system

Abstract

The system according to the embodiment aims to enable people with visual or hearing impairments to properly recognize information about their surroundings. [Solution] A system according to an embodiment includes a camera unit, an audio output unit, a microphone unit, and a character display unit. The camera unit recognizes surrounding visual information. The audio output unit reads out the visual information recognized by the camera unit. The microphone unit recognizes surrounding audio information. The character display unit converts the audio information recognized by the microphone unit into text and displays it.

Description

[Technical Field]

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

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

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

[0004] Conventional technologies have had the problem that it is difficult for people with visual or hearing impairments to properly recognize information about their surroundings.

[0005] The system according to the embodiment aims to enable people with visual or hearing impairments to properly recognize information about their surroundings. [Means for solving the problem]

[0006] The system according to the embodiment includes a camera unit, an audio output unit, a microphone unit, and a character display unit. The camera unit recognizes surrounding visual information. The audio output unit reads out the visual information recognized by the camera unit. The microphone unit recognizes surrounding audio information. The character display unit converts the audio information recognized by the microphone unit into text and displays it. [Effects of the Invention]

[0007] The system according to the embodiment can enable people with visual or hearing impairments to properly recognize information about their surroundings. [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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[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 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

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

[0028] (Example 1) A smart glasses system according to an embodiment of the present invention is a system for use by visually impaired or hearing impaired individuals. This smart glasses system includes a camera unit that recognizes surrounding visual information, an audio output unit that reads out the visual information recognized by the camera unit, a microphone unit that recognizes surrounding audio information, and a text display unit that converts the audio information recognized by the microphone unit into text and displays it. For example, when used by a visually impaired individual, the smart glasses use a camera to recognize surrounding visual information and read that information out loud. For example, it can communicate route directions, text on signs, and the movements of people in the vicinity by audio. Next, when used by a hearing impaired individual, the smart glasses use a microphone to recognize surrounding audio information and convert that information into text and display it. For example, it can display the content of conversations, surrounding sounds, and warning sounds as text. First, when used by a visually impaired individual, the smart glasses use a camera to recognize surrounding visual information. In this case, the camera captures surrounding images at high resolution and analyzes the visual information using image processing technology. For example, it can recognize text on signs, route directions, and the movements of people in the vicinity. Next, the recognized visual information is converted into audio using speech synthesis technology. Smart glasses communicate visual information to users via audio through built-in speakers. For example, they can provide voice guidance such as "There is a crosswalk ahead" or "Turn right." Meanwhile, when used by hearing-impaired people, smart glasses use microphones to recognize surrounding audio information. The microphones capture surrounding sounds with high sensitivity and analyze the audio information using voice recognition technology. For example, they can recognize conversations, warning sounds, and ambient sounds. The recognized audio information is converted into text and displayed on the smart glasses' display. For example, text information such as "Hello, how are you?" or "Caution, a car is approaching" can be displayed. This mechanism allows blind and hearing-impaired people to accurately grasp information about their surroundings and live safely and comfortably. This smart glasses system allows blind and hearing-impaired people to accurately grasp information about their surroundings and live safely and comfortably.

[0029] A smart glasses system according to an embodiment includes a camera unit, an audio output unit, a microphone unit, and a text display unit. The camera unit recognizes surrounding visual information. For example, the camera unit captures surrounding video at high resolution and analyzes the visual information using image processing technology. For example, the camera unit can recognize text on signs, road signs, and the movements of people in the vicinity. For example, the camera unit can capture video at 1080p resolution and analyze the visual information using image processing technology such as edge detection, face recognition, and object detection. The audio output unit reads out the visual information recognized by the camera unit. For example, the audio output unit converts the visual information into audio using speech synthesis technology and transmits the audio to the user through a built-in speaker. For example, the audio output unit can provide audio guidance such as "There is a crosswalk ahead" or "Turn right." For example, the audio output unit can convert the visual information into audio using text-to-speech (TTS) technology and transmit the audio to the user. The microphone unit recognizes surrounding audio information. The microphone unit, for example, captures surrounding sounds with high sensitivity and analyzes the audio information using voice recognition technology. For example, the microphone unit can recognize the content of conversations, warning sounds, and surrounding environmental sounds. For example, the microphone unit can capture sounds with a sensitivity of -40 dB and analyze the audio information using deep learning-based voice recognition technology. The text display unit converts the audio information recognized by the microphone unit into text and displays it on the smart glasses' display. For example, the text display unit can display text information such as "Hello, how are you?" or "Caution, a car is approaching." For example, the text display unit can display text information with high resolution on the smart glasses' display to convey it to the user. As a result, the smart glasses system according to the embodiment enables visually impaired and hearing impaired people to appropriately grasp information about their surroundings and live safely and comfortably.

[0030] The camera unit can capture surrounding video at a specific resolution (e.g., 1080p) and analyze the visual information using image processing technology. The camera unit captures surrounding video at a resolution of, for example, 1080p. For example, the camera unit can obtain detailed visual information by capturing high-resolution video. The camera unit also analyzes the visual information using image processing technology. For example, the camera unit can detect the contours of an object using edge detection technology and analyze the visual information. The camera unit can also recognize a person's face using face recognition technology and analyze the visual information. Furthermore, the camera unit can recognize a specific object using object detection technology and analyze the visual information. In this way, the camera unit can provide more detailed information by analyzing the visual information at high resolution. Some or all of the above-described processing in the camera unit may be performed using, for example, AI, or may be performed without using AI. For example, the camera unit can input the acquired video data to a generation AI and have the generation AI analyze the visual information.

[0031] The audio output unit can convert visual information into audio using audio synthesis technology and communicate it to the user through a built-in speaker. The audio output unit can convert visual information into audio using, for example, audio synthesis technology. For example, the audio output unit can convert visual information into audio using text-to-speech (TTS) technology and communicate it to the user. The audio output unit can also generate more natural audio using audio modeling technology. For example, the audio output unit can generate audio based on visual information and communicate it to the user through a built-in speaker. In this way, the audio output unit can effectively communicate visual information by audio using audio synthesis technology. Some or all of the above-mentioned processing in the audio output unit can be performed using, for example, AI, or can be performed without using AI. For example, the audio output unit can input visual information to a generation AI and have the generation AI generate audio.

[0032] The microphone unit can capture ambient sounds at a specific sensitivity (e.g., -40 dB) and analyze the audio information using voice recognition technology. The microphone unit captures ambient sounds at a sensitivity of, for example, -40 dB. For example, by using a high-sensitivity microphone, the microphone unit can capture ambient sounds in detail. The microphone unit also analyzes the audio information using voice recognition technology. For example, the microphone unit can analyze ambient audio information using deep learning-based voice recognition technology. The microphone unit can also recognize specific keywords using keyword spotting technology. For example, the microphone unit can analyze ambient audio information and recognize the content of conversations, warning sounds, and environmental sounds. As a result, the microphone unit can provide more detailed audio information by analyzing the audio information at high sensitivity. Some or all of the above-described processing in the microphone unit may be performed using, for example, AI, or may be performed without using AI. For example, the microphone unit can input the acquired audio data to a generation AI and have the generation AI analyze the audio information.

[0033] The character display unit can convert the recognized voice information into text and display it on the smart glasses' display. The character display unit can, for example, convert the recognized voice information into text. For example, the character display unit can convert voice information into text using voice recognition technology and display it on the smart glasses' display. The character display unit can also adjust the font and size of the text to improve visibility. For example, the character display unit can display text information in high resolution on the smart glasses' display and convey it to the user. By converting voice information into text and displaying it, the character display unit can make it easier for hearing-impaired people to understand the information. Some or all of the above-mentioned processing in the character display unit can be performed using, for example, AI, or can be performed without AI. For example, the character display unit can input recognized voice data to a generation AI and have the generation AI generate text information.

