System

Abstract

An object of a system according to an embodiment is to support diet and health management of a user and maintain motivation.SOLUTION: A system includes a character linkage unit, a chat encouragement unit, a recommendation unit, and a family linkage unit. The character-linked unit changes the appearance of the character based on the calorie intake and the amount of exercise of the user. The chat encouragement unit sends a message of encouragement through a chat with the user. The recommendation unit recommends a meal or an exercise menu suitable for an individual. The family cooperation unit checks the state of the user in cooperation with the family.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] In conventional technologies, there is a problem in that it is difficult to maintain the motivation of users in systems that support users in dieting and health management.

[0005] The system according to the embodiment aims to support the user in dieting and health management, and to maintain motivation. [Means for solving the problem]

[0006] The system according to the embodiment includes a character linking unit, a chat encouragement unit, a recommendation unit, and a family linking unit. The character linking unit changes the appearance of the character based on the user's calorie intake and amount of exercise. The chat encouragement unit sends encouraging messages through chat with the user. The recommendation unit recommends personalized diet and exercise menus. The family linking unit checks the user's condition in cooperation with family members. [Effects of the Invention]

[0007] The system according to the embodiment can support the user in dieting and health management, and maintain motivation. [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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[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 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[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) A diet support system according to an embodiment of the present invention changes the appearance of a character based on the user's calorie intake and exercise volume, encourages the user through a chat function, recommends personalized meals and exercise menus, and checks the user's condition in cooperation with family members. This allows the diet support system to visually show the user's diet progress and maintain motivation through encouragement and recommendations.

[0029] A diet support system according to an embodiment includes a character linking unit, a chat encouragement unit, a recommendation unit, and a family linking unit. The character linking unit changes the character's appearance based on the user's calorie intake and exercise volume. For example, if the user achieves a target calorie limit or exercise volume, the character becomes slimmer and can wear new clothes. Furthermore, if the user overeats or does not exercise enough, the character becomes fat and loses control of their clothes. The chat encouragement unit sends encouraging messages to the user through chat. For example, the chat encouragement unit sends messages such as, "Let's exercise hard today!" or "Yesterday's meal was well-balanced!" The chat encouragement unit analyzes user data and recommends personalized diet and exercise menus. For example, the chat encouragement unit provides specific advice such as, "This exercise is effective for you" or "This diet menu is recommended." The recommendation unit analyzes user data and recommends personalized diet and exercise menus. For example, the chat encouragement unit provides specific advice such as, "This exercise is effective for you" or "This diet menu is recommended." The family collaboration unit allows users to collaborate with their family members to check their condition. For example, family members can check the user's diet progress and send encouraging messages. Family members can also check the user's diet and exercise records and provide advice. This allows the diet support system to visually show the user's diet progress and maintain motivation through encouragement and recommendations. For example, users can enjoy the changes in the character's appearance while working toward achieving their goals. They can also maintain motivation with the support of their family.

[0030] The character interaction unit can change the character's appearance based on the user's health condition. For example, the character interaction unit analyzes the user's heart rate and sleep data and changes the character's appearance based on that data. For example, if the user has had a good night's sleep, the character may appear energetic. Furthermore, if the user's heart rate is high, the character interaction unit may display a message encouraging exercise. This allows for feedback based on the user's health condition.

[0031] The character interaction unit can customize the appearance of the character based on the user's hobbies and interests and provide individualized feedback. The character interaction unit customizes the character's appearance based on the user's hobbies and interests, for example. For example, if the user likes sports, the character can wear sportswear. Also, if the user likes music, the character interaction unit can have the character hold a musical instrument. This allows feedback according to the user's hobbies and interests.

[0032] The character linking unit can share with the user's friends and community, promoting competition and cooperation. The character linking unit adds a function for sharing, for example, changes in the character's appearance with the user's friends and community. For example, the user can compare the character's progress with friends. The character linking unit also allows the user to take part in a diet challenge with friends. This allows the user to work together with friends and the community to advance their diet.

[0033] The recommendation unit can provide personalized advice based on the user's diet and exercise history. For example, the recommendation unit analyzes the user's diet and exercise history and provides personalized advice via chat. For example, it can send a message such as, "Based on the amount of exercise you did yesterday, we recommend this exercise for today." The recommendation unit can also suggest nutritionally balanced meal menus based on the user's diet history. This makes it possible to provide specific advice based on the user's diet and exercise history.

