System

Abstract

An object of a system according to an embodiment is to provide an idol that meets various needs of a user while managing a fire risk without being restricted by time and language.SOLUTION: A system according to an embodiment includes a content generation part, an activity management part, a feature setting part, a multilingual handling part, and a burning risk management part. The content generating unit generates content such as a sentence, an image, and a sound using the generative AI. The activity manager manages idles that are active 24 hours a day, 365 days a year. The feature setting unit sets a feature according to a user's preference. The multilingual adaptation unit generates multilingual content. The burning risk management part manages a burning risk.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] With conventional technology, idols' activities were subject to time and language restrictions, and there was also the risk of online outrage, making it difficult to meet the diverse needs of users.

[0005] The system according to the embodiment aims to provide idols that meet the diverse needs of users without being restricted by time or language, while managing the risk of online outrage. [Means for solving the problem]

[0006] The system according to the embodiment includes a content generation unit, an activity management unit, a feature setting unit, a multilingual support unit, and a flame risk management unit. The content generation unit uses generative AI to generate content such as text, images, and sounds. The activity management unit manages idols who are active 24 hours a day, 365 days a year. The feature setting unit sets features according to user preferences. The multilingual support unit generates content in multiple languages. The flame risk management unit manages the risk of flames. [Effects of the Invention]

[0007] The system according to the embodiment can provide idols that meet the diverse needs of users without being restricted by time or language, while managing the risk of online outrage. [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) The idol creation system according to an embodiment of the present invention uses generative AI to generate content such as text, images, and sounds, and is a system that provides idols that are active 24 hours a day, 365 days a year, have characteristics that match the user's preferences, are multilingual, and do not pose a risk of causing a backlash. As a result, the idol creation system provides new-generation idols that match the user's preferences, are active 24 hours a day, 365 days a year, are multilingual, and do not pose a risk of causing a backlash.

[0029] An idol generation system according to an embodiment includes a content generation unit, an activity management unit, a feature setting unit, a multilingual support unit, and a flame risk management unit. The content generation unit generates content such as text, images, and sounds using a generative AI. For example, if a user inputs a prompt such as "I want a cheerful greeting," the generation AI generates a cheerful greeting text or audio based on the instruction. Also, if a user inputs a prompt such as "I want to see the idol's new outfit," the generation AI generates an image or video of the idol wearing the new outfit based on the instruction. The activity management unit manages idols who are active 24 hours a day, 365 days a year. For example, even if a user wants to interact with an idol late at night, the generative AI can respond immediately, allowing the user to enjoy the conversation. The feature setting unit sets features according to the user's preferences. For example, if a user inputs a prompt such as "I like idols with a cheerful and energetic personality," the generation AI generates an idol with a cheerful and energetic personality based on the instruction. Also, if a user inputs a prompt such as "I like a specific hairstyle or outfit," the generation AI generates an idol with that hairstyle or outfit based on the instruction. The multilingual support unit generates content in multiple languages. For example, depending on the language used by the user, such as English, Spanish, or Chinese, the generation AI can generate content and dialogue in that language. The flame risk management unit manages the risk of flame wars. For example, even if the user enters an inappropriate prompt, the generation AI will ignore the prompt and generate an appropriate response. This allows the idol generation system to provide new-generation idols tailored to the user's preferences, operate 24 hours a day, 365 days a year, support multiple languages, and eliminate the risk of flame wars.

[0030] The content generation unit can analyze a user's past interaction history or behavioral patterns to generate individually optimized content. For example, the content generation unit analyzes what kind of content the user has liked in the past and generates new content based on that data. For example, if a user has liked cheerful messages in the past, the AI ​​generates similar messages. The content generation unit also analyzes the user's behavioral patterns to provide content optimal for specific times of day. For example, if a user often feels like relaxing at night, the AI ​​generates content that helps them relax in the evening. The content generation unit also generates individually customized content based on the user's interaction history. For example, if a user frequently talks about a particular topic, the AI ​​generates content related to that topic. This makes it possible to provide optimized content based on the user's past behavior.

