System

Abstract

An object of the system according to the embodiment is to integrally provide functions such as voice amplification, translation, and subtitle display.SOLUTION: A system according to an embodiment includes a sound amplification unit, a viewpoint recognition unit, a translation unit, and a caption display unit. The sound amplification unit amplifies sound. The viewpoint recognition unit recognizes a viewpoint of a user. The translation unit translates speech in different languages. The caption display unit converts the voice into text and displays the text.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology does not provide a system that integrates functions such as audio amplification, translation, and subtitle display, and there is room for improvement.

[0005] The system according to the embodiment aims to provide integrated functions such as audio amplification, translation, and subtitle display. [Means for solving the problem]

[0006] The system according to the embodiment includes an audio amplifier, a viewpoint recognition unit, a translation unit, and a subtitle display unit. The audio amplifier amplifies audio. The viewpoint recognition unit recognizes a user's viewpoint. The translation unit translates audio in different languages. The subtitle display unit converts audio into text and displays it. [Effects of the Invention]

[0007] The system according to the embodiment can provide integrated functions such as audio amplification, translation, and subtitle display. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) The audio glasses system according to the embodiment of the present invention amplifies sound, recognizes viewpoints, translates speech between different languages, and converts speech into text for display, thereby improving user convenience and quality of life.

[0029] An audio glasses system according to an embodiment includes an audio amplifier, a gaze recognition unit, a translation unit, and a subtitle display unit. The audio amplifier amplifies audio. For example, the audio amplifier analyzes ambient sounds and amplifies only necessary sounds. The audio amplifier can also emphasize and amplify specific frequency bands. The audio amplifier can also amplify audio according to the user's hearing characteristics. The gaze recognition unit recognizes the user's gaze. For example, the gaze recognition unit can identify the user's gaze using eye tracking technology. The gaze recognition unit can also recognize the user's gaze using a camera. The gaze recognition unit can also identify an object the user is focusing on. The translation unit translates audio from different languages. For example, the translation unit can translate audio from different languages ​​in real time. The translation unit can also translate into the user's native language. The translation unit can also output the translated audio as a voice. The subtitle display unit converts audio into text and displays it. For example, the subtitle display unit converts audio into text in real time. The subtitle display unit can also display the text in the user's field of view. The subtitle display unit can also analyze subtitle data to provide supplemental information. As a result, the audio glasses system according to the embodiment can improve the convenience and quality of life of users. For example, the audio glasses system can clearly hear people's voices even in noisy places. The audio glasses system can also provide information about an object that the user is paying attention to. The audio glasses system can also facilitate communication between different languages. The audio glasses system can also enable users with hearing impairments to understand the content of conversations.

[0030] The sound amplifier unit can analyze ambient sounds and adjust specific frequency bands in real time to optimize them for the user's hearing characteristics. For example, the sound amplifier unit uses AI to analyze ambient sounds in real time and emphasize or suppress specific frequency bands to provide audio tailored to the user's hearing characteristics. For example, it can emphasize high-pitched sounds for users who have difficulty hearing high-pitched sounds. The sound amplifier unit also uses AI to analyze ambient sounds based on the user's hearing characteristic data and dynamically adjust specific frequency bands. For example, it can suppress low-pitched sounds in noisy environments to make human voices clearer. The sound amplifier unit also uses AI to analyze ambient sounds and adjust specific frequency bands in real time to provide audio optimized for the user's hearing characteristics. For example, it can adjust to the characteristics of the music when listening to music. This makes it possible to provide audio optimized for the user's hearing characteristics.

[0031] The audio amplifier unit can analyze audio data, identify specific sound sources, and prioritize amplify them. For example, AI can analyze audio data to identify and prioritize the voices of specific people. For example, during a meeting, the speaker's voice can be prioritized for clearer sound. The audio amplifier unit also provides an interface that allows the user to select a specific sound source, and the AI ​​can identify and prioritize the amplification of that sound source. For example, a setting can be made to prioritize the amplification of family members' voices. The audio amplifier unit also develops an algorithm that analyzes audio data using AI to identify and prioritize the amplification of specific sound sources. For example, background noise can be suppressed to make a specific person's voice clearer in a noisy environment. This prioritizes the amplification of specific sound sources, allowing important sounds to be heard clearly.