[0034] The camera unit can learn the user's behavioral patterns based on the recognized visual information and select the optimal timing for capturing images. The camera unit, for example, learns the user's behavioral patterns based on the recognized visual information. For example, the camera unit can learn the user's behavioral patterns using a machine learning algorithm. The camera unit can also collect user behavioral data using a data collection method and learn the user's behavioral patterns. The camera unit then selects the optimal timing for capturing images based on the learned behavioral patterns. For example, the camera unit can learn the user's frequent walking route and automatically start capturing images at important points. The camera unit can also learn the user's habit of stopping at specific locations and capture detailed visual information at those times. Furthermore, the camera unit can set the camera to automatically start capturing images when the user performs a specific action. In this way, the camera unit can learn the user's behavioral patterns and capture visual information at the optimal timing. Some or all of the above-described processing in the camera unit may be performed using, for example, AI, or may be performed without using AI. For example, the camera unit can input user behavior data into the generation AI and have the generation AI select the optimal timing for taking a photo.

[0035] The camera unit can add a filtering function that prioritizes capturing specific objects or people based on the visual information it recognizes. The camera unit, for example, prioritizes capturing specific objects or people based on the visual information it recognizes. For example, the camera unit can recognize a specific person using facial recognition technology and automatically capture that person when they come into view. The camera unit can also prioritize capturing specific objects (e.g., signs or road signs) using an object detection algorithm. Furthermore, the camera unit can prioritize capturing a specific action (e.g., waving) when a user performs that action. This allows the camera unit to prioritize capturing specific objects or people, thereby ensuring that important information is not missed. Some or all of the above-described processing in the camera unit may be performed using, for example, AI, or may be performed without AI. For example, the camera unit can input visual information to a generation AI and have the generation AI perform filtering of specific objects or people.

[0036] The camera unit can prioritize capturing highly relevant information based on the recognized visual information and taking into account the user's geographical location information. The camera unit, for example, considers the user's geographical location information based on the recognized visual information. For example, the camera unit can acquire the user's geographical location information using GPS data and prioritize capturing highly relevant visual information based on that information. For example, when the user is in a tourist spot, the camera unit can prioritize capturing tourist attractions and information boards. Furthermore, when the user is in a commercial facility, the camera unit can prioritize capturing store signs and sale information. Furthermore, when the user is using public transportation, the camera unit can prioritize capturing station names and bus stop information. In this way, the camera unit can provide highly relevant information to the user by taking into account the geographical location information. Some or all of the above-described processing in the camera unit may be performed using, for example, AI, or may be performed without using AI. For example, the camera unit can input geographical location information to a generation AI and cause the generation AI to select highly relevant information.

[0037] The camera unit can analyze the user's social media activity based on the recognized visual information and capture related visual information. The camera unit can, for example, analyze the user's social media activity based on the recognized visual information. For example, the camera unit can analyze the content of social media posts and capture related visual information based on the content frequently posted by the user. If the user is participating in a specific event, the camera unit can also capture visual information related to the event. Furthermore, if the user uses a specific hashtag, the camera unit can also capture visual information related to the hashtag. In this way, the camera unit can provide visual information that is highly relevant to the user by analyzing the social media activity. Some or all of the above-described processing in the camera unit may be performed using, for example, AI, or may be performed without using AI. For example, the camera unit can input social media data into a generation AI and cause the generation AI to select related visual information.

[0038] The voice output unit can provide optimal voice guidance by referring to the user's past voice guidance history based on the generated voice. The voice output unit, for example, can refer to the user's past voice guidance history based on the generated voice. For example, the voice output unit can store the user's past voice guidance history using a database and provide optimal voice guidance based on that history. The voice output unit can also provide optimal voice guidance based on the user's preferred voice guidance tone and speed in the past. Furthermore, the voice output unit can provide optimal voice guidance based on routes and places the user has frequently used in the past. For example, the voice output unit can provide voice guidance tailored to a specific situation based on the user's past voice guidance history. As a result, the voice output unit can provide optimal voice guidance for the user by referring to the past voice guidance history. Some or all of the above-described processing in the voice output unit may be performed using, for example, AI, or may be performed without using AI. For example, the voice output unit can input past voice guidance history data into a generation AI and cause the generation AI to provide optimal voice guidance.

[0039] The audio output unit can provide customized audio guidance for a specific situation based on the generated audio. The audio output unit can provide customized audio guidance for a specific situation based on the generated audio, for example. For example, when a user is in a tourist spot, the audio output unit can provide audio guidance including an explanation of a tourist attraction. Furthermore, when a user is in a commercial facility, the audio output unit can provide audio guidance including store information and sales information. Furthermore, when a user is using public transportation, the audio output unit can provide audio guidance including station names and bus stop information. This allows the audio output unit to provide more useful information to the user by providing audio guidance tailored to the specific situation. Some or all of the above-described processing in the audio output unit can be performed using, for example, AI, or without AI. For example, the audio output unit can input situation data to a generation AI and cause the generation AI to provide customized audio guidance.

[0040] The voice output unit can provide optimal voice guidance based on the generated voice, taking into account the user's geographical location information. The voice output unit, for example, considers the user's geographical location information based on the generated voice. For example, the voice output unit can acquire the user's geographical location information using GPS data and provide optimal voice guidance based on that information. For example, when the user is in a tourist spot, the voice output unit can provide voice guidance including an explanation of tourist attractions. Furthermore, when the user is in a commercial facility, the voice output unit can provide voice guidance including store information and sales information. Furthermore, when the user is using public transportation, the voice output unit can provide voice guidance including station names and bus stop information. In this way, the voice output unit can provide voice guidance that is highly relevant to the user by taking into account the geographical location information. Some or all of the above-described processing in the voice output unit may be performed using, for example, AI, or may be performed without using AI. For example, the voice output unit can input geographical location information to a generation AI and cause the generation AI to provide optimal voice guidance.

[0041] The audio output unit can analyze the user's social media activity based on the generated audio and provide related audio guidance. The audio output unit can, for example, analyze the user's social media activity based on the generated audio. For example, the audio output unit can analyze the content of social media posts and provide related audio guidance based on the user's frequent posts. If the user is participating in a specific event, the audio output unit can also provide audio guidance related to the event. Furthermore, if the user uses a specific hashtag, the audio output unit can provide audio guidance related to the hashtag. In this way, the audio output unit can provide audio guidance that is highly relevant to the user by analyzing the social media activity. Some or all of the above-described processing in the audio output unit can be performed using, for example, AI, or can be performed without using AI. For example, the audio output unit can input social media data to a generation AI and cause the generation AI to provide related audio guidance.

[0042] The microphone unit can learn a user's behavioral patterns based on the recognized voice information and select the optimal timing for voice capture. The microphone unit, for example, learns a user's behavioral patterns based on the recognized voice information. For example, the microphone unit can learn a user's behavioral patterns using a machine learning algorithm. The microphone unit can also collect user behavioral data using a data collection method and learn the user's behavioral patterns. Next, the microphone unit selects the optimal timing for voice capture based on the learned behavioral patterns. For example, the microphone unit can learn the time periods when the user frequently converses and increase the sensitivity of the microphone during those time periods. The microphone unit can also learn the user's habit of conversing in a specific location and prioritize voice capture in that location. Furthermore, the microphone unit can be set to automatically start voice capture when the user performs a specific action. In this way, the microphone unit can learn the user's behavioral patterns and capture voice information at the optimal timing. Some or all of the above-described processing in the microphone unit may be performed using, for example, AI or without AI. For example, the microphone unit can input user behavior data into the generation AI and have the generation AI select the optimal timing for voice capture.

[0043] The microphone unit can add a filtering function that prioritizes capturing specific sounds and voices based on the recognized audio information. The microphone unit, for example, prioritizes capturing specific sounds and voices based on the recognized audio information. For example, the microphone unit can recognize the voice of a specific person using a voice recognition algorithm and automatically capture that person's voice when it is heard. The microphone unit can also prioritize capturing specific sounds (e.g., warning sounds). Furthermore, the microphone unit can prioritize capturing sounds when a user performs a specific action (e.g., clapping). In this way, the microphone unit prioritizes capturing specific sounds and voices so that important information is not missed. Some or all of the above-described processing in the microphone unit may be performed using, for example, AI, or may be performed without AI. For example, the microphone unit can input audio data to a generation AI and have the generation AI filter out specific sounds and voices.

[0044] The microphone unit can prioritize capturing highly relevant voice information based on the recognized voice information, taking into account the user's geographical location information. The microphone unit, for example, considers the user's geographical location information based on the recognized voice information. For example, the microphone unit can acquire the user's geographical location information using GPS data and prioritize capturing highly relevant voice information based on that information. For example, when the user is in a tourist spot, the microphone unit can prioritize capturing voice information including descriptions of tourist attractions. Furthermore, when the user is in a commercial facility, the microphone unit can prioritize capturing voice information including store guides and sales information. Furthermore, when the user is using public transportation, the microphone unit can prioritize capturing voice information including station names and bus stop guides. In this way, the microphone unit can provide highly relevant voice information to the user by taking into account the geographical location information. Some or all of the above-described processing in the microphone unit may be performed using, for example, AI, or may be performed without using AI. For example, the microphone unit can input geographical location information to a generation AI and cause the generation AI to select highly relevant voice information.

[0045] The microphone unit can analyze the user's social media activities based on the recognized voice information and capture related voice information. The microphone unit can, for example, analyze the user's social media activities based on the recognized voice information. For example, the microphone unit can analyze the content of social media posts and capture related voice information based on the content frequently posted by the user. In addition, if the user is participating in a specific event, the microphone unit can capture voice information related to the event. Furthermore, if the user uses a specific hashtag, the microphone unit can capture voice information related to the hashtag. In this way, the microphone unit can provide highly relevant voice information to the user by analyzing social media activities. Some or all of the above-described processing in the microphone unit may be performed using, for example, AI, or may be performed without using AI. For example, the microphone unit can input social media data into a generation AI and cause the generation AI to select related voice information.

[0046] The character display unit can refer to the user's past display history based on the character information to be displayed and provide an optimal display method. The character display unit, for example, refers to the user's past display history based on the character information to be displayed. For example, the character display unit can store the user's past display history using a database and provide an optimal display method based on that history. The character display unit can also provide an optimal display method based on the user's preferred fonts and sizes in the past. Furthermore, the character display unit can provide an optimal display method based on information that the user has frequently displayed in the past. For example, the character display unit can provide a display method suited to a specific situation based on the user's past display history. In this way, the character display unit can provide an optimal display method for the user by referring to the past display history. Some or all of the above-described processing in the character display unit may be performed using, for example, AI, or may be performed without AI. For example, the character display unit can input past display history data to a generation AI and cause the generation AI to provide an optimal display method.

[0047] The character display unit can provide a customized display method according to a specific situation based on the displayed character information. The character display unit can provide a customized display method according to a specific situation based on the displayed character information, for example. For example, when the user is in a tourist spot, the character display unit can provide a display method including an explanation of tourist attractions. Furthermore, when the user is in a commercial facility, the character display unit can provide a display method including store guides and sale information. Furthermore, when the user is using public transportation, the character display unit can provide a display method including station names and bus stop guides. In this way, the character display unit can provide more useful information to the user by providing a display method according to a specific situation. Some or all of the above-described processing in the character display unit can be performed using, for example, AI, or can be performed without using AI. For example, the character display unit can input situation data to a generation AI and cause the generation AI to provide a customized display method.

[0048] The character display unit can provide an optimal display method based on the displayed character information, taking into account the user's geographical location information. The character display unit, for example, considers the user's geographical location information based on the displayed character information. For example, the character display unit can acquire the user's geographical location information using GPS data and provide an optimal display method based on that information. For example, if the user is in a tourist spot, the character display unit can provide a display method including an explanation of tourist attractions. Furthermore, if the user is in a commercial facility, the character display unit can provide a display method including store information and sale information. Furthermore, if the user is using public transportation, the character display unit can provide a display method including station names and bus stop information. In this way, the character display unit can provide information that is highly relevant to the user by taking into account the geographical location information. Some or all of the above-described processing in the character display unit may be performed using, for example, AI, or may be performed without using AI. For example, the character display unit can input geographical location information to a generation AI and cause the generation AI to provide an optimal display method.

[0049] The text display unit can analyze the user's social media activity based on the displayed text information and display related text information. The text display unit can, for example, analyze the user's social media activity based on the displayed text information. For example, the text display unit can analyze the content of social media posts and display related text information based on the content frequently posted by the user. Furthermore, if the user is participating in a specific event, the text display unit can display text information related to the event. Furthermore, if the user uses a specific hashtag, the text display unit can display text information related to the hashtag. In this way, the text display unit can provide highly relevant information to the user by analyzing social media activity. Some or all of the above-described processing in the text display unit can be performed using, for example, AI, or without AI. For example, the text display unit can input social media data to a generation AI and cause the generation AI to display related text information.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The smart glasses system may further include a vibration feedback unit. The vibration feedback unit may vibrate to notify the user when the user encounters a specific situation. For example, when the user approaches a pedestrian crossing, the vibration feedback unit may generate a slight vibration to alert the user. When the user approaches a dangerous location, the vibration feedback unit may generate a strong vibration to warn the user. Furthermore, when the user reaches a specific destination, the vibration feedback unit may generate a short vibration to notify the user of arrival. This allows the smart glasses system to provide information to the user using tactile senses in addition to visual and auditory senses.

[0052] The smart glasses system may further include a temperature sensor unit. The temperature sensor unit can detect the ambient temperature and provide appropriate information to the user. For example, the temperature sensor unit can issue a warning to the user if the outside temperature changes suddenly. The temperature sensor unit can also display a message urging the user to take appropriate measures if the user is in an environment where there is a risk of heatstroke. Furthermore, the temperature sensor unit can also urge the user to take measures to protect themselves from the cold when used in cold regions. In this way, the smart glasses system can use temperature information to improve the safety and comfort of the user.

[0053] The smart glasses system may further include a heart rate sensor unit. The heart rate sensor unit can monitor the user's heart rate and issue a warning if an abnormality is detected. For example, the heart rate sensor unit can display a message encouraging the user to relax if the user's heart rate suddenly increases. The heart rate sensor unit can also provide guidance for the user to maintain an appropriate heart rate during exercise. Furthermore, the heart rate sensor unit can suggest relaxation methods if the user is feeling stressed. This allows the smart glasses system to monitor the user's health condition in real time and provide appropriate advice.

[0054] The smart glasses system may further include a location information sharing unit. The location information sharing unit may share the user's current location in real time. For example, the location information sharing unit may ensure safety by allowing the user to share their location information with family and friends. The location information sharing unit may also enable the user to quickly request rescue if they become lost. Furthermore, the location information sharing unit may also share their location information with other participants when the user participates in a specific event or gathering. In this way, the smart glasses system may utilize the user's location information to improve safety and convenience.

[0055] The smart glasses system may further include a gesture recognition unit. The gesture recognition unit may recognize the movements of the user's hands or fingers and execute specific operations. For example, the gesture recognition unit may pause audio guidance when the user waves their hand. The gesture recognition unit may also scroll text display when the user slides their finger. The gesture recognition unit may also start capturing images with the camera when the user performs a specific gesture. This allows the smart glasses system to realize intuitive operations using the user's gestures.

[0056] The processing flow of the first embodiment will be briefly explained below.

