system

Abstract

An object of a system according to an embodiment is to provide an individualized space mission based on a reaction or selection of a user.SOLUTION: In one embodiment, a system comprises a VR headset, a generation AI, a mission generator, and an experience provider. The VR headset captures the user's reactions and selections. The generative AI analyzes the user's reactions and selections captured by the VR headset. The mission generation part generates an individual space mission based on a result analyzed by the generation AI. The experience providing unit provides the user with the individual space mission generated by the mission generating unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Existing technologies fall short in providing a personalized VR experience based on user responses and choices, leaving room for improvement.

[0005] The system according to the embodiment aims to provide a personalized space mission based on the user's responses and choices. [Means for solving the problem]

[0006] A system according to an embodiment includes a VR headset, a generation AI, a mission generation unit, and an experience provision unit. The VR headset acquires a user's reactions and selections. The generation AI analyzes the user's reactions and selections acquired by the VR headset. The mission generation unit generates an individual space mission based on the results of the analysis by the generation AI. The experience provision unit provides the user with the individual space mission generated by the mission generation unit. [Effects of the Invention]

[0007] An embodiment of the system can provide personalized space missions based on user responses and selections. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) A virtual reality experience service according to an embodiment of the present invention is a system that allows a user to experience being an astronaut from the comfort of their own home simply by wearing a VR headset. This system utilizes AI technology to generate individual space missions based on the user's responses and selections, and realizes a realistic space adventure in a virtual space, from piloting a spaceship to spacewalking and exploring alien planets. As a result, the virtual reality experience service generates individual space missions based on the user's responses and selections, allowing a realistic space adventure to be realized in a virtual space.

[0029] A virtual reality experience service according to an embodiment includes a VR headset, a generation AI, a mission generation unit, and an experience provision unit. The VR headset acquires a user's reactions and selections. For example, the VR headset acquires the user's gaze movement using eye tracking technology. It can also acquire the user's hand movement using gesture recognition technology. It can also acquire the user's voice commands using voice recognition technology. The generation AI analyzes the user's reactions and selections acquired by the VR headset. For example, the generation AI analyzes the user's reactions using a machine learning algorithm. It can also analyze the user's selections using data mining technology. It can also analyze the user's voice commands using natural language processing technology. The mission generation unit generates an individual space mission based on the results of the analysis by the generation AI. For example, if a user selects "I'm interested in piloting a spaceship," it generates a mission centered on piloting a spaceship. If a user selects "I'm interested in exploring alien planets," it can generate a mission centered on exploring alien planets. If a user selects "I'm interested in spacewalks," it can generate a mission centered on spacewalks. The experience provision unit provides the individual space mission generated by the mission generation unit to the user. For example, a spaceship piloting simulation can be provided in a VR environment. Also, an alien planet exploration simulation can be provided in a VR environment. Furthermore, a spacewalk simulation can be provided in a VR environment. Thus, the virtual reality experience service according to the embodiment generates individual space missions based on the user's responses and selections, enabling a realistic space adventure to be realized in a virtual space.

[0030] The mission generation unit can generate a specific space mission based on the user's selection. For example, if the user selects "I'm interested in piloting a spaceship," the mission generation unit can generate a mission centered on piloting a spaceship. Alternatively, if the user selects "I'm interested in exploring alien planets," the mission generation unit can generate a mission centered on exploring alien planets. Alternatively, if the user selects "I'm interested in spacewalks," the mission generation unit can generate a mission centered on spacewalks. This allows for the provision of a personalized experience by generating a specific space mission based on the user's selection.

[0031] The experience providing unit can analyze the user's movements in real time and reflect the movements and operations within the virtual space. The experience providing unit, for example, analyzes the user's movements in real time using motion capture technology. For example, when the user reaches out and touches the outer wall of the space station, the sensation is fed back. Furthermore, when the user walks, the movement within the virtual space can be reflected. Furthermore, when the user performs a specific gesture, the operation within the virtual space can be reflected. In this way, by analyzing the user's movements in real time and reflecting the movements and operations within the virtual space, a more realistic experience can be provided.

[0032] The experience providing unit can monitor the user's heart rate and electrodermal response and automatically adjust the difficulty of the virtual environment according to the stress level. The experience providing unit, for example, monitors the user's heart rate using a heart rate sensor. For example, if the heart rate is high, the difficulty of the virtual environment can be lowered. The experience providing unit can also monitor the user's electrodermal response using an electrodermal sensor. For example, if the electrodermal response is high, the difficulty of the virtual environment can be lowered. The experience providing unit can also monitor both the heart rate and electrodermal response and automatically adjust the difficulty of the virtual environment according to the stress level. This makes it possible to provide a more comfortable experience by automatically adjusting the difficulty of the virtual environment according to the user's stress level.

[0033] The experience providing unit can recognize the user's voice and perform settings using voice commands. The experience providing unit recognizes the user's voice using, for example, voice recognition technology. For example, when the user says "Enter your name," a voice input screen is displayed. Also, when the user says "Proceed to next setting," the user can proceed to the next setting screen. Also, when the user says "Exit," the user can end the setting. This allows for more intuitive operation by recognizing the user's voice and performing settings using voice commands.