[0034] The recommendation unit can include specific suggestions that take into account the local ingredients and exercise facilities of the user. For example, the recommendation unit recommends a meal menu that takes into account the local ingredients of the user. For example, the recommendation unit provides advice such as, "We recommend this recipe using fresh local vegetables." The recommendation unit can also suggest an exercise menu that takes into account the local exercise facilities of the user. For example, the recommendation unit provides advice such as, "Try this exercise at a nearby gym." This makes it possible to provide specific suggestions that utilize the local resources of the user.

[0035] The family collaboration unit can collect health data from family members and support health management for the entire family. For example, the family collaboration unit can collect health data from all family members and build a system to support health management for the entire family. For example, it can analyze the heart rates and exercise levels of all family members and provide comprehensive health advice. The family collaboration unit can also share records of diet and exercise for all family members and manage the health of the entire family. This makes it possible to support health management for the entire family.

[0036] The family collaboration unit can expand collaboration with family members to include the user's friends and community, building a broader support network. The family collaboration unit can, for example, expand collaboration with family members to include friends and community, building a support network. For example, a diet challenge can be held together with friends. The family collaboration unit can also manage health across the entire community. For example, it can suggest participating in a local health event. This makes it possible to build a broader support network.

[0037] The character linking unit can provide not only character clothes but also coupons and benefits that the user can actually use when the user achieves their goal. For example, the character linking unit can provide not only character clothes but also coupons that the user can actually use when the user achieves their goal. For example, it can provide a discount coupon for a restaurant. The character linking unit can also award points as a benefit when the user achieves their goal. This can increase motivation by providing coupons and benefits that the user can actually use.

[0038] When the user fails to achieve a goal, the character linking unit can not only change the character's appearance but also provide specific advice to improve the user's behavior. For example, when the user fails to achieve a goal, the character linking unit can not only change the character's appearance but also provide specific advice. For example, the character linking unit can provide advice such as "Try this exercise next time." Furthermore, the character linking unit can also suggest a specific meal menu if the user needs to improve their diet. This makes it possible to provide specific advice to improve the user's behavior.

[0039] The character linking unit can provide multiple reward options from which the user can choose. For example, when the user achieves a goal, the character linking unit can provide multiple reward options in addition to clothing for the character. For example, the user can choose from clothing, coupons, and special offers. The character linking unit can also change the appearance of the character depending on the reward selected by the user. This can increase motivation by providing multiple reward options from which the user can choose.

[0040] The character linking unit can not only change the character's appearance when the user fails to achieve a goal, but also set a challenge for the user to improve. For example, when the user fails to achieve a goal, the character linking unit can not only change the character's appearance but also set a challenge for improvement. For example, the character linking unit can provide a challenge such as "Try this exercise next time." Furthermore, the character linking unit can also suggest a specific meal menu when the user needs to improve their diet. This makes it possible to provide a specific challenge for the user to improve.

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

[0042] The diet support system can also analyze the user's sleep data and change the character's appearance based on the quality of their sleep. For example, if the user has had a good night's sleep, the character may appear energetic. On the other hand, if the user has not had enough sleep, the character may appear tired. This allows the user to visually check the quality of their sleep and raise awareness of the need to improve.

[0043] The diet support system can also analyze the nutritional balance of the user's diet and change the character's appearance based on the nutritional balance. For example, if the user eats a balanced diet, the character may appear healthy. Conversely, if the user eats an unbalanced diet, the character may appear unhealthy. This allows the user to visually check the nutritional balance of their own diet and raise awareness of the need to improve.

[0044] The diet support system can also analyze the user's exercise data and change the character's movements based on the type of exercise. For example, if the user runs, the character may appear running. If the user practices yoga, the character may appear in a yoga pose. This allows the user to visually confirm the type of exercise they are doing and continue exercising while having fun.

[0045] The diet support system can also analyze the user's stress level and change the character's appearance based on the stress level. For example, if the user is feeling stressed, the character may appear to encourage relaxation. Alternatively, if the user is relaxed, the character may appear to be energetic. This allows the user to visually check their own stress level and increase their awareness of relaxation.

[0046] The diet support system can also analyze the user's activity level and change the character's energy level based on the amount of activity. For example, if the user exercises a lot, the character may appear to have high energy. On the other hand, if the user does not exercise much, the character may appear to have low energy. This allows the user to visually check their activity level and increase their awareness of exercise.

