System

Abstract

An object of a system according to an embodiment is to enable a visually impaired person to efficiently acquire visual information.SOLUTION: A system according to an embodiment includes a sunglasses type apparatus, a camera, a generation AI, and a headphone. The sunglasses device captures visual information. The camera captures visual information. The production AI analyzes and verbalizes the visual information captured by the camera. The headphone reads the information verbalized by the generated AI as voice.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 it is difficult for visually impaired people to efficiently acquire visual information.

[0005] The system according to the embodiment aims to enable visually impaired people to efficiently acquire visual information. [Means for solving the problem]

[0006] A system according to an embodiment includes a sunglasses-type device, a camera, a generation AI, and headphones. The sunglasses-type device captures visual information. The camera captures visual information. The generation AI analyzes and verbalizes the visual information captured by the camera. The headphones read out the information verbalized by the generation AI as audio. [Effects of the Invention]

[0007] The system according to the embodiment can enable a visually impaired person to efficiently acquire visual information. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) The visual information reading system according to an embodiment of the present invention is a system in which a visually impaired person wears a sunglasses-type device, captures visual information with a camera, and a generating AI analyzes and verbalizes the information, which is then read aloud through headphones built into the ears. This allows the visually impaired person to enjoy visual information as audio.

[0029] A visual information reading-out system according to an embodiment includes a sunglasses-type device, a camera, a generation AI, and headphones. The sunglasses-type device is worn by a visually impaired person and has a built-in camera that captures visual information. For example, by simply wearing the sunglasses, the camera captures visual information such as a book, painting, picture book, or manga in front of the person. The camera captures the visual information at high resolution and sends it to the generation AI. The generation AI analyzes and verbalizes the visual information captured by the sunglasses-type device's camera. For example, the generation AI converts the visual information into text data using a text generation AI (e.g., LLM). The generation AI can also analyze and verbalize the visual information using a multimodal generation AI. The generation AI analyzes the content of the visual information and converts it into text data using an image recognition algorithm. The headphones read out the information verbalized by the generation AI as audio. For example, the headphones generate audio data based on the text data analyzed by the generation AI and read it out as audio from speakers built into the earpiece. This allows even visually impaired people to understand the contents of a book. The headphones use speech synthesis technology to generate natural audio and provide it to the user. For example, headphones use speech synthesis technology to convert text data into natural speech and provide it to the user. This allows the visual information reading system according to the embodiment to allow visually impaired people to enjoy visual information as audio. For example, by simply wearing a sunglasses-type device, the contents of a book can be heard aloud. Furthermore, the contents of paintings, picture books, and manga can also be enjoyed as audio, allowing for a richer experience of visual information.

[0030] The sunglasses-type device uses a built-in microphone to collect surrounding environmental sounds, and the generation AI can analyze the environmental sounds and explain them to the user. The sunglasses-type device uses a built-in microphone to collect surrounding environmental sounds. For example, the sunglasses-type device can capture the sounds of cars and people talking in the city, and the generation AI can analyze the sounds and explain them to the user. The generation AI can use a voice recognition algorithm to analyze the environmental sounds and explain them to the user. For example, the sunglasses-type device can capture the sounds of cars and people talking in the city, and the generation AI can analyze the sounds and explain them to the user. This makes it possible to provide not only visual information but also auditory information.

[0031] The sunglasses-type device is equipped with a temperature sensor and a humidity sensor, and the generation AI can analyze the data collected by the sensors and notify the user. The sunglasses-type device is equipped with a temperature sensor and a humidity sensor to measure the ambient temperature and humidity in real time. For example, a temperature sensor is installed in the sunglasses-type device to measure the ambient temperature in real time. The generation AI analyzes the data collected by the sensors and notifies the user of the current temperature and humidity by voice. For example, the generation AI analyzes the data collected by the temperature sensor and a humidity sensor to notify the user of the current temperature and humidity by voice. This makes it possible to notify the user of the ambient temperature and humidity in real time. For example, it notifies the user of changes in temperature when the user is out. This makes it possible to notify the user of the ambient temperature and humidity in real time.