[0034] The experience providing unit can capture the user's physical movements and provide an interface for setting up through gesture operations. The experience providing unit captures the user's physical movements using, for example, motion capture technology. For example, when the user waves their hand, the screen moves to the next settings screen. When the user raises their hand, the settings can be saved. When the user lowers their hand, the settings can be canceled. In this way, by capturing the user's physical movements and providing an interface for setting up through gesture operations, more intuitive operation becomes possible.

[0035] The mission generation unit can analyze the user's past mission history and optimize the next mission based on the user's individual learning curve. The mission generation unit, for example, retrieves the user's past mission history from a database and analyzes it. For example, the mission generation unit can adjust the difficulty of the next mission based on data on missions the user has previously succeeded in. It can also change the content of the next mission based on data on missions the user has previously failed in. It can also analyze the user's learning curve and set a goal for the next mission. In this way, by analyzing the user's past mission history and optimizing the next mission based on the user's individual learning curve, it is possible to provide a more effective learning experience.

[0036] The mission generation unit can monitor the user's real-time reactions and dynamically change the scenario during the mission. For example, the mission generation unit can use facial expression recognition technology to monitor the user's real-time reactions. For example, if the user makes a surprised expression, a new event can be added to the scenario. The mission generation unit can also monitor the tone and speed of the user's voice using voice analysis technology. For example, if the user makes an excited voice, the difficulty of the scenario can be increased. The mission generation unit can also monitor the user's heart rate and electrodermal activity using a biosensor. For example, if the user's heart rate increases, the progress of the scenario can be slowed down. This makes it possible to provide a more adaptive experience by monitoring the user's real-time reactions and dynamically changing the scenario during the mission.

[0037] The mission generation unit can incorporate astronomical phenomena specific to a region by taking into account the user's geographical location information. The mission generation unit, for example, acquires the user's geographical location information from GPS data. For example, if the user is in the Northern Hemisphere, a mission to observe the aurora can be generated. Also, if the user is in the Southern Hemisphere, a mission to observe southern constellations can be generated. Furthermore, astronomical phenomena specific to a region can be incorporated based on the user's geographical location information. In this way, a more realistic experience can be provided by taking into account the user's geographical location information and incorporating astronomical phenomena specific to a region.

[0038] The experience providing unit can analyze the user's operation data in real time and provide feedback to support the improvement of piloting skills. The experience providing unit, for example, uses an algorithm with high data processing speed to analyze the user's operation data in real time. For example, when the user makes a piloting error, the experience providing unit presents the correct operation method. It can also provide feedback to support the improvement of piloting skills based on the user's operation data. For example, if the user repeatedly makes mistakes in a particular operation, it can suggest training related to that operation. In this way, by analyzing the user's operation data in real time and providing feedback to support the improvement of piloting skills, it is possible to provide a more effective learning experience.

[0039] The experience providing unit can incorporate data from an actual spacecraft to provide a more realistic piloting experience. For example, the experience providing unit acquires design data and operational data from an actual spacecraft and reflects this in the simulation. For example, the unit incorporates instrument data and operational procedures from the spacecraft into the simulation. The unit can also reflect the operating characteristics and environmental conditions of the spacecraft in the simulation. In this way, by incorporating data from an actual spacecraft, a more realistic piloting experience can be provided.

[0040] The experience providing unit can introduce cooperative play with other users and enable multiple people to pilot the spaceship. The experience providing unit, for example, provides a mission in which multiple users cooperate to pilot a spaceship. For example, multiple users each take on different roles and cooperate to pilot the spaceship. In addition, a voice chat function can be provided to support communication between users. This allows for cooperative play with other users and enables multiple people to pilot the spaceship, making it possible to provide a more diverse range of experiences.

[0041] The experience providing unit can play music selected by the user in the background to provide a relaxing environment. The experience providing unit, for example, uses music playback technology to play music selected by the user in the background. For example, the user can operate the vehicle while playing their favorite music. It is also possible to clarify the music selection method and playback technology. This allows the user to play music selected by the user in the background to provide a relaxing environment, thereby providing a more comfortable experience.

[0042] The experience providing unit can track the user's movements with high precision and provide feedback in real time. The experience providing unit can track the user's movements with high precision, for example, using motion capture technology. For example, when the user reaches out and touches the outer wall of the space station, the sensation is fed back. Also, when the user performs a specific action, feedback corresponding to that action can be displayed. Furthermore, by tracking the user's movements in real time and providing feedback, a more realistic experience can be provided. In this way, by tracking the user's movements with high precision and providing feedback in real time, a more realistic experience can be provided.

[0043] The experience providing unit can incorporate data from an actual space station to recreate a more realistic environment. For example, the experience providing unit acquires design data and operational data from an actual space station and reflects this in the simulation. For example, the outer walls and internal structure of the space station can be realistically reproduced. The operating characteristics and environmental conditions of the space station can also be reflected in the simulation. In this way, by incorporating data from an actual space station, a more realistic environment can be recreated.