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

[0048] Step 1: The character interaction unit changes the character's appearance based on the user's calorie intake and exercise volume. For example, if the user achieves their calorie limit or exercise volume goal, the character will slim down and be able to wear new clothes. On the other hand, if the user eats too much or exercises too little, the character will gain weight and become unable to fit into their clothes. Step 2: The chat encouragement section sends encouraging messages to the user through chat, such as "Let's exercise hard today!" or "Yesterday's meal was well-balanced!" Step 3: The recommendation section analyzes the user's data and recommends a diet and exercise menu that is tailored to the individual. For example, it provides specific advice such as "This exercise is effective for you" or "This diet menu is recommended." Step 4: The family collaboration unit allows the user to collaborate with family members to check their condition. For example, family members can check the user's diet progress and send encouraging messages. Family members can also check the user's diet and exercise records and provide advice.

[0049] (Example 2) A diet support system according to an embodiment of the present invention changes the appearance of a character based on the user's calorie intake and exercise volume, encourages the user through a chat function, recommends personalized meals and exercise menus, and checks the user's condition in cooperation with family members. This allows the diet support system to visually show the user's diet progress and maintain motivation through encouragement and recommendations.

[0050] A diet support system according to an embodiment includes a character linking unit, a chat encouragement unit, a recommendation unit, and a family linking unit. The character linking unit changes the character's appearance based on the user's calorie intake and exercise volume. For example, if the user achieves a target calorie limit or exercise volume, the character becomes slimmer and can wear new clothes. Furthermore, if the user overeats or does not exercise enough, the character becomes fat and loses control of their clothes. The chat encouragement unit sends encouraging messages to the user through chat. For example, the chat encouragement unit sends messages such as, "Let's exercise hard today!" or "Yesterday's meal was well-balanced!" The chat encouragement unit analyzes user data and recommends personalized diet and exercise menus. For example, the chat encouragement unit provides specific advice such as, "This exercise is effective for you" or "This diet menu is recommended." The recommendation unit analyzes user data and recommends personalized diet and exercise menus. For example, the chat encouragement unit provides specific advice such as, "This exercise is effective for you" or "This diet menu is recommended." The family collaboration unit allows users to collaborate with their family members to check their condition. For example, family members can check the user's diet progress and send encouraging messages. Family members can also check the user's diet and exercise records and provide advice. This allows the diet support system to visually show the user's diet progress and maintain motivation through encouragement and recommendations. For example, users can enjoy the changes in the character's appearance while working toward achieving their goals. They can also maintain motivation with the support of their family.

[0051] The character linking unit can analyze the user's tone of voice and facial expression and change the character's facial expression and voice in sync. For example, the character linking unit analyzes the user's tone of voice and facial expression via a smartphone or wearable device, and changes the character's facial expression and voice in real time based on that data. For example, when the user smiles while speaking, the character also smiles and the tone of their voice becomes brighter. The character linking unit can also have the character offer words of encouragement when the user is sad. This enables real-time feedback according to the user's emotions.

[0052] The character interaction unit can change the character's appearance based on the user's health condition. For example, the character interaction unit analyzes the user's heart rate and sleep data and changes the character's appearance based on that data. For example, if the user has had a good night's sleep, the character may appear energetic. Furthermore, if the user's heart rate is high, the character interaction unit may display a message encouraging exercise. This allows for feedback based on the user's health condition.

[0053] The character interaction unit can use the emotion estimation function to change the appearance and behavior of the character according to the user's emotional state. For example, the character interaction unit can use the emotion estimation function to analyze the user's emotional state, causing the character to look and act in accordance with the user's emotion. For example, the character can offer words of encouragement when the user is sad. The character interaction unit can also make the character dance when the user is happy. This allows feedback according to the user's emotions.

[0054] The character interaction unit can customize the appearance of the character based on the user's hobbies and interests and provide individualized feedback. The character interaction unit customizes the character's appearance based on the user's hobbies and interests, for example. For example, if the user likes sports, the character can wear sportswear. Also, if the user likes music, the character interaction unit can have the character hold a musical instrument. This allows feedback according to the user's hobbies and interests.

[0055] The character linking unit can share with the user's friends and community, promoting competition and cooperation. The character linking unit adds a function for sharing, for example, changes in the character's appearance with the user's friends and community. For example, the user can compare the character's progress with friends. The character linking unit also allows the user to take part in a diet challenge with friends. This allows the user to work together with friends and the community to advance their diet.

