System

Abstract

An object of the system according to the embodiment is to enable a blind person or an extremely weak-sighted person to visually recognize the real world.SOLUTION: A system according to an embodiment includes a glass-type device, a camera, a generation AI, and a virtual reality generation unit. The glass-type device includes a camera. The camera captures a video. The production AI analyzes the video captured by the camera. The virtual reality generator provides the virtual reality generated by the generation AI to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has had the problem that people who are blind or have severe low vision have difficulty visually recognizing the real world.

[0005] The system according to the embodiment aims to enable people who are blind or have severe low vision to visually recognize the real world. [Means for solving the problem]

[0006] A system according to an embodiment includes a glasses-type device, a camera, a generation AI, and a virtual reality generation unit. The glasses-type device includes a camera. The camera captures video. The generation AI analyzes the video captured by the camera. The virtual reality generation unit provides the user with virtual reality generated by the generation AI. [Effects of the Invention]

[0007] The system according to the embodiment can enable people who are blind or have severe low vision to visually perceive the real world. [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 visual support system according to an embodiment of the present invention allows blind or severely visually impaired people to obtain visual information. This system uses a glasses-type device, captures images of the real world with a camera, analyzes the images with a generation AI to generate a virtual reality, and provides the virtual reality to the user. This allows blind or severely visually impaired people to obtain visual information, enabling them to become independent in their daily lives and social activities.

[0029] A visual support system according to an embodiment includes a glasses-type device, a camera, a generation AI, and a virtual reality generation unit. The glasses-type device is worn by individuals who are blind or have severe low vision. The camera is mounted on the glasses-type device and captures images of the real world. For example, the camera has a high resolution and a wide-angle lens. The generation AI analyzes the images captured by the camera and generates a virtual reality. For example, the generation AI uses deep learning technology to recognize objects in the images and reproduce them in a virtual reality space. The virtual reality generation unit provides the virtual reality generated by the generation AI to a user. For example, the virtual reality generation unit uses a VR engine to render the virtual reality in real time and provide visual information to the user. This enables the visual support system to provide visual information to individuals who are blind or have severe low vision, enabling them to become independent in their daily lives and social activities. For example, visually impaired individuals can shop independently and use public transportation. Furthermore, obtaining visual information also enables them to enjoy hobbies and entertainment.

[0030] The camera may be equipped with a sensor that dynamically adjusts the viewing angle in response to the user's head movement. For example, the camera may be equipped with a sensor that detects the user's head movement in real time. For example, a gyro sensor or an acceleration sensor may be used to accurately measure head movement, and the camera's viewing angle may be automatically adjusted based on that data. This allows the camera to provide an optimal field of view in response to the user's head movement. For example, when the user turns to the right, the camera's viewing angle also moves to the right, changing the surrounding scenery. This allows the user to have a natural visual experience.

[0031] Generative AI can recognize objects in real time from images captured by a camera and highlight important information. For example, generative AI uses deep learning technology to recognize objects in real time from images captured by a camera. For example, it uses a convolutional neural network (CNN) to recognize objects in the image with high accuracy and highlight important information. This allows users to quickly grasp the information they need. For example, highlighting important information such as obstacles and signs can help users move safely.

[0032] The generating AI can detect the user's movement speed and direction in real time and adjust the update frequency of the virtual reality accordingly. For example, the generating AI is equipped with an acceleration sensor and a gyro sensor to detect the user's movement speed and direction in real time. For example, if the user walks fast, the update frequency of the virtual reality increases, and if the user walks slowly, the update frequency decreases. This allows the update frequency of the virtual reality to be adjusted according to the user's movement, providing a seamless experience. For example, when the user is running, the virtual reality space is also updated at high speed, and the surrounding scenery changes smoothly.