[0044] The experience providing unit can introduce cooperative play with other users, enabling multiple users to swim together. The experience providing unit can, for example, provide a mission in which multiple users work together to repair a space station. For example, multiple users each take on different roles and work together to repair the space station. A voice chat function can also be provided to support communication between users. This allows for cooperative play with other users and allows multiple users to swim together, making it possible to provide a more diverse experience.

[0045] The experience providing unit can play music selected by the user in the background to provide a relaxing environment. The experience providing unit, for example, uses music playback technology to play music selected by the user in the background. For example, the user can swim while playing their favorite music. It is also possible to clarify the music selection method and playback technology. This allows the user to play music selected by the user in the background to provide a relaxing environment, thereby providing a more comfortable experience.

[0046] The experience providing unit can track the user's movements with high accuracy during the exploration of the alien planet and provide feedback in real time. The experience providing unit can track the user's movements with high accuracy, for example, using motion capture technology. For example, when the user performs a specific action, feedback corresponding to that action is displayed. Furthermore, by tracking the user's movements in real time and providing feedback, a more realistic experience can be provided. In this way, by tracking the user's movements with high accuracy during the exploration of the alien planet and providing feedback in real time, a more realistic experience can be provided.

[0047] The experience providing unit can introduce cooperative play with other users into the alien exploration experience, enabling exploration by multiple people. The experience providing unit, for example, provides a mission in which multiple users cooperate to explore the terrain of an alien planet. For example, multiple users each take on different roles and cooperate to explore the terrain of an alien planet. In addition, a voice chat function can be provided to support communication between users. This allows cooperative play with other users to be introduced into the alien exploration experience, enabling exploration by multiple people, thereby providing a more diverse experience.

[0048] The experience providing unit can play music selected by the user in the background while exploring the alien planet, providing a relaxing environment. The experience providing unit, for example, uses music playback technology to play music selected by the user in the background. For example, the user explores while playing their favorite music. It can also clarify the music selection method and playback technology. This allows the user to play music selected by the user in the background and provide a relaxing environment, providing a more comfortable experience.

[0049] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0050] The experience providing unit can recognize the user's voice and perform settings using voice commands. For example, the user's voice is recognized using voice recognition technology. When the user says "Enter your name," a voice input screen is displayed. Also, when the user says "Proceed to next setting," the user can proceed to the next setting screen. Furthermore, when the user says "Exit," the setting can be finished. This allows for more intuitive operation by recognizing the user's voice and performing settings using voice commands.

[0051] The experience providing unit can capture the user's physical movements and provide an interface for setting up using gesture operations. For example, the user's physical movements can be captured using motion capture technology. When the user waves their hand, they can proceed to the next setting screen. When the user raises their hand, they can also save the settings. Furthermore, when the user lowers their hand, they can also cancel the settings. In this way, by capturing the user's physical movements and providing an interface for setting up using gesture operations, more intuitive operation becomes possible.

[0052] The mission generation unit can analyze the user's past mission history and optimize the next mission based on the user's individual learning curve. For example, the mission generation unit retrieves the user's past mission history from a database and analyzes it. The unit adjusts the difficulty of the next mission based on data on missions the user has previously succeeded in. The unit can also change the content of the next mission based on data on missions the user has previously failed in. Furthermore, the unit can analyze the user's learning curve and set a goal for the next mission. This makes it possible to provide a more effective learning experience by analyzing the user's past mission history and optimizing the next mission based on the user's individual learning curve.

[0053] The mission generation unit can incorporate astronomical phenomena specific to a region, taking into account the user's geographical location information. For example, the user's geographical location information is obtained from GPS data. If the user is in the Northern Hemisphere, a mission to observe the aurora can be generated. If the user is in the Southern Hemisphere, a mission to observe southern constellations can be generated. Furthermore, astronomical phenomena specific to a region can also be incorporated based on the user's geographical location information. In this way, a more realistic experience can be provided by taking into account the user's geographical location information and incorporating astronomical phenomena specific to a region.

[0054] The experience providing unit can analyze the user's operation data in real time and provide feedback to support the improvement of piloting skills. For example, to analyze the user's operation data in real time, an algorithm with high data processing speed is used. When the user makes a piloting error, the correct operation method is presented. It can also provide feedback to support the improvement of piloting skills based on the user's operation data. If the user repeatedly makes mistakes in a particular operation, it can also suggest training for that operation. In this way, a more effective learning experience can be provided by analyzing the user's operation data in real time and providing feedback to support the improvement of piloting skills.

