System

Abstract

An object of a system according to an embodiment is to provide entertainment in real time on the basis of a user's behavior or conversation content.SOLUTION: A system according to an embodiment includes a story generation unit, a video generation unit, a digital twin generation unit, and a live entertainment providing unit. The story generation unit analyzes a user's action or conversation content and generates a story. The video generation unit generates a video on the basis of the story generated by the story generation unit. The digital twin generation unit generates a digital twin in accordance with a user's action or conversation content. The live entertainment providing unit provides entertainment in real time based on the user's behavior or conversation content.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technologies have had the problem of making it difficult to provide entertainment in real time based on user behavior and conversation content.

[0005] The system according to the embodiment aims to provide entertainment in real time based on the user's actions and conversations. [Means for solving the problem]

[0006] The system according to the embodiment includes a story generation unit, a video generation unit, a digital twin generation unit, and a live entertainment provision unit. The story generation unit analyzes user behavior and conversation content to generate a story. The video generation unit generates video based on the story generated by the story generation unit. The digital twin generation unit generates a digital twin according to user behavior and conversation content. The live entertainment provision unit provides entertainment in real time based on user behavior and conversation content. [Effects of the Invention]

[0007] The system according to the embodiment can provide entertainment in real time based on the user's actions and conversations. [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 pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

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

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

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

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

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

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

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

[0028] (Example 1) A time machine travel system according to an embodiment of the present invention is a system that allows users to experience events from the past or future in a virtual reality (VR) space. This system realizes a digital twin in which a multimodal generation AI dynamically changes the story in response to the user's actions and conversations, and AI-powered live VR entertainment. As a result, the time machine travel system allows users to experience events from the past or future in a realistic way and enjoy time machine travel.

[0029] A time machine travel system according to an embodiment includes a story generation unit, a video generation unit, a digital twin generation unit, and a live entertainment provider. The story generation unit analyzes a user's actions and conversation content to generate a story. For example, if a user travels to a specific time in the past in a time machine and converses with a historical figure, the story generation unit changes the story according to the conversation content. The story generation unit also generates a story based on prompts including the user's actions and conversation content. The video generation unit generates video based on the story generated by the story generation unit. For example, the video generation unit accurately recreates a past cityscape or a future urban landscape, allowing the user to move freely within the landscape. The video generation unit also generates video based on prompts including information about the time period or place to be recreated. The digital twin generation unit generates a digital twin according to the user's actions and conversation content. For example, if a user takes a specific action, the digital twin generation unit changes the digital twin's reaction and story according to that action. The digital twin generation unit also analyzes the user's actions and conversation content and generates the digital twin's behavior and reaction based on the analysis. The live entertainment providing unit provides entertainment in real time based on the user's actions and conversation content. For example, the live entertainment providing unit allows the user to travel to a past battlefield in a time machine and experience a historical battle. The live entertainment providing unit also analyzes the user's actions and conversation content and generates stories and images in real time based on the analysis. As a result, the time machine travel system according to the embodiment allows the user to realistically experience events from the past and future and enjoy time machine travel. For example, by experiencing historical events, the user can deepen their understanding of history. Furthermore, by exploring a city of the future, the user can gain insight into future technology and lifestyles. Furthermore, because the story changes depending on the user's actions and conversation content, the user can enjoy new experiences over and over again.

[0030] The story generation unit can learn the user's past behavioral history and generate a story optimized for each individual user. For example, the story generation unit stores the user's past behavioral history in a database and customizes the story based on that data. For example, it presents new options taking into account options previously selected. The story generation unit also learns the user's behavioral patterns and optimizes the story based on them. For example, it prioritizes the development of scenarios that the user prefers. This makes it possible to provide a more personalized experience by optimizing the story based on the user's past behavioral history.

[0031] The story generation unit can introduce characters from different cultural and linguistic backgrounds and develop a story from an international perspective. For example, the story generation unit registers characters from different cultural and linguistic backgrounds in a database and has them appear in a story. For example, Japanese samurai or French aristocrats. The story generation unit also develops a scenario based on the settings of characters from different cultural and linguistic backgrounds. For example, it creates a scenario of intercultural exchange. The story generation unit also realistically reproduces the actions and conversations of characters from different cultural and linguistic backgrounds. For example, characters display greetings and customs unique to that culture. In this way, by introducing characters from different cultural and linguistic backgrounds, it is possible to develop a story from an international perspective.

[0032] The story generation unit can incorporate music and background sounds selected by the user to provide a more immersive experience. For example, the story generation unit incorporates music selected by the user as background sounds for the story. For example, the story progresses while the user's favorite song is played. The story generation unit also incorporates background sounds selected by the user into the story. For example, sounds of nature or city noise. The story generation unit also dynamically changes the music and background sounds based on the user's selection. For example, it switches music according to changes in the scene. In this way, by incorporating the music and background sounds selected by the user, a more immersive experience can be provided.

[0033] The image generation unit can analyze the user's gaze tracking data and dynamically adjust the focus and details of the image according to the gaze movement. For example, the image generation unit analyzes the user's gaze tracking data in real time and emphasizes the details of the object in front of the gaze. For example, it increases the resolution of the area where the user is looking. The image generation unit also dynamically changes the focus of the image according to the user's gaze movement. For example, when the user moves their gaze, it focuses on the object in front of the new gaze. The image generation unit also adjusts the details of the image based on the user's gaze tracking data. For example, it changes the details of the background according to the gaze movement. This makes it possible to provide a more realistic experience by dynamically adjusting the focus and details of the image according to the user's gaze.

[0034] The image generation unit can capture the user's movements in real time and dynamically change objects in the VR space according to those movements. For example, the image generation unit captures the user's hand movements and manipulates objects in the VR space according to those movements. For example, an object moves when the user reaches out. The image generation unit also captures the user's entire body movements and dynamically changes objects in the VR space based on those movements. For example, when the user jumps, the character in the VR space also jumps. The image generation unit also changes the position and shape of objects in the VR space based on the user's movement data. For example, an object deforms when the user performs a specific movement. This allows for dynamic changes to objects in the VR space according to the user's movements, providing a more interactive experience.

[0035] The image generation unit can combine information from different eras and locations to generate a VR space in which the user can seamlessly travel between multiple eras and locations. For example, the image generation unit combines information from different eras to generate a VR space in which the user can seamlessly travel. For example, the user can instantly travel from ancient Rome to modern-day New York. The image generation unit also combines information from different locations to generate a VR space in which the user can seamlessly travel. For example, the user can instantly travel from a desert to a rainforest. The image generation unit also generates a VR space based on information from different eras and locations, allowing the user to move freely. For example, the user can travel from a battlefield in the past to a city in the future. This allows the user to seamlessly travel between different eras and locations, thereby providing a more diverse experience.

[0036] The image generation unit can recreate specific historical events or future scenarios based on a theme selected by the user. For example, the image generation unit recreates historical events selected by the user with high accuracy. For example, it recreates a battlefield from World War II. The image generation unit also recreates future scenarios selected by the user. For example, it recreates a futuristic cityscape. The image generation unit also recreates specific themes based on the user's selection. For example, it develops a scenario based on the theme selected by the user. This allows for a more personalized experience by recreating historical events or future scenarios based on the theme selected by the user.

[0037] The digital twin generation unit can learn the user's past behavioral patterns and prepare the digital twin's response in advance based on predicted behavior. The digital twin generation unit, for example, stores the user's past behavioral patterns in a database and prepares the digital twin's response based on that data. For example, specific responses are set in advance for actions that the user often takes. The digital twin generation unit also learns the user's behavioral patterns and predicts the digital twin's response based on that. For example, the digital twin reacts before the user takes a specific action. The digital twin generation unit also prepares scenarios based on the user's behavioral patterns. For example, it develops scenarios based on options that the user often chooses. This allows for smoother dialogue by preparing the digital twin's response in advance based on the user's past behavioral patterns.

[0038] The digital twin generation unit can give digital twins different occupations and roles, allowing users to interact with different digital twins in a variety of scenarios. For example, the digital twin generation unit can give digital twins different occupations (doctor, teacher, engineer, etc.), allowing users to enjoy interactions based on that occupation. For example, having a health consultation with a doctor's digital twin. The digital twin generation unit can also give digital twins different roles, allowing users to enjoy interactions in a variety of scenarios. For example, holding a class with a teacher's digital twin. The digital twin generation unit can also develop scenarios based on the digital twin's occupation and role. For example, having a technical discussion with an engineer's digital twin. In this way, by giving digital twins different occupations and roles, users can enjoy interactions in a variety of scenarios.

[0039] The digital twin generation unit can incorporate the characteristics of the user's friends and family into the digital twin, enabling more intimate interactions. The digital twin generation unit, for example, incorporates the characteristics (voice, appearance, personality, etc.) of the user's friends and family into the digital twin, enabling more intimate interactions. For example, it can reproduce the voice of a friend. The digital twin generation unit also incorporates the behavioral patterns of the user's friends and family to change the behavior of the digital twin. For example, it can reproduce the habits of family members. The digital twin generation unit also develops scenarios based on the characteristics of the user's friends and family. For example, it can reproduce conversations with family members. In this way, by incorporating the characteristics of the user's friends and family into the digital twin, it is possible to achieve more intimate interactions.

[0040] The live entertainment providing unit can analyze real-time behavioral data of the user and dynamically adjust the progress of the live event based on that data. The live entertainment providing unit, for example, analyzes user behavioral data (movement, gestures, etc.) in real time and dynamically adjusts the progress of the live event. For example, if the user moves to a specific location, the event scene is changed. The live entertainment providing unit also adjusts the progress of the event based on the user behavioral data. For example, if the user performs a specific gesture, the event development is changed. The live entertainment providing unit also adjusts the event scenario in real time based on the user behavioral data. For example, the event timeline is changed according to the user's behavior. In this way, a more interactive experience can be provided by dynamically adjusting the progress of the live event based on the user's real-time behavioral data.

[0041] The live entertainment providing unit can learn the user's past entertainment history and provide a live event optimized for each individual user. For example, the live entertainment providing unit stores the user's past entertainment history in a database and customizes the live event based on that data. For example, it designs a new event based on data from events previously attended. The live entertainment providing unit also learns the user's entertainment history and optimizes the event based on that data. For example, it prioritizes providing events in genres that the user prefers. The live entertainment providing unit also adjusts the content of the event based on the user's entertainment history. For example, it incorporates elements that the user enjoyed in the past. This makes it possible to provide a more personalized experience by optimizing the live event based on the user's past entertainment history.

[0042] The live entertainment providing unit can combine different genres of entertainment (music, sports, theater, etc.) to allow users to enjoy a variety of experiences. For example, the live entertainment providing unit provides a live event that combines entertainment of different genres. For example, it can combine a live music event with a sports event. The live entertainment providing unit also develops a scenario that combines entertainment of different genres. For example, it can provide an interactive experience that combines theater and games. The live entertainment providing unit also dynamically changes the entertainment genre so that users can enjoy a variety of experiences. For example, it can switch genres in the middle of an event. In this way, by combining entertainment of different genres, users can enjoy a variety of experiences.

[0043] The live entertainment providing unit can recreate specific historical events or future scenarios live based on a theme selected by the user. For example, the live entertainment providing unit recreates a historical event selected by the user live. For example, it recreates a battlefield scene selected by the user in real time. The live entertainment providing unit also recreates a future scenario selected by the user live. For example, it recreates a futuristic cityscape in real time. The live entertainment providing unit also recreates a specific theme live based on the user's selection. For example, it develops a scenario based on the theme selected by the user. This makes it possible to provide a more personalized experience by recreating a historical event or future scenario live based on the theme selected by the user.

[0044] The user interface design unit can learn the user's operation history and dynamically generate an interface optimized for each individual user. For example, the user interface design unit stores the user's operation history in a database and customizes the interface based on that data. For example, it may prioritize the display of frequently used functions. The user interface design unit also learns the user's operation patterns and optimizes the interface based on that. For example, it may make buttons that the user uses frequently larger. The user interface design unit also dynamically changes the interface layout based on the user's operation history. For example, it may adjust the layout according to the user's operations. In this way, the interface can be optimized based on the user's operation history to provide a more user-friendly experience.

[0045] The user interface design unit can analyze the user's gaze tracking data and dynamically arrange interface elements according to the gaze movement. For example, the user interface design unit analyzes the user's gaze tracking data in real time and emphasizes the interface element in front of the user's gaze. For example, it enlarges the button the user is looking at. The user interface design unit also dynamically arranges interface elements according to the user's gaze movement. For example, it displays a menu in front of the user's gaze. The user interface design unit also adjusts the interface layout based on the user's gaze tracking data. For example, it changes the position of elements according to the gaze movement. This makes it possible to provide more intuitive operation by dynamically arranging interface elements according to the user's gaze.

[0046] The user interface design department can automatically generate interfaces that are compatible with different devices (smartphones, tablets, PCs, etc.). The user interface design department, for example, builds a system that automatically generates interfaces that are compatible with different devices. For example, it automatically switches between an interface for smartphones and an interface for PCs. The user interface design department also generates interfaces optimized for each device. For example, it automatically generates an interface for tablets. The user interface design department also employs responsive designs to support different devices. For example, it adjusts the layout according to the screen size. This allows for automatic generation of interfaces that are compatible with different devices, making it possible to provide operations on a wider variety of devices.

[0047] The user interface design unit can reflect a specific design and layout in the interface based on a theme selected by the user. The user interface design unit dynamically changes the design and layout of the interface based on, for example, the theme selected by the user. For example, it reflects the colors and style selected by the user. The user interface design unit also customizes the theme of the interface based on the user's selection. For example, it changes icons and fonts based on the theme selected by the user. The user interface design unit also adjusts the layout of the interface in accordance with the user's selection. For example, it automatically adjusts the layout based on the theme. This makes it possible to provide a more personalized operation by reflecting the design and layout of the interface based on the theme selected by the user.

[0048] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0049] The time machine travel system can also include a health management unit that monitors the user's health data. For example, the health management unit can monitor the user's heart rate and blood pressure in real time and issue a warning if an abnormality is detected. The health management unit can also adjust the progress of the story according to the user's health condition. For example, if the user is tired, it can provide a scene that allows the user to relax. Furthermore, the health management unit can provide appropriate advice on exercise and rest based on the user's health data. This allows the time machine travel system to provide an experience that takes the user's health into consideration.

[0050] The story generation unit can learn not only the user's past behavioral history but also the user's hobbies and interests, and customize the story based on that. For example, if the user is interested in history, the unit can develop a story centered around historical events. If the user is interested in sports, the unit can provide a story that includes sporting events. Furthermore, the story generation unit can suggest new scenarios based on the user's hobbies and interests. For example, it can introduce genres that the user has not experienced. This makes it possible to provide a personalized experience that matches the user's hobbies and interests.

[0051] The story generation unit can not only analyze the user's tone of voice and facial expressions, but also analyze the user's gestures and change the character's reaction based on the analysis. For example, when the user waves, the character waves back. Also, when the user points, the character looks in that direction. Furthermore, the story generation unit can adjust the progress of the story based on the user's gestures. For example, when the user claps, the story progresses. This makes it possible to provide an interactive experience that responds to the user's gestures.

[0052] The story generation unit not only introduces characters with different cultural and linguistic backgrounds, but also incorporates educational elements to help users learn about different cultures. For example, it may introduce the customs and history of different cultures in the story, or provide dialogue scenes for users to learn the language of the different culture. Furthermore, the story generation unit may enable users to deepen their understanding of different cultures through intercultural exchange scenarios. For example, it may provide a scenario in which characters from different cultures cooperate to solve a problem. This allows users to have fun while learning about different cultures.

[0053] The video generation unit not only analyzes the user's gaze tracking data, but can also add interactive elements according to the user's gaze movements. For example, when the user looks at a specific object, the object begins to move. Also, when the user moves their gaze, new information is displayed. Furthermore, the video generation unit can adjust the progress of the story based on the user's gaze movements. For example, the story progresses when the user looks at a specific location. This makes it possible to provide an interactive experience that responds to the user's gaze.

[0054] The video generation unit can not only capture the user's movements in real time, but also provide feedback based on the user's movements. For example, if the user performs a correct movement, it can provide positive feedback. Also, if the user performs a wrong movement, it can provide advice on how to correct it. Furthermore, the video generation unit can provide a training mode based on the user's movement data. For example, it can display a guide for the user to practice a specific movement. This allows for a more effective training experience by providing feedback according to the user's movements.

[0055] The processing flow of the first embodiment will be briefly explained below.

[0056] Step 1: The story generation unit analyzes the user's actions and conversation content and generates a story. For example, if the user travels to a specific time in the past in a time machine and talks with a historical figure, the story will change depending on the content of that conversation. The unit also generates a story based on prompts that include the user's actions and conversation content. Step 2: The video generation unit generates a video based on the story generated by the story generation unit. For example, it can accurately recreate a cityscape from the past or a future one, allowing the user to move freely through it. It also generates a video based on prompts containing information about the time period and place to be recreated. Step 3: The digital twin generation unit generates a digital twin based on the user's actions and conversations. For example, if the user takes a specific action, the digital twin's reaction and story will change based on that action. The unit also analyzes the user's actions and conversations and generates the digital twin's behavior and reactions based on that analysis. Step 4: The live entertainment provider provides real-time entertainment based on the user's behavior and conversations. For example, the user can travel to a past battlefield in a time machine and experience a historical battle. The provider also analyzes the user's behavior and conversations and generates stories and videos in real time.

[0057] (Example 2) A time machine travel system according to an embodiment of the present invention is a system that allows users to experience events from the past or future in a virtual reality (VR) space. This system realizes a digital twin in which a multimodal generation AI dynamically changes the story in response to the user's actions and conversations, and AI-powered live VR entertainment. As a result, the time machine travel system allows users to experience events from the past or future in a realistic way and enjoy time machine travel.

[0058] A time machine travel system according to an embodiment includes a story generation unit, a video generation unit, a digital twin generation unit, and a live entertainment provider. The story generation unit analyzes a user's actions and conversation content to generate a story. For example, if a user travels to a specific time in the past in a time machine and converses with a historical figure, the story generation unit changes the story according to the conversation content. The story generation unit also generates a story based on prompts including the user's actions and conversation content. The video generation unit generates video based on the story generated by the story generation unit. For example, the video generation unit accurately recreates a past cityscape or a future urban landscape, allowing the user to move freely within the landscape. The video generation unit also generates video based on prompts including information about the time period or place to be recreated. The digital twin generation unit generates a digital twin according to the user's actions and conversation content. For example, if a user takes a specific action, the digital twin generation unit changes the digital twin's reaction and story according to that action. The digital twin generation unit also analyzes the user's actions and conversation content and generates the digital twin's behavior and reaction based on the analysis. The live entertainment providing unit provides entertainment in real time based on the user's actions and conversation content. For example, the live entertainment providing unit allows the user to travel to a past battlefield in a time machine and experience a historical battle. The live entertainment providing unit also analyzes the user's actions and conversation content and generates stories and images in real time based on the analysis. As a result, the time machine travel system according to the embodiment allows the user to realistically experience events from the past and future and enjoy time machine travel. For example, by experiencing historical events, the user can deepen their understanding of history. Furthermore, by exploring a city of the future, the user can gain insight into future technology and lifestyles. Furthermore, because the story changes depending on the user's actions and conversation content, the user can enjoy new experiences over and over again.

[0059] The story generation unit can analyze the user's emotions in real time and dynamically adjust the development of the story in response to changes in emotions. The story generation unit, for example, analyzes the user's facial expressions and voice tone in real time to detect changes in emotions. For example, if the user has a surprised expression, the story development takes a sudden turn. The story generation unit also dynamically adjusts the development of the story based on the user's emotional data. For example, if the user has a sad expression, the story development is changed to a more moving one. In this way, by dynamically adjusting the development of the story in response to the user's emotions, a more immersive experience can be provided.

[0060] The story generation unit can learn the user's past behavioral history and generate a story optimized for each individual user. For example, the story generation unit stores the user's past behavioral history in a database and customizes the story based on that data. For example, it presents new options taking into account options previously selected. The story generation unit also learns the user's behavioral patterns and optimizes the story based on them. For example, it prioritizes the development of scenarios that the user prefers. This makes it possible to provide a more personalized experience by optimizing the story based on the user's past behavioral history.

[0061] The story generation unit can analyze the user's tone of voice and facial expression and change the character's reaction based on that. The story generation unit, for example, analyzes the user's tone of voice to measure the intensity of the emotion. For example, if the voice gets higher, the character will show a surprised reaction. The story generation unit also analyzes the user's facial expression to detect changes in emotion. For example, if the user smiles, the character will also smile. The story generation unit also analyzes the user's tone of voice and facial expression in combination to comprehensively change the character's reaction. For example, if the user shows an angry expression and tone of voice, the character will show an apologetic reaction. In this way, by changing the character's reaction based on the user's tone of voice and facial expression, more natural dialogue can be achieved.

[0062] The story generation unit can introduce characters from different cultural and linguistic backgrounds and develop a story from an international perspective. For example, the story generation unit registers characters from different cultural and linguistic backgrounds in a database and has them appear in a story. For example, Japanese samurai or French aristocrats. The story generation unit also develops a scenario based on the settings of characters from different cultural and linguistic backgrounds. For example, it creates a scenario of intercultural exchange. The story generation unit also realistically reproduces the actions and conversations of characters from different cultural and linguistic backgrounds. For example, characters display greetings and customs unique to that culture. In this way, by introducing characters from different cultural and linguistic backgrounds, it is possible to develop a story from an international perspective.

[0063] The story generation unit can incorporate music and background sounds selected by the user to provide a more immersive experience. For example, the story generation unit incorporates music selected by the user as background sounds for the story. For example, the story progresses while the user's favorite song is played. The story generation unit also incorporates background sounds selected by the user into the story. For example, sounds of nature or city noise. The story generation unit also dynamically changes the music and background sounds based on the user's selection. For example, it switches music according to changes in the scene. In this way, by incorporating the music and background sounds selected by the user, a more immersive experience can be provided.

[0064] The story generation unit can use the emotion estimation function to identify the story development that the user is most interested in and emphasize that development. The story generation unit, for example, analyzes the user's emotion data to identify the story development that the user is most interested in. For example, it emphasizes scenes that the user is excited about. The story generation unit also uses the emotion estimation function to measure the user's interests and adjust the story based on that. For example, it develops the story around a character that the user is interested in. The story generation unit also emphasizes important scenes in the story based on the user's emotion data. For example, it describes moving scenes in greater detail. This makes it possible to provide a more engaging experience by emphasizing the story development that the user is most interested in.

[0065] The image generation unit can analyze the user's gaze tracking data and dynamically adjust the focus and details of the image according to the gaze movement. For example, the image generation unit analyzes the user's gaze tracking data in real time and emphasizes the details of the object in front of the gaze. For example, it increases the resolution of the area where the user is looking. The image generation unit also dynamically changes the focus of the image according to the user's gaze movement. For example, when the user moves their gaze, it focuses on the object in front of the new gaze. The image generation unit also adjusts the details of the image based on the user's gaze tracking data. For example, it changes the details of the background according to the gaze movement. This makes it possible to provide a more realistic experience by dynamically adjusting the focus and details of the image according to the user's gaze.

[0066] The image generation unit can capture the user's movements in real time and dynamically change objects in the VR space according to those movements. For example, the image generation unit captures the user's hand movements and manipulates objects in the VR space according to those movements. For example, an object moves when the user reaches out. The image generation unit also captures the user's entire body movements and dynamically changes objects in the VR space based on those movements. For example, when the user jumps, the character in the VR space also jumps. The image generation unit also changes the position and shape of objects in the VR space based on the user's movement data. For example, an object deforms when the user performs a specific movement. This allows for dynamic changes to objects in the VR space according to the user's movements, providing a more interactive experience.

[0067] The image generation unit can analyze the user's emotions and reflect changes in color tone and light according to the emotions in the image. The image generation unit, for example, analyzes the user's emotional data and dynamically changes the color tone of the image according to the emotion. For example, when the user is sad, the image is made darker. The image generation unit also adjusts changes in the light of the image based on the user's emotions. For example, when the user is excited, the image is made brighter. The image generation unit also reflects changes in color tone and light of the image in real time based on the user's emotional data. For example, the atmosphere of the image changes according to changes in emotion. This makes it possible to provide a more emotional experience by changing the color tone and light of the image according to the user's emotions.

[0068] The image generation unit can combine information from different eras and locations to generate a VR space in which the user can seamlessly travel between multiple eras and locations. For example, the image generation unit combines information from different eras to generate a VR space in which the user can seamlessly travel. For example, the user can instantly travel from ancient Rome to modern-day New York. The image generation unit also combines information from different locations to generate a VR space in which the user can seamlessly travel. For example, the user can instantly travel from a desert to a rainforest. The image generation unit also generates a VR space based on information from different eras and locations, allowing the user to move freely. For example, the user can travel from a battlefield in the past to a city in the future. This allows the user to seamlessly travel between different eras and locations, thereby providing a more diverse experience.

[0069] The image generation unit can recreate specific historical events or future scenarios based on a theme selected by the user. For example, the image generation unit recreates historical events selected by the user with high accuracy. For example, it recreates a battlefield from World War II. The image generation unit also recreates future scenarios selected by the user. For example, it recreates a futuristic cityscape. The image generation unit also recreates specific themes based on the user's selection. For example, it develops a scenario based on the theme selected by the user. This allows for a more personalized experience by recreating historical events or future scenarios based on the theme selected by the user.

[0070] The video generation unit can use the emotion estimation function to identify the video scene that moves the user the most and emphasize that scene. The video generation unit, for example, analyzes the user's emotion data to identify the most moving scene. For example, it emphasizes a scene in which the user sheds tears. The video generation unit also uses the emotion estimation function to measure the user's emotion and adjusts scenes based on that. For example, it extends the depiction of a scene that moves the user. The video generation unit also emphasizes important scenes in the video based on the user's emotion data. For example, it emphasizes moving scenes by changing the color tone or light. This allows the video generation unit to provide a more moving experience by emphasizing the video scene that moves the user the most.

[0071] The digital twin generation unit analyzes the user's biometric data (heart rate, body temperature, etc.) and can dynamically change the digital twin's reactions based on that data. For example, the digital twin generation unit monitors the user's heart rate in real time, and if the heart rate rises, the digital twin will show a tense reaction. The digital twin generation unit also monitors the user's body temperature, and if the body temperature rises, the digital twin will show an excited reaction. The digital twin generation unit also changes the digital twin's movements and facial expressions based on the user's biometric data. For example, if the user is relaxed, the digital twin will also show relaxed movements. This makes it possible to provide a more realistic experience by dynamically changing the digital twin's reactions based on the user's biometric data.

[0072] The digital twin generation unit can learn the user's past behavioral patterns and prepare the digital twin's response in advance based on predicted behavior. The digital twin generation unit, for example, stores the user's past behavioral patterns in a database and prepares the digital twin's response based on that data. For example, specific responses are set in advance for actions that the user often takes. The digital twin generation unit also learns the user's behavioral patterns and predicts the digital twin's response based on that. For example, the digital twin reacts before the user takes a specific action. The digital twin generation unit also prepares scenarios based on the user's behavioral patterns. For example, it develops scenarios based on options that the user often chooses. This allows for smoother dialogue by preparing the digital twin's response in advance based on the user's past behavioral patterns.

[0073] The digital twin generation unit can analyze the user's emotions and generate the digital twin's facial expressions and actions according to the emotions. The digital twin generation unit, for example, analyzes the user's emotional data and generates the digital twin's facial expressions according to the emotions. For example, if the user smiles, the digital twin also smiles. The digital twin generation unit also generates the digital twin's actions based on the user's emotions. For example, when the user is sad, the digital twin will take actions to comfort the user. The digital twin generation unit also generates the digital twin's facial expressions and actions in real time based on the user's emotional data. For example, the digital twin's actions change according to changes in emotions. This allows the digital twin's facial expressions and actions to be generated according to the user's emotions, enabling more natural interactions.

[0074] The digital twin generation unit can give digital twins different occupations and roles, allowing users to interact with different digital twins in a variety of scenarios. For example, the digital twin generation unit can give digital twins different occupations (doctor, teacher, engineer, etc.), allowing users to enjoy interactions based on that occupation. For example, having a health consultation with a doctor's digital twin. The digital twin generation unit can also give digital twins different roles, allowing users to enjoy interactions in a variety of scenarios. For example, holding a class with a teacher's digital twin. The digital twin generation unit can also develop scenarios based on the digital twin's occupation and role. For example, having a technical discussion with an engineer's digital twin. In this way, by giving digital twins different occupations and roles, users can enjoy interactions in a variety of scenarios.

[0075] The digital twin generation unit can incorporate the characteristics of the user's friends and family into the digital twin, enabling more intimate interactions. The digital twin generation unit, for example, incorporates the characteristics (voice, appearance, personality, etc.) of the user's friends and family into the digital twin, enabling more intimate interactions. For example, it can reproduce the voice of a friend. The digital twin generation unit also incorporates the behavioral patterns of the user's friends and family to change the behavior of the digital twin. For example, it can reproduce the habits of family members. The digital twin generation unit also develops scenarios based on the characteristics of the user's friends and family. For example, it can reproduce conversations with family members. In this way, by incorporating the characteristics of the user's friends and family into the digital twin, it is possible to achieve more intimate interactions.

[0076] The digital twin generation unit can use the emotion estimation function to identify the digital twin character with which the user most empathizes and emphasize that character. The digital twin generation unit, for example, analyzes the user's emotion data and identifies the digital twin character with which the user most empathizes. For example, it emphasizes a character with which the user smiles. The digital twin generation unit also uses the emotion estimation function to measure the user's empathy and adjusts the character based on that. For example, it develops a scenario centered on a character with which the user empathizes. The digital twin generation unit also emphasizes important scenes of the character based on the user's emotion data. For example, it emphasizes empathetic scenes by changing color tones or lighting. This allows the digital twin generation unit to provide a more empathetic experience by emphasizing the digital twin character with which the user most empathizes.

[0077] The live entertainment providing unit can analyze real-time behavioral data of the user and dynamically adjust the progress of the live event based on that data. The live entertainment providing unit, for example, analyzes user behavioral data (movement, gestures, etc.) in real time and dynamically adjusts the progress of the live event. For example, if the user moves to a specific location, the event scene is changed. The live entertainment providing unit also adjusts the progress of the event based on the user behavioral data. For example, if the user performs a specific gesture, the event development is changed. The live entertainment providing unit also adjusts the event scenario in real time based on the user behavioral data. For example, the event timeline is changed according to the user's behavior. In this way, a more interactive experience can be provided by dynamically adjusting the progress of the live event based on the user's real-time behavioral data.

[0078] The live entertainment providing unit can learn the user's past entertainment history and provide a live event optimized for each individual user. For example, the live entertainment providing unit stores the user's past entertainment history in a database and customizes the live event based on that data. For example, it designs a new event based on data from events previously attended. The live entertainment providing unit also learns the user's entertainment history and optimizes the event based on that data. For example, it prioritizes providing events in genres that the user prefers. The live entertainment providing unit also adjusts the content of the event based on the user's entertainment history. For example, it incorporates elements that the user enjoyed in the past. This makes it possible to provide a more personalized experience by optimizing the live event based on the user's past entertainment history.

[0079] The live entertainment providing unit can combine different genres of entertainment (music, sports, theater, etc.) to allow users to enjoy a variety of experiences. For example, the live entertainment providing unit provides a live event that combines entertainment of different genres. For example, it can combine a live music event with a sports event. The live entertainment providing unit also develops a scenario that combines entertainment of different genres. For example, it can provide an interactive experience that combines theater and games. The live entertainment providing unit also dynamically changes the entertainment genre so that users can enjoy a variety of experiences. For example, it can switch genres in the middle of an event. In this way, by combining entertainment of different genres, users can enjoy a variety of experiences.

[0080] The live entertainment providing unit can recreate specific historical events or future scenarios live based on a theme selected by the user. For example, the live entertainment providing unit recreates a historical event selected by the user live. For example, it recreates a battlefield scene selected by the user in real time. The live entertainment providing unit also recreates a future scenario selected by the user live. For example, it recreates a futuristic cityscape in real time. The live entertainment providing unit also recreates a specific theme live based on the user's selection. For example, it develops a scenario based on the theme selected by the user. This makes it possible to provide a more personalized experience by recreating a historical event or future scenario live based on the theme selected by the user.

[0081] The live entertainment providing unit can use the emotion estimation function to identify the scene of a live event that excites the user most and emphasize that scene. For example, the live entertainment providing unit analyzes the user's emotion data to identify the most exciting scene. For example, it emphasizes a scene that excites the user. The live entertainment providing unit also uses the emotion estimation function to measure the user's excitement and adjusts the scene based on that. For example, it extends the scene that excites the user. The live entertainment providing unit also emphasizes important scenes of the live event based on the user's emotion data. For example, it emphasizes exciting scenes by changing the color tone or light. In this way, a more exciting experience can be provided by emphasizing the scene of the live event that excites the user most.

[0082] The user interface design unit can learn the user's operation history and dynamically generate an interface optimized for each individual user. For example, the user interface design unit stores the user's operation history in a database and customizes the interface based on that data. For example, it may prioritize the display of frequently used functions. The user interface design unit also learns the user's operation patterns and optimizes the interface based on that. For example, it may make buttons that the user uses frequently larger. The user interface design unit also dynamically changes the interface layout based on the user's operation history. For example, it may adjust the layout according to the user's operations. In this way, the interface can be optimized based on the user's operation history to provide a more user-friendly experience.

[0083] The user interface design unit can analyze the user's gaze tracking data and dynamically arrange interface elements according to the gaze movement. For example, the user interface design unit analyzes the user's gaze tracking data in real time and emphasizes the interface element in front of the user's gaze. For example, it enlarges the button the user is looking at. The user interface design unit also dynamically arranges interface elements according to the user's gaze movement. For example, it displays a menu in front of the user's gaze. The user interface design unit also adjusts the interface layout based on the user's gaze tracking data. For example, it changes the position of elements according to the gaze movement. This makes it possible to provide more intuitive operation by dynamically arranging interface elements according to the user's gaze.

[0084] The user interface design unit can analyze the user's emotions and dynamically adjust the color tone and design of the interface according to the emotion. The user interface design unit, for example, analyzes the user's emotional data and dynamically changes the color tone of the interface according to the emotion. For example, when the user is relaxed, the color tone is made calm. The user interface design unit also adjusts the interface design based on the user's emotions. For example, when the user is excited, the design is made vivid. The user interface design unit also changes the color tone and design of the interface in real time based on the user's emotional data. For example, the design changes according to changes in emotion. In this way, the color tone and design of the interface can be dynamically adjusted according to the user's emotions, providing a more comfortable operation.

[0085] The user interface design department can automatically generate interfaces that are compatible with different devices (smartphones, tablets, PCs, etc.). The user interface design department, for example, builds a system that automatically generates interfaces that are compatible with different devices. For example, it automatically switches between an interface for smartphones and an interface for PCs. The user interface design department also generates interfaces optimized for each device. For example, it automatically generates an interface for tablets. The user interface design department also employs responsive designs to support different devices. For example, it adjusts the layout according to the screen size. This allows for automatic generation of interfaces that are compatible with different devices, making it possible to provide operations on a wider variety of devices.

[0086] The user interface design unit can reflect a specific design and layout in the interface based on a theme selected by the user. The user interface design unit dynamically changes the design and layout of the interface based on, for example, the theme selected by the user. For example, it reflects the colors and style selected by the user. The user interface design unit also customizes the theme of the interface based on the user's selection. For example, it changes icons and fonts based on the theme selected by the user. The user interface design unit also adjusts the layout of the interface in accordance with the user's selection. For example, it automatically adjusts the layout based on the theme. This makes it possible to provide a more personalized operation by reflecting the design and layout of the interface based on the theme selected by the user.

[0087] The user interface design unit can use the emotion estimation function to identify the interface design that the user finds easiest to use and emphasize that design. The user interface design unit, for example, analyzes the user's emotion data to identify the interface design that the user finds easiest to use. For example, it emphasizes a design that is appropriate when the user is relaxed. The user interface design unit also uses the emotion estimation function to measure the user's ease of use and adjusts the design based on that. For example, it builds an interface centered on a design that the user finds easy to use. The user interface design unit also emphasizes important aspects of the interface based on the user's emotion data. For example, it emphasizes elements that the user finds easy to use using color tone or placement. This allows the user to provide a more comfortable operation by emphasizing the interface design that the user finds easiest to use.

[0088] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0089] The time machine travel system can also include a health management unit that monitors the user's health data. For example, the health management unit can monitor the user's heart rate and blood pressure in real time and issue a warning if an abnormality is detected. The health management unit can also adjust the progress of the story according to the user's health condition. For example, if the user is tired, it can provide a scene that allows the user to relax. Furthermore, the health management unit can provide appropriate advice on exercise and rest based on the user's health data. This allows the time machine travel system to provide an experience that takes the user's health into consideration.

[0090] The story generation unit can not only analyze the user's emotions, but also analyze the user's stress level and provide a story development that reduces stress. For example, if the user is feeling high stress, the story generation unit can provide relaxing scenes and music. The story generation unit can also adjust the difficulty of the story according to the user's stress level. For example, if the user is feeling high stress, the story generation unit can provide easy options. Furthermore, the story generation unit can dynamically adjust the progress of the story based on the user's stress level to allow the user to relax. This makes it possible to provide an experience that suits the user's stress level.

[0091] The story generation unit can learn not only the user's past behavioral history but also the user's hobbies and interests, and customize the story based on that. For example, if the user is interested in history, the unit can develop a story centered around historical events. If the user is interested in sports, the unit can provide a story that includes sporting events. Furthermore, the story generation unit can suggest new scenarios based on the user's hobbies and interests. For example, it can introduce genres that the user has not experienced. This makes it possible to provide a personalized experience that matches the user's hobbies and interests.

[0092] The story generation unit can not only analyze the user's tone of voice and facial expressions, but also analyze the user's gestures and change the character's reaction based on the analysis. For example, when the user waves, the character waves back. Also, when the user points, the character looks in that direction. Furthermore, the story generation unit can adjust the progress of the story based on the user's gestures. For example, when the user claps, the story progresses. This makes it possible to provide an interactive experience that responds to the user's gestures.

[0093] The story generation unit not only introduces characters with different cultural and linguistic backgrounds, but also incorporates educational elements to help users learn about different cultures. For example, it may introduce the customs and history of different cultures in the story, or provide dialogue scenes for users to learn the language of the different culture. Furthermore, the story generation unit may enable users to deepen their understanding of different cultures through intercultural exchange scenarios. For example, it may provide a scenario in which characters from different cultures cooperate to solve a problem. This allows users to have fun while learning about different cultures.

[0094] The story generation unit can not only incorporate music and background sounds selected by the user, but can also dynamically change the music and background sounds according to the user's emotions. For example, it can play soft music when the user is relaxed and fast-paced music when the user is excited. The story generation unit can also adjust the background sounds based on the user's emotions. For example, it can provide soft background sounds when the user is nervous. Furthermore, the story generation unit can change the music and background sounds in real time based on the user's emotional data. This allows for a more immersive experience by providing music and background sounds according to the user's emotions.

[0095] The story generation unit not only uses the emotion estimation function to identify the story development that the user is most interested in, but can also adjust the tempo of the story based on the user's emotions. For example, if the user is excited, the tempo of the story can be increased. Conversely, if the user is relaxed, the tempo of the story can be decreased. Furthermore, the story generation unit can emphasize important scenes in the story based on the user's emotion data. For example, moving scenes can be depicted longer. This allows the user to have a more engaging experience by providing a story tempo that matches the user's emotions.

[0096] The video generation unit not only analyzes the user's gaze tracking data, but can also add interactive elements according to the user's gaze movements. For example, when the user looks at a specific object, the object begins to move. Also, when the user moves their gaze, new information is displayed. Furthermore, the video generation unit can adjust the progress of the story based on the user's gaze movements. For example, the story progresses when the user looks at a specific location. This makes it possible to provide an interactive experience that responds to the user's gaze.

[0097] The video generation unit can not only capture the user's movements in real time, but also provide feedback based on the user's movements. For example, if the user performs a correct movement, it can provide positive feedback. Also, if the user performs a wrong movement, it can provide advice on how to correct it. Furthermore, the video generation unit can provide a training mode based on the user's movement data. For example, it can display a guide for the user to practice a specific movement. This allows for a more effective training experience by providing feedback according to the user's movements.

[0098] The video generation unit can not only analyze the user's emotions, but also dynamically adjust the sound effects of the video according to the user's emotions. For example, it can emphasize sound effects when the user is surprised, or provide quieter sound effects when the user is sad. Furthermore, the video generation unit can change the sound effects in real time based on the user's emotional data. For example, it can adjust the sound effects according to changes in emotions. This allows for a more emotional experience by providing sound effects according to the user's emotions.

[0099] The processing flow of the second embodiment will be briefly explained below.

[0100] Step 1: The story generation unit analyzes the user's actions and conversation content and generates a story. For example, if the user travels to a specific time in the past in a time machine and talks with a historical figure, the story will change depending on the content of that conversation. The unit also generates a story based on prompts that include the user's actions and conversation content. Step 2: The video generation unit generates a video based on the story generated by the story generation unit. For example, it can accurately recreate a cityscape from the past or a future one, allowing the user to move freely through it. It also generates a video based on prompts containing information about the time period and place to be recreated. Step 3: The digital twin generation unit generates a digital twin based on the user's actions and conversations. For example, if the user takes a specific action, the digital twin's reaction and story will change based on that action. The unit also analyzes the user's actions and conversations and generates the digital twin's behavior and reactions based on that analysis. Step 4: The live entertainment provider provides real-time entertainment based on the user's behavior and conversations. For example, the user can travel to a past battlefield in a time machine and experience a historical battle. The provider also analyzes the user's behavior and conversations and generates stories and videos in real time.

[0101] 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.

[0102] 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.

[0103] 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.

[0104] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0105] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0106] 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.

[0107] 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.

[0108] 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.

[0109] 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).

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0120] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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).

[0125] 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.

[0126] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0135] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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).

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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).

[0154] 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 "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[0155] 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."

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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]

[0168] 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 story generation unit that analyzes user behavior and conversation content and generates a story; a video generation unit that generates a video based on the story generated by the story generation unit; a digital twin generation unit that generates a digital twin according to the user's actions and conversation content; a live entertainment providing unit that provides entertainment in real time based on the user's actions and conversation content. A system characterized by:

2. The story generation unit The emotions of the user are analyzed in real time, and the development of the story is dynamically adjusted according to changes in the emotions.

2. The system of claim 1.

3. The image generation unit Analyzing the user's eye-tracking data and dynamically adjusting focus and detail of the video in response to eye movements.

2. The system of claim 1.

4. The digital twin generation unit is Analyzing the user's biometric data and dynamically changing the digital twin's response based on the biometric data.

2. The system of claim 1.

5. The live entertainment providing department Analyzing real-time behavioral data of the user and dynamically adjusting the progress of the live event based thereon.

2. The system of claim 1.

6. The story generation unit Analyze the user's tone of voice and facial expressions and change the character's reactions based on that.

2. The system of claim 1.

7. The image generation unit Analyzing the user's emotions and reflecting changes in color tone and light in accordance with the emotions in the video.

2. The system of claim 1.

8. The digital twin generation unit is Analyzing the emotions of the user and generating facial expressions and movements of the digital twin in accordance with the emotions.

2. The system of claim 1.

Images