression.

[0063] The color scheme customization unit can also suggest textures and patterns according to the user's emotions, diversifying the expression of emotions. For example, if the user wants to relax, it can suggest a calm texture. The color scheme customization unit can also change the type of texture or pattern according to the user's emotions. Furthermore, when the user inputs an emotion, the generation AI can suggest textures and patterns according to that emotion, enhancing the expression of that emotion.

[0064] The history deletion unit can also anonymize the user's emotional history and make it available for data analysis. For example, it can anonymize and analyze changes and trends in emotions. The history deletion unit can also anonymize and analyze ways to deal with specific emotional states based on the user's emotional history. Furthermore, the history deletion unit can anonymize and analyze emotional ups and downs and suggest appropriate ways to deal with them. In this way, anonymizing the emotional history and using it for data analysis enables effective use of data while protecting the user's privacy.

[0065] The mental health service provider can analyze the user's emotions in real time and immediately contact a specialist in an emergency. For example, when a user inputs their emotions, the generation AI analyzes them in real time and contacts a specialist if their emotions change suddenly. The mental health service provider can also suggest ways to cope with the user's emotions that have a relaxing effect. Furthermore, when a user inputs their emotions, the generation AI can analyze the heightening or calming of emotions in real time and suggest appropriate ways to cope. This allows emotions to be analyzed in real time and experts to be contacted immediately in an emergency, allowing users to receive prompt and appropriate support.

[0066] The processing flow of the first embodiment will be briefly explained below.

[0067] Step 1: The emotion expression unit allows the user to anonymously express their emotions. For example, the user can input their emotions in text, and the generation AI will analyze the emotions and provide appropriate feedback. The emotion expression unit can also accept voice input, understand emotions through voice analysis, and provide feedback. Step 2: The virtual space provider processes the emotions expressed by the emotion expression component and provides a virtual space where the user can "vent" their emotions in peace. For example, the generation AI generates a virtual avatar according to the user's emotions to support emotional expression. The virtual space provider can also automatically change the environment settings according to the user's emotions to encourage emotional expression. Step 3: The color scheme customization unit customizes the color scheme of the virtual space provided by the virtual space provision unit. For example, the generation AI suggests a color scheme according to the user's emotions, allowing the user to select a color that matches their emotion. The color scheme customization unit can also refer to the user's past selection history to make more personalized suggestions. Step 4: The history deletion unit deletes the history of emotions expressed by the emotion expression unit. For example, if a user inputs, "I want to delete the history of past emotional expressions," the generation AI will delete the history according to that instruction. The history deletion unit can also analyze the user's emotional history and notify them of important information before deletion. Step 5: The mental health service provider provides professional mental health services based on the emotions expressed by the emotion expression unit. For example, the generation AI analyzes the user's emotion history and recommends the most suitable mental health professional. The mental health service provider can also analyze the user's emotions in real time and immediately contact a professional in an emergency.

[0068] (Example 2) The "Kokoro Note" system according to an embodiment of the present invention is a system that provides a virtual space in which users can freely and anonymously express their emotions. This allows users to express their emotions with peace of mind and facilitates access to professional mental health services.

[0069] The "Kokoro Note" system according to the embodiment includes an emotion expression unit, a virtual space providing unit, a color scheme customization unit, a history deletion unit, and a mental health service providing unit. The emotion expression unit allows users to anonymously express their emotions. For example, the user inputs their emotions in text, and the generation AI analyzes the emotions and provides appropriate feedback. The emotion expression unit can also accept voice input, understand the emotions through voice analysis, and provide feedback. The virtual space providing unit processes the emotions expressed by the emotion expression unit and provides a virtual space where the user can "vent" their emotions in peace. For example, the generation AI generates a virtual avatar based on the user's emotions to support the expression of emotions. The virtual space providing unit can also automatically change environmental settings based on the user's emotions to promote the expression of emotions. The color scheme customization unit customizes the color scheme of the virtual space provided by the virtual space providing unit. For example, the generation AI suggests a color scheme based on the user's emotions, allowing the user to select a color that matches their emotions. The color scheme customization unit can also refer to the user's past selection history to make more personalized suggestions. The history deletion unit deletes the history of emotions expressed by the emotion expression unit. For example, if a user inputs, "I want to delete the history of past emotional expressions," the generation AI deletes the history according to that instruction. The history deletion unit can also analyze the user's emotion history and notify the user of important information before deletion. The mental health service provision unit provides specialized mental health services based on the emotions expressed by the emotion expression unit. For example, the generation AI can analyze the user's emotion history and recommend the most appropriate mental health professional. The mental health service provision unit can also analyze the user's emotions in real time and immediately contact a professional in an emergency. This allows the "Kokoro Note" system according to the embodiment to allow users to express their emotions with peace of mind and facilitate access to specialized mental health services. For example, users can maintain their mental health by anonymously expressing their daily stresses and worries and receiving feedback on their responses.Additionally, more serious issues can be addressed by accessing specialized mental health services when needed.