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

[0056] Step 1: The VR headset captures the user's reactions and selections. For example, it uses eye tracking technology to capture the user's eye movements, gesture recognition technology to capture the user's hand movements, and voice recognition technology to capture the user's voice commands. Step 2: The generative AI analyzes the user's reactions and choices captured by the VR headset. For example, it can use machine learning algorithms to analyze the user's reactions and data mining techniques to analyze the user's choices. It can also use natural language processing techniques to analyze the user's voice commands. Step 3: The mission generation unit generates individual space missions based on the results of the analysis by the generation AI. For example, if the user selects "I'm interested in piloting a spaceship," a mission centered on piloting a spaceship is generated. Also, if the user selects "I'm interested in exploring other planets," a mission centered on exploring other planets can be generated. Furthermore, if the user selects "I'm interested in spacewalks," a mission centered on spacewalks can be generated. Step 4: The experience provider provides the user with the individual space mission generated by the mission generator. For example, it can provide a spacecraft piloting simulation in a VR environment, as well as an alien planet exploration simulation or spacewalk simulation.

[0057] (Example 2) A virtual reality experience service according to an embodiment of the present invention is a system that allows a user to experience being an astronaut from the comfort of their own home simply by wearing a VR headset. This system utilizes AI technology to generate individual space missions based on the user's responses and selections, and realizes a realistic space adventure in a virtual space, from piloting a spaceship to spacewalking and exploring alien planets. As a result, the virtual reality experience service generates individual space missions based on the user's responses and selections, allowing a realistic space adventure to be realized in a virtual space.

[0058] A virtual reality experience service according to an embodiment includes a VR headset, a generation AI, a mission generation unit, and an experience provision unit. The VR headset acquires a user's reactions and selections. For example, the VR headset acquires the user's gaze movement using eye tracking technology. It can also acquire the user's hand movement using gesture recognition technology. It can also acquire the user's voice commands using voice recognition technology. The generation AI analyzes the user's reactions and selections acquired by the VR headset. For example, the generation AI analyzes the user's reactions using a machine learning algorithm. It can also analyze the user's selections using data mining technology. It can also analyze the user's voice commands using natural language processing technology. The mission generation unit generates an individual space mission based on the results of the analysis by the generation AI. For example, if a user selects "I'm interested in piloting a spaceship," it generates a mission centered on piloting a spaceship. If a user selects "I'm interested in exploring alien planets," it can generate a mission centered on exploring alien planets. If a user selects "I'm interested in spacewalks," it can generate a mission centered on spacewalks. The experience provision unit provides the individual space mission generated by the mission generation unit to the user. For example, a spaceship piloting simulation can be provided in a VR environment. Also, an alien planet exploration simulation can be provided in a VR environment. Furthermore, a spacewalk simulation can be provided in a VR environment. Thus, the virtual reality experience service according to the embodiment generates individual space missions based on the user's responses and selections, enabling a realistic space adventure to be realized in a virtual space.

[0059] The mission generation unit can generate a specific space mission based on the user's selection. For example, if the user selects "I'm interested in piloting a spaceship," the mission generation unit can generate a mission centered on piloting a spaceship. Alternatively, if the user selects "I'm interested in exploring alien planets," the mission generation unit can generate a mission centered on exploring alien planets. Alternatively, if the user selects "I'm interested in spacewalks," the mission generation unit can generate a mission centered on spacewalks. This allows for the provision of a personalized experience by generating a specific space mission based on the user's selection.

[0060] The experience providing unit can analyze the user's movements in real time and reflect the movements and operations within the virtual space. The experience providing unit, for example, analyzes the user's movements in real time using motion capture technology. For example, when the user reaches out and touches the outer wall of the space station, the sensation is fed back. Furthermore, when the user walks, the movement within the virtual space can be reflected. Furthermore, when the user performs a specific gesture, the operation within the virtual space can be reflected. In this way, by analyzing the user's movements in real time and reflecting the movements and operations within the virtual space, a more realistic experience can be provided.

[0061] The experience providing unit can analyze the emotional state of the user and provide feedback according to the emotional state. The experience providing unit, for example, analyzes the emotional state of the user using an emotion estimation function. For example, the emotional state can be estimated by analyzing the user's facial expression using facial expression recognition technology. The emotional state can also be estimated by analyzing the tone and speed of the user's voice using voice analysis technology. The emotional state can also be estimated by analyzing the user's heart rate and electrodermal activity using a biosensor. This makes it possible to provide a more personalized experience by providing feedback according to the user's emotional state.

[0062] The experience providing unit can monitor the user's heart rate and electrodermal response and automatically adjust the difficulty of the virtual environment according to the stress level. The experience providing unit, for example, monitors the user's heart rate using a heart rate sensor. For example, if the heart rate is high, the difficulty of the virtual environment can be lowered. The experience providing unit can also monitor the user's electrodermal response using an electrodermal sensor. For example, if the electrodermal response is high, the difficulty of the virtual environment can be lowered. The experience providing unit can also monitor both the heart rate and electrodermal response and automatically adjust the difficulty of the virtual environment according to the stress level. This makes it possible to provide a more comfortable experience by automatically adjusting the difficulty of the virtual environment according to the user's stress level.

[0063] The experience providing unit can recognize the user's voice and perform settings using voice commands. The experience providing unit recognizes the user's voice using, for example, voice recognition technology. For example, when the user says "Enter your name," a voice input screen is displayed. Also, when the user says "Proceed to next setting," the user can proceed to the next setting screen. Also, when the user says "Exit," the user can end the setting. This allows for more intuitive operation by recognizing the user's voice and performing settings using voice commands.

[0064] The experience providing unit can capture the user's physical movements and provide an interface for setting up through gesture operations. The experience providing unit captures the user's physical movements using, for example, motion capture technology. For example, when the user waves their hand, the screen moves to the next settings screen. When the user raises their hand, the settings can be saved. When the user lowers their hand, the settings can be canceled. In this way, by capturing the user's physical movements and providing an interface for setting up through gesture operations, more intuitive operation becomes possible.

[0065] The experience providing unit can propose customization settings according to the user's emotions and provide a more personalized experience. The experience providing unit, for example, uses an emotion estimation function to analyze the user's emotional state. For example, the experience providing unit can analyze the user's facial expressions using facial expression recognition technology to estimate the emotional state. The experience providing unit can also use voice analysis technology to analyze the tone and speed of the user's voice to estimate the emotional state. The experience providing unit can also use a biosensor to analyze the user's heart rate and electrodermal activity to estimate the emotional state. This allows the experience providing unit to propose customization settings according to the user's emotional state and provide a more personalized experience.

[0066] The mission generation unit can analyze the user's past mission history and optimize the next mission based on the user's individual learning curve. The mission generation unit, for example, retrieves the user's past mission history from a database and analyzes it. For example, the mission generation unit can adjust the difficulty of the next mission based on data on missions the user has previously succeeded in. It can also change the content of the next mission based on data on missions the user has previously failed in. It can also analyze the user's learning curve and set a goal for the next mission. In this way, by analyzing the user's past mission history and optimizing the next mission based on the user's individual learning curve, it is possible to provide a more effective learning experience.

[0067] The mission generation unit can monitor the user's real-time reactions and dynamically change the scenario during the mission. For example, the mission generation unit can use facial expression recognition technology to monitor the user's real-time reactions. For example, if the user makes a surprised expression, a new event can be added to the scenario. The mission generation unit can also monitor the tone and speed of the user's voice using voice analysis technology. For example, if the user makes an excited voice, the difficulty of the scenario can be increased. The mission generation unit can also monitor the user's heart rate and electrodermal activity using a biosensor. For example, if the user's heart rate increases, the progress of the scenario can be slowed down. This makes it possible to provide a more adaptive experience by monitoring the user's real-time reactions and dynamically changing the scenario during the mission.

[0068] The mission generation unit can use the emotion estimation function to adjust the difficulty and content of the mission based on the user's emotional state. The mission generation unit, for example, uses the emotion estimation function to analyze the user's emotional state. For example, the mission generation unit can use facial expression recognition technology to analyze the user's facial expression and estimate the emotional state. It can also use voice analysis technology to analyze the tone and speed of the user's voice and estimate the emotional state. It can also use a biosensor to analyze the user's heart rate and electrodermal activity and estimate the emotional state. This makes it possible to provide a more adaptive experience by adjusting the difficulty and content of the mission based on the user's emotional state.

[0069] The mission generation unit can incorporate astronomical phenomena specific to a region by taking into account the user's geographical location information. The mission generation unit, for example, acquires the user's geographical location information from GPS data. For example, if the user is in the Northern Hemisphere, a mission to observe the aurora can be generated. Also, if the user is in the Southern Hemisphere, a mission to observe southern constellations can be generated. Furthermore, astronomical phenomena specific to a region can be incorporated based on the user's geographical location information. In this way, a more realistic experience can be provided by taking into account the user's geographical location information and incorporating astronomical phenomena specific to a region.

[0070] The mission generation unit can use the emotion estimation function to suggest mission themes and storylines according to the user's emotions. The mission generation unit, for example, uses the emotion estimation function to analyze the user's emotional state. For example, the mission generation unit can use facial expression recognition technology to analyze the user's facial expressions and estimate the emotional state. It can also use voice analysis technology to analyze the tone and speed of the user's voice and estimate the emotional state. It can also use a biosensor to analyze the user's heart rate and electrodermal activity and estimate the emotional state. This makes it possible to provide a more personalized experience by suggesting mission themes and storylines according to the user's emotional state.

[0071] The experience providing unit can analyze the user's operation data in real time and provide feedback to support the improvement of piloting skills. The experience providing unit, for example, uses an algorithm with high data processing speed to analyze the user's operation data in real time. For example, when the user makes a piloting error, the experience providing unit presents the correct operation method. It can also provide feedback to support the improvement of piloting skills based on the user's operation data. For example, if the user repeatedly makes mistakes in a particular operation, it can suggest training related to that operation. In this way, by analyzing the user's operation data in real time and providing feedback to support the improvement of piloting skills, it is possible to provide a more effective learning experience.

[0072] The experience providing unit can incorporate data from an actual spacecraft to provide a more realistic piloting experience. For example, the experience providing unit acquires design data and operational data from an actual spacecraft and reflects this in the simulation. For example, the unit incorporates instrument data and operational procedures from the spacecraft into the simulation. The unit can also reflect the operating characteristics and environmental conditions of the spacecraft in the simulation. In this way, by incorporating data from an actual spacecraft, a more realistic piloting experience can be provided.