[0032] The viewpoint recognition unit can provide detailed information about an object that a user is focusing on in real time. The viewpoint recognition unit, for example, uses a viewpoint recognition function to provide detailed information about an object that a user is focusing on in real time. For example, information about a product that the user is looking at is explained by voice. The viewpoint recognition unit also identifies an object that a user is focusing on using the viewpoint recognition function and provides detailed information about it in real time. For example, the history and background information of a tourist spot is explained by voice. The viewpoint recognition unit also uses the viewpoint recognition function to build a system that provides detailed information about an object that a user is focusing on in real time. For example, an explanation of an exhibit at an art museum is provided by voice. This makes it possible to provide information about an object that a user is focusing on in real time.

[0033] The viewpoint recognition unit can analyze the viewpoint recognition data, learn the user's interests, and provide personalized information. The viewpoint recognition unit, for example, analyzes the viewpoint recognition data and develops an algorithm that learns the user's interests. For example, it identifies subjects that the user frequently focuses on and provides related information. The viewpoint recognition unit also learns the user's interests based on the viewpoint recognition data and provides personalized information. For example, it provides news in areas that interest the user by audio. The viewpoint recognition unit also analyzes the viewpoint recognition data and builds a system that learns the user's interests. For example, it automatically provides information related to subjects that the user focuses on. This makes it possible to provide information based on the user's interests.

[0034] The translation unit can translate speech in different languages ​​in real time and output speech in the user's native language. For example, the translation unit uses a translation function to translate speech in different languages ​​in real time and output speech in the user's native language. For example, it can instantly translate what is spoken to it in a foreign language and convey it in speech. The translation unit also builds a system in which AI analyzes speech in different languages, translates it in real time, and outputs speech in the user's native language. For example, it can be used to understand local languages ​​while traveling. The translation unit also uses the translation function to develop algorithms that translate speech in different languages ​​in real time and output speech in the user's native language. For example, it can support multilingual communication in business meetings. This facilitates communication between different languages ​​by translating speech in different languages ​​in real time and outputting speech in the user's native language.

[0035] The translation unit can analyze the translation data and provide a learning mode to assist the user in language acquisition. For example, the translation unit can analyze the translation data and provide a learning mode to assist the user in language acquisition. For example, the translation unit can add a function that allows the user to repeatedly practice translated phrases. The translation unit can also build a system in which AI analyzes the translation data and provides a learning mode to assist the user in language acquisition. For example, the translation unit can support pronunciation practice of translated words and phrases. The translation unit can also develop an algorithm based on the translation data to provide a learning mode to assist the user in language acquisition. For example, the translation unit can learn grammar and vocabulary based on translated sentences. This can provide a learning mode to assist the user in language acquisition.

[0036] The subtitle display unit can convert audio into text in real time and display it in the user's field of vision. For example, the subtitle display unit uses a subtitle display function to convert audio into text in real time and display it in the user's field of vision. For example, the content of a conversation is displayed as subtitles. The subtitle display unit also builds a system in which AI analyzes audio, converts it into text in real time, and displays it in the user's field of vision. For example, the content of a presentation is displayed as subtitles. The subtitle display unit also develops an algorithm that uses the subtitle display function to convert audio into text in real time and display it in the user's field of vision. For example, this can be used to display subtitles for movies and TV programs. By converting audio into text in real time and displaying it in the user's field of vision, even users with hearing impairments can understand the content.

[0037] The subtitle display unit can analyze subtitle data and provide supplemental information to improve the user's understanding. For example, the subtitle display unit analyzes subtitle data and provides supplemental information to improve the user's understanding. For example, it displays explanations of technical terms and related information. The subtitle display unit also builds a system in which AI analyzes subtitle data and provides supplemental information to improve the user's understanding. For example, it displays the meaning of difficult words. The subtitle display unit also develops an algorithm based on the subtitle data that provides supplemental information to improve the user's understanding. For example, it explains background information and context. This makes it possible to provide supplemental information to improve the user's understanding.