[0056] The character interaction unit can use the emotion estimation function to add character behavior that corresponds to the user's emotion, thereby enhancing the entertainment element. For example, the character interaction unit can use the emotion estimation function to analyze the user's emotional state, causing the character to perform an action that corresponds to the user's emotion. For example, the character can dance when the user is happy. The character interaction unit can also make the character sing when the user wants to relax. This makes it possible to provide entertainment elements that correspond to the user's emotion.

[0057] The chat encouragement unit can cite the user's past successes and positive events to increase individual motivation. For example, the chat encouragement unit stores the user's past successes in a database and cites them in encouraging messages in chat. For example, it can send a message such as, "You've been successful with this exercise before!" The chat encouragement unit can also cite the user's positive events and send messages to increase motivation. This makes it possible to utilize the user's past successes to increase motivation.

[0058] The recommendation unit can provide personalized advice based on the user's diet and exercise history. For example, the recommendation unit analyzes the user's diet and exercise history and provides personalized advice via chat. For example, it can send a message such as, "Based on the amount of exercise you did yesterday, we recommend this exercise for today." The recommendation unit can also suggest nutritionally balanced meal menus based on the user's diet history. This makes it possible to provide specific advice based on the user's diet and exercise history.

[0059] The chat encouragement unit uses the emotion estimation function to generate an encouraging message according to the user's emotional state, thereby improving the user's mood. The chat encouragement unit, for example, uses the emotion estimation function to analyze the user's emotional state and generate an encouraging message. For example, when the user is feeling down, the chat encouragement unit can send a message such as "Don't worry, you can do it!". The chat encouragement unit can also send a message such as "Great! Keep it up!" when the user is happy. This makes it possible to provide an encouraging message according to the user's emotions.

[0060] The chat encouragement unit provides encouraging messages as audio and video messages, enabling more realistic support. The chat encouragement unit provides encouraging messages in chat as audio messages, for example, sending an audio message such as "Let's exercise hard today!" The chat encouragement unit can also send encouraging words as video messages, for example, sending a video message such as "You can do it!" This makes it possible to provide more realistic support through audio and video messages.

[0061] The recommendation unit can include specific suggestions that take into account the local ingredients and exercise facilities of the user. For example, the recommendation unit recommends a meal menu that takes into account the local ingredients of the user. For example, the recommendation unit provides advice such as, "We recommend this recipe using fresh local vegetables." The recommendation unit can also suggest an exercise menu that takes into account the local exercise facilities of the user. For example, the recommendation unit provides advice such as, "Try this exercise at a nearby gym." This makes it possible to provide specific suggestions that utilize the local resources of the user.

[0062] The recommendation unit uses the emotion estimation function to recommend music and videos that correspond to the user's emotions, thereby promoting relaxation and improving motivation. The recommendation unit, for example, uses the emotion estimation function to analyze the user's emotional state and recommend music that corresponds to the emotions. For example, when the user wants to relax, the recommendation unit suggests relaxing music. The recommendation unit can also suggest videos that will motivate the user when they want to increase their motivation. For example, it can provide videos that will motivate the user when the user watches them before exercising. This makes it possible to provide music and videos that correspond to the user's emotions.

[0063] The family collaboration unit can collect health data from family members and support health management for the entire family. For example, the family collaboration unit can collect health data from all family members and build a system to support health management for the entire family. For example, it can analyze the heart rates and exercise levels of all family members and provide comprehensive health advice. The family collaboration unit can also share records of diet and exercise for all family members and manage the health of the entire family. This makes it possible to support health management for the entire family.

[0064] The family collaboration unit allows the generation AI to provide encouragement and advice to family members when they check the user's progress. For example, when a family member checks the user's progress, the family collaboration unit allows the generation AI to send encouraging messages to the family. For example, it sends a message such as "Let's do our best together!" The family collaboration unit also allows the generation AI to provide advice to the family. For example, it provides advice such as "Try this exercise together." This allows family members to receive encouragement and advice, thereby strengthening support for the user.

[0065] The family collaboration unit can use the emotion estimation function to generate messages according to the emotional state of family members and promote communication between family members. For example, the family collaboration unit can use the emotion estimation function to analyze the emotional state of family members and generate messages according to the emotions. For example, when a family member is feeling stressed, the family collaboration unit can send a message such as "Let's relax together." In addition, when a family member is happy, the family collaboration unit can send a message such as "Great! Keep it up!". This makes it possible to facilitate communication between family members.