[0070] The emotion expression unit can refer to the user's past emotional history and provide more personalized feedback. For example, when a user expresses an emotion, the generation AI refers to the user's past emotional history and provides advice based on past feedback for similar emotional states. For example, it may re-suggest ways to deal with stress in the past. The emotion expression unit also analyzes the user's past emotional history, finds specific patterns, and provides feedback based on those patterns. For example, it may identify regular times when stress is felt and suggest preventative measures. The emotion expression unit also analyzes emotional changes and trends based on the user's past emotional history and provides long-term advice. For example, it may predict emotional ups and downs and suggest appropriate ways to deal with the situation. This allows the generation AI to provide more appropriate feedback to the user.

[0071] The emotion expression unit can generate art and graphics that visually express the user's emotions. For example, when a user inputs an emotion, the generation AI generates abstract art based on that emotion to visually express the emotion. For example, it generates a red spiral to represent anger or a blue teardrop to represent sadness. The emotion expression unit also analyzes the user's emotion and generates graphics that match that emotion. For example, it generates bright flowers to represent joy or dark clouds to represent stress. When a user inputs an emotion, the generation AI generates dynamic animations based on that emotion to visually express changes in emotion. For example, it generates wave movements to represent rising emotions or a tranquil landscape to represent calming emotions. This visual representation of the user's emotions allows for a deeper understanding of emotions.

[0072] The emotion expression unit can analyze the user's emotions in real time and provide feedback according to changes in emotions. For example, when a user inputs an emotion, the emotion expression unit allows the generation AI to analyze the emotion in real time and provide feedback according to changes in emotion. For example, if emotions change suddenly, it will suggest ways to relax. The emotion expression unit also allows the generation AI to analyze the user's emotions in real time and adjust the feedback according to changes in emotion. For example, if emotions start to calm down, it will suggest positive action as the next step. The emotion expression unit also allows the generation AI to analyze the emotion in real time when a user inputs an emotion and provide advice according to changes in emotion. For example, if emotions are heightened, it will suggest deep breathing or meditation. This makes it possible to provide feedback that responds immediately to changes in the user's emotions.

[0073] The emotion expression unit can accept voice input, understand emotions through voice analysis, and provide feedback. For example, when a user expresses emotions through voice, the generation AI analyzes the voice to understand the emotions and provide feedback. For example, it analyzes the tone and speed of the voice and suggests ways to relax if the user is feeling stressed. The emotion expression unit also accepts voice input, understands emotions through voice analysis, and provides appropriate feedback. For example, it analyzes the intonation and strength of the voice to detect heightened emotions and provide advice. The emotion expression unit also accepts voice input, understands emotions, and provides feedback. For example, it checks whether the content of the voice matches the emotions and suggests specific ways to deal with the situation. This makes it possible to understand the user's emotions through voice input and provide appropriate feedback.

[0074] The emotion expression unit generates poetry or lyrics from the user's emotions, thereby diversifying the ways in which emotions can be expressed. For example, when a user inputs an emotion, the emotion expression unit allows the generation AI to generate poetry based on that emotion to express that emotion. For example, it generates poetry that expresses sadness or poetry that expresses joy. The emotion expression unit also allows the generation AI to analyze the user's emotions and generate lyrics based on those emotions. For example, when the user is feeling stressed, it generates lyrics that encourage relaxation. The emotion expression unit also allows the generation AI to generate poetry or lyrics based on the user's emotions, thereby diversifying the ways in which emotions can be expressed. For example, it generates poetry that expresses heightened emotions or lyrics that express calming emotions. In this way, the ways in which emotions can be expressed can be diversified by expressing the user's emotions as poetry or lyrics.