[0057] Step 1: The camera unit recognizes the surrounding visual information. The camera unit captures the surrounding video at high resolution and analyzes the visual information using image processing technology. For example, it can recognize the characters on signs, road signs, and the movements of people in the surrounding area. The camera unit captures video at 1080p resolution and analyzes the visual information using image processing technology such as edge detection, face recognition, and object detection. Step 2: The voice output unit reads out the visual information recognized by the camera unit. The voice output unit converts the visual information into voice using speech synthesis technology and communicates it to the user through the built-in speaker. For example, it can provide voice guidance such as "There is a crosswalk ahead" or "Turn right." The voice output unit can convert the visual information into voice using text-to-speech (TTS) technology and communicate it to the user. Step 3: The microphone recognizes surrounding audio information. The microphone captures surrounding sounds with high sensitivity and analyzes the audio information using voice recognition technology. For example, it can recognize the content of conversations, warning sounds, and surrounding environmental sounds. The microphone captures sounds with a sensitivity of -40dB and can analyze the audio information using deep learning-based voice recognition technology. Step 4: The character display unit converts the voice information recognized by the microphone unit into text and displays it on the smart glasses' display. For example, it can display text information such as "Hello, how are you?" or "Caution, a car is approaching." The character display unit can display the text information in high resolution on the smart glasses' display and communicate it to the user.

[0058] (Example 2) A smart glasses system according to an embodiment of the present invention is a system for use by visually impaired or hearing impaired individuals. This smart glasses system includes a camera unit that recognizes surrounding visual information, an audio output unit that reads out the visual information recognized by the camera unit, a microphone unit that recognizes surrounding audio information, and a text display unit that converts the audio information recognized by the microphone unit into text and displays it. For example, when used by a visually impaired individual, the smart glasses use a camera to recognize surrounding visual information and read that information out loud. For example, it can communicate route directions, text on signs, and the movements of people in the vicinity by audio. Next, when used by a hearing impaired individual, the smart glasses use a microphone to recognize surrounding audio information and convert that information into text and display it. For example, it can display the content of conversations, surrounding sounds, and warning sounds as text. First, when used by a visually impaired individual, the smart glasses use a camera to recognize surrounding visual information. In this case, the camera captures surrounding images at high resolution and analyzes the visual information using image processing technology. For example, it can recognize text on signs, route directions, and the movements of people in the vicinity. Next, the recognized visual information is converted into audio using speech synthesis technology. Smart glasses communicate visual information to users via audio through built-in speakers. For example, they can provide voice guidance such as "There is a crosswalk ahead" or "Turn right." Meanwhile, when used by hearing-impaired people, smart glasses use microphones to recognize surrounding audio information. The microphones capture surrounding sounds with high sensitivity and analyze the audio information using voice recognition technology. For example, they can recognize conversations, warning sounds, and ambient sounds. The recognized audio information is converted into text and displayed on the smart glasses' display. For example, text information such as "Hello, how are you?" or "Caution, a car is approaching" can be displayed. This mechanism allows blind and hearing-impaired people to accurately grasp information about their surroundings and live safely and comfortably. This smart glasses system allows blind and hearing-impaired people to accurately grasp information about their surroundings and live safely and comfortably.

[0059] A smart glasses system according to an embodiment includes a camera unit, an audio output unit, a microphone unit, and a text display unit. The camera unit recognizes surrounding visual information. For example, the camera unit captures surrounding video at high resolution and analyzes the visual information using image processing technology. For example, the camera unit can recognize text on signs, road signs, and the movements of people in the vicinity. For example, the camera unit can capture video at 1080p resolution and analyze the visual information using image processing technology such as edge detection, face recognition, and object detection. The audio output unit reads out the visual information recognized by the camera unit. For example, the audio output unit converts the visual information into audio using speech synthesis technology and transmits the audio to the user through a built-in speaker. For example, the audio output unit can provide audio guidance such as "There is a crosswalk ahead" or "Turn right." For example, the audio output unit can convert the visual information into audio using text-to-speech (TTS) technology and transmit the audio to the user. The microphone unit recognizes surrounding audio information. The microphone unit, for example, captures surrounding sounds with high sensitivity and analyzes the audio information using voice recognition technology. For example, the microphone unit can recognize the content of conversations, warning sounds, and surrounding environmental sounds. For example, the microphone unit can capture sounds with a sensitivity of -40 dB and analyze the audio information using deep learning-based voice recognition technology. The text display unit converts the audio information recognized by the microphone unit into text and displays it on the smart glasses' display. For example, the text display unit can display text information such as "Hello, how are you?" or "Caution, a car is approaching." For example, the text display unit can display text information with high resolution on the smart glasses' display to convey it to the user. As a result, the smart glasses system according to the embodiment enables visually impaired and hearing impaired people to appropriately grasp information about their surroundings and live safely and comfortably.

[0060] The camera unit can capture surrounding video at a specific resolution (e.g., 1080p) and analyze the visual information using image processing technology. The camera unit captures surrounding video at a resolution of, for example, 1080p. For example, the camera unit can obtain detailed visual information by capturing high-resolution video. The camera unit also analyzes the visual information using image processing technology. For example, the camera unit can detect the contours of an object using edge detection technology and analyze the visual information. The camera unit can also recognize a person's face using face recognition technology and analyze the visual information. Furthermore, the camera unit can recognize a specific object using object detection technology and analyze the visual information. In this way, the camera unit can provide more detailed information by analyzing the visual information at high resolution. Some or all of the above-described processing in the camera unit may be performed using, for example, AI, or may be performed without using AI. For example, the camera unit can input the acquired video data to a generation AI and have the generation AI analyze the visual information.

[0061] The audio output unit can convert visual information into audio using audio synthesis technology and communicate it to the user through a built-in speaker. The audio output unit can convert visual information into audio using, for example, audio synthesis technology. For example, the audio output unit can convert visual information into audio using text-to-speech (TTS) technology and communicate it to the user. The audio output unit can also generate more natural audio using audio modeling technology. For example, the audio output unit can generate audio based on visual information and communicate it to the user through a built-in speaker. In this way, the audio output unit can effectively communicate visual information by audio using audio synthesis technology. Some or all of the above-mentioned processing in the audio output unit can be performed using, for example, AI, or can be performed without using AI. For example, the audio output unit can input visual information to a generation AI and have the generation AI generate audio.

[0062] The microphone unit can capture ambient sounds at a specific sensitivity (e.g., -40 dB) and analyze the audio information using voice recognition technology. The microphone unit captures ambient sounds at a sensitivity of, for example, -40 dB. For example, by using a high-sensitivity microphone, the microphone unit can capture ambient sounds in detail. The microphone unit also analyzes the audio information using voice recognition technology. For example, the microphone unit can analyze ambient audio information using deep learning-based voice recognition technology. The microphone unit can also recognize specific keywords using keyword spotting technology. For example, the microphone unit can analyze ambient audio information and recognize the content of conversations, warning sounds, and environmental sounds. As a result, the microphone unit can provide more detailed audio information by analyzing the audio information at high sensitivity. Some or all of the above-described processing in the microphone unit may be performed using, for example, AI, or may be performed without using AI. For example, the microphone unit can input the acquired audio data to a generation AI and have the generation AI analyze the audio information.

[0063] The character display unit can convert the recognized voice information into text and display it on the smart glasses' display. The character display unit can, for example, convert the recognized voice information into text. For example, the character display unit can convert voice information into text using voice recognition technology and display it on the smart glasses' display. The character display unit can also adjust the font and size of the text to improve visibility. For example, the character display unit can display text information in high resolution on the smart glasses' display and convey it to the user. By converting voice information into text and displaying it, the character display unit can make it easier for hearing-impaired people to understand the information. Some or all of the above-mentioned processing in the character display unit can be performed using, for example, AI, or can be performed without AI. For example, the character display unit can input recognized voice data to a generation AI and have the generation AI generate text information.