[0032] The sunglasses-type device is equipped with a GPS function, and the generation AI can analyze information about the current location and destination obtained by the GPS function and provide it to the user by voice. The sunglasses-type device is equipped with a GPS function, allowing the user to obtain information about the current location and destination by voice. For example, the sunglasses-type device is equipped with a GPS function, allowing the user to check their current location by voice. The generation AI analyzes information about the current location and destination obtained by the GPS function and provides it to the user by voice. For example, the generation AI analyzes information about the current location and destination obtained by the GPS function and provides it to the user by voice. This allows the user to obtain information about the current location and destination by voice. For example, it supports navigation in a city. This allows the user to obtain information about the current location and destination by voice.

[0033] The sunglasses-type device is equipped with a facial recognition function, and the generation AI can analyze information acquired by the facial recognition function to enable the user to identify acquaintances and family members. The sunglasses-type device is equipped with a facial recognition function to enable the user to identify acquaintances and family members. For example, the sunglasses-type device is equipped with a facial recognition function to enable the user to identify acquaintances and family members. The generation AI analyzes the information acquired by the facial recognition function to enable the user to identify acquaintances and family members. For example, the generation AI analyzes the information acquired by the facial recognition function to enable the user to identify acquaintances and family members. This allows the user to identify acquaintances and family members. For example, when the user meets an acquaintance on the street, the device notifies the user by voice. This allows the user to identify acquaintances and family members.

[0034] A generative AI can analyze video captured by a camera in real time, track the movement of objects, and verbalize that movement to communicate it to the user. A generative AI can analyze video captured by a camera in real time and track the movement of objects. For example, a generative AI can analyze video captured by a camera in real time and track the movement of objects. A generative AI can verbalize the movement of objects and communicate it to the user. For example, a generative AI can analyze video captured by a camera in real time, track the movement of objects, and verbalize that movement to communicate it to the user. This makes it possible to track the movement of objects in real time, verbalize that movement, and communicate it to the user. For example, a generative AI can analyze the movements of players in a sporting event, verbalize that movement, and communicate it to the user. This makes it possible to track the movement of objects in real time, verbalize that movement, and communicate it to the user.

[0035] A generative AI can simultaneously analyze multiple pieces of visual information captured by a camera, integrate relevant information, and provide it to the user. A generative AI can simultaneously analyze multiple pieces of visual information captured by a camera, integrate relevant information, and provide it to the user. For example, a generative AI can simultaneously analyze multiple pieces of visual information captured by a camera, integrate relevant information, and provide it to the user. This makes it possible to simultaneously analyze multiple pieces of visual information, integrate relevant information, and provide it to the user. For example, a generative AI can analyze multiple pages of a book, and provide related content together to the user. This makes it possible to simultaneously analyze multiple pieces of visual information, integrate relevant information, and provide it to the user.

[0036] The generation AI can refer to the user's past visual information history and provide related information. The generation AI can refer to the user's past visual information history and provide related information. For example, the generation AI can refer to the user's past visual information history and provide related information. The generation AI can refer to the user's past visual information history and provide related information. For example, the generation AI can refer to the user's past visual information history and provide related information. This makes it possible to refer to the user's past visual information history and provide related information. For example, based on the contents of books previously read, related information about a book currently being read is provided. This makes it possible to refer to the user's past visual information history and provide related information.

[0037] When performing voice reading, the generation AI can automatically adjust the tone and speed of the voice according to the user's preferences. When performing voice reading, the generation AI automatically adjusts the tone and speed of the voice according to the user's preferences. For example, the generation AI analyzes the user's past voice reading history and automatically adjusts the tone and speed of the voice according to the user's preferences. The generation AI automatically adjusts the tone and speed of the voice according to the user's preferences. For example, the generation AI analyzes the user's past voice reading history and automatically adjusts the tone and speed of the voice according to the user's preferences. This makes it possible to automatically adjust the tone and speed of the voice according to the user's preferences. For example, the generation AI learns the user's preferred tone and speed and reflects them in the next reading. This makes it possible to automatically adjust the tone and speed of the voice according to the user's preferences.