[0033] The virtual reality generation unit can display avatars of other users, allowing them to jointly experience virtual reality. The virtual reality generation unit, for example, introduces real-time communication technology to display avatars of other users in the virtual reality space. For example, WebRTC can be used to communicate data between users, allowing them to jointly experience virtual reality. This allows users to jointly experience virtual reality, strengthening social connections. For example, a visually impaired person can participate in activities with friends and family in a virtual reality space.

[0034] The virtual reality generation unit can add a navigation function to enable the user to easily reach their destination. The virtual reality generation unit is equipped with, for example, a GPS sensor to add a navigation function to the virtual reality space. For example, the virtual reality generation unit can display a route to the destination based on the user's location information, enabling the user to easily reach the destination. This can enable the user to easily reach the destination. For example, when a visually impaired person uses public transportation, the virtual reality generation unit can provide guidance on the locations of bus stops and stations.

[0035] The virtual reality generation unit can provide real-time navigation information to visually impaired people when they use public transportation. For example, the virtual reality generation unit is equipped with a GPS sensor to provide real-time navigation information to visually impaired people when they use public transportation. For example, the virtual reality generation unit can provide the location of bus stops and train stations based on the user's location information. This allows the visually impaired people to use public transportation by providing real-time navigation information, thereby improving the safety and convenience of their travel. For example, the visually impaired people can accurately determine the location of bus stops and train stations and travel safely.

[0036] The virtual reality generation unit can add an obstacle detection function to the virtual reality space so that the visually impaired person can move around safely. The virtual reality generation unit is equipped with, for example, an ultrasonic sensor to add the obstacle detection function to the virtual reality space so that the visually impaired person can move around safely. For example, the ultrasonic sensor can be used to detect surrounding obstacles and issue a warning to the user. This allows the visually impaired person to move around safely. For example, the visually impaired person can detect and avoid obstacles while walking.

[0037] The virtual reality generation unit can provide an online platform for visually impaired people to access educational and career opportunities. The virtual reality generation unit enhances accessibility functions, for example, by incorporating a text-to-speech function and a magnifying display function. This can promote social participation by providing an online platform for visually impaired people to access educational and career opportunities. For example, the virtual reality generation unit can enable visually impaired people to take online courses and access remote work opportunities.

[0038] The virtual reality generation unit can develop virtual reality content for visually impaired people to enjoy hobbies and entertainment. The virtual reality generation unit, for example, enhances the audio guide function to develop virtual reality content for visually impaired people to enjoy hobbies and entertainment. For example, the virtual reality generation unit provides narration and explanations within the virtual reality space. This can improve the quality of life by providing virtual reality content for visually impaired people to enjoy hobbies and entertainment. For example, the visually impaired can enjoy music or appreciate paintings in the virtual reality space.

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

[0040] The visual assistance system can further include a voice recognition unit. The voice recognition unit analyzes the user's voice commands and assists in operating the system. For example, if the user says, "Tell me about obstacles ahead," the voice recognition unit can analyze the command, identify obstacles ahead from the images captured by the camera, and notify the user by voice. Also, if the user asks, "Where is the next bus stop?", the voice recognition unit can work with the GPS sensor to provide voice guidance on the location of the next bus stop. This allows visually impaired people to operate the system using voice commands and obtain information more intuitively.

[0041] The visual assistance system can also be equipped with a temperature sensor. The temperature sensor measures the ambient temperature in real time and notifies the user. For example, if there is a sudden change in temperature while the user is out, the temperature sensor can detect the change and issue an audio warning to the user. Also, if the indoor temperature exceeds a comfortable range, the temperature sensor can provide that information to the user and prompt them to take appropriate action. This allows visually impaired people to respond quickly to temperature changes and maintain a comfortable environment.

[0042] The visual assistance system may further include a vibration feedback unit. The vibration feedback unit provides information through vibration when the user encounters a specific situation. For example, if the user approaches an obstacle while walking, the vibration feedback unit may generate a vibration to alert the user. Also, when the user approaches a corner during navigation, the vibration feedback unit may notify the user of a turn through vibration. This allows visually impaired people to obtain information through their sense of touch and assists them in traveling safely.