[0031] The content generation unit can add a function to share content generated by users with other users, thereby promoting interaction within the community. For example, the content generation unit provides a platform that allows users to easily share content generated by users with other users. For example, it adds a function to share generated messages and images on social media. The content generation unit also provides a function that allows users within the community to evaluate content generated by each other. For example, users can "like" or comment on content generated by other users. The content generation unit also classifies user-generated content by theme, providing a place where users with similar interests can interact with each other. For example, it can create a forum that collects content related to a specific theme. This promotes interaction between users and revitalizes the community.

[0032] The activity management unit can automatically adjust the idol's activity schedule based on the user's lifestyle rhythm. The activity management unit, for example, analyzes the user's lifestyle rhythm and builds a system that automatically adjusts the idol's activity schedule based on that data. For example, if the user is often active in the morning, the idol is set to be active in the morning as well. The activity management unit also works with the user's calendar or schedule app to automatically adjust the idol's activity schedule. For example, if the user plans to participate in a specific event, the idol will also be active to coincide with that event. The activity management unit also provides a function to customize the idol's activity content according to the user's lifestyle rhythm. For example, if the user wants to relax in the evening, the idol will be provided with content that will help them relax. This makes it possible for the idol's activities to be tailored to the user's lifestyle rhythm.

[0033] The activity management unit can provide a function that allows a user to receive special messages or content from idols in accordance with specific events or anniversaries. The activity management unit provides a function that allows a user to receive special messages or content from idols in accordance with, for example, a user's birthday or anniversaries. For example, an idol sends a birthday message on the user's birthday. The activity management unit also adds a function that allows an idol to provide special performances or content in accordance with specific events. For example, an idol gives a special live performance on Christmas or New Year's. The activity management unit also builds a system in which an idol generates special messages or content in accordance with anniversaries set by the user. For example, if a user sets a wedding anniversary, an idol will send a special message on that day. This allows a user to receive content in accordance with special events or anniversaries.

[0034] The feature setting unit continues to learn user preferences and can evolve idols' features over time. For example, the feature setting unit could incorporate AI that continuously learns user preferences and build a system that evolves idols' features over time. For example, if a user prefers a particular hairstyle or clothing, the AI ​​could evolve the idols' appearance to match those preferences. The feature setting unit also analyzes the user's dialogue history and behavioral patterns to provide a function for evolving the idols' personalities and hobbies. For example, if a user frequently talks about a particular topic, the AI ​​could generate idols with hobbies related to that topic. The feature setting unit could also develop a system that evolves idols' features based on user feedback. For example, if a user prefers a particular feature of an idol, the AI ​​could strengthen that feature. This allows idols' features to evolve according to the user's preferences, providing longer-term satisfaction.

[0035] The multilingual support unit can generate content based on cultural backgrounds and nuances when users converse in different languages. For example, the multilingual support unit builds a system that generates content that takes cultural backgrounds and nuances into account when users converse in different languages. For example, when a user types "thank you" in Japanese, an AI generates a thank you message that is tailored to Japanese culture. The multilingual support unit also uses the multilingual content generation function to provide content that takes into account the cultural backgrounds and nuances of the languages ​​used by the user. For example, when a user types "congratulations" in French, an AI generates a congratulatory message that is tailored to French culture. The multilingual support unit also develops a system that generates content in real time that takes cultural backgrounds and nuances into account when users converse in different languages. For example, when a user types "good morning" in German, an AI generates a greeting that is tailored to German culture. This makes it possible to provide content that takes cultural backgrounds and nuances into account when conversing in different languages.

[0036] The multilingual support unit can provide a function in which a user selects a language they want to learn and the idol supports learning in that language. For example, the multilingual support unit builds a system in which a user selects a language they want to learn and the idol supports learning in that language. For example, if a user wants to learn English, the idol provides dialogue and learning content in English. The multilingual support unit also provides a function in which the idol supports learning in that language based on the language selected by the user. For example, if a user wants to learn Spanish, the idol provides Spanish lessons and practice questions. The multilingual support unit also develops a system in which a user selects a language they want to learn and the idol generates content to support learning in that language. For example, if a user wants to learn Chinese, the idol provides Chinese conversation practice and grammar explanations. This supports learning in the language the user wants to learn, thereby improving learning effectiveness.