[0038] When performing a voice readout, the generation AI can add background music and sound effects to provide a more realistic audio experience. When performing a voice readout, the generation AI can add background music and sound effects. For example, when the generation AI performs a voice readout, background music is added. The generation AI can add background music and sound effects to provide a more realistic audio experience. For example, when the generation AI performs a voice readout, background music is added to provide a more realistic audio experience. This allows for the addition of background music and sound effects to provide a more realistic audio experience. For example, playing music that matches the scene in the story enhances the sense of realism. This allows for the addition of background music and sound effects to provide a more realistic audio experience.

[0039] When performing a voice readout, the generation AI can collect user feedback in real time and improve the content of the readout based on that feedback. When performing a voice readout, the generation AI collects user feedback in real time. For example, when the generation AI performs a voice readout, it collects user feedback in real time. The generation AI improves the content of the readout based on that feedback. For example, when the generation AI performs a voice readout, it collects user feedback in real time and improves the content of the readout based on that feedback. This allows the generation AI to collect user feedback in real time and improve the content of the readout based on that feedback. For example, this responds to a case where a user requests that the reading speed be slowed down. This allows the generation AI to collect user feedback in real time and improve the content of the readout based on that feedback.

[0040] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0041] The visual information reading system can also be equipped with a vibration feedback function to support the user's walking. For example, a vibration motor built into a sunglasses-type device can vibrate to warn the user when they approach an obstacle. This allows the user to understand their surroundings through tactile information as well as visual information. It is also possible to inform the user of the type and distance of an obstacle by changing the vibration intensity and pattern. Furthermore, vibration feedback can also be used to indicate when the user should proceed in a specific direction, serving as a navigation aid.

[0042] The visual information reading system can also be equipped with a blood pressure measurement function to monitor the user's health condition. For example, a blood pressure sensor built into a sunglasses-type device can periodically measure the user's blood pressure, and the generating AI can analyze the data and notify the user. This allows the user to understand their own health condition in real time. If an abnormal blood pressure value is detected, the generating AI can also issue a warning and suggest necessary measures. Furthermore, blood pressure data can be shared with medical institutions and used as part of remote medical consultations.

[0043] The visual information reading system can also be equipped with a nutritional information provision function to support the user's dietary management. For example, a camera built into a sunglasses-type device captures the food the user is eating, and the generating AI analyzes the image to provide nutritional information. This allows the user to understand the nutritional balance of their meal in real time. The generating AI can also provide dietary advice based on the user's health condition and goals. It can also record dietary history to help with long-term health management.

[0044] The visual information reading system can also be equipped with fitness functions to support the user's exercise. For example, an acceleration sensor built into a sunglasses-type device measures the user's exercise volume, and the generating AI analyzes the data to provide exercise advice. This allows the user to understand their own exercise habits in real time. The generating AI can also suggest exercise plans based on the user's goals. Furthermore, exercise data can be shared with medical institutions and used as part of health management.

[0045] The visual information reading system can also be equipped with educational functions to support the user's learning. For example, a camera built into a sunglasses-type device can capture the learning material the user is studying, and the generation AI can analyze the content and explain it aloud. This allows the user to progress through learning not only through visual information but also through auditory information. The generation AI can also provide additional explanations and practice questions based on the user's level of understanding. Furthermore, the learning history can be recorded and used to help with long-term learning planning.

[0046] The visual information reading system can also be equipped with a translation function to support user communication. For example, a microphone built into a sunglasses-type device can capture foreign language conversations the user hears, and the generation AI can translate the content in real time and provide it as audio. This allows the user to understand the foreign language conversation. The generation AI can also translate what the user says into the foreign language and convey it to the other person. It can also record translation history and refer to past conversation content.