[0043] The visual assistance system can further include an environmental sound analysis unit. The environmental sound analysis unit analyzes surrounding sounds in real time and provides important information to the user. For example, if the unit detects the sound of a car horn or siren, it can analyze the sound and issue an audio warning to the user. It can also analyze public transportation announcements and provide information about the next stop and destination. This allows visually impaired people to efficiently use information about surrounding sounds and travel safely and comfortably.

[0044] The visual assistance system can also be equipped with a health management unit that monitors the user's health condition. The health management unit measures biometric information such as heart rate and blood pressure in real time and notifies the user if an abnormality is detected. For example, if the user's heart rate suddenly increases, the health management unit can analyze the information and encourage the user to rest. It can also periodically record health conditions and support health management in cooperation with medical institutions. This allows visually impaired people to constantly monitor their health condition and take appropriate measures.

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

[0046] Step 1: The glasses are worn by people with blindness or severe low vision. A camera is installed in the glasses to capture images of the real world. For example, the camera has a high resolution and a wide-angle lens. Step 2: The generative AI analyzes the video captured by the camera and generates a virtual reality. For example, the generative AI uses deep learning technology to recognize objects in the video and recreate them in the virtual reality space. Step 3: The virtual reality generator provides the user with the virtual reality generated by the generation AI. For example, the virtual reality generator uses a VR engine to render the virtual reality in real time and provide visual information to the user.

[0047] (Example 2) A visual support system according to an embodiment of the present invention allows blind or severely visually impaired people to obtain visual information. This system uses a glasses-type device, captures images of the real world with a camera, analyzes the images with a generation AI to generate a virtual reality, and provides the virtual reality to the user. This allows blind or severely visually impaired people to obtain visual information, enabling them to become independent in their daily lives and social activities.

[0048] A visual support system according to an embodiment includes a glasses-type device, a camera, a generation AI, and a virtual reality generation unit. The glasses-type device is worn by individuals who are blind or have severe low vision. The camera is mounted on the glasses-type device and captures images of the real world. For example, the camera has a high resolution and a wide-angle lens. The generation AI analyzes the images captured by the camera and generates a virtual reality. For example, the generation AI uses deep learning technology to recognize objects in the images and reproduce them in a virtual reality space. The virtual reality generation unit provides the virtual reality generated by the generation AI to a user. For example, the virtual reality generation unit uses a VR engine to render the virtual reality in real time and provide visual information to the user. This enables the visual support system to provide visual information to individuals who are blind or have severe low vision, enabling them to become independent in their daily lives and social activities. For example, visually impaired individuals can shop independently and use public transportation. Furthermore, obtaining visual information also enables them to enjoy hobbies and entertainment.

[0049] The camera may be equipped with a sensor that dynamically adjusts the viewing angle in response to the user's head movement. For example, the camera may be equipped with a sensor that detects the user's head movement in real time. For example, a gyro sensor or an acceleration sensor may be used to accurately measure head movement, and the camera's viewing angle may be automatically adjusted based on that data. This allows the camera to provide an optimal field of view in response to the user's head movement. For example, when the user turns to the right, the camera's viewing angle also moves to the right, changing the surrounding scenery. This allows the user to have a natural visual experience.

[0050] Generative AI can recognize objects in real time from images captured by a camera and highlight important information. For example, generative AI uses deep learning technology to recognize objects in real time from images captured by a camera. For example, it uses a convolutional neural network (CNN) to recognize objects in the image with high accuracy and highlight important information. This allows users to quickly grasp the information they need. For example, highlighting important information such as obstacles and signs can help users move safely.