[0073] The experience providing unit can use the emotion estimation function to adjust the difficulty of the piloting experience based on the user's emotional state and reduce stress. The experience providing unit, for example, uses the emotion estimation function to analyze the user's emotional state. For example, it can use facial expression recognition technology to analyze the user's facial expression and estimate the emotional state. It can also use voice analysis technology to analyze the tone and speed of the user's voice and estimate the emotional state. It can also use a biosensor to analyze the user's heart rate and electrodermal activity and estimate the emotional state. This makes it possible to adjust the difficulty of the piloting experience based on the user's emotional state and reduce stress, thereby providing a more comfortable experience.

[0074] The experience providing unit can introduce cooperative play with other users and enable multiple people to pilot the spaceship. The experience providing unit, for example, provides a mission in which multiple users cooperate to pilot a spaceship. For example, multiple users each take on different roles and cooperate to pilot the spaceship. In addition, a voice chat function can be provided to support communication between users. This allows for cooperative play with other users and enables multiple people to pilot the spaceship, making it possible to provide a more diverse range of experiences.

[0075] The experience providing unit can play music selected by the user in the background to provide a relaxing environment. The experience providing unit, for example, uses music playback technology to play music selected by the user in the background. For example, the user can operate the vehicle while playing their favorite music. It is also possible to clarify the music selection method and playback technology. This allows the user to play music selected by the user in the background to provide a relaxing environment, thereby providing a more comfortable experience.

[0076] The experience providing unit can use the emotion estimation function to propose a piloting mission scenario according to the user's emotion. The experience providing unit, for example, uses the emotion estimation function to analyze the user's emotional state. For example, the experience providing unit can use facial expression recognition technology to analyze the user's facial expression and estimate the emotional state. It can also use voice analysis technology to analyze the tone and speed of the user's voice and estimate the emotional state. It can also use a biosensor to analyze the user's heart rate and electrodermal activity and estimate the emotional state. This makes it possible to provide a more personalized experience by proposing a piloting mission scenario according to the user's emotional state.

[0077] The experience providing unit can track the user's movements with high precision and provide feedback in real time. The experience providing unit can track the user's movements with high precision, for example, using motion capture technology. For example, when the user reaches out and touches the outer wall of the space station, the sensation is fed back. Also, when the user performs a specific action, feedback corresponding to that action can be displayed. Furthermore, by tracking the user's movements in real time and providing feedback, a more realistic experience can be provided. In this way, by tracking the user's movements with high precision and providing feedback in real time, a more realistic experience can be provided.

[0078] The experience providing unit can incorporate data from an actual space station to recreate a more realistic environment. For example, the experience providing unit acquires design data and operational data from an actual space station and reflects this in the simulation. For example, the outer walls and internal structure of the space station can be realistically reproduced. The operating characteristics and environmental conditions of the space station can also be reflected in the simulation. In this way, by incorporating data from an actual space station, a more realistic environment can be recreated.

[0079] The experience providing unit can use the emotion estimation function to adjust the difficulty and content of the swimming experience based on the user's emotional state. The experience providing unit, for example, uses the emotion estimation function to analyze the user's emotional state. For example, the experience providing unit can use facial expression recognition technology to analyze the user's facial expression and estimate the emotional state. It can also use voice analysis technology to analyze the tone and speed of the user's voice and estimate the emotional state. It can also use a biosensor to analyze the user's heart rate and electrodermal activity and estimate the emotional state. This makes it possible to provide a more comfortable experience by adjusting the difficulty and content of the swimming experience based on the user's emotional state.

[0080] The experience providing unit can introduce cooperative play with other users, enabling multiple users to swim together. The experience providing unit can, for example, provide a mission in which multiple users work together to repair a space station. For example, multiple users each take on different roles and work together to repair the space station. A voice chat function can also be provided to support communication between users. This allows for cooperative play with other users and allows multiple users to swim together, making it possible to provide a more diverse experience.

[0081] The experience providing unit can play music selected by the user in the background to provide a relaxing environment. The experience providing unit, for example, uses music playback technology to play music selected by the user in the background. For example, the user can swim while playing their favorite music. It is also possible to clarify the music selection method and playback technology. This allows the user to play music selected by the user in the background to provide a relaxing environment, thereby providing a more comfortable experience.

[0082] The experience providing unit can use the emotion estimation function to propose a swimming mission scenario that corresponds to the user's emotion. The experience providing unit, for example, uses the emotion estimation function to analyze the user's emotional state. For example, the experience providing unit can use facial expression recognition technology to analyze the user's facial expression and estimate the emotional state. It can also use voice analysis technology to analyze the tone and speed of the user's voice and estimate the emotional state. It can also use a biosensor to analyze the user's heart rate and electrodermal activity and estimate the emotional state. This makes it possible to provide a more personalized experience by proposing a swimming mission scenario that corresponds to the user's emotional state.

[0083] The experience providing unit can track the user's movements with high accuracy during the exploration of the alien planet and provide feedback in real time. The experience providing unit can track the user's movements with high accuracy, for example, using motion capture technology. For example, when the user performs a specific action, feedback corresponding to that action is displayed. Furthermore, by tracking the user's movements in real time and providing feedback, a more realistic experience can be provided. In this way, by tracking the user's movements with high accuracy during the exploration of the alien planet and providing feedback in real time, a more realistic experience can be provided.

[0084] The experience providing unit can use the emotion estimation function to adjust the difficulty and content of the exploration experience based on the user's emotional state. The experience providing unit, for example, uses the emotion estimation function to analyze the user's emotional state. For example, the experience providing unit can use facial expression recognition technology to analyze the user's facial expression and estimate the emotional state. It can also use voice analysis technology to analyze the tone and speed of the user's voice and estimate the emotional state. It can also use a biosensor to analyze the user's heart rate and electrodermal activity and estimate the emotional state. This makes it possible to provide a more comfortable experience by adjusting the difficulty and content of the exploration experience based on the user's emotional state.

[0085] The experience providing unit can introduce cooperative play with other users into the alien exploration experience, enabling exploration by multiple people. The experience providing unit, for example, provides a mission in which multiple users cooperate to explore the terrain of an alien planet. For example, multiple users each take on different roles and cooperate to explore the terrain of an alien planet. In addition, a voice chat function can be provided to support communication between users. This allows cooperative play with other users to be introduced into the alien exploration experience, enabling exploration by multiple people, thereby providing a more diverse experience.

[0086] The experience providing unit can play music selected by the user in the background while exploring the alien planet, providing a relaxing environment. The experience providing unit, for example, uses music playback technology to play music selected by the user in the background. For example, the user explores while playing their favorite music. It can also clarify the music selection method and playback technology. This allows the user to play music selected by the user in the background and provide a relaxing environment, providing a more comfortable experience.

[0087] The experience providing unit can use the emotion estimation function to propose an exploration mission scenario that corresponds to the user's emotion. The experience providing unit, for example, uses the emotion estimation function to analyze the user's emotional state. For example, the experience providing unit can use facial expression recognition technology to analyze the user's facial expression and estimate the emotional state. It can also use voice analysis technology to analyze the tone and speed of the user's voice and estimate the emotional state. It can also use a biosensor to analyze the user's heart rate and electrodermal activity and estimate the emotional state. This makes it possible to provide a more personalized experience by proposing an exploration mission scenario that corresponds to the user's emotional state.

[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 experience providing unit can analyze the user's emotional state and provide feedback according to the emotional state. For example, the emotional state of the user can be analyzed using an emotion estimation function. The emotional state can be estimated by analyzing the user's facial expressions using facial expression recognition technology. The emotional state can also be estimated by analyzing the tone and speed of the user's voice using voice analysis technology. Furthermore, the emotional state can be estimated by analyzing the user's heart rate and electrodermal activity using a biosensor. This makes it possible to provide a more personalized experience by providing feedback according to the user's emotional state.

[0090] The experience providing unit can monitor the user's heart rate and electrodermal response and automatically adjust the difficulty of the virtual environment according to the user's stress level. For example, the user's heart rate can be monitored using a heart rate sensor. If the heart rate is high, the difficulty of the virtual environment can be lowered. The user's electrodermal response can also be monitored using an electrodermal sensor. If the electrodermal response is high, the difficulty of the virtual environment can also be lowered. Furthermore, both the heart rate and electrodermal response can be monitored and the difficulty of the virtual environment can be automatically adjusted according to the user's stress level. This makes it possible to provide a more comfortable experience by automatically adjusting the difficulty of the virtual environment according to the user's stress level.

[0091] The experience providing unit can recognize the user's voice and perform settings using voice commands. For example, the user's voice is recognized using voice recognition technology. When the user says "Enter your name," a voice input screen is displayed. Also, when the user says "Proceed to next setting," the user can proceed to the next setting screen. Furthermore, when the user says "Exit," the setting can be finished. This allows for more intuitive operation by recognizing the user's voice and performing settings using voice commands.

[0092] The experience providing unit can capture the user's physical movements and provide an interface for setting up using gesture operations. For example, the user's physical movements can be captured using motion capture technology. When the user waves their hand, they can proceed to the next setting screen. When the user raises their hand, they can also save the settings. Furthermore, when the user lowers their hand, they can also cancel the settings. In this way, by capturing the user's physical movements and providing an interface for setting up using gesture operations, more intuitive operation becomes possible.

[0093] The experience providing unit can propose customization settings according to the user's emotions and provide a more personalized experience. For example, the emotional state of the user is analyzed using an emotion estimation function. The emotional state is estimated by analyzing the user's facial expressions using facial expression recognition technology. The emotional state can also be estimated by analyzing the tone and speed of the user's voice using voice analysis technology. Furthermore, the emotional state can also be estimated by analyzing the user's heart rate and electrodermal activity using a biosensor. This makes it possible to propose customization settings according to the user's emotional state and provide a more personalized experience.