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

[0048] Step 1: The sunglasses-type device is worn by the visually impaired and has a built-in camera that captures visual information. For example, just by putting on the sunglasses, the camera captures visual information from books, paintings, picture books, manga, and other objects in front of the user. Step 2: The camera captures visual information in high resolution and sends it to the generative AI. Step 3: The generative AI analyzes and verbalizes the visual information captured by the sunglasses device's camera. For example, the generative AI converts the visual information into text data using a text generation AI (e.g., LLM). The generative AI can also analyze and verbalize the visual information using a multimodal generative AI. The generative AI uses an image recognition algorithm to analyze the content of the visual information and convert it into text data. Step 4: The headphones read out the information verbalized by the generative AI as audio. For example, the headphones generate audio data based on the text data analyzed by the generative AI and read it out as audio from speakers built into the earpiece. This allows even visually impaired people to understand the contents of the book. The headphones use speech synthesis technology to generate natural-sounding audio and provide it to the user. For example, the headphones use speech synthesis technology to convert text data into natural-sounding audio and provide it to the user.

[0049] (Example 2) The visual information reading system according to an embodiment of the present invention is a system in which a visually impaired person wears a sunglasses-type device, captures visual information with a camera, and a generating AI analyzes and verbalizes the information, which is then read aloud through headphones built into the ears. This allows the visually impaired person to enjoy visual information as audio.

[0050] A visual information reading-out system according to an embodiment includes a sunglasses-type device, a camera, a generation AI, and headphones. The sunglasses-type device is worn by a visually impaired person and has a built-in camera that captures visual information. For example, by simply wearing the sunglasses, the camera captures visual information such as a book, painting, picture book, or manga in front of the person. The camera captures the visual information at high resolution and sends it to the generation AI. The generation AI analyzes and verbalizes the visual information captured by the sunglasses-type device's camera. For example, the generation AI converts the visual information into text data using a text generation AI (e.g., LLM). The generation AI can also analyze and verbalize the visual information using a multimodal generation AI. The generation AI analyzes the content of the visual information and converts it into text data using an image recognition algorithm. The headphones read out the information verbalized by the generation AI as audio. For example, the headphones generate audio data based on the text data analyzed by the generation AI and read it out as audio from speakers built into the earpiece. This allows even visually impaired people to understand the contents of a book. The headphones use speech synthesis technology to generate natural audio and provide it to the user. For example, headphones use speech synthesis technology to convert text data into natural speech and provide it to the user. This allows the visual information reading system according to the embodiment to allow visually impaired people to enjoy visual information as audio. For example, by simply wearing a sunglasses-type device, the contents of a book can be heard aloud. Furthermore, the contents of paintings, picture books, and manga can also be enjoyed as audio, allowing for a richer experience of visual information.

[0051] The sunglasses-type device uses a built-in microphone to collect surrounding environmental sounds, and the generation AI can analyze the environmental sounds and explain them to the user. The sunglasses-type device uses a built-in microphone to collect surrounding environmental sounds. For example, the sunglasses-type device can capture the sounds of cars and people talking in the city, and the generation AI can analyze the sounds and explain them to the user. The generation AI can use a voice recognition algorithm to analyze the environmental sounds and explain them to the user. For example, the sunglasses-type device can capture the sounds of cars and people talking in the city, and the generation AI can analyze the sounds and explain them to the user. This makes it possible to provide not only visual information but also auditory information.

[0052] The sunglasses-type device is equipped with a temperature sensor and a humidity sensor, and the generation AI can analyze the data collected by the sensors and notify the user. The sunglasses-type device is equipped with a temperature sensor and a humidity sensor to measure the ambient temperature and humidity in real time. For example, a temperature sensor is installed in the sunglasses-type device to measure the ambient temperature in real time. The generation AI analyzes the data collected by the sensors and notifies the user of the current temperature and humidity by voice. For example, the generation AI analyzes the data collected by the temperature sensor and a humidity sensor to notify the user of the current temperature and humidity by voice. This makes it possible to notify the user of the ambient temperature and humidity in real time. For example, it notifies the user of changes in temperature when the user is out. This makes it possible to notify the user of the ambient temperature and humidity in real time.

[0053] The sunglasses-type device measures the user's heart rate and electrodermal response with a built-in sensor, and the generation AI analyzes the data to estimate the user's emotional state and provide relaxation music if the user is under high stress. The sunglasses-type device measures the user's heart rate and electrodermal response with a built-in sensor. For example, the sunglasses-type device measures the user's heart rate and electrodermal response with a built-in sensor, and the generation AI analyzes the data to estimate the user's emotional state. The generation AI analyzes the data to estimate the user's emotional state and provides relaxation music if the user is under high stress. For example, the generation AI analyzes heart rate and electrodermal response data to estimate the user's emotional state and provides relaxation music if the user is under high stress. This makes it possible to monitor the user's emotional state in real time and provide music to reduce stress. For example, the sunglasses-type device measures the user's heart rate and electrodermal response, and provides relaxation music if the user is under high stress. This makes it possible to monitor the user's emotional state in real time and provide music to reduce stress.

[0054] The sunglasses-type device is equipped with a GPS function, and the generation AI can analyze information about the current location and destination obtained by the GPS function and provide it to the user by voice. The sunglasses-type device is equipped with a GPS function, allowing the user to obtain information about the current location and destination by voice. For example, the sunglasses-type device is equipped with a GPS function, allowing the user to check their current location by voice. The generation AI analyzes information about the current location and destination obtained by the GPS function and provides it to the user by voice. For example, the generation AI analyzes information about the current location and destination obtained by the GPS function and provides it to the user by voice. This allows the user to obtain information about the current location and destination by voice. For example, it supports navigation in a city. This allows the user to obtain information about the current location and destination by voice.

[0055] The sunglasses-type device is equipped with a facial recognition function, and the generation AI can analyze information acquired by the facial recognition function to enable the user to identify acquaintances and family members. The sunglasses-type device is equipped with a facial recognition function to enable the user to identify acquaintances and family members. For example, the sunglasses-type device is equipped with a facial recognition function to enable the user to identify acquaintances and family members. The generation AI analyzes the information acquired by the facial recognition function to enable the user to identify acquaintances and family members. For example, the generation AI analyzes the information acquired by the facial recognition function to enable the user to identify acquaintances and family members. This allows the user to identify acquaintances and family members. For example, when the user meets an acquaintance on the street, the device notifies the user by voice. This allows the user to identify acquaintances and family members.

[0056] A generative AI can analyze video captured by a camera in real time, track the movement of objects, and verbalize that movement to communicate it to the user. A generative AI can analyze video captured by a camera in real time and track the movement of objects. For example, a generative AI can analyze video captured by a camera in real time and track the movement of objects. A generative AI can verbalize the movement of objects and communicate it to the user. For example, a generative AI can analyze video captured by a camera in real time, track the movement of objects, and verbalize that movement to communicate it to the user. This makes it possible to track the movement of objects in real time, verbalize that movement, and communicate it to the user. For example, a generative AI can analyze the movements of players in a sporting event, verbalize that movement, and communicate it to the user. This makes it possible to track the movement of objects in real time, verbalize that movement, and communicate it to the user.

[0057] A generative AI can simultaneously analyze multiple pieces of visual information captured by a camera, integrate relevant information, and provide it to the user. A generative AI can simultaneously analyze multiple pieces of visual information captured by a camera, integrate relevant information, and provide it to the user. For example, a generative AI can simultaneously analyze multiple pieces of visual information captured by a camera, integrate relevant information, and provide it to the user. This makes it possible to simultaneously analyze multiple pieces of visual information, integrate relevant information, and provide it to the user. For example, a generative AI can analyze multiple pages of a book, and provide related content together to the user. This makes it possible to simultaneously analyze multiple pieces of visual information, integrate relevant information, and provide it to the user.

[0058] Generative AI can analyze the emotions of people in images captured by a camera and provide an explanation based on those emotions. Generative AI can analyze the emotions of people in images captured by a camera and provide an explanation based on those emotions. For example, generative AI can analyze the facial expressions of people in images captured by a camera and estimate their emotions. Generative AI can provide an explanation based on those emotions. For example, generative AI can analyze the emotions of people in images captured by a camera and provide an explanation based on those emotions. This makes it possible to analyze the emotions of people in images and provide an explanation based on those emotions. For example, it can analyze the emotions of characters in a picture book and provide an explanation based on those emotions. This makes it possible to analyze the emotions of people in images and provide an explanation based on those emotions.

[0059] The generation AI can refer to the user's past visual information history and provide related information. The generation AI can refer to the user's past visual information history and provide related information. For example, the generation AI can refer to the user's past visual information history and provide related information. The generation AI can refer to the user's past visual information history and provide related information. For example, the generation AI can refer to the user's past visual information history and provide related information. This makes it possible to refer to the user's past visual information history and provide related information. For example, based on the contents of books previously read, related information about a book currently being read is provided. This makes it possible to refer to the user's past visual information history and provide related information.

[0060] The generation AI can analyze the user's facial expression, infer their emotions in response to specific visual information, and provide information based on those emotions. The generation AI analyzes the user's facial expression, infer their emotions in response to specific visual information. For example, the generation AI analyzes the user's facial expression, infer their emotions in response to specific visual information, and provide information based on those emotions. For example, the generation AI analyzes the user's facial expression, infer their emotions in response to specific visual information, and provide information based on those emotions. This makes it possible to provide information based on the user's emotions. For example, it can analyze their emotions in response to a picture book story, and provide information based on those emotions. This makes it possible to provide information based on the user's emotions.

[0061] When performing voice reading, the generation AI can automatically adjust the tone and speed of the voice according to the user's preferences. When performing voice reading, the generation AI automatically adjusts the tone and speed of the voice according to the user's preferences. For example, the generation AI analyzes the user's past voice reading history and automatically adjusts the tone and speed of the voice according to the user's preferences. The generation AI automatically adjusts the tone and speed of the voice according to the user's preferences. For example, the generation AI analyzes the user's past voice reading history and automatically adjusts the tone and speed of the voice according to the user's preferences. This makes it possible to automatically adjust the tone and speed of the voice according to the user's preferences. For example, the generation AI learns the user's preferred tone and speed and reflects them in the next reading. This makes it possible to automatically adjust the tone and speed of the voice according to the user's preferences.

[0062] When performing voice reading, the generation AI adjusts the tone and content of the voice according to the user's emotional state, allowing for more empathetic reading. When performing voice reading, the generation AI adjusts the tone and content of the voice according to the user's emotional state. For example, the generation AI analyzes the user's emotional state and adjusts the tone of the voice according to that state. The generation AI adjusts the tone and content of the voice according to the user's emotional state, allowing for more empathetic reading. For example, the generation AI analyzes the user's emotional state and adjusts the tone of the voice according to that state, allowing for more empathetic reading. This allows for more empathetic reading by adjusting the tone and content of the voice according to the user's emotional state. For example, if the user is sad, the AI ​​will read in a gentle tone. This allows for more empathetic reading by adjusting the tone and content of the voice according to the user's emotional state.

[0063] When performing a voice readout, the generation AI can add background music and sound effects to provide a more realistic audio experience. When performing a voice readout, the generation AI can add background music and sound effects. For example, when the generation AI performs a voice readout, background music is added. The generation AI can add background music and sound effects to provide a more realistic audio experience. For example, when the generation AI performs a voice readout, background music is added to provide a more realistic audio experience. This allows for the addition of background music and sound effects to provide a more realistic audio experience. For example, playing music that matches the scene in the story enhances the sense of realism. This allows for the addition of background music and sound effects to provide a more realistic audio experience.