[0064] The camera unit can estimate the user's emotions and automatically adjust the camera's shooting angle based on the estimated user's emotions. The camera unit, for example, estimates the user's emotions. For example, the camera unit can estimate the user's emotions using facial expression recognition technology. The camera unit can also estimate the user's emotions using voice analysis technology. Furthermore, the camera unit can estimate the user's emotions using biometrics technology. Next, the camera unit automatically adjusts the camera's shooting angle based on the estimated user's emotions. For example, if the user is nervous, the camera unit can widen the camera's shooting angle to capture more surrounding information. If the user is relaxed, the camera unit can narrow the camera's shooting angle to focus on a specific subject. Furthermore, if the user is in a hurry, the camera unit can dynamically adjust the camera's shooting angle to prioritize capturing important information. This allows the camera unit to provide more appropriate visual information by adjusting the camera's shooting angle according to the user's emotions. Some or all of the above-described processing in the camera unit may be performed using, for example, AI or without AI. For example, the camera unit can input the user's emotional data into the generation AI and have the generation AI adjust the camera's shooting angle.

[0065] The camera unit can learn the user's behavioral patterns based on the recognized visual information and select the optimal timing for capturing images. The camera unit, for example, learns the user's behavioral patterns based on the recognized visual information. For example, the camera unit can learn the user's behavioral patterns using a machine learning algorithm. The camera unit can also collect user behavioral data using a data collection method and learn the user's behavioral patterns. The camera unit then selects the optimal timing for capturing images based on the learned behavioral patterns. For example, the camera unit can learn the user's frequently walked route and automatically start capturing images at important points. The camera unit can also learn the user's habit of stopping at specific locations and capture detailed visual information at those times. Furthermore, the camera unit can set the camera to automatically start capturing images when the user performs a specific action. In this way, the camera unit can learn the user's behavioral patterns and capture visual information at the optimal timing. Some or all of the above-described processing in the camera unit may be performed using, for example, AI, or may be performed without using AI. For example, the camera unit can input user behavior data into the generation AI and have the generation AI select the optimal timing for taking a photo.

[0066] The camera unit can add a filtering function that prioritizes capturing specific objects or people based on the visual information it recognizes. The camera unit, for example, prioritizes capturing specific objects or people based on the visual information it recognizes. For example, the camera unit can recognize a specific person using facial recognition technology and automatically capture that person when they come into view. The camera unit can also prioritize capturing specific objects (e.g., signs or road signs) using an object detection algorithm. Furthermore, the camera unit can prioritize capturing a specific action (e.g., waving) when a user performs that action. This allows the camera unit to prioritize capturing specific objects or people, thereby ensuring that important information is not missed. Some or all of the above-described processing in the camera unit may be performed using, for example, AI, or may be performed without AI. For example, the camera unit can input visual information to a generation AI and have the generation AI perform filtering of specific objects or people.

[0067] The camera unit can estimate the user's emotions and automatically adjust the camera resolution based on the estimated user emotions. The camera unit, for example, estimates the user's emotions. For example, the camera unit can estimate the user's emotions using facial expression recognition technology. The camera unit can also estimate the user's emotions using voice analysis technology. Furthermore, the camera unit can estimate the user's emotions using biometrics technology. Next, the camera unit automatically adjusts the camera resolution based on the estimated user emotions. For example, if the user is nervous, the camera unit can increase the camera resolution to capture more detailed information. If the user is relaxed, the camera unit can also decrease the camera resolution to reduce battery consumption. Furthermore, if the user is in a hurry, the camera unit can dynamically adjust the camera resolution to prioritize capturing important information. In this way, the camera unit can provide more appropriate visual information by adjusting the camera resolution according to the user's emotions. Some or all of the above-described processing in the camera unit may be performed using, for example, AI or without AI. For example, the camera unit can input the user's emotional data into the generation AI and have the generation AI adjust the camera resolution.

[0068] The camera unit can prioritize capturing highly relevant information based on the recognized visual information and taking into account the user's geographical location information. The camera unit, for example, considers the user's geographical location information based on the recognized visual information. For example, the camera unit can acquire the user's geographical location information using GPS data and prioritize capturing highly relevant visual information based on that information. For example, when the user is in a tourist spot, the camera unit can prioritize capturing tourist attractions and information boards. Furthermore, when the user is in a commercial facility, the camera unit can prioritize capturing store signs and sale information. Furthermore, when the user is using public transportation, the camera unit can prioritize capturing station names and bus stop information. In this way, the camera unit can provide highly relevant information to the user by taking into account the geographical location information. Some or all of the above-described processing in the camera unit may be performed using, for example, AI, or may be performed without using AI. For example, the camera unit can input geographical location information to a generation AI and cause the generation AI to select highly relevant information.

[0069] The camera unit can analyze the user's social media activity based on the recognized visual information and capture related visual information. The camera unit can, for example, analyze the user's social media activity based on the recognized visual information. For example, the camera unit can analyze the content of social media posts and capture related visual information based on the content frequently posted by the user. If the user is participating in a specific event, the camera unit can also capture visual information related to the event. Furthermore, if the user uses a specific hashtag, the camera unit can also capture visual information related to the hashtag. In this way, the camera unit can provide visual information that is highly relevant to the user by analyzing the social media activity. Some or all of the above-described processing in the camera unit may be performed using, for example, AI, or may be performed without using AI. For example, the camera unit can input social media data into a generation AI and cause the generation AI to select related visual information.

[0070] The voice output unit can estimate the user's emotion and adjust the tone and speed of the voice based on the estimated user's emotion. The voice output unit, for example, estimates the user's emotion. For example, the voice output unit can estimate the user's emotion using facial expression recognition technology. The voice output unit can also estimate the user's emotion using voice analysis technology. Furthermore, the voice output unit can estimate the user's emotion using biometrics technology. Next, the voice output unit adjusts the tone and speed of the voice based on the estimated user's emotion. For example, if the user is nervous, the voice output unit can output voice slowly in a calm tone. If the user is relaxed, the voice output unit can output voice in a bright tone. Furthermore, if the user is in a hurry, the voice output unit can output voice quickly and concisely. In this way, the voice output unit can provide more appropriate voice guidance by adjusting the tone and speed of the voice according to the user's emotion. Some or all of the above-described processing in the voice output unit may be performed using, for example, AI, or may be performed without using AI. For example, the voice output unit can input the user's emotional data into the generation AI and have the generation AI adjust the tone and speed of the voice.

[0071] The voice output unit can provide optimal voice guidance by referring to the user's past voice guidance history based on the generated voice. The voice output unit, for example, can refer to the user's past voice guidance history based on the generated voice. For example, the voice output unit can store the user's past voice guidance history using a database and provide optimal voice guidance based on that history. The voice output unit can also provide optimal voice guidance based on the user's preferred voice guidance tone and speed in the past. Furthermore, the voice output unit can provide optimal voice guidance based on routes and places the user has frequently used in the past. For example, the voice output unit can provide voice guidance tailored to a specific situation based on the user's past voice guidance history. As a result, the voice output unit can provide optimal voice guidance for the user by referring to the past voice guidance history. Some or all of the above-described processing in the voice output unit may be performed using, for example, AI, or may be performed without using AI. For example, the voice output unit can input past voice guidance history data into a generation AI and cause the generation AI to provide optimal voice guidance.

[0072] The audio output unit can provide customized audio guidance for a specific situation based on the generated audio. The audio output unit can provide customized audio guidance for a specific situation based on the generated audio, for example. For example, when a user is in a tourist spot, the audio output unit can provide audio guidance including an explanation of a tourist attraction. Furthermore, when a user is in a commercial facility, the audio output unit can provide audio guidance including store information and sales information. Furthermore, when a user is using public transportation, the audio output unit can provide audio guidance including station names and bus stop information. This allows the audio output unit to provide more useful information to the user by providing audio guidance tailored to the specific situation. Some or all of the above-described processing in the audio output unit can be performed using, for example, AI, or without AI. For example, the audio output unit can input situation data to a generation AI and cause the generation AI to provide customized audio guidance.

[0073] The audio output unit can estimate the user's emotion and automatically adjust the volume of the audio based on the estimated user's emotion. The audio output unit, for example, estimates the user's emotion. For example, the audio output unit can estimate the user's emotion using facial expression recognition technology. The audio output unit can also estimate the user's emotion using voice analysis technology. Furthermore, the audio output unit can estimate the user's emotion using biometrics technology. Next, the audio output unit automatically adjusts the volume of the audio based on the estimated user's emotion. For example, if the user is nervous, the audio output unit can lower the volume of the audio to provide a calm environment. If the user is relaxed, the audio output unit can also adjust the volume of the audio appropriately. Furthermore, if the user is in a hurry, the audio output unit can increase the volume of the audio to emphasize important information. In this way, the audio output unit can adjust the volume of the audio according to the user's emotion, thereby providing more appropriate audio guidance. Some or all of the above-described processing in the audio output unit may be performed using, for example, AI, or may be performed without using AI. For example, the audio output unit can input the user's emotional data into the generation AI and have the generation AI adjust the volume of the audio.

[0074] The voice output unit can provide optimal voice guidance based on the generated voice, taking into account the user's geographical location information. The voice output unit, for example, considers the user's geographical location information based on the generated voice. For example, the voice output unit can acquire the user's geographical location information using GPS data and provide optimal voice guidance based on that information. For example, when the user is in a tourist spot, the voice output unit can provide voice guidance including an explanation of tourist attractions. Furthermore, when the user is in a commercial facility, the voice output unit can provide voice guidance including store information and sales information. Furthermore, when the user is using public transportation, the voice output unit can provide voice guidance including station names and bus stop information. In this way, the voice output unit can provide voice guidance that is highly relevant to the user by taking into account the geographical location information. Some or all of the above-described processing in the voice output unit may be performed using, for example, AI, or may be performed without using AI. For example, the voice output unit can input geographical location information to a generation AI and cause the generation AI to provide optimal voice guidance.

[0075] The audio output unit can analyze the user's social media activity based on the generated audio and provide related audio guidance. The audio output unit can, for example, analyze the user's social media activity based on the generated audio. For example, the audio output unit can analyze the content of social media posts and provide related audio guidance based on the user's frequent posts. If the user is participating in a specific event, the audio output unit can also provide audio guidance related to the event. Furthermore, if the user uses a specific hashtag, the audio output unit can provide audio guidance related to the hashtag. In this way, the audio output unit can provide audio guidance that is highly relevant to the user by analyzing the social media activity. Some or all of the above-described processing in the audio output unit can be performed using, for example, AI, or can be performed without using AI. For example, the audio output unit can input social media data to a generation AI and cause the generation AI to provide related audio guidance.

[0076] The microphone unit can estimate a user's emotion and automatically adjust the microphone sensitivity based on the estimated user's emotion. The microphone unit, for example, estimates the user's emotion. For example, the microphone unit can estimate the user's emotion using facial expression recognition technology. The microphone unit can also estimate the user's emotion using voice analysis technology. Furthermore, the microphone unit can estimate the user's emotion using biometrics technology. Next, the microphone unit automatically adjusts the microphone sensitivity based on the estimated user's emotion. For example, if the user is nervous, the microphone unit can increase the microphone sensitivity to capture ambient sounds in detail. If the user is relaxed, the microphone unit can also decrease the microphone sensitivity to eliminate unnecessary sounds. Furthermore, if the user is in a hurry, the microphone unit can dynamically adjust the microphone sensitivity to prioritize capturing important sounds. In this way, the microphone unit can provide more appropriate audio information by adjusting the microphone sensitivity according to the user's emotion. Some or all of the above-described processing in the microphone unit may be performed using, for example, AI or without AI. For example, the microphone unit can input the user's emotional data into the generation AI and have the generation AI adjust the microphone sensitivity.

[0077] The microphone unit can learn a user's behavioral patterns based on the recognized voice information and select the optimal timing for voice capture. The microphone unit, for example, learns a user's behavioral patterns based on the recognized voice information. For example, the microphone unit can learn a user's behavioral patterns using a machine learning algorithm. The microphone unit can also collect user behavioral data using a data collection method and learn the user's behavioral patterns. Next, the microphone unit selects the optimal timing for voice capture based on the learned behavioral patterns. For example, the microphone unit can learn the time periods when the user frequently converses and increase the sensitivity of the microphone during those time periods. The microphone unit can also learn the user's habit of conversing in a specific location and prioritize voice capture in that location. Furthermore, the microphone unit can be set to automatically start voice capture when the user performs a specific action. In this way, the microphone unit can learn the user's behavioral patterns and capture voice information at the optimal timing. Some or all of the above-described processing in the microphone unit may be performed using, for example, AI or without AI. For example, the microphone unit can input user behavior data into the generation AI and have the generation AI select the optimal timing for voice capture.

[0078] The microphone unit can add a filtering function that prioritizes capturing specific sounds and voices based on the recognized audio information. The microphone unit, for example, prioritizes capturing specific sounds and voices based on the recognized audio information. For example, the microphone unit can recognize the voice of a specific person using a voice recognition algorithm and automatically capture that person's voice when it is heard. The microphone unit can also prioritize capturing specific sounds (e.g., warning sounds). Furthermore, the microphone unit can prioritize capturing sounds when a user performs a specific action (e.g., clapping). In this way, the microphone unit prioritizes capturing specific sounds and voices so that important information is not missed. Some or all of the above-described processing in the microphone unit may be performed using, for example, AI, or may be performed without AI. For example, the microphone unit can input audio data to a generation AI and have the generation AI filter out specific sounds and voices.

[0079] The microphone unit can estimate a user's emotion and automatically adjust the microphone's noise canceling function based on the estimated user's emotion. The microphone unit, for example, estimates the user's emotion. For example, the microphone unit can estimate the user's emotion using facial expression recognition technology. The microphone unit can also estimate the user's emotion using voice analysis technology. Furthermore, the microphone unit can estimate the user's emotion using biometrics technology. The microphone unit then automatically adjusts the microphone's noise canceling function based on the estimated user's emotion. For example, if the user is nervous, the microphone unit can enhance the noise canceling function to eliminate ambient noise. If the user is relaxed, the microphone unit can also moderately adjust the noise canceling function. Furthermore, if the user is in a hurry, the microphone unit can dynamically adjust the noise canceling function to prioritize capturing important sounds. This allows the microphone unit to provide more appropriate audio information by adjusting the noise canceling function according to the user's emotion. Some or all of the above-described processing in the microphone unit may be performed using, for example, AI, or may be performed without AI. For example, the microphone unit can input the user's emotional data into the generation AI and have the generation AI adjust the noise canceling function.

[0080] The microphone unit can prioritize capturing highly relevant voice information based on the recognized voice information, taking into account the user's geographical location information. The microphone unit, for example, considers the user's geographical location information based on the recognized voice information. For example, the microphone unit can acquire the user's geographical location information using GPS data and prioritize capturing highly relevant voice information based on that information. For example, when the user is in a tourist spot, the microphone unit can prioritize capturing voice information including descriptions of tourist attractions. Furthermore, when the user is in a commercial facility, the microphone unit can prioritize capturing voice information including store guides and sales information. Furthermore, when the user is using public transportation, the microphone unit can prioritize capturing voice information including station names and bus stop guides. In this way, the microphone unit can provide highly relevant voice information to the user by taking into account the geographical location information. Some or all of the above-described processing in the microphone unit may be performed using, for example, AI, or may be performed without using AI. For example, the microphone unit can input geographical location information to a generation AI and cause the generation AI to select highly relevant voice information.

[0081] The microphone unit can analyze the user's social media activities based on the recognized voice information and capture related voice information. The microphone unit can, for example, analyze the user's social media activities based on the recognized voice information. For example, the microphone unit can analyze the content of social media posts and capture related voice information based on the content frequently posted by the user. In addition, if the user is participating in a specific event, the microphone unit can capture voice information related to the event. Furthermore, if the user uses a specific hashtag, the microphone unit can capture voice information related to the hashtag. In this way, the microphone unit can provide highly relevant voice information to the user by analyzing social media activities. Some or all of the above-described processing in the microphone unit may be performed using, for example, AI, or may be performed without using AI. For example, the microphone unit can input social media data into a generation AI and cause the generation AI to select related voice information.

[0082] The character display unit can estimate the user's emotion and automatically adjust the font and size of the characters based on the estimated user's emotion. The character display unit, for example, estimates the user's emotion. For example, the character display unit can estimate the user's emotion using facial expression recognition technology. The character display unit can also estimate the user's emotion using voice analysis technology. Furthermore, the character display unit can estimate the user's emotion using biometrics technology. Next, the character display unit automatically adjusts the font and size of the characters based on the estimated user's emotion. For example, the character display unit can use a large font with high visibility when the user is nervous. The character display unit can also use a standard font that is easy to read when the user is relaxed. Furthermore, the character display unit can increase the font size to emphasize important information when the user is in a hurry. In this way, the character display unit can provide more appropriate information by adjusting the font and size of the characters according to the user's emotion. Some or all of the above-mentioned processing in the character display unit may be performed using, for example, AI, or may be performed without AI. For example, the character display unit can input the user's emotional data into the generation AI and have the generation AI adjust the font and size of the characters.

[0083] The character display unit can refer to the user's past display history based on the character information to be displayed and provide an optimal display method. The character display unit, for example, refers to the user's past display history based on the character information to be displayed. For example, the character display unit can store the user's past display history using a database and provide an optimal display method based on that history. The character display unit can also provide an optimal display method based on the user's preferred fonts and sizes in the past. Furthermore, the character display unit can provide an optimal display method based on information that the user has frequently displayed in the past. For example, the character display unit can provide a display method suited to a specific situation based on the user's past display history. In this way, the character display unit can provide an optimal display method for the user by referring to the past display history. Some or all of the above-described processing in the character display unit may be performed using, for example, AI, or may be performed without AI. For example, the character display unit can input past display history data to a generation AI and cause the generation AI to provide an optimal display method.

[0084] The character display unit can provide a customized display method according to a specific situation based on the displayed character information. The character display unit can provide a customized display method according to a specific situation based on the displayed character information, for example. For example, when the user is in a tourist spot, the character display unit can provide a display method including an explanation of tourist attractions. Furthermore, when the user is in a commercial facility, the character display unit can provide a display method including store guides and sale information. Furthermore, when the user is using public transportation, the character display unit can provide a display method including station names and bus stop guides. In this way, the character display unit can provide more useful information to the user by providing a display method according to a specific situation. Some or all of the above-described processing in the character display unit can be performed using, for example, AI, or can be performed without using AI. For example, the character display unit can input situation data to a generation AI and cause the generation AI to provide a customized display method.

[0085] The character display unit can estimate the user's emotion and automatically adjust the character color and background color based on the estimated user's emotion. The character display unit, for example, estimates the user's emotion. For example, the character display unit can estimate the user's emotion using facial expression recognition technology. The character display unit can also estimate the user's emotion using voice analysis technology. Furthermore, the character display unit can estimate the user's emotion using biometrics technology. Next, the character display unit automatically adjusts the character color and background color based on the estimated user's emotion. For example, if the user is nervous, the character display unit can use subdued character and background colors. If the user is relaxed, the character display unit can use bright character and background colors. Furthermore, if the user is in a hurry, the character display unit can use high-contrast colors with high visibility. In this way, the character display unit can provide more appropriate information by adjusting the character color and background color according to the user's emotion. Some or all of the above-mentioned processing in the character display unit may be performed using, for example, AI, or may be performed without AI. For example, the character display unit can input the user's emotional data into the generation AI and have the generation AI adjust the character color and background color.

[0086] The character display unit can provide an optimal display method based on the displayed character information, taking into account the user's geographical location information. The character display unit, for example, considers the user's geographical location information based on the displayed character information. For example, the character display unit can acquire the user's geographical location information using GPS data and provide an optimal display method based on that information. For example, if the user is in a tourist spot, the character display unit can provide a display method including an explanation of tourist attractions. Furthermore, if the user is in a commercial facility, the character display unit can provide a display method including store information and sale information. Furthermore, if the user is using public transportation, the character display unit can provide a display method including station names and bus stop information. In this way, the character display unit can provide information that is highly relevant to the user by taking into account the geographical location information. Some or all of the above-described processing in the character display unit may be performed using, for example, AI, or may be performed without using AI. For example, the character display unit can input geographical location information to a generation AI and cause the generation AI to provide an optimal display method.

[0087] The text display unit can analyze the user's social media activity based on the displayed text information and display related text information. The text display unit can, for example, analyze the user's social media activity based on the displayed text information. For example, the text display unit can analyze the content of social media posts and display related text information based on the content frequently posted by the user. Furthermore, if the user is participating in a specific event, the text display unit can display text information related to the event. Furthermore, if the user uses a specific hashtag, the text display unit can display text information related to the hashtag. In this way, the text display unit can provide highly relevant information to the user by analyzing social media activity. Some or all of the above-described processing in the text display unit can be performed using, for example, AI, or without AI. For example, the text display unit can input social media data to a generation AI and cause the generation AI to display related text information. === Hard Collateral 1-1 === Each of the multiple elements, including the camera unit, audio output unit, microphone unit, and character display unit, described above, is implemented, for example, by at least one of the smart device 14 and the data processing device 12. For example, the camera unit is implemented by the camera 42 of the smart device 14, capturing surrounding visual information at high resolution and analyzing it using image processing technology. The audio output unit is implemented by the speaker 40B of the smart device 14, converting the visual information into audio and transmitting it to the user. The microphone unit is implemented by the microphone 38B of the smart device 14, capturing surrounding audio information with high sensitivity and analyzing it using voice recognition technology. The character display unit is implemented by the display 40A of the smart device 14, converting the recognized audio information into text and displaying it. === Hard Collateral 1-2 === Each of the multiple elements, including the camera unit, audio output unit, microphone unit, and character display unit, described above, is implemented, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the camera unit is implemented by the camera 42 of the smart glasses 214, capturing surrounding visual information at high resolution and analyzing it using image processing technology. The audio output unit is implemented, for example, by the speaker 240 of the smart glasses 214, converting the visual information into audio and transmitting it to the user. The microphone unit is implemented, for example, by the microphone 238 of the smart glasses 214, capturing surrounding audio information with high sensitivity and analyzing it using voice recognition technology. The character display unit is implemented, for example, by the display of the smart glasses 214, converting the recognized audio information into text and displaying it. === Hard Collateral 1-3 === Each of the multiple elements including the camera unit, audio output unit, microphone unit, and character display unit described above is realized, for example, by at least one of the headset terminal 314 and the data processing device 12. For example, the camera unit is realized by the camera 42 of the headset terminal 314, which captures surrounding visual information at high resolution and analyzes it using image processing technology. The audio output unit is realized by the speaker 240 of the headset terminal 314, which converts visual information into audio and conveys it to the user. The microphone unit is realized by the microphone 238 of the headset terminal 314, which captures surrounding audio information with high sensitivity and analyzes it using voice recognition technology. The character display unit is realized by the display 343 of the headset terminal 314, which converts recognized audio information into text and displays it. === Hard Collateral 1-4 === Each of the multiple elements including the camera unit, audio output unit, microphone unit, and character display unit described above is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the camera unit is realized by the camera 42 of the robot 414, which captures surrounding visual information at high resolution and analyzes it using image processing technology. The audio output unit is realized, for example, by the speaker 240 of the robot 414, which converts visual information into audio and conveys it to the user. The microphone unit is realized, for example, by the microphone 238 of the robot 414, which captures surrounding audio information with high sensitivity and analyzes it using voice recognition technology. The character display unit is realized, for example, by the display of the robot 414, which converts recognized audio information into text and displays it.