[0094] The mission generation unit can analyze the user's past mission history and optimize the next mission based on the user's individual learning curve. For example, the mission generation unit retrieves the user's past mission history from a database and analyzes it. The unit adjusts the difficulty of the next mission based on data on missions the user has previously succeeded in. The unit can also change the content of the next mission based on data on missions the user has previously failed in. Furthermore, the unit can analyze the user's learning curve and set a goal for the next mission. This makes it possible to provide a more effective learning experience by analyzing the user's past mission history and optimizing the next mission based on the user's individual learning curve.

[0095] The mission generation unit can monitor the user's real-time reactions and dynamically change the scenario during the mission. For example, facial expression recognition technology can be used to monitor the user's real-time reactions. If the user makes a surprised expression, a new event can be added to the scenario. Voice analysis technology can also be used to monitor the tone and speed of the user's voice. If the user makes an excited voice, the difficulty of the scenario can be increased. Furthermore, biosensors can be used to monitor the user's heart rate and electrodermal activity. If the user's heart rate increases, the progress of the scenario can be slowed down. This makes it possible to provide a more adaptive experience by monitoring the user's real-time reactions and dynamically changing the scenario during the mission.

[0096] The mission generation unit can incorporate astronomical phenomena specific to a region, taking into account the user's geographical location information. For example, the user's geographical location information is obtained from GPS data. If the user is in the Northern Hemisphere, a mission to observe the aurora can be generated. If the user is in the Southern Hemisphere, a mission to observe southern constellations can be generated. Furthermore, astronomical phenomena specific to a region can also be incorporated based on the user's geographical location information. In this way, a more realistic experience can be provided by taking into account the user's geographical location information and incorporating astronomical phenomena specific to a region.

[0097] The mission generation unit can use the emotion estimation function to adjust the difficulty and content of the mission based on the user's emotional state. For example, the emotion estimation function can be used to analyze the user's emotional state. Facial expression recognition technology can be used to analyze the user's facial expression and estimate the emotional state. Voice analysis technology can also be used to analyze the tone and speed of the user's voice and estimate the emotional state. Furthermore, a biosensor can be used to analyze the user's heart rate and electrodermal activity and estimate the emotional state. This allows the difficulty and content of the mission to be adjusted based on the user's emotional state, providing a more adaptive experience.

[0098] The experience providing unit can analyze the user's operation data in real time and provide feedback to support the improvement of piloting skills. For example, to analyze the user's operation data in real time, an algorithm with high data processing speed is used. When the user makes a piloting error, the correct operation method is presented. It can also provide feedback to support the improvement of piloting skills based on the user's operation data. If the user repeatedly makes mistakes in a particular operation, it can also suggest training for that operation. In this way, a more effective learning experience can be provided by analyzing the user's operation data in real time and providing feedback to support the improvement of piloting skills.

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

[0100] Step 1: The VR headset captures the user's reactions and selections. For example, it uses eye tracking technology to capture the user's eye movements, gesture recognition technology to capture the user's hand movements, and voice recognition technology to capture the user's voice commands. Step 2: The generative AI analyzes the user's reactions and choices captured by the VR headset. For example, it can use machine learning algorithms to analyze the user's reactions and data mining techniques to analyze the user's choices. It can also use natural language processing techniques to analyze the user's voice commands. Step 3: The mission generation unit generates individual space missions based on the results of the analysis by the generation AI. For example, if the user selects "I'm interested in piloting a spaceship," a mission centered on piloting a spaceship is generated. Also, if the user selects "I'm interested in exploring other planets," a mission centered on exploring other planets can be generated. Furthermore, if the user selects "I'm interested in spacewalks," a mission centered on spacewalks can be generated. Step 4: The experience provider provides the user with the individual space mission generated by the mission generator. For example, it can provide a spacecraft piloting simulation in a VR environment, as well as an alien planet exploration simulation or spacewalk simulation.

[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 type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

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

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

[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. VR headset and Generative AI and a mission generation unit; and an experience provision department. The VR headset is Obtaining user responses and selections; The generated AI is analyzing the user's reactions and selections captured by the VR headset; The mission generation unit generating an individual space mission based on the results analyzed by the generating AI; The experience providing unit providing the individual space mission generated by the mission generation unit to a user; A system characterized by:

2. The mission generation unit Generate a specific space mission based on the user's selections The system of claim 1 .

3. The experience providing unit The user's heart rate and electrodermal response are monitored, and the difficulty of the virtual environment is automatically adjusted according to the user's stress level. The system of claim 1 .

4. The mission generation unit Analyzing the user's past mission history and optimizing the next mission based on the individual learning curve. The system of claim 1 .

5. The experience providing unit Analyzing the user's operation data in real time and providing feedback to support the improvement of piloting skills The system of claim 1 .

6. The experience providing unit Tracking the user's movements with high precision and providing real-time feedback The system of claim 1 .

7. The experience providing unit The alien terrain and environment are generated in real time and dynamically change according to the user's exploration behavior. The system of claim 1 .

8. The experience providing unit Analyzing an emotional state of the user and providing feedback according to the emotional state. The system of claim 1 .

Images