[0066] The family collaboration unit can expand collaboration with family members to include the user's friends and community, building a broader support network. The family collaboration unit can, for example, expand collaboration with family members to include friends and community, building a support network. For example, a diet challenge can be held together with friends. The family collaboration unit can also manage health across the entire community. For example, it can suggest participating in a local health event. This makes it possible to build a broader support network.

[0067] The family collaboration unit can add a video call function when family members check the user's progress, enabling real-time support. For example, the family collaboration unit can add a video call function when family members check the user's progress, providing real-time support. For example, exercising together with family members. The family collaboration unit can also enable family members to give words of encouragement to the user through video calls, thereby enabling real-time support.

[0068] The family collaboration unit can use the emotion estimation function to suggest joint activities according to the emotions of family members and strengthen family ties. For example, the family collaboration unit can use the emotion estimation function to analyze the emotional state of family members and suggest joint activities according to the emotions. For example, when a family wants to relax, they can cook together. The family collaboration unit can also play sports together when a family wants to enjoy exercise. This makes it possible to suggest joint activities that deepen family ties.

[0069] The character linking unit can provide not only character clothes but also coupons and benefits that the user can actually use when the user achieves their goal. For example, the character linking unit can provide not only character clothes but also coupons that the user can actually use when the user achieves their goal. For example, it can provide a discount coupon for a restaurant. The character linking unit can also award points as a benefit when the user achieves their goal. This can increase motivation by providing coupons and benefits that the user can actually use.

[0070] When the user fails to achieve a goal, the character linking unit can not only change the character's appearance but also provide specific advice to improve the user's behavior. For example, when the user fails to achieve a goal, the character linking unit can not only change the character's appearance but also provide specific advice. For example, the character linking unit can provide advice such as "Try this exercise next time." Furthermore, the character linking unit can also suggest a specific meal menu if the user needs to improve their diet. This makes it possible to provide specific advice to improve the user's behavior.

[0071] The character linking unit can use the emotion estimation function to customize rewards and penalties according to the user's emotional state and maintain motivation. The character linking unit, for example, uses the emotion estimation function to analyze the user's emotional state and provide a reward according to the emotion. For example, a special reward can be provided when the user is happy. The character linking unit can also reduce the penalty when the user is depressed. This makes it possible to maintain motivation by providing rewards and penalties according to the user's emotions.

[0072] The character linking unit can provide multiple reward options from which the user can choose. For example, when the user achieves a goal, the character linking unit can provide multiple reward options in addition to clothing for the character. For example, the user can choose from clothing, coupons, and special offers. The character linking unit can also change the appearance of the character depending on the reward selected by the user. This can increase motivation by providing multiple reward options from which the user can choose.

[0073] The character linking unit can not only change the character's appearance when the user fails to achieve a goal, but also set a challenge for the user to improve. For example, when the user fails to achieve a goal, the character linking unit can not only change the character's appearance but also set a challenge for improvement. For example, the character linking unit can provide a challenge such as "Try this exercise next time." Furthermore, the character linking unit can also suggest a specific meal menu when the user needs to improve their diet. This makes it possible to provide a specific challenge for the user to improve.

[0074] The character linking unit can use the emotion estimation function to adjust the content of rewards and penalties in real time according to the user's emotions and provide optimal feedback. For example, the character linking unit can use the emotion estimation function to analyze the user's emotional state and provide rewards according to the emotions. For example, a special reward can be provided when the user is happy. The character linking unit can also reduce penalties when the user is depressed. This makes it possible to maintain motivation by providing rewards and penalties according to the user's emotions.

[0075] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0076] The diet support system can also analyze the user's sleep data and change the character's appearance based on the quality of their sleep. For example, if the user has had a good night's sleep, the character may appear energetic. On the other hand, if the user has not had enough sleep, the character may appear tired. This allows the user to visually check the quality of their sleep and raise awareness of the need to improve.

[0077] The diet support system can also analyze the nutritional balance of the user's diet and change the character's appearance based on the nutritional balance. For example, if the user eats a balanced diet, the character may appear healthy. Conversely, if the user eats an unbalanced diet, the character may appear unhealthy. This allows the user to visually check the nutritional balance of their own diet and raise awareness of the need to improve.

[0078] The diet support system can also analyze the user's exercise data and change the character's movements based on the type of exercise. For example, if the user runs, the character may appear running. If the user practices yoga, the character may appear in a yoga pose. This allows the user to visually confirm the type of exercise they are doing and continue exercising while having fun.