[0051] The generating AI can detect the user's movement speed and direction in real time and adjust the update frequency of the virtual reality accordingly. For example, the generating AI is equipped with an acceleration sensor and a gyro sensor to detect the user's movement speed and direction in real time. For example, if the user walks fast, the update frequency of the virtual reality increases, and if the user walks slowly, the update frequency decreases. This allows the update frequency of the virtual reality to be adjusted according to the user's movement, providing a seamless experience. For example, when the user is running, the virtual reality space is also updated at high speed, and the surrounding scenery changes smoothly.

[0052] The virtual reality generation unit can dynamically change the virtual reality scene according to the user's emotions using the emotion estimation function. For example, the virtual reality generation unit uses the emotion estimation function to analyze the user's emotional state in real time and build a system that dynamically changes the virtual reality scene based on the results. For example, if the user is feeling stressed, the scene can be changed to one that helps the user relax. This allows the virtual reality scene to be changed according to the user's emotions, providing a positive experience. For example, when the user feels like relaxing, the virtual reality space can be changed to a natural landscape.

[0053] The virtual reality generation unit can display avatars of other users, allowing them to jointly experience virtual reality. The virtual reality generation unit, for example, introduces real-time communication technology to display avatars of other users in the virtual reality space. For example, WebRTC can be used to communicate data between users, allowing them to jointly experience virtual reality. This allows users to jointly experience virtual reality, strengthening social connections. For example, a visually impaired person can participate in activities with friends and family in a virtual reality space.

[0054] The virtual reality generation unit can add a navigation function to enable the user to easily reach their destination. The virtual reality generation unit is equipped with, for example, a GPS sensor to add a navigation function to the virtual reality space. For example, the virtual reality generation unit can display a route to the destination based on the user's location information, enabling the user to easily reach the destination. This can enable the user to easily reach the destination. For example, when a visually impaired person uses public transportation, the virtual reality generation unit can provide guidance on the locations of bus stops and stations.

[0055] The virtual reality generation unit can use the emotion estimation function to automatically change the virtual reality space to one that is appropriate for a particular emotion when the user expresses that emotion. For example, the virtual reality generation unit can use the emotion estimation function to build a system in which, when the user expresses a particular emotion, the virtual reality space automatically changes to one that is appropriate for that emotion. For example, when the user feels like relaxing, the virtual reality space changes to a natural landscape. This makes it possible to improve the user's experience by dynamically changing the virtual reality space according to the user's emotion. For example, if the user is feeling stressed, the scene can be changed to one that is relaxing.

[0056] The virtual reality generation unit can provide real-time navigation information to visually impaired people when they use public transportation. For example, the virtual reality generation unit is equipped with a GPS sensor to provide real-time navigation information to visually impaired people when they use public transportation. For example, the virtual reality generation unit can provide the location of bus stops and train stations based on the user's location information. This allows the visually impaired people to use public transportation by providing real-time navigation information, thereby improving the safety and convenience of their travel. For example, the visually impaired people can accurately determine the location of bus stops and train stations and travel safely.

[0057] The virtual reality generation unit can add an obstacle detection function to the virtual reality space so that the visually impaired person can move around safely. The virtual reality generation unit is equipped with, for example, an ultrasonic sensor to add the obstacle detection function to the virtual reality space so that the visually impaired person can move around safely. For example, the ultrasonic sensor can be used to detect surrounding obstacles and issue a warning to the user. This allows the visually impaired person to move around safely. For example, the visually impaired person can detect and avoid obstacles while walking.

[0058] The virtual reality generation unit can use the emotion estimation function to provide a relaxing environment for visually impaired people when they feel stressed. The virtual reality generation unit, for example, uses the emotion estimation function to build a system that provides a relaxing environment for visually impaired people when they feel stressed. For example, when a user feels stressed, relaxing music or scenery is provided. This allows the visually impaired people to feel stressed by providing a relaxing environment, thereby reducing their mental burden. For example, when a user feels like relaxing, the virtual reality space changes to a natural landscape.

[0059] The virtual reality generation unit can provide an online platform for visually impaired people to access educational and career opportunities. The virtual reality generation unit enhances accessibility functions, for example, by incorporating a text-to-speech function and a magnifying display function. This can promote social participation by providing an online platform for visually impaired people to access educational and career opportunities. For example, the virtual reality generation unit can enable visually impaired people to take online courses and access remote work opportunities.

[0060] The virtual reality generation unit can develop virtual reality content for visually impaired people to enjoy hobbies and entertainment. The virtual reality generation unit, for example, enhances the audio guide function to develop virtual reality content for visually impaired people to enjoy hobbies and entertainment. For example, the virtual reality generation unit provides narration and explanations within the virtual reality space. This can improve the quality of life by providing virtual reality content for visually impaired people to enjoy hobbies and entertainment. For example, the visually impaired can enjoy music or appreciate paintings in the virtual reality space.

[0061] The virtual reality generation unit can use the emotion estimation function to automatically change the virtual reality space to one that is appropriate for a visually impaired person's specific emotion. For example, the virtual reality generation unit can use the emotion estimation function to build a system in which, when a visually impaired person expresses a specific emotion, the virtual reality space automatically changes to one that is appropriate for that emotion. For example, when a user feels like relaxing, the virtual reality space changes to a natural landscape. This allows the user's experience to be improved by automatically changing the virtual reality space to one that is appropriate for that emotion when the visually impaired person expresses a specific emotion. For example, if the user is feeling stressed, the scene can be changed to one that is relaxing.

[0062] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0063] The visual assistance system can further include a voice recognition unit. The voice recognition unit analyzes the user's voice commands and assists in operating the system. For example, if the user says, "Tell me about obstacles ahead," the voice recognition unit can analyze the command, identify obstacles ahead from the images captured by the camera, and notify the user by voice. Also, if the user asks, "Where is the next bus stop?", the voice recognition unit can work with the GPS sensor to provide voice guidance on the location of the next bus stop. This allows visually impaired people to operate the system using voice commands and obtain information more intuitively.

[0064] The visual assistance system can also be equipped with a temperature sensor. The temperature sensor measures the ambient temperature in real time and notifies the user. For example, if there is a sudden change in temperature while the user is out, the temperature sensor can detect the change and issue an audio warning to the user. Also, if the indoor temperature exceeds a comfortable range, the temperature sensor can provide that information to the user and prompt them to take appropriate action. This allows visually impaired people to respond quickly to temperature changes and maintain a comfortable environment.

[0065] The visual assistance system may further include a vibration feedback unit. The vibration feedback unit provides information through vibration when the user encounters a specific situation. For example, if the user approaches an obstacle while walking, the vibration feedback unit may generate a vibration to alert the user. Also, when the user approaches a corner during navigation, the vibration feedback unit may notify the user of a turn through vibration. This allows visually impaired people to obtain information through their sense of touch and assists them in traveling safely.

[0066] The visual assistance system can further include an environmental sound analysis unit. The environmental sound analysis unit analyzes surrounding sounds in real time and provides important information to the user. For example, if the unit detects the sound of a car horn or siren, it can analyze the sound and issue an audio warning to the user. It can also analyze public transportation announcements and provide information about the next stop and destination. This allows visually impaired people to efficiently use information about surrounding sounds and travel safely and comfortably.

[0067] The visual assistance system can also be equipped with a health management unit that monitors the user's health condition. The health management unit measures biometric information such as heart rate and blood pressure in real time and notifies the user if an abnormality is detected. For example, if the user's heart rate suddenly increases, the health management unit can analyze the information and encourage the user to rest. It can also periodically record health conditions and support health management in cooperation with medical institutions. This allows visually impaired people to constantly monitor their health condition and take appropriate measures.

[0068] The visual assistance system may further include a music providing unit that estimates the user's emotions and selects music based on the estimated emotions. For example, if the user is feeling stressed, the music providing unit may select relaxing music and provide it to the user. Alternatively, if the user feels like cheering up, the music providing unit may select upbeat music. In this way, by providing music that corresponds to the user's emotions, the mental health of visually impaired people can be supported.