[0064] When performing a voice readout, the generation AI can collect user feedback in real time and improve the content of the readout based on that feedback. When performing a voice readout, the generation AI collects user feedback in real time. For example, when the generation AI performs a voice readout, it collects user feedback in real time. The generation AI improves the content of the readout based on that feedback. For example, when the generation AI performs a voice readout, it collects user feedback in real time and improves the content of the readout based on that feedback. This allows the generation AI to collect user feedback in real time and improve the content of the readout based on that feedback. For example, this responds to a case where a user requests that the reading speed be slowed down. This allows the generation AI to collect user feedback in real time and improve the content of the readout based on that feedback.

[0065] The generation AI can analyze the user's emotional state, estimate the emotion in response to specific voice content, and adjust the voice content based on that emotion. The generation AI analyzes the user's emotional state and estimates the emotion in response to specific voice content. For example, the generation AI analyzes the user's emotional state and estimates the emotion in response to specific voice content. The generation AI adjusts the voice content based on that emotion. For example, the generation AI analyzes the user's emotional state, estimates the emotion in response to specific voice content, and adjusts the voice content based on that emotion. This makes it possible to adjust the voice content based on the user's emotion. For example, if the user is moved, voice content based on that emotion is provided. This makes it possible to adjust the voice content based on the user's emotion.

[0066] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0067] The visual information reading system can also be equipped with a vibration feedback function to support the user's walking. For example, a vibration motor built into a sunglasses-type device can vibrate to warn the user when they approach an obstacle. This allows the user to understand their surroundings through tactile information as well as visual information. It is also possible to inform the user of the type and distance of an obstacle by changing the vibration intensity and pattern. Furthermore, vibration feedback can also be used to indicate when the user should proceed in a specific direction, serving as a navigation aid.

[0068] The visual information reading system can also be equipped with a blood pressure measurement function to monitor the user's health condition. For example, a blood pressure sensor built into a sunglasses-type device can periodically measure the user's blood pressure, and the generating AI can analyze the data and notify the user. This allows the user to understand their own health condition in real time. If an abnormal blood pressure value is detected, the generating AI can also issue a warning and suggest necessary measures. Furthermore, blood pressure data can be shared with medical institutions and used as part of remote medical consultations.

[0069] The visual information reading system can also analyze the user's emotional state and provide appropriate advice based on the estimated emotions. For example, if the generating AI analyzes the user's facial expressions and voice tone and the user feels stressed, it can suggest deep breathing techniques or simple stretches for relaxation. If the user feels happy, it can also provide positive messages to further enhance that emotion. Furthermore, it can recommend content that the user may be interested in based on their emotional state.

[0070] The visual information reading system can also be equipped with a nutritional information provision function to support the user's dietary management. For example, a camera built into a sunglasses-type device captures the food the user is eating, and the generating AI analyzes the image to provide nutritional information. This allows the user to understand the nutritional balance of their meal in real time. The generating AI can also provide dietary advice based on the user's health condition and goals. It can also record dietary history to help with long-term health management.

[0071] The visual information reading system can also analyze the user's emotional state and recommend appropriate music based on the estimated emotion. For example, if the generation AI analyzes the user's facial expression and vocal tone and the user wants to relax, it can recommend relaxing music. If the user is feeling energetic, it can also recommend upbeat music. Furthermore, it can recommend new songs based on the user's past favorite music, depending on the user's emotional state.

[0072] The visual information reading system can also be equipped with fitness functions to support the user's exercise. For example, an acceleration sensor built into a sunglasses-type device measures the user's exercise volume, and the generating AI analyzes the data to provide exercise advice. This allows the user to understand their own exercise habits in real time. The generating AI can also suggest exercise plans based on the user's goals. Furthermore, exercise data can be shared with medical institutions and used as part of health management.

[0073] The visual information reading system can also analyze the user's emotional state and provide appropriate feedback based on the estimated emotion. For example, if the generating AI analyzes the user's facial expression and voice tone and the user feels anxious, it can provide a message to reassure them. If the user feels excited, it can also provide advice to calm them down. Furthermore, it can provide new advice based on the user's past feedback depending on the emotional state.