[0075] The emotion expression unit can automatically generate background music according to the user's emotion and emphasize the emotional atmosphere. For example, when a user inputs an emotion, the emotion expression unit has the generation AI automatically generate background music based on that emotion to emphasize the emotional atmosphere. For example, if the user wants to relax, it generates calm music. The emotion expression unit also analyzes the user's emotion and automatically generates background music that matches that emotion. For example, if the user is feeling stressed, it generates music that has a relaxing effect. The emotion expression unit also inputs an emotion, and the emotion expression unit automatically generates background music based on that emotion to emphasize the emotional atmosphere. For example, it generates intense music that represents heightened emotions and quiet music that represents calmed emotions. In this way, the emotional atmosphere can be emphasized by generating background music according to the user's emotion.

[0076] The virtual space providing unit generates a virtual avatar according to the user's emotions and can support the expression of emotions. For example, when a user inputs an emotion, the virtual space providing unit has the generation AI generate a virtual avatar according to that emotion and support the expression of emotions. For example, if the user is feeling sad, it generates an avatar that is shedding tears. The virtual space providing unit also has the generation AI analyze the user's emotions and generate a virtual avatar that matches that emotion. For example, if the user is feeling happy, it generates an avatar that is smiling. The virtual space providing unit also has the user input an emotion, and the generation AI generates a virtual avatar according to that emotion and supports the expression of emotions. For example, if the user is feeling stressed, it generates an avatar with a tired expression. In this way, the expression of emotions can be supported by generating a virtual avatar according to the user's emotions.

[0077] The virtual space providing unit automatically changes the environmental settings according to the user's emotions, thereby promoting emotional expression. For example, when a user inputs an emotion, the virtual space providing unit causes the generation AI to automatically change the environmental settings according to that emotion. For example, if the user wants to relax, the generation AI sets a calm landscape or sunny weather. The virtual space providing unit also analyzes the user's emotions and automatically changes the environmental settings to match that emotion. For example, if the user is feeling stressed, the generation AI sets a quiet forest or ocean landscape. The virtual space providing unit also automatically changes the environmental settings according to that emotion, promoting emotional expression. For example, stormy weather is set to represent heightened emotions, or a calm sunset is set to represent calming emotions. In this way, changing the environmental settings according to the user's emotions can promote emotional expression.

[0078] The virtual space providing unit generates an interactive story according to the user's emotions, thereby deepening the expression of emotions. For example, when a user inputs an emotion, the virtual space providing unit has the generation AI generate an interactive story based on that emotion, thereby deepening the expression of emotions. For example, it generates an adventure story that expresses heightened emotions, or a healing story that expresses calming emotions. In addition, the virtual space providing unit has the generation AI analyze the user's emotions and generate an interactive story that matches those emotions. For example, if the user is feeling stressed, it generates a story that has a relaxing effect. In addition, when a user inputs an emotion, the virtual space providing unit has the generation AI generate an interactive story based on that emotion, thereby deepening the expression of emotions. For example, it generates a dynamic story in which the story progresses according to changes in emotions. In this way, it is possible to deepen the expression of emotions by generating an interactive story according to the user's emotions.

[0079] The virtual space providing unit can provide a virtual pet that corresponds to the user's emotions and support the expression of emotions. For example, when a user inputs an emotion, the virtual space providing unit causes the generation AI to provide a virtual pet that corresponds to that emotion and support the expression of emotions. For example, if the user wants to relax, the virtual space providing unit can provide a pet that moves gently. The virtual space providing unit can also analyze the user's emotions and provide a virtual pet that matches that emotion. For example, if the user is feeling stressed, the virtual space providing unit can provide a pet that has a soothing effect. When a user inputs an emotion, the virtual space providing unit causes the generation AI to provide a virtual pet that corresponds to that emotion and support the expression of emotions. For example, the virtual space providing unit can provide an active pet that represents heightened emotions or a quiet pet that represents calmed emotions. In this way, the virtual space providing unit can support the expression of emotions by providing a virtual pet that corresponds to the user's emotions.

[0080] The virtual space providing unit generates a virtual garden according to the user's emotions, thereby promoting the expression of emotions. For example, when a user inputs an emotion, the virtual space providing unit has the generation AI generate a virtual garden according to that emotion, thereby promoting the expression of emotions. For example, if the user wants to relax, the generation AI generates a garden with a tranquil landscape. The virtual space providing unit also analyzes the user's emotions and generates a virtual garden that matches those emotions. For example, if the user is feeling stressed, the generation AI generates a garden that has a soothing effect. The virtual space providing unit also generates a virtual garden according to the emotion, thereby promoting the expression of emotions. For example, it generates a colorful garden that represents heightened emotions or a tranquil garden that represents calmed emotions. In this way, the generation of a virtual garden according to the user's emotions can be promoted.

[0081] The virtual space providing unit can hold a virtual event according to the user's emotions, thereby deepening the expression of the emotion. For example, when a user inputs an emotion, the virtual space providing unit causes the generation AI to hold a virtual event according to that emotion, thereby deepening the expression of the emotion. For example, if the user wants to relax, the generation AI can hold a calming music concert. The virtual space providing unit also analyzes the user's emotions and holds a virtual event that matches that emotion. For example, if the user is feeling stressed, the generation AI can hold an exhibition that has a soothing effect. The virtual space providing unit also inputs an emotion, and the generation AI can hold a virtual event according to that emotion, thereby deepening the expression of the emotion. For example, the generation AI can hold an energetic concert that represents heightened emotions or a quiet exhibition that represents calming emotions. In this way, the expression of the emotion can be deepened by holding a virtual event according to the user's emotions.

[0082] The color scheme customization unit can refer to the user's past selection history to make more personalized suggestions. For example, when a user customizes a color scheme, the generation AI refers to the user's past selection history to suggest colors chosen in similar situations. For example, the color scheme customization unit re-suggests colors chosen in the past when the user wanted to relax. The color scheme customization unit also analyzes the user's past color scheme selection history, finds specific patterns, and makes suggestions based on those patterns. For example, it suggests colors chosen for specific emotional states. Furthermore, when a user customizes a color scheme, the generation AI analyzes emotional changes and trends based on the user's past selection history to make long-term suggestions. For example, it suggests color schemes that correspond to emotional ups and downs. In this way, by referring to the user's past selection history, more appropriate color schemes can be suggested.

[0083] The color scheme customization unit can add animation effects according to the user's emotions to enhance emotional expression. For example, when a user customizes a color scheme, the color scheme customization unit has the generation AI analyze the emotion and add animation effects according to that emotion. For example, if the user wants to relax, a gentle animation is added. The color scheme customization unit also has the generation AI analyze the user's emotions and add animation effects that match the emotion. For example, if the user is feeling stressed, an animation with a soothing effect is added. The color scheme customization unit also has the generation AI analyze the emotion when a user customizes a color scheme and add animation effects according to the emotion. For example, a dynamic animation that represents an increase in emotion or a calm animation that represents a decrease in emotion is added. In this way, by adding animation effects according to the user's emotions, emotional expression can be enhanced.

[0084] The color scheme customization unit can analyze a user's emotions in real time and suggest a color scheme that corresponds to changes in emotions. For example, when a user customizes a color scheme, the color scheme customization unit uses the generation AI to analyze emotions in real time and suggest a color scheme that corresponds to changes in emotions. For example, if there is a sudden change in emotions, the generation AI suggests an appropriate color. The color scheme customization unit also analyzes a user's emotions in real time and adjusts the color scheme according to changes in emotions. For example, if emotions are calming down, the generation AI suggests a color that has a relaxing effect. When a user customizes a color scheme, the generation AI also analyzes emotions in real time and suggests a color scheme that corresponds to changes in emotions. For example, it suggests bright colors that represent heightened emotions and calm colors that represent calmed emotions. This makes it possible to optimize the expression of emotions by suggesting color schemes that correspond to changes in the user's emotions.

[0085] The color scheme customization unit suggests textures and patterns according to the user's emotions, thereby diversifying the expression of emotions. For example, when a user customizes a color scheme, the color scheme customization unit uses the generation AI to analyze the user's emotions and suggest textures and patterns according to that emotion. For example, if the user wants to relax, it suggests a calm texture. The color scheme customization unit also analyzes the user's emotions and suggests textures and patterns that match that emotion. For example, if the user is feeling stressed, it suggests a pattern that has a soothing effect. The color scheme customization unit also analyzes the user's emotions when a user customizes a color scheme, and suggests textures and patterns according to that emotion. For example, it suggests a dynamic pattern that represents heightened emotions and a calm texture that represents calmed emotions. In this way, by suggesting textures and patterns according to the user's emotions, it is possible to diversify the expression of emotions.

[0086] The color scheme customization unit can suggest light intensity and shadow effects according to the user's emotions, thereby enhancing emotional expression. For example, when a user customizes a color scheme, the generation AI analyzes the user's emotions and suggests light intensity and shadow effects according to that emotion. For example, if the user wants to relax, a gentle light intensity is suggested. The color scheme customization unit can also analyze the user's emotions and suggest light intensity and shadow effects that match that emotion. For example, if the user is feeling stressed, a shadow effect with a soothing effect is suggested. When a user customizes a color scheme, the generation AI analyzes the user's emotions and suggests light intensity and shadow effects according to that emotion. For example, a strong light that represents heightened emotions and a soft shadow that represents calmed emotions are suggested. This makes it possible to enhance emotional expression by suggesting light intensity and shadow effects according to the user's emotions.

[0087] The color scheme customization unit generates virtual art according to the user's emotions, thereby deepening the expression of emotions. For example, when a user customizes a color scheme, the color scheme customization unit uses a generation AI to analyze the user's emotions and generate virtual art according to those emotions. For example, if the user wants to relax, the color scheme customization unit generates art with calming colors. The color scheme customization unit also analyzes the user's emotions and generates virtual art that matches those emotions. For example, if the user is feeling stressed, the color scheme customization unit generates art that has a soothing effect. The color scheme customization unit also analyzes the user's emotions when a user customizes a color scheme, the color scheme customization unit uses a generation AI to analyze the user's emotions and generate virtual art according to those emotions. For example, the color scheme customization unit generates dynamic art that represents heightened emotions or tranquil art that represents calmed emotions. This allows the user to deepen their emotional expression by generating virtual art according to their emotions.

[0088] The history deletion unit can analyze the user's emotional history and notify the user of important information before deletion. For example, when the user deletes the history, the generation AI analyzes the emotional history and notifies the user of important information. For example, it notifies the user of past emotional changes and trends. The history deletion unit also analyzes the user's emotional history and notifies the user of important information before deletion. For example, it notifies the user of how to deal with a particular emotional state. The history deletion unit also analyzes the emotional history and notifies the user of important information when the user deletes the history. For example, it predicts emotional ups and downs and notifies the user of appropriate ways to deal with the situation. In this way, by notifying the user of important information before deleting the emotional history, the user does not lose necessary information.

[0089] The history deletion unit can back up the user's emotion history and enable it to be restored as needed. For example, when the user deletes the history, the history deletion unit enables the generation AI to back up the emotion history and restore it as needed. For example, past changes and trends in emotions are restored. The history deletion unit also enables the generation AI to back up the user's emotion history and restore it as needed. For example, it restores countermeasures for specific emotional states. The history deletion unit also enables the generation AI to back up the emotion history and restore it as needed when the user deletes the history. For example, it predicts emotional ups and downs and restores appropriate countermeasures. In this way, by backing up the emotion history and enabling it to be restored as needed, the user does not lose important information.

[0090] The history deletion unit can analyze the user's emotions, predict emotional changes after deletion, and provide feedback. For example, when a user deletes history, the generation AI in the history deletion unit analyzes the user's emotions, predicts emotional changes after deletion, and provides feedback. For example, if emotions change suddenly, the generation AI suggests an appropriate way to deal with the situation. The history deletion unit also analyzes the user's emotions, predicts emotional changes after deletion, and provides feedback. For example, if emotions begin to calm down, the generation AI suggests a way to deal with emotions that has a relaxing effect. The history deletion unit also analyzes the user's emotions, predicts emotional changes after deletion, and provides feedback. For example, it suggests a way to deal with emotions that indicates an increase in emotions or a way to calm emotions. In this way, the generation AI can predict emotional changes after deleting emotional history and provide appropriate feedback, thereby stabilizing the user's emotions.

[0091] The history deletion unit can anonymize the user's emotional history so that it can be used for data analysis. For example, when a user deletes their history, the history deletion unit allows the generation AI to anonymize the emotional history so that it can be used for data analysis. For example, it anonymizes and analyzes emotional changes and trends. The history deletion unit also anonymizes the user's emotional history so that it can be used for data analysis. For example, it anonymizes and analyzes ways to deal with specific emotional states. The history deletion unit also anonymizes the emotional history so that it can be used for data analysis when a user deletes their history. For example, it anonymizes and analyzes emotional ups and downs and suggests appropriate ways to deal with them. In this way, by anonymizing the emotional history and using it for data analysis, it is possible to effectively utilize data while protecting the user's privacy.

[0092] The history deletion unit can compress the user's emotional history and enable partial deletion as needed. For example, when a user deletes the history, the history deletion unit enables the generation AI to compress the emotional history and enable partial deletion as needed. For example, it compresses and saves emotional history for a specific period of time. The history deletion unit also enables the generation AI to compress the user's emotional history and enable partial deletion as needed. For example, it compresses and saves ways to deal with specific emotional states. The history deletion unit also enables the generation AI to compress the emotional history and enable partial deletion as needed when a user deletes the history. For example, it compresses and saves emotional ups and downs and suggests appropriate ways to deal with them. In this way, by compressing the emotional history and enabling partial deletion as needed, data management is made easier while protecting the user's privacy.

[0093] The history deletion unit can analyze the user's emotions and monitor emotional changes after deletion in real time. For example, when a user deletes history, the generation AI in the history deletion unit analyzes the user's emotions and monitors emotional changes after deletion in real time. For example, if there is a sudden change in emotions, it proposes an appropriate response. The history deletion unit also analyzes the user's emotions and monitors emotional changes after deletion in real time. For example, if the emotions begin to calm down, it proposes a response that has a relaxing effect. The history deletion unit also analyzes the user's emotions when a user deletes history, and monitors emotional changes after deletion in real time. For example, it proposes a response that indicates an increase in emotions or a response that indicates a calming of emotions. In this way, by monitoring emotional changes in real time after deleting emotional history, it is possible to stabilize the user's emotions.

[0094] The mental health service provision unit can analyze the user's emotional history and recommend the most appropriate mental health specialist. For example, when the user inputs their emotions, the mental health service provision unit has the generation AI analyze the emotional history and recommend the most appropriate mental health specialist. For example, it recommends a specialist for a specific emotional state. The mental health service provision unit also has the generation AI analyze the user's emotional history and recommend the most appropriate mental health specialist. For example, it recommends an appropriate specialist based on past emotional history. The mental health service provision unit also has the generation AI analyze the user's emotional history and recommend the most appropriate mental health specialist. For example, it analyzes emotional changes and trends and recommends an appropriate specialist. In this way, by analyzing the emotional history and recommending the most appropriate mental health specialist, the user can receive appropriate support.

[0095] The mental health service provision unit can automatically make a reservation for a specialized mental health service based on the user's emotional history. For example, when a user inputs their emotions, the mental health service provision unit has a generation AI automatically make a reservation for a specialized mental health service based on the emotional history. For example, it reserves a service for a specific emotional state. In addition, the mental health service provision unit has a generation AI analyze the user's emotional history and automatically make a reservation for a specialized mental health service. For example, it reserves an appropriate service based on past emotional history. In addition, when a user inputs their emotions, the generation AI automatically makes a reservation for a specialized mental health service based on the emotional history. For example, it analyzes emotional changes and trends and reserves an appropriate service. In this way, by automatically making a reservation for a specialized mental health service based on the emotional history, the user can receive support quickly.

[0096] The mental health service provision unit analyzes the user's emotions in real time and can immediately contact a specialist in an emergency. For example, when a user inputs their emotions, the mental health service provision unit has the generation AI analyze the emotions in real time and immediately contact a specialist in an emergency. For example, a specialist will be contacted if there is a sudden change in emotions. The mental health service provision unit also analyzes the user's emotions in real time and immediately contacts a specialist in an emergency. For example, if the emotions begin to calm down, it will suggest a coping method that has a relaxing effect. The mental health service provision unit also analyzes the user's emotions in real time and immediately contacts a specialist in an emergency. For example, it will suggest a coping method that represents an increase in emotions and a coping method that represents a calming emotion. In this way, emotions are analyzed in real time and a specialist is immediately contacted in an emergency, allowing the user to receive prompt and appropriate support.