[0079] The diet support system can also analyze the user's stress level and change the character's appearance based on the stress level. For example, if the user is feeling stressed, the character may appear to encourage relaxation. Alternatively, if the user is relaxed, the character may appear to be energetic. This allows the user to visually check their own stress level and increase their awareness of relaxation.

[0080] The diet support system can also analyze the user's activity level and change the character's energy level based on the amount of activity. For example, if the user exercises a lot, the character may appear to have high energy. On the other hand, if the user does not exercise much, the character may appear to have low energy. This allows the user to visually check their activity level and increase their awareness of exercise.

[0081] The diet support system can also estimate the user's emotions and change the character's facial expression based on the estimated emotions. For example, if the user is happy, the character will show a smile. If the user is sad, the character will show a sad expression. This allows the user to visually confirm their own emotions and notice changes in their emotions.

[0082] The diet support system can also estimate the user's emotions and change the character's behavior based on the estimated emotions. For example, if the user is feeling stressed, the character can perform actions that encourage relaxation. Alternatively, if the user is relaxed, the character can perform energetic actions. This allows the user to receive feedback that corresponds to their own emotions.

[0083] The diet support system can also estimate the user's emotions and change the character's voice based on the estimated emotions. For example, if the user is feeling down, the character can speak to them in a gentle voice. If the user is happy, the character can speak to them in a cheerful voice. This allows the user to receive feedback that reflects their own emotions.

[0084] The diet support system can also estimate the user's emotions and change the character's behavior based on the estimated emotions. For example, if the user wants to relax, the character can perform an action that encourages relaxation. Also, if the user wants to enjoy exercise, the character can perform an action that encourages exercise. This allows the user to receive feedback that corresponds to their own emotions.

[0085] The diet support system can also estimate the user's emotions and change the character's behavior based on the estimated emotions. For example, if the user is feeling stressed, the character can perform actions that encourage relaxation. Alternatively, if the user is relaxed, the character can perform energetic actions. This allows the user to receive feedback that corresponds to their own emotions.

[0086] The processing flow of the second embodiment will be briefly explained below.

[0087] Step 1: The character interaction unit changes the character's appearance based on the user's calorie intake and exercise volume. For example, if the user achieves their calorie limit or exercise volume goal, the character will slim down and be able to wear new clothes. On the other hand, if the user eats too much or exercises too little, the character will gain weight and become unable to fit into their clothes. Step 2: The chat encouragement section sends encouraging messages to the user through chat, such as "Let's exercise hard today!" or "Yesterday's meal was well-balanced!" Step 3: The recommendation section analyzes the user's data and recommends a diet and exercise menu that is tailored to the individual. For example, it provides specific advice such as "This exercise is effective for you" or "This diet menu is recommended." Step 4: The family collaboration unit allows the user to collaborate with family members to check their condition. For example, family members can check the user's diet progress and send encouraging messages. Family members can also check the user's diet and exercise records and provide advice.

[0088] 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.

[0089] 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.

[0090] 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.

[0091] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0092] 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.

[0093] 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.

[0094] 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.

[0095] 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.

[0096] 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).

[0097] 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.

[0098] 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.

[0099] 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.

[0100] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0101] 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. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0107] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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).

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0116] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0122] 7, a 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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).

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0132] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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).

[0141] 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.

[0142] 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."

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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]

[0155] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a character linking unit that changes the appearance of the character based on the user's calorie intake and exercise amount; a chat encouragement section that sends encouraging messages to users through chat; The recommendation department recommends meals and exercise menus that are suited to individuals, A family cooperation unit that cooperates with family members to check the user's condition. A system characterized by:

2. The character linking unit The tone of voice and facial expression of the user are analyzed, and the facial expression and voice of the character are changed in conjunction with each other.

2. The system of claim 1.

3. The character linking unit Customize the character's appearance based on the user's hobbies and interests and provide personalized feedback 2. The system of claim 1.

4. The chat encouragement unit Citing the user's past successes and positive events to increase individual motivation 2. The system of claim 1.

5. The recommendation unit Providing personalized advice based on the user's diet and exercise history 2. The system of claim 1.

6. The Family Collaboration Department: Incorporating the family's health data to support the health management of the entire family 2. The system of claim 1.

7. The Family Collaboration Department: A message is generated according to the emotional state of the family member, and communication between the family members is promoted.

2. The system of claim 1.

8. The character linking unit To customize rewards and penalties according to the emotional state of the user and maintain motivation.

2. The system of claim 1.

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