[0037] The Flame Risk Management Department can pre-filter user input and automatically detect and eliminate inappropriate content. The Flame Risk Management Department will, for example, build a system that pre-filters user input and automatically detects and eliminates inappropriate content. For example, if a user enters inappropriate language, AI will detect and ignore the language. The Flame Risk Management Department will also introduce a filtering system that automatically detects and eliminates inappropriate content and provide idols with the ability to generate appropriate responses. For example, if a user enters offensive language, AI will ignore the language and generate an appropriate response. The Flame Risk Management Department will also develop a system that filters user input in real time and automatically detects and eliminates inappropriate content. For example, if a user enters discriminatory language, AI will detect and ignore the language. This will reduce the risk of flame wars by filtering inappropriate content in advance.

[0038] The flame risk management unit can analyze feedback provided by users to idols and automatically generate improvement measures to reduce the risk of flame wars. The flame risk management unit, for example, builds a system that analyzes feedback provided by users to idols and automatically generates improvement measures to reduce the risk of flame wars. For example, it adjusts the content of the idol's comments based on user feedback. The flame risk management unit also provides a function that automatically generates improvement measures to reduce the risk of flame wars based on user feedback data. For example, it analyzes comments that users find offensive and has AI improve those comments. The flame risk management unit also develops a system that analyzes user feedback in real time and automatically generates improvement measures to reduce the risk of flame wars. For example, if a user provides negative feedback, the AI ​​will suggest an improvement measure based on that feedback. This makes it possible to analyze user feedback and automatically generate improvement measures to reduce the risk of flame wars.

[0039] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0040] The idol generation system can also include a health management unit that monitors the user's health and provides health advice. For example, if the idol detects that the user has been sitting for a long time, it can send a message encouraging the user to stretch or do some light exercise. It can also analyze the user's food records and suggest balanced meals. It can also monitor the user's sleep patterns and provide advice on how to get better quality sleep. This can support the user's health and help them live a more fulfilling life.

[0041] The idol generation system can also include an event suggestion unit that suggests related events and activities based on the user's hobbies and interests. For example, if the user is interested in music, information about nearby concerts and music festivals can be provided. If the user is interested in sports, information about local sporting events and matches can be provided. Furthermore, if the user is interested in art, information about exhibitions at museums and galleries can be provided. This allows the system to suggest events and activities that match the user's hobbies and interests, supporting a more fulfilling life.

[0042] The activity management unit can use the user's geographic location information to provide idols with content specific to their region. For example, if the user lives in a particular city, news and event information related to that city can be provided. If the user is traveling, information about tourist attractions and restaurants at the destination can be provided. Furthermore, if the user is interested in the culture and customs of a particular region, content related to that region can be provided. This allows for personalized content based on the user's geographic location information, providing a more fulfilling experience.

[0043] The idol generation system can also have an education section that supports users' learning and skill development. For example, if a user wants to learn a new language, it can provide lessons and exercises for that language. If a user wants to improve a particular skill, it can provide learning materials and training programs related to that skill. It can also provide information and resources related to areas that interest the user. This can support users' learning and skill development and help them live a more fulfilling life.

[0044] The idol generation system may further include an environment adaptation unit that provides content according to the user's environment. For example, if the user is outdoors, content according to the weather and temperature may be provided. Also, if the user is indoors, content according to the indoor environment may be provided. Furthermore, if the user is in a specific location, information and content related to that location may be provided. This allows for the provision of personalized content according to the user's environment, providing a more fulfilling experience.

[0045] The processing flow of the first embodiment will be briefly explained below.

[0046] Step 1: The content generation unit uses generative AI to generate content such as text, images, and sounds. For example, if a user inputs a prompt such as "I want a cheerful greeting," the generation AI generates cheerful greeting text and audio based on that instruction. Similarly, if a user inputs a prompt such as "I want to see the idol's new costume," the generation AI generates images and videos of the idol wearing the new costume based on that instruction. Step 2: The activity management unit manages the idols, who are active 24 hours a day, 365 days a year. For example, even if a user wants to talk to an idol late at night, the generative AI will respond immediately, allowing them to enjoy a conversation. Step 3: The feature setting unit sets features that match the user's preferences. For example, if the user inputs a prompt such as "I like idols with bright and lively personalities," the generation AI will generate an idol with a bright and lively personality based on that instruction. Also, if the user inputs a prompt such as "I like a specific hairstyle or outfit," the generation AI will generate an idol with that hairstyle or outfit based on that instruction. Step 4: The multilingual support unit generates multilingual content. For example, depending on the language used by the user, such as English, Spanish, or Chinese, the generation AI can generate content in that language and engage in dialogue. Step 5: The Flame Risk Management Unit manages the risk of a flare-up. For example, even if the user enters an inappropriate prompt, the generation AI ignores the prompt and generates an appropriate response.

[0047] (Example 2) The idol creation system according to an embodiment of the present invention uses generative AI to generate content such as text, images, and sounds, and is a system that provides idols that are active 24 hours a day, 365 days a year, have characteristics that match the user's preferences, are multilingual, and do not pose a risk of causing a backlash. As a result, the idol creation system provides new-generation idols that match the user's preferences, are active 24 hours a day, 365 days a year, are multilingual, and do not pose a risk of causing a backlash.

[0048] An idol generation system according to an embodiment includes a content generation unit, an activity management unit, a feature setting unit, a multilingual support unit, and a flame risk management unit. The content generation unit generates content such as text, images, and sounds using a generative AI. For example, if a user inputs a prompt such as "I want a cheerful greeting," the generation AI generates a cheerful greeting text or audio based on the instruction. Also, if a user inputs a prompt such as "I want to see the idol's new outfit," the generation AI generates an image or video of the idol wearing the new outfit based on the instruction. The activity management unit manages idols who are active 24 hours a day, 365 days a year. For example, even if a user wants to interact with an idol late at night, the generative AI can respond immediately, allowing the user to enjoy the conversation. The feature setting unit sets features according to the user's preferences. For example, if a user inputs a prompt such as "I like idols with a cheerful and energetic personality," the generation AI generates an idol with a cheerful and energetic personality based on the instruction. Also, if a user inputs a prompt such as "I like a specific hairstyle or outfit," the generation AI generates an idol with that hairstyle or outfit based on the instruction. The multilingual support unit generates content in multiple languages. For example, depending on the language used by the user, such as English, Spanish, or Chinese, the generation AI can generate content and dialogue in that language. The flame risk management unit manages the risk of flame wars. For example, even if the user enters an inappropriate prompt, the generation AI will ignore the prompt and generate an appropriate response. This allows the idol generation system to provide new-generation idols tailored to the user's preferences, operate 24 hours a day, 365 days a year, support multiple languages, and eliminate the risk of flame wars.

[0049] The content generation unit can estimate a user's emotions in real time and generate content that corresponds to those emotions. For example, if a user is feeling sad, the generative AI generates uplifting messages and music. For example, if a user inputs, "I'm feeling down today," the AI ​​provides encouraging words and upbeat music. If a user is excited, the generative AI generates content that further enhances that excitement. For example, if a user inputs, "Today is a special day," the AI ​​generates congratulatory messages and upbeat music. If a user feels like relaxing, the generative AI generates relaxing content. For example, if a user inputs, "I want to relax," the AI ​​provides calm music and relaxing messages. This allows for a more personalized experience by providing content that corresponds to the user's emotions.

[0050] The content generation unit can analyze a user's past interaction history or behavioral patterns to generate individually optimized content. For example, the content generation unit analyzes what kind of content the user has liked in the past and generates new content based on that data. For example, if a user has liked cheerful messages in the past, the AI ​​generates similar messages. The content generation unit also analyzes the user's behavioral patterns to provide content optimal for specific times of day. For example, if a user often feels like relaxing at night, the AI ​​generates content that helps them relax in the evening. The content generation unit also generates individually customized content based on the user's interaction history. For example, if a user frequently talks about a particular topic, the AI ​​generates content related to that topic. This makes it possible to provide optimized content based on the user's past behavior.

[0051] The content generation unit can add a function to share content generated by users with other users, thereby promoting interaction within the community. For example, the content generation unit provides a platform that allows users to easily share content generated by users with other users. For example, it adds a function to share generated messages and images on social media. The content generation unit also provides a function that allows users within the community to evaluate content generated by each other. For example, users can "like" or comment on content generated by other users. The content generation unit also classifies user-generated content by theme, providing a place where users with similar interests can interact with each other. For example, it can create a forum that collects content related to a specific theme. This promotes interaction between users and revitalizes the community.

[0052] The activity management unit can automatically adjust the idol's activity schedule based on the user's lifestyle rhythm. The activity management unit, for example, analyzes the user's lifestyle rhythm and builds a system that automatically adjusts the idol's activity schedule based on that data. For example, if the user is often active in the morning, the idol is set to be active in the morning as well. The activity management unit also works with the user's calendar or schedule app to automatically adjust the idol's activity schedule. For example, if the user plans to participate in a specific event, the idol will also be active to coincide with that event. The activity management unit also provides a function to customize the idol's activity content according to the user's lifestyle rhythm. For example, if the user wants to relax in the evening, the idol will be provided with content that will help them relax. This makes it possible for the idol's activities to be tailored to the user's lifestyle rhythm.

[0053] The activity management unit can provide a function that allows a user to receive special messages or content from idols in accordance with specific events or anniversaries. The activity management unit provides a function that allows a user to receive special messages or content from idols in accordance with, for example, a user's birthday or anniversaries. For example, an idol sends a birthday message on the user's birthday. The activity management unit also adds a function that allows an idol to provide special performances or content in accordance with specific events. For example, an idol gives a special live performance on Christmas or New Year's. The activity management unit also builds a system in which an idol generates special messages or content in accordance with anniversaries set by the user. For example, if a user sets a wedding anniversary, an idol will send a special message on that day. This allows a user to receive content in accordance with special events or anniversaries.

[0054] The activity management unit can add a function that monitors the user's emotional state and allows the idol to send encouraging or comforting messages as needed. For example, the activity management unit builds a system that monitors the user's emotional state in real time and allows the idol to send encouraging messages when negative emotions increase. For example, if the user is feeling sad, the idol will send encouraging words. The activity management unit also provides a function that analyzes the user's emotional state and allows the idol to send comforting messages as needed. For example, if the user is feeling stressed, the idol will send a message that helps the user relax. The activity management unit also develops a system that allows the idol to send encouraging or comforting messages at appropriate times based on the user's emotional data. For example, if the user is feeling tired, the idol will send a message encouraging the user to rest. This makes it possible to provide appropriate messages according to the user's emotional state.

[0055] The feature setting unit can analyze the user's emotions and generate idol characteristics that best suit those emotions. For example, if the user feels like relaxing, the generative AI generates an idol with a calm personality. For example, if the user inputs "I want to relax," the AI ​​generates an idol with a calm voice and facial expression. If the user feels like cheering up, the generative AI generates an idol with a bright and lively personality. For example, if the user inputs "I want to feel energized," the AI ​​generates an active and energetic idol. If the user feels like calming down, the generative AI generates an idol with a calm and intelligent personality. For example, if the user inputs "I want to calm down," the AI ​​generates an intelligent and calm idol. This allows for a more personalized experience by generating idol characteristics that correspond to the user's emotions.

[0056] The feature setting unit continues to learn user preferences and can evolve idols' features over time. For example, the feature setting unit could incorporate AI that continuously learns user preferences and build a system that evolves idols' features over time. For example, if a user prefers a particular hairstyle or clothing, the AI ​​could evolve the idols' appearance to match those preferences. The feature setting unit also analyzes the user's dialogue history and behavioral patterns to provide a function for evolving the idols' personalities and hobbies. For example, if a user frequently talks about a particular topic, the AI ​​could generate idols with hobbies related to that topic. The feature setting unit could also develop a system that evolves idols' features based on user feedback. For example, if a user prefers a particular feature of an idol, the AI ​​could strengthen that feature. This allows idols' features to evolve according to the user's preferences, providing longer-term satisfaction.

[0057] The multilingual support unit can analyze user emotions in multiple languages ​​in real time and generate content that corresponds to those emotions. For example, the multilingual support unit will build a system that analyzes emotions in real time and generates content that corresponds to those emotions, regardless of the language the user speaks. For example, if a user inputs "sad" in English, the AI ​​will generate an encouraging message in English. The multilingual support unit will also use its multilingual emotion analysis function to generate content that corresponds to the language the user speaks. For example, if a user inputs "happy" in Spanish, the AI ​​will generate a congratulatory message in Spanish. The multilingual support unit will also develop a system that analyzes user emotions in multiple languages ​​in real time and generates optimal content based on that data. For example, if a user inputs "I want to relax" in Chinese, the AI ​​will generate relaxing content in Chinese. This allows the system to provide optimal content based on multilingual emotion analysis.

[0058] The multilingual support unit can generate content based on cultural backgrounds and nuances when users converse in different languages. For example, the multilingual support unit builds a system that generates content that takes cultural backgrounds and nuances into account when users converse in different languages. For example, when a user types "thank you" in Japanese, an AI generates a thank you message that is tailored to Japanese culture. The multilingual support unit also uses the multilingual content generation function to provide content that takes into account the cultural backgrounds and nuances of the languages ​​used by the user. For example, when a user types "congratulations" in French, an AI generates a congratulatory message that is tailored to French culture. The multilingual support unit also develops a system that generates content in real time that takes cultural backgrounds and nuances into account when users converse in different languages. For example, when a user types "good morning" in German, an AI generates a greeting that is tailored to German culture. This makes it possible to provide content that takes cultural backgrounds and nuances into account when conversing in different languages.

[0059] The multilingual support unit can provide a function in which a user selects a language they want to learn and the idol supports learning in that language. For example, the multilingual support unit builds a system in which a user selects a language they want to learn and the idol supports learning in that language. For example, if a user wants to learn English, the idol provides dialogue and learning content in English. The multilingual support unit also provides a function in which the idol supports learning in that language based on the language selected by the user. For example, if a user wants to learn Spanish, the idol provides Spanish lessons and practice questions. The multilingual support unit also develops a system in which a user selects a language they want to learn and the idol generates content to support learning in that language. For example, if a user wants to learn Chinese, the idol provides Chinese conversation practice and grammar explanations. This supports learning in the language the user wants to learn, thereby improving learning effectiveness.

[0060] The flame risk management unit monitors users' emotions in real time and can take appropriate action if negative emotions rise. For example, the flame risk management unit builds a system that monitors users' emotions in real time and allows idols to take appropriate action if negative emotions rise. For example, if a user is feeling angry, the idol will send a calm message. The flame risk management unit also provides a function that takes appropriate action if negative emotions rise based on the user's emotional data. For example, if a user is feeling sad, the idol will send an encouraging message. The flame risk management unit also monitors users' emotional state in real time and develops a system that takes appropriate action if negative emotions rise based on that data. For example, if a user is feeling stressed, the idol will send a relaxing message. This allows appropriate action to be taken if negative emotions rise, thereby reducing the risk of flames.

[0061] The Flame Risk Management Department can pre-filter user input and automatically detect and eliminate inappropriate content. The Flame Risk Management Department will, for example, build a system that pre-filters user input and automatically detects and eliminates inappropriate content. For example, if a user enters inappropriate language, AI will detect and ignore the language. The Flame Risk Management Department will also introduce a filtering system that automatically detects and eliminates inappropriate content and provide idols with the ability to generate appropriate responses. For example, if a user enters offensive language, AI will ignore the language and generate an appropriate response. The Flame Risk Management Department will also develop a system that filters user input in real time and automatically detects and eliminates inappropriate content. For example, if a user enters discriminatory language, AI will detect and ignore the language. This will reduce the risk of flame wars by filtering inappropriate content in advance.

[0062] The flame risk management unit can analyze feedback provided by users to idols and automatically generate improvement measures to reduce the risk of flame wars. The flame risk management unit, for example, builds a system that analyzes feedback provided by users to idols and automatically generates improvement measures to reduce the risk of flame wars. For example, it adjusts the content of the idol's comments based on user feedback. The flame risk management unit also provides a function that automatically generates improvement measures to reduce the risk of flame wars based on user feedback data. For example, it analyzes comments that users find offensive and has AI improve those comments. The flame risk management unit also develops a system that analyzes user feedback in real time and automatically generates improvement measures to reduce the risk of flame wars. For example, if a user provides negative feedback, the AI ​​will suggest an improvement measure based on that feedback. This makes it possible to analyze user feedback and automatically generate improvement measures to reduce the risk of flame wars.

[0063] The flame risk management unit uses the emotion estimation function to analyze how users feel toward idols and can take measures to reduce the risk of flame wars based on the results. For example, the flame risk management unit uses the emotion estimation function to build a system that analyzes how users feel toward idols in real time. For example, if a user is feeling negative emotions, AI takes measures based on that data. The flame risk management unit also develops a system that takes measures to reduce the risk of flame wars based on user emotion data. For example, if a user is feeling uncomfortable, AI sends a message to ease those emotions. The flame risk management unit also builds a system that analyzes how users feel toward idols based on the emotion estimation data and takes measures to reduce the risk of flame wars based on the results. For example, if a user is feeling angry, AI takes measures to ease those emotions. This makes it possible to analyze user emotions and take measures to reduce the risk of flame wars.

[0064] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0065] The idol generation system can also include a health management unit that monitors the user's health and provides health advice. For example, if the idol detects that the user has been sitting for a long time, it can send a message encouraging the user to stretch or do some light exercise. It can also analyze the user's food records and suggest balanced meals. It can also monitor the user's sleep patterns and provide advice on how to get better quality sleep. This can support the user's health and help them live a more fulfilling life.

[0066] The content generation unit can estimate the user's emotions and provide appropriate feedback based on those emotions. For example, if the user is feeling stressed, it can provide relaxing music or a meditation guide. If the user is feeling joyful, it can also generate messages or images to share that joy. Furthermore, if the user is feeling anxious, it can also suggest messages that provide a sense of security or ways to relax. This allows the system to provide appropriate feedback according to the user's emotions and provide a more personalized experience.

[0067] The idol generation system can also include an event suggestion unit that suggests related events and activities based on the user's hobbies and interests. For example, if the user is interested in music, information about nearby concerts and music festivals can be provided. If the user is interested in sports, information about local sporting events and matches can be provided. Furthermore, if the user is interested in art, information about exhibitions at museums and galleries can be provided. This allows the system to suggest events and activities that match the user's hobbies and interests, supporting a more fulfilling life.

[0068] The content generation unit can estimate the user's emotions and suggest appropriate exercise and fitness programs based on those emotions. For example, if the user is tired, it can suggest a relaxing yoga or stretching program. If the user is feeling energetic, it can also suggest high-intensity training. Furthermore, if the user is feeling stressed, it can suggest relaxation or meditation exercises. This allows the system to provide appropriate exercise and fitness programs according to the user's emotions and support a healthy lifestyle.

[0069] The activity management unit can use the user's geographic location information to provide idols with content specific to their region. For example, if the user lives in a particular city, news and event information related to that city can be provided. If the user is traveling, information about tourist attractions and restaurants at the destination can be provided. Furthermore, if the user is interested in the culture and customs of a particular region, content related to that region can be provided. This allows for personalized content based on the user's geographic location information, providing a more fulfilling experience.

[0070] The activity management unit can monitor the user's emotional state and send reminders and notifications according to the emotion. For example, if the user is feeling stressed, it can remind the user to take a break to relax. If the user is feeling happy, it can send a message to share that joy. Furthermore, if the user is feeling anxious, it can send a reminder to provide reassurance. This allows the system to provide appropriate reminders and notifications according to the user's emotional state and provide more personalized support.

[0071] The idol generation system can also have an education section that supports users' learning and skill development. For example, if a user wants to learn a new language, it can provide lessons and exercises for that language. If a user wants to improve a particular skill, it can provide learning materials and training programs related to that skill. It can also provide information and resources related to areas that interest the user. This can support users' learning and skill development and help them live a more fulfilling life.

[0072] The feature setting unit can analyze the user's emotions and dynamically change the idol's appearance and personality based on those emotions. For example, if the user feels like relaxing, the idol's appearance can be changed to be calm and composed. If the user feels like cheering up, the idol's appearance can be changed to be bright and lively. Furthermore, if the user feels like calming down, the idol's appearance can be changed to be intelligent and calm. In this way, the idol's appearance and personality can be dynamically changed according to the user's emotions, providing a more personalized experience.

[0073] The idol generation system may further include an environment adaptation unit that provides content according to the user's environment. For example, if the user is outdoors, content according to the weather and temperature may be provided. Also, if the user is indoors, content according to the indoor environment may be provided. Furthermore, if the user is in a specific location, information and content related to that location may be provided. This allows for the provision of personalized content according to the user's environment, providing a more fulfilling experience.

[0074] The multilingual support unit can analyze user emotions in multiple languages ​​in real time and generate content that corresponds to those emotions. For example, we will build a system that analyzes emotions in real time and generates content that corresponds to those emotions, regardless of the language the user speaks. For example, if a user inputs "sad" in English, the AI ​​will generate an encouraging message in English. The multilingual support unit also uses multilingual emotion analysis functions to generate content that corresponds to the language the user speaks. For example, if a user inputs "happy" in Spanish, the AI ​​will generate a congratulatory message in Spanish. The multilingual support unit will also develop a system that analyzes user emotions in multiple languages ​​in real time and generates optimal content based on that data. For example, if a user inputs "I want to relax" in Chinese, the AI ​​will generate relaxing content in Chinese. This makes it possible to provide optimal content based on multilingual emotion analysis.

[0075] The processing flow of the second embodiment will be briefly explained below.

[0076] Step 1: The content generation unit uses generative AI to generate content such as text, images, and sounds. For example, if a user inputs a prompt such as "I want a cheerful greeting," the generation AI generates cheerful greeting text and audio based on that instruction. Similarly, if a user inputs a prompt such as "I want to see the idol's new costume," the generation AI generates images and videos of the idol wearing the new costume based on that instruction. Step 2: The activity management unit manages the idols, who are active 24 hours a day, 365 days a year. For example, even if a user wants to talk to an idol late at night, the generative AI will respond immediately, allowing them to enjoy a conversation. Step 3: The feature setting unit sets features that match the user's preferences. For example, if the user inputs a prompt such as "I like idols with bright and lively personalities," the generation AI will generate an idol with a bright and lively personality based on that instruction. Also, if the user inputs a prompt such as "I like a specific hairstyle or outfit," the generation AI will generate an idol with that hairstyle or outfit based on that instruction. Step 4: The multilingual support unit generates multilingual content. For example, depending on the language used by the user, such as English, Spanish, or Chinese, the generation AI can generate content in that language and engage in dialogue. Step 5: The Flame Risk Management Unit manages the risk of a flare-up. For example, even if the user enters an inappropriate prompt, the generation AI ignores the prompt and generates an appropriate response.

[0077] 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.

[0078] 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.

[0079] 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.

[0080] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0081] 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.

[0082] 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.

[0083] 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.

[0084] 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.

[0085] 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).

[0086] 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.

[0087] 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.

[0088] 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.

[0089] 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.

[0090] 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.

[0091] 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.

[0092] 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.

[0093] 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.

[0094] 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.

[0095] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] 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).

[0101] 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.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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).

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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).

[0130] 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.

[0131] 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."

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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]

[0144] 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 content generation unit that uses generative AI to generate content such as text, images, and sounds; The Activity Management Department manages the idols who are active 24 hours a day, 365 days a year, a feature setting unit for setting features according to user preferences; a multilingual support unit that generates multilingual content; A flame risk management department that manages flame risks. A system characterized by:

2. The content generation unit Analyzing the user's past interaction history or behavioral patterns to generate individually optimized content 2. The system of claim 1.

3. The activity management unit The activity schedule of the idol is automatically adjusted based on the user's daily rhythm.

2. The system of claim 1.

4. The feature setting unit Provide an interface that allows the user to fine-tune the personality or appearance of the idol 2. The system of claim 1.

5. The multilingual support unit Generating the content based on cultural background and nuances when the users interact in different languages 2. The system of claim 1.

6. The flame risk management department Monitor the user's emotions in real time and take appropriate action if negative emotions increase.

2. The system of claim 1.

Images