[0097] The mental health service providing unit can analyze the user's emotional history and suggest online counseling or support groups. For example, when a user inputs their emotions, the mental health service providing unit has the generation AI analyze the emotional history and suggest online counseling or support groups. For example, it suggests counseling for a specific emotional state. The mental health service providing unit also has the generation AI analyze the user's emotional history and suggest online counseling or support groups. For example, it suggests appropriate counseling based on past emotional history. The mental health service providing unit also has the generation AI analyze the user's emotional history and suggest online counseling or support groups. For example, it analyzes emotional changes and trends and suggests appropriate counseling. In this way, by analyzing the emotional history and suggesting online counseling or support groups, the user can receive appropriate support.

[0098] The mental health service providing unit can provide self-care resources based on the user's emotional history. For example, when the user inputs their emotions, the generation AI provides self-care resources based on the emotional history. For example, it may provide a meditation guide for a specific emotional state. In addition, the mental health service providing unit analyzes the user's emotional history and provides self-care resources. For example, it may provide appropriate relaxation techniques based on past emotional history. In addition, when the user inputs their emotions, the generation AI provides self-care resources based on the emotional history. For example, it may analyze emotional changes and trends and provide appropriate self-care resources. In this way, providing self-care resources based on emotional history makes it easier for the user to manage themselves.

[0099] The mental health service providing unit can analyze a user's emotions in real time and provide mental health resources corresponding to the emotions in real time. For example, when a user inputs an emotion, the mental health service providing unit has the generation AI analyze the emotion in real time and provide mental health resources corresponding to the emotion. For example, if an emotion suddenly changes, an appropriate resource is provided. The mental health service providing unit also has the generation AI analyze a user's emotions in real time and provide mental health resources corresponding to the emotion. For example, if an emotion is calming down, a resource with a relaxing effect is provided. The mental health service providing unit also has the generation AI analyze a user's emotions in real time and provide mental health resources corresponding to the emotion. For example, a resource representing an increase in emotion or a resource representing a calming emotion is provided. In this way, emotions are analyzed in real time and mental health resources corresponding to the emotion are provided in real time, allowing the user to receive appropriate support quickly.

[0100] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0101] The emotion expression unit can also generate a music playlist based on the user's emotions. For example, if the user is feeling sad, a playlist of soothing music is provided. The emotion expression unit can also suggest relaxing music or music that boosts energy, depending on the user's emotions. Furthermore, the emotion expression unit can dynamically update the playlist in response to changes in the user's emotions, always providing the most appropriate music.

[0102] The virtual space provider can also generate a virtual pet based on the user's emotions to support emotional expression. For example, if the user is feeling stressed, the virtual space provider can provide a pet that moves in a way that has a relaxing effect. The virtual space provider can also change the pet's behavior and reactions according to the user's emotions. Furthermore, when the user inputs an emotion, the generating AI can suggest actions for the pet that correspond to that emotion, encouraging emotional expression.

[0103] The color scheme customization unit can also add animation effects according to the user's emotions to enhance emotional expression. For example, if the user wants to relax, it can add a gentle animation. The color scheme customization unit can also adjust the speed and pattern of the animation according to the user's emotions. Furthermore, when the user inputs an emotion, the generation AI can suggest animation effects according to that emotion, making it possible to diversify emotional expression.

[0104] The history deletion unit can also analyze the user's emotional history and notify the user of important information before deletion. For example, it can notify the user of past emotional changes and trends. The history deletion unit can also notify the user of how to deal with a specific emotional state based on the user's emotional history. Furthermore, the history deletion unit can predict emotional ups and downs and suggest appropriate ways to deal with them. In this way, by notifying the user of important information before deleting the emotional history, the user can avoid losing necessary information.

[0105] The mental health service provider can also provide self-care resources based on the user's emotional history. For example, it can provide a meditation guide for a specific emotional state. The mental health service provider can also analyze the user's emotional history and provide appropriate relaxation techniques. Furthermore, when the user inputs their emotions, the generation AI can analyze emotional changes and trends and suggest appropriate self-care resources. In this way, providing self-care resources based on emotional history makes it easier for users to manage themselves.

[0106] The emotion expression unit can also generate poems or lyrics based on the user's emotions. For example, if the user is feeling sad, it can generate soothing poetry. The emotion expression unit can also suggest lyrics that have a relaxing effect or lyrics that boost energy, depending on the user's emotions. Furthermore, the emotion expression unit can dynamically update poems or lyrics according to changes in the user's emotions, always providing the most appropriate expression.

[0107] The virtual space providing unit can also generate a virtual garden based on the user's emotions, encouraging emotional expression. For example, if the user wants to relax, it can generate a garden with a tranquil landscape. The virtual space providing unit can also change the garden's environment and the types of plants depending on the user's emotions. Furthermore, when the user inputs their emotions, the generating AI can suggest actions for the garden that correspond to those emotions, deepening the emotional expression.

[0108] The color scheme customization unit can also suggest textures and patterns according to the user's emotions, diversifying the expression of emotions. For example, if the user wants to relax, it can suggest a calm texture. The color scheme customization unit can also change the type of texture or pattern according to the user's emotions. Furthermore, when the user inputs an emotion, the generation AI can suggest textures and patterns according to that emotion, enhancing the expression of that emotion.

[0109] The history deletion unit can also anonymize the user's emotional history and make it available for data analysis. For example, it can anonymize and analyze changes and trends in emotions. The history deletion unit can also anonymize and analyze ways to deal with specific emotional states based on the user's emotional history. Furthermore, the history deletion unit can anonymize and analyze emotional ups and downs and suggest appropriate ways to deal with them. In this way, anonymizing the emotional history and using it for data analysis enables effective use of data while protecting the user's privacy.

[0110] The mental health service provider can analyze the user's emotions in real time and immediately contact a specialist in an emergency. For example, when a user inputs their emotions, the generation AI analyzes them in real time and contacts a specialist if their emotions change suddenly. The mental health service provider can also suggest ways to cope with the user's emotions that have a relaxing effect. Furthermore, when a user inputs their emotions, the generation AI can analyze the heightening or calming of emotions in real time and suggest appropriate ways to cope. This allows emotions to be analyzed in real time and experts to be contacted immediately in an emergency, allowing users to receive prompt and appropriate support.

[0111] The processing flow of the second embodiment will be briefly explained below.

[0112] Step 1: The emotion expression unit allows the user to anonymously express their emotions. For example, the user can input their emotions in text, and the generation AI will analyze the emotions and provide appropriate feedback. The emotion expression unit can also accept voice input, understand emotions through voice analysis, and provide feedback. Step 2: The virtual space provider processes the emotions expressed by the emotion expression component and provides a virtual space where the user can "vent" their emotions in peace. For example, the generation AI generates a virtual avatar according to the user's emotions to support emotional expression. The virtual space provider can also automatically change the environment settings according to the user's emotions to encourage emotional expression. Step 3: The color scheme customization unit customizes the color scheme of the virtual space provided by the virtual space provision unit. For example, the generation AI suggests a color scheme according to the user's emotions, allowing the user to select a color that matches their emotion. The color scheme customization unit can also refer to the user's past selection history to make more personalized suggestions. Step 4: The history deletion unit deletes the history of emotions expressed by the emotion expression unit. For example, if a user inputs, "I want to delete the history of past emotional expressions," the generation AI will delete the history according to that instruction. The history deletion unit can also analyze the user's emotional history and notify them of important information before deletion. Step 5: The mental health service provider provides professional mental health services based on the emotions expressed by the emotion expression unit. For example, the generation AI analyzes the user's emotion history and recommends the most suitable mental health professional. The mental health service provider can also analyze the user's emotions in real time and immediately contact a professional in an emergency.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0117] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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).

[0122] 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.

[0123] 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.

[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 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.

[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 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.

[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 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.

[0131] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0132] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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).

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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).

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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).

[0166] 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.

[0167] 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."

[0168] 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.

[0169] 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.

[0170] 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.

[0171] 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.

[0172] 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.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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.

[0177] 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.

[0178] 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.

[0179] 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]

[0180] 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. an emotion expression section that expresses emotions anonymously; a virtual space providing unit that processes the emotions expressed by the emotion expression unit; a color scheme customization unit that customizes a color scheme of the virtual space provided by the virtual space providing unit; a history deletion unit that deletes a history of emotions expressed by the emotion expression unit; a mental health service providing unit that provides professional mental health services based on the emotion expressed by the emotion expression unit. A system characterized by:

2. The emotion expression unit Refer to the user's past emotional history to provide more personalized feedback 2. The system of claim 1.

3. The emotion expression unit Generate art and graphics that visually express user emotions 2. The system of claim 1.

4. The emotion expression unit Analyzes user emotions in real time and provides feedback according to changes in emotions 2. The system of claim 1.

5. The emotion expression unit Accepts voice input, understands the emotion through voice analysis, and provides feedback 2. The system of claim 1.

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