[0069] The visual assistance system can further estimate the user's emotions and change the color tone of the virtual reality space based on the estimated emotions. For example, if the user feels like relaxing, the color tone of the virtual reality space can be changed to warm colors to provide a relaxing environment. On the other hand, if the user feels like concentrating, the color tone can be changed to cool colors to provide an environment that is conducive to concentration. This allows the experience of visually impaired people to be improved by changing the color tone according to the user's emotions.

[0070] The visual assistance system can also estimate the user's emotions and change the acoustic environment of the virtual reality space based on the estimated emotions. For example, if the user feels like relaxing, it can add natural sounds or calming music to the virtual reality space. Alternatively, if the user feels like concentrating, it can reduce noise and provide a quiet environment. This can improve the experience of visually impaired people by changing the acoustic environment according to the user's emotions.

[0071] The visual assistance system can also estimate the user's emotions and adjust interactions in the virtual reality space based on the estimated emotions. For example, if the user feels like relaxing, the frequency of interactions can be reduced to provide a calm experience. Alternatively, if the user feels like being active, the frequency of interactions can be increased to provide a lively experience. This can improve the experience for visually impaired people by adjusting interactions according to the user's emotions.

[0072] The visual assistance system can further estimate the user's emotions and adjust the navigation information in the virtual reality space based on the estimated emotions. For example, if the user is stressed, the system can simplify the navigation information to make it easier for the user to understand. Alternatively, if the user is relaxed, the system can provide detailed navigation information to allow the user to obtain more information. This improves the experience of visually impaired people by adjusting the navigation information according to the user's emotions.

[0073] The processing flow of the second embodiment will be briefly explained below.

[0074] Step 1: The glasses are worn by people with blindness or severe low vision. A camera is installed in the glasses to capture images of the real world. For example, the camera has a high resolution and a wide-angle lens. Step 2: The generative AI analyzes the video captured by the camera and generates a virtual reality. For example, the generative AI uses deep learning technology to recognize objects in the video and recreate them in the virtual reality space. Step 3: The virtual reality generator provides the user with the virtual reality generated by the generation AI. For example, the virtual reality generator uses a VR engine to render the virtual reality in real time and provide visual information to the user.

[0075] 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.

[0076] 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.

[0077] 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.

[0078] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0079] 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.

[0080] 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.

[0081] 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.

[0082] 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.

[0083] 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).

[0084] 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.

[0085] 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.

[0086] 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.

[0087] 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.

[0088] 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.

[0089] 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.

[0090] 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.

[0091] 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 AI 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.

[0092] 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.

[0093] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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).

[0099] 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.

[0100] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0101] 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.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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 AI 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.

[0107] 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.

[0108] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0109] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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).

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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 AI 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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).

[0128] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[0129] 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."

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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]

[0142] 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. Equipped with a glass-type device, a camera mounted on the glass-type device; A generation AI that analyzes the video captured by the camera; a virtual reality generation unit that provides a user with the virtual reality generated by the generation AI. A system characterized by:

2. The camera is Equipped with a sensor that dynamically adjusts the viewing angle according to the user's head movements 2. The system of claim 1.

3. The generated AI is The camera performs real-time object recognition on the images captured by the camera and highlights important information.

2. The system of claim 1.

4. The generated AI is Detects the user's movement speed and direction in real time and adjusts the frequency of virtual reality updates accordingly 2. The system of claim 1.

5. The virtual reality generation unit Dynamically changing a virtual reality scene according to user emotions 2. The system of claim 1.

6. The virtual reality generation unit You can view other users' avatars and experience virtual reality together.

2. The system of claim 1.

7. The virtual reality generation unit Providing real-time navigation information for visually impaired people using public transport 2. The system of claim 1.

8. The virtual reality generation unit Providing a relaxing environment for visually impaired people when they feel stressed 2. The system of claim 1.

Images