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

[0089] The smart glasses system may further include a vibration feedback unit. The vibration feedback unit may vibrate to notify the user when the user encounters a specific situation. For example, when the user approaches a pedestrian crossing, the vibration feedback unit may generate a slight vibration to alert the user. When the user approaches a dangerous location, the vibration feedback unit may generate a strong vibration to warn the user. Furthermore, when the user reaches a specific destination, the vibration feedback unit may generate a short vibration to notify the user of arrival. This allows the smart glasses system to provide information to the user using tactile senses in addition to visual and auditory senses.

[0090] The smart glasses system may further include a temperature sensor unit. The temperature sensor unit can detect the ambient temperature and provide appropriate information to the user. For example, the temperature sensor unit can issue a warning to the user if the outside temperature changes suddenly. The temperature sensor unit can also display a message urging the user to take appropriate measures if the user is in an environment where there is a risk of heatstroke. Furthermore, the temperature sensor unit can also urge the user to take measures to protect themselves from the cold when used in cold regions. In this way, the smart glasses system can use temperature information to improve the safety and comfort of the user.

[0091] The smart glasses system may further include a heart rate sensor unit. The heart rate sensor unit can monitor the user's heart rate and issue a warning if an abnormality is detected. For example, the heart rate sensor unit can display a message encouraging the user to relax if the user's heart rate suddenly increases. The heart rate sensor unit can also provide guidance for the user to maintain an appropriate heart rate during exercise. Furthermore, the heart rate sensor unit can suggest relaxation methods if the user is feeling stressed. This allows the smart glasses system to monitor the user's health condition in real time and provide appropriate advice.

[0092] The smart glasses system may further include a location information sharing unit. The location information sharing unit may share the user's current location in real time. For example, the location information sharing unit may ensure safety by allowing the user to share their location information with family and friends. The location information sharing unit may also enable the user to quickly request rescue if they become lost. Furthermore, the location information sharing unit may also share their location information with other participants when the user participates in a specific event or gathering. In this way, the smart glasses system may utilize the user's location information to improve safety and convenience.

[0093] The smart glasses system may further include a gesture recognition unit. The gesture recognition unit may recognize the movements of the user's hands or fingers and execute specific operations. For example, the gesture recognition unit may pause audio guidance when the user waves their hand. The gesture recognition unit may also scroll text display when the user slides their finger. The gesture recognition unit may also start capturing images with the camera when the user performs a specific gesture. This allows the smart glasses system to realize intuitive operations using the user's gestures.

[0094] The smart glasses system can estimate the user's emotions and customize the content of the voice guidance based on the estimated emotions. For example, if the user is nervous, the voice guidance can be changed to encourage relaxation. If the user is excited, the voice guidance can provide advice on staying calm. Furthermore, if the user is sad, the voice guidance can include an encouraging message. This allows the smart glasses system to provide appropriate voice guidance according to the user's emotions.

[0095] The smart glasses system can estimate the user's emotions and customize the content of the text display based on the estimated emotions. For example, if the user is nervous, the text display can be changed to content encouraging relaxation. If the user is excited, the text display can provide advice on staying calm. Furthermore, if the user is sad, the text display can include an encouraging message. This allows the smart glasses system to provide appropriate text display according to the user's emotions.

[0096] The smart glasses system can estimate a user's emotions and automatically adjust the camera's zoom function based on the estimated emotions. For example, if the user is nervous, the camera's zoom can be set to a wide angle to capture more of the surrounding information. Alternatively, if the user is relaxed, the camera's zoom can be set to a narrow angle to focus on a specific subject. Furthermore, if the user is in a hurry, the camera's zoom can be dynamically adjusted to prioritize capturing important information. This allows the smart glasses system to provide more appropriate visual information by adjusting the camera's zoom function according to the user's emotions.

[0097] The smart glasses system can estimate the user's emotions and automatically switch the language of the voice output based on the estimated emotions. For example, if the user is nervous, it can provide voice guidance in the user's native language. If the user is relaxed, it can provide voice guidance in a foreign language the user is learning. Furthermore, if the user is in a hurry, it can provide voice guidance in a language that the user can understand most easily. This allows the smart glasses system to provide more appropriate voice guidance by adjusting the language of the voice output according to the user's emotions.

[0098] The smart glasses system can estimate the user's emotions and provide humorous audio output content based on the estimated emotions. For example, if the user is nervous, it can provide humorous audio guidance to encourage relaxation. If the user is sad, it can provide a humorous message to lighten the user's mood. Furthermore, if the user is excited, it can provide humorous advice to help the user stay calm. This allows the smart glasses system to provide more appropriate support by providing humorous audio guidance according to the user's emotions.

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

[0100] Step 1: The camera unit recognizes the surrounding visual information. The camera unit captures the surrounding video at high resolution and analyzes the visual information using image processing technology. For example, it can recognize the characters on signs, road signs, and the movements of people in the surrounding area. The camera unit captures video at 1080p resolution and analyzes the visual information using image processing technology such as edge detection, face recognition, and object detection. Step 2: The voice output unit reads out the visual information recognized by the camera unit. The voice output unit converts the visual information into voice using speech synthesis technology and communicates it to the user through the built-in speaker. For example, it can provide voice guidance such as "There is a crosswalk ahead" or "Turn right." The voice output unit can convert the visual information into voice using text-to-speech (TTS) technology and communicate it to the user. Step 3: The microphone recognizes surrounding audio information. The microphone captures surrounding sounds with high sensitivity and analyzes the audio information using voice recognition technology. For example, it can recognize the content of conversations, warning sounds, and surrounding environmental sounds. The microphone captures sounds with a sensitivity of -40dB and can analyze the audio information using deep learning-based voice recognition technology. Step 4: The character display unit converts the voice information recognized by the microphone unit into text and displays it on the smart glasses' display. For example, it can display text information such as "Hello, how are you?" or "Caution, a car is approaching." The character display unit can display the text information in high resolution on the smart glasses' display and communicate it to the user.

[0101] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0102] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of the generative AI include a neural network (NN) and a neural network (NN). 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 (e.g., still image data or video data). 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 one or more data formats of voice data, text data, image data, etc. 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 may perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-mentioned parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. The processing performed by an AI including the generative AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI including the generative AI.

[0103] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0104] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0105] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0106] 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.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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).

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0115] 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. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0116] 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.

[0117] 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.

[0118] 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 including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0119] 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.

[0120] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0121] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0122] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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).

[0127] 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.

[0128] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0129] 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.

[0130] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0131] 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 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0132] 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.

[0133] 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.

[0134] 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 including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0135] 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.

[0136] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0137] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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).

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0148] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. 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 the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0149] 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.

[0150] 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.

[0151] 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 including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0152] 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.

[0153] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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).

[0158] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0159] 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."

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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.

[0171] 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.

[0172] [Explanation of symbols]

[0173] 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 camera unit that recognizes surrounding visual information; an audio output unit that reads out the visual information recognized by the camera unit; A microphone unit that recognizes surrounding audio information; a character display unit that converts the voice information recognized by the microphone unit into characters and displays the characters; A system characterized by:

2. The camera unit includes: Captures surrounding images at a specific resolution and analyzes the visual information using image processing technology 2. The system of claim 1.

3. The audio output unit It uses speech synthesis technology to convert visual information into speech and communicate it to the user through the built-in speaker.

2. The system of claim 1.

4. The microphone unit is Captures surrounding sounds with a certain sensitivity and analyzes the audio information using voice recognition technology 2. The system of claim 1.

5. The character display unit is The recognized voice information is converted into text and displayed on the smart glasses display.

2. The system of claim 1.

6. The camera unit includes: Estimates the user's emotions and automatically adjusts the camera's shooting angle based on the estimated user emotions.

2. The system of claim 1.

7. The camera unit includes: Based on the visual information it recognizes, it learns the user's behavioral patterns and selects the optimal timing for taking a photo.

2. The system of claim 1.

8. The camera unit includes: Add a filtering function to prioritize capturing specific objects or people based on recognized visual information.

2. The system of claim 1.

Images