[0074] The visual information reading system can also be equipped with educational functions to support the user's learning. For example, a camera built into a sunglasses-type device can capture the learning material the user is studying, and the generation AI can analyze the content and explain it aloud. This allows the user to progress through learning not only through visual information but also through auditory information. The generation AI can also provide additional explanations and practice questions based on the user's level of understanding. Furthermore, the learning history can be recorded and used to help with long-term learning planning.

[0075] The visual information reading system can also analyze the user's emotional state and provide appropriate reminders based on the estimated emotion. For example, the generative AI can analyze the user's facial expressions and voice tone and, if the user is tired, remind them to take a break. It can also provide advice on how to maintain concentration if the user is concentrating. Furthermore, it can provide new reminders based on the user's previously set reminders, depending on the user's emotional state.

[0076] The visual information reading system can also be equipped with a translation function to support user communication. For example, a microphone built into a sunglasses-type device can capture foreign language conversations the user hears, and the generation AI can translate the content in real time and provide it as audio. This allows the user to understand the foreign language conversation. The generation AI can also translate what the user says into the foreign language and convey it to the other person. It can also record translation history and refer to past conversation content.

[0077] The processing flow of the second embodiment will be briefly explained below.

[0078] Step 1: The sunglasses-type device is worn by the visually impaired and has a built-in camera that captures visual information. For example, just by putting on the sunglasses, the camera captures visual information from books, paintings, picture books, manga, and other objects in front of the user. Step 2: The camera captures visual information in high resolution and sends it to the generative AI. Step 3: The generative AI analyzes and verbalizes the visual information captured by the sunglasses device's camera. For example, the generative AI converts the visual information into text data using a text generation AI (e.g., LLM). The generative AI can also analyze and verbalize the visual information using a multimodal generative AI. The generative AI uses an image recognition algorithm to analyze the content of the visual information and convert it into text data. Step 4: The headphones read out the information verbalized by the generative AI as audio. For example, the headphones generate audio data based on the text data analyzed by the generative AI and read it out as audio from speakers built into the earpiece. This allows even visually impaired people to understand the contents of the book. The headphones use speech synthesis technology to generate natural-sounding audio and provide it to the user. For example, the headphones use speech synthesis technology to convert text data into natural-sounding audio and provide it to the user.

[0079] 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.

[0080] 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.

[0081] 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.

[0082] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0083] 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.

[0084] 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.

[0085] 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.

[0086] 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.

[0087] 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).

[0088] 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.

[0089] 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.

[0090] 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.

[0091] 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.

[0092] 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.

[0093] 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.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0098] 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.

[0099] 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.

[0100] 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.

[0101] 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.

[0102] 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).

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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).

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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).

[0132] 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.

[0133] 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."

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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]

[0146] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A sunglasses-type device, a camera for capturing visual information; A generation AI that analyzes and verbalizes the visual information captured by the camera; headphones that read out the information verbalized by the generation AI as a voice; A system characterized by:

2. The sunglasses-type device comprises: It uses a built-in microphone to collect ambient sounds, The generated AI is Analyze the environmental sound and explain it to the user 2. The system of claim 1.

3. The sunglasses-type device comprises: Equipped with GPS functionality, The generated AI is The information about the current location and destination obtained by the GPS function is analyzed and provided to the user by voice.

2. The system of claim 1.

4. The generated AI is When reading aloud, automatically adjust the tone and speed of the voice according to the user's preferences.

2. The system of claim 1.

5. The sunglasses-type device comprises: Built-in sensors measure the user's heart rate and skin electrical response, The generated AI is Analyze the data to estimate the user's emotional state, Provide relaxation music when stress levels are high 2. The system of claim 1.

6. The generated AI is Analyzes the emotions of people in images captured by the camera and provides explanations based on those emotions.

2. The system of claim 1.

7. The generated AI is Analyzes the user's facial expressions, estimates their emotions in response to specific visual information, and provides information based on those emotions.

2. The system of claim 1.

8. The generated AI is Analyze the user's emotional state, estimate their emotions in response to specific audio content, and adjust the audio content based on those emotions.

2. The system of claim 1.

Images