[0038] The hearing aid function can amplify sounds in real time according to the user's hearing characteristics. For example, the hearing aid function uses the hearing aid function to amplify sounds in real time according to the user's hearing characteristics. For example, for a user who has difficulty hearing high-pitched sounds, the high-pitched sounds can be emphasized and amplified. The hearing aid function also builds a system in which AI analyzes the user's hearing characteristics data and performs sound amplification in real time. For example, this can be used to make conversations clearer in noisy environments. The hearing aid function also develops an algorithm that uses the hearing aid function to perform sound amplification in real time according to the user's hearing characteristics. For example, when listening to music, the sound is amplified according to the characteristics of the music. This allows sound amplification in real time according to the user's hearing characteristics.

[0039] The hearing aid function can analyze hearing aid data and provide personalized audio filtering based on the user's hearing characteristics. For example, the hearing aid function analyzes hearing aid data and provides personalized audio filtering based on the user's hearing characteristics. For example, filtering can be performed to emphasize specific frequency bands. The hearing aid function also builds a system in which AI analyzes hearing aid data and provides audio filtering based on the user's hearing characteristics. For example, it can suppress background noise while making conversation clearer. The hearing aid function also develops an algorithm that provides personalized audio filtering tailored to the user's hearing characteristics based on the hearing aid data. For example, it can preferentially amplify specific sound sources. This makes it possible to provide personalized audio filtering based on the user's hearing characteristics.

[0040] The hearing aid function can amplify a specific sound source preferentially. For example, the hearing aid function adds a function to amplify a specific sound source (e.g., a specific person's voice) preferentially. For example, to make a speaker's voice clearer during a meeting, the hearing aid function may preferentially amplify the speaker's voice. The hearing aid function may also provide an interface that allows the user to select a specific sound source, and the hearing aid function may preferentially amplify that sound source. For example, a setting may be made to preferentially amplify the voices of family members. The hearing aid function may also develop an algorithm to preferentially amplify a specific sound source. For example, to make a specific person's voice clearer in a noisy environment, background noise may be suppressed. This allows important sounds to be heard clearly by preferentially amplifying a specific sound source.

[0041] The hearing aid function can filter environmental sounds and amplify only the sounds the user needs. For example, the hearing aid function adds a function to filter environmental sounds and amplify only the sounds the user needs. For example, background noise can be suppressed to make conversations clearer in noisy places. The hearing aid function also builds a system that uses AI to analyze environmental sounds and provide a filtering function that amplifies only the sounds the user needs. For example, it amplifies conversations while suppressing office noise. The hearing aid function also develops an algorithm that filters environmental sounds and amplifies only the sounds the user needs. For example, it can clear conversations while leaving natural sounds intact. This allows the user to hear important audio clearly by amplifying only the sounds they need.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The audio glasses system can further include a health management unit that monitors the user's health condition. For example, the health management unit can measure the user's heart rate and blood pressure and issue an alert if an abnormality is detected. The health management unit can also record the user's number of steps and calories burned to support daily health management. Furthermore, the health management unit can analyze the user's sleep patterns and provide advice to promote quality sleep. This allows the audio glasses system to comprehensively support the user's health condition.

[0044] The audio glasses system may further include a location information acquisition unit that acquires the user's location information. For example, the location information acquisition unit may use GPS to identify the user's current location and display it on a map. The location information acquisition unit may also record a history of places the user has visited so that the history can be referenced later. Furthermore, if the user becomes lost, the location information acquisition unit may provide guidance to the nearest safe place or a route to the user's destination. In this way, the audio glasses system can utilize the user's location information to provide a more convenient and safe experience.

[0045] The audio glasses system may further include an activity recording unit that records the user's activities. For example, the activity recording unit may record the amount and duration of the user's exercise and provide daily activity data. The activity recording unit may also analyze the user's exercise patterns and provide advice to promote healthy lifestyle habits. Furthermore, the activity recording unit may evaluate the user's goal achievement level based on the user's activity data and provide feedback to increase motivation. In this way, the audio glasses system can support the user's healthy lifestyle.

[0046] The audio glasses system can further analyze the user's visual information and provide visual feedback. For example, the audio glasses system can analyze the visual information to highlight the color or shape of the object the user is looking at. The audio glasses system can also analyze the visual information to display detailed information about the object the user is looking at. The audio glasses system can also analyze the visual information to provide relevant information about the object the user is looking at. In this way, the audio glasses system can utilize the user's visual information to provide a richer visual experience.

[0047] The audio glasses system can further analyze the user's voice commands and support voice operations. For example, it can analyze the voice commands and perform the operations instructed by the user. It can also analyze the voice commands and provide information requested by the user. It can also analyze the voice commands and automatically perform tasks set by the user. In this way, the audio glasses system can utilize the user's voice commands to provide a more convenient operation experience.

[0048] The processing flow of the first embodiment will be briefly explained below.

[0049] Step 1: The audio amplifier amplifies the sound. For example, the audio amplifier analyzes the surrounding sounds and amplifies only the necessary sounds. It can also emphasize and amplify specific frequency bands, and amplify sounds according to the user's hearing characteristics. Step 2: The viewpoint recognition unit recognizes the user's viewpoint. For example, it identifies the user's viewpoint using eye tracking technology. It can also recognize the user's viewpoint using a camera, and identify the object the user is focusing on. Step 3: The translation unit translates the speech in different languages. For example, it can translate speech in different languages ​​in real time and translate it into the user's native language. It can also output the translated speech. Step 4: The subtitle display unit converts the audio into text and displays it. For example, it can convert audio into text in real time and display the text in the user's field of view. It can also analyze the subtitle data to provide supplemental information.

[0050] (Example 2) The audio glasses system according to the embodiment of the present invention amplifies sound, recognizes viewpoints, translates speech between different languages, and converts speech into text for display, thereby improving user convenience and quality of life.

[0051] An audio glasses system according to an embodiment includes an audio amplifier, a gaze recognition unit, a translation unit, and a subtitle display unit. The audio amplifier amplifies audio. For example, the audio amplifier analyzes ambient sounds and amplifies only necessary sounds. The audio amplifier can also emphasize and amplify specific frequency bands. The audio amplifier can also amplify audio according to the user's hearing characteristics. The gaze recognition unit recognizes the user's gaze. For example, the gaze recognition unit can identify the user's gaze using eye tracking technology. The gaze recognition unit can also recognize the user's gaze using a camera. The gaze recognition unit can also identify an object the user is focusing on. The translation unit translates audio from different languages. For example, the translation unit can translate audio from different languages ​​in real time. The translation unit can also translate into the user's native language. The translation unit can also output the translated audio as a voice. The subtitle display unit converts audio into text and displays it. For example, the subtitle display unit converts audio into text in real time. The subtitle display unit can also display the text in the user's field of view. The subtitle display unit can also analyze subtitle data to provide supplemental information. As a result, the audio glasses system according to the embodiment can improve the convenience and quality of life of users. For example, the audio glasses system can clearly hear people's voices even in noisy places. The audio glasses system can also provide information about an object that the user is paying attention to. The audio glasses system can also facilitate communication between different languages. The audio glasses system can also enable users with hearing impairments to understand the content of conversations.

[0052] The sound amplifier unit can analyze ambient sounds and adjust specific frequency bands in real time to optimize them for the user's hearing characteristics. For example, the sound amplifier unit uses AI to analyze ambient sounds in real time and emphasize or suppress specific frequency bands to provide audio tailored to the user's hearing characteristics. For example, it can emphasize high-pitched sounds for users who have difficulty hearing high-pitched sounds. The sound amplifier unit also uses AI to analyze ambient sounds based on the user's hearing characteristic data and dynamically adjust specific frequency bands. For example, it can suppress low-pitched sounds in noisy environments to make human voices clearer. The sound amplifier unit also uses AI to analyze ambient sounds and adjust specific frequency bands in real time to provide audio optimized for the user's hearing characteristics. For example, it can adjust to the characteristics of the music when listening to music. This makes it possible to provide audio optimized for the user's hearing characteristics.

[0053] The audio amplifier unit can analyze audio data, identify specific sound sources, and prioritize amplify them. For example, AI can analyze audio data to identify and prioritize the voices of specific people. For example, during a meeting, the speaker's voice can be prioritized for clearer sound. The audio amplifier unit also provides an interface that allows the user to select a specific sound source, and the AI ​​can identify and prioritize the amplification of that sound source. For example, a setting can be made to prioritize the amplification of family members' voices. The audio amplifier unit also develops an algorithm that analyzes audio data using AI to identify and prioritize the amplification of specific sound sources. For example, background noise can be suppressed to make a specific person's voice clearer in a noisy environment. This prioritizes the amplification of specific sound sources, allowing important sounds to be heard clearly.

[0054] The audio amplifier unit can use the emotion estimation function to automatically adjust the tone and volume of the audio according to the emotional state of the user. For example, the audio amplifier unit uses the emotion estimation function to soften the tone of the audio and lower the volume when the user is relaxed. This is applied, for example, when playing relaxing music. Furthermore, the audio amplifier unit uses the emotion estimation function to clear the tone of the audio and adjust the volume appropriately when the user is concentrating. This is applied, for example, when the user is studying or working. Furthermore, the audio amplifier unit uses the emotion estimation function to soften the tone of the audio and lower the volume when the user is feeling stressed. This is applied, for example, when playing audio content that has a relaxing effect. This makes it possible to adjust the audio according to the emotional state of the user.

[0055] The viewpoint recognition unit can provide detailed information about an object that a user is focusing on in real time. The viewpoint recognition unit, for example, uses a viewpoint recognition function to provide detailed information about an object that a user is focusing on in real time. For example, information about a product that the user is looking at is explained by voice. The viewpoint recognition unit also identifies an object that a user is focusing on using the viewpoint recognition function and provides detailed information about it in real time. For example, the history and background information of a tourist spot is explained by voice. The viewpoint recognition unit also uses the viewpoint recognition function to build a system that provides detailed information about an object that a user is focusing on in real time. For example, an explanation of an exhibit at an art museum is provided by voice. This makes it possible to provide information about an object that a user is focusing on in real time.

[0056] The viewpoint recognition unit can analyze the viewpoint recognition data, learn the user's interests, and provide personalized information. The viewpoint recognition unit, for example, analyzes the viewpoint recognition data and develops an algorithm that learns the user's interests. For example, it identifies subjects that the user frequently focuses on and provides related information. The viewpoint recognition unit also learns the user's interests based on the viewpoint recognition data and provides personalized information. For example, it provides news in areas that interest the user by audio. The viewpoint recognition unit also analyzes the viewpoint recognition data and builds a system that learns the user's interests. For example, it automatically provides information related to subjects that the user focuses on. This makes it possible to provide information based on the user's interests.

[0057] The viewpoint recognition unit can use the emotion estimation function to analyze the emotional response of the user to an object that the user is focusing on and provide appropriate information. For example, the viewpoint recognition unit uses the emotion estimation function to analyze the emotional response of the user to an object that the user is focusing on and provide appropriate information. For example, information related to an object that the user has positive emotions about is provided. The viewpoint recognition unit also analyzes the user's emotional response in real time and builds a system that provides appropriate information for the object that the user is focusing on. For example, the content of the information is adjusted based on the emotion score. The viewpoint recognition unit also uses the emotion estimation function to analyze the emotional response of the user to an object that the user is focusing on and develops an algorithm that provides appropriate information. For example, information related to an object that the user has negative emotions about is withheld. This makes it possible to provide information based on the user's emotional response.

[0058] The translation unit can translate speech in different languages ​​in real time and output speech in the user's native language. For example, the translation unit uses a translation function to translate speech in different languages ​​in real time and output speech in the user's native language. For example, it can instantly translate what is spoken to it in a foreign language and convey it in speech. The translation unit also builds a system in which AI analyzes speech in different languages, translates it in real time, and outputs speech in the user's native language. For example, it can be used to understand local languages ​​while traveling. The translation unit also uses the translation function to develop algorithms that translate speech in different languages ​​in real time and output speech in the user's native language. For example, it can support multilingual communication in business meetings. This facilitates communication between different languages ​​by translating speech in different languages ​​in real time and outputting speech in the user's native language.

[0059] The translation unit can analyze the translation data and provide a learning mode to assist the user in language acquisition. For example, the translation unit can analyze the translation data and provide a learning mode to assist the user in language acquisition. For example, the translation unit can add a function that allows the user to repeatedly practice translated phrases. The translation unit can also build a system in which AI analyzes the translation data and provides a learning mode to assist the user in language acquisition. For example, the translation unit can support pronunciation practice of translated words and phrases. The translation unit can also develop an algorithm based on the translation data to provide a learning mode to assist the user in language acquisition. For example, the translation unit can learn grammar and vocabulary based on translated sentences. This can provide a learning mode to assist the user in language acquisition.

[0060] The translation unit can use the emotion estimation function to preserve the emotional tone of the translated speech and achieve natural communication. The translation unit, for example, uses the emotion estimation function to preserve the emotional tone of the translated speech and achieve natural communication. For example, it provides translated speech that includes emotions such as joy and surprise. The translation unit also builds a system in which AI analyzes the emotional tone of the translated speech and outputs translated speech while preserving the emotion. For example, this is used to achieve emotionally rich conversations. The translation unit also uses the emotion estimation function to develop an algorithm that preserves the emotional tone of the translated speech and achieves natural communication. For example, this is used to convey emotions in business negotiations. This allows the emotional tone of the translated speech to be preserved and achieve natural communication.

[0061] The subtitle display unit can convert audio into text in real time and display it in the user's field of vision. For example, the subtitle display unit uses a subtitle display function to convert audio into text in real time and display it in the user's field of vision. For example, the content of a conversation is displayed as subtitles. The subtitle display unit also builds a system in which AI analyzes audio, converts it into text in real time, and displays it in the user's field of vision. For example, the content of a presentation is displayed as subtitles. The subtitle display unit also develops an algorithm that uses the subtitle display function to convert audio into text in real time and display it in the user's field of vision. For example, this can be used to display subtitles for movies and TV programs. By converting audio into text in real time and displaying it in the user's field of vision, even users with hearing impairments can understand the content.

[0062] The subtitle display unit can analyze subtitle data and provide supplemental information to improve the user's understanding. For example, the subtitle display unit analyzes subtitle data and provides supplemental information to improve the user's understanding. For example, it displays explanations of technical terms and related information. The subtitle display unit also builds a system in which AI analyzes subtitle data and provides supplemental information to improve the user's understanding. For example, it displays the meaning of difficult words. The subtitle display unit also develops an algorithm based on the subtitle data that provides supplemental information to improve the user's understanding. For example, it explains background information and context. This makes it possible to provide supplemental information to improve the user's understanding.

[0063] The subtitle display unit can use the emotion estimation function to adjust the timing and format of subtitle display according to the user's emotional state. For example, the subtitle display unit uses the emotion estimation function to adjust the timing of subtitle display according to the user's emotional state. For example, it delays the display of subtitles when the user is concentrating. The subtitle display unit also analyzes the user's emotional state in real time and builds a system to adjust the format of subtitles. For example, it changes the color and size of subtitles based on the emotion score. The subtitle display unit also uses the emotion estimation function to develop an algorithm that adjusts the timing and format of subtitle display according to the user's emotional state. For example, it displays subtitles in soft colors when the user is relaxed. This makes it possible to display subtitles according to the user's emotional state.

[0064] The hearing aid function can amplify sounds in real time according to the user's hearing characteristics. For example, the hearing aid function uses the hearing aid function to amplify sounds in real time according to the user's hearing characteristics. For example, for a user who has difficulty hearing high-pitched sounds, the high-pitched sounds can be emphasized and amplified. The hearing aid function also builds a system in which AI analyzes the user's hearing characteristics data and performs sound amplification in real time. For example, this can be used to make conversations clearer in noisy environments. The hearing aid function also develops an algorithm that uses the hearing aid function to perform sound amplification in real time according to the user's hearing characteristics. For example, when listening to music, the sound is amplified according to the characteristics of the music. This allows sound amplification in real time according to the user's hearing characteristics.

[0065] The hearing aid function can analyze hearing aid data and provide personalized audio filtering based on the user's hearing characteristics. For example, the hearing aid function analyzes hearing aid data and provides personalized audio filtering based on the user's hearing characteristics. For example, filtering can be performed to emphasize specific frequency bands. The hearing aid function also builds a system in which AI analyzes hearing aid data and provides audio filtering based on the user's hearing characteristics. For example, it can suppress background noise while making conversation clearer. The hearing aid function also develops an algorithm that provides personalized audio filtering tailored to the user's hearing characteristics based on the hearing aid data. For example, it can preferentially amplify specific sound sources. This makes it possible to provide personalized audio filtering based on the user's hearing characteristics.

[0066] The hearing aid function can use the emotion estimation function to automatically adjust the tone and volume of a voice according to the user's emotional state. For example, the hearing aid function uses the emotion estimation function to automatically adjust the tone and volume of a voice according to the user's emotional state. For example, when the user is relaxed, the tone of the voice is softened and the volume is lowered. The hearing aid function also analyzes the user's emotional state in real time and builds a system that automatically adjusts the tone and volume of a voice. For example, when the user is concentrating, the tone of the voice is made clear and the volume is adjusted appropriately. The hearing aid function also uses the emotion estimation function to develop an algorithm that automatically adjusts the tone and volume of a voice according to the user's emotional state. For example, when the user is feeling stressed, the tone of the voice is softened and the volume is lowered. This makes it possible to adjust the voice according to the user's emotional state.

[0067] The hearing aid function can amplify a specific sound source preferentially. For example, the hearing aid function adds a function to amplify a specific sound source (e.g., a specific person's voice) preferentially. For example, to make a speaker's voice clearer during a meeting, the hearing aid function may preferentially amplify the speaker's voice. The hearing aid function may also provide an interface that allows the user to select a specific sound source, and the hearing aid function may preferentially amplify that sound source. For example, a setting may be made to preferentially amplify the voices of family members. The hearing aid function may also develop an algorithm to preferentially amplify a specific sound source. For example, to make a specific person's voice clearer in a noisy environment, background noise may be suppressed. This allows important sounds to be heard clearly by preferentially amplifying a specific sound source.

[0068] The hearing aid function can filter environmental sounds and amplify only the sounds the user needs. For example, the hearing aid function adds a function to filter environmental sounds and amplify only the sounds the user needs. For example, background noise can be suppressed to make conversations clearer in noisy places. The hearing aid function also builds a system that uses AI to analyze environmental sounds and provide a filtering function that amplifies only the sounds the user needs. For example, it amplifies conversations while suppressing office noise. The hearing aid function also develops an algorithm that filters environmental sounds and amplifies only the sounds the user needs. For example, it can clear conversations while leaving natural sounds intact. This allows the user to hear important audio clearly by amplifying only the sounds they need.

[0069] The hearing aid function can use the emotion estimation function to automatically adjust the voice filtering settings according to the user's emotional state. The hearing aid function, for example, uses the emotion estimation function to automatically adjust the voice filtering settings according to the user's emotional state. For example, when the user is relaxed, more natural sounds are retained. The hearing aid function also builds a system that analyzes the user's emotional state in real time and automatically adjusts the voice filtering settings. For example, when the user is concentrating, the voice filtering settings are made clearer. The hearing aid function also uses the emotion estimation function to develop an algorithm that automatically adjusts the voice filtering settings according to the user's emotional state. For example, when the user is feeling stressed, background sounds are suppressed. This makes it possible to set voice filtering according to the user's emotional state.

[0070] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0071] The audio glasses system can further include a health management unit that monitors the user's health condition. For example, the health management unit can measure the user's heart rate and blood pressure and issue an alert if an abnormality is detected. The health management unit can also record the user's number of steps and calories burned to support daily health management. Furthermore, the health management unit can analyze the user's sleep patterns and provide advice to promote quality sleep. This allows the audio glasses system to comprehensively support the user's health condition.

[0072] The audio glasses system may further include a location information acquisition unit that acquires the user's location information. For example, the location information acquisition unit may use GPS to identify the user's current location and display it on a map. The location information acquisition unit may also record a history of places the user has visited so that the history can be referenced later. Furthermore, if the user becomes lost, the location information acquisition unit may provide guidance to the nearest safe place or a route to the user's destination. In this way, the audio glasses system can utilize the user's location information to provide a more convenient and safe experience.

[0073] The audio glasses system may further include an activity recording unit that records the user's activities. For example, the activity recording unit may record the amount and duration of the user's exercise and provide daily activity data. The activity recording unit may also analyze the user's exercise patterns and provide advice to promote healthy lifestyle habits. Furthermore, the activity recording unit may evaluate the user's goal achievement level based on the user's activity data and provide feedback to increase motivation. In this way, the audio glasses system can support the user's healthy lifestyle.

[0074] The audio glasses system can further analyze the user's emotional state and provide audio content with a relaxing effect. For example, using the emotion estimation function, when the user is feeling stressed, relaxing music or natural sounds can be played. Also, using the emotion estimation function, when the user is tired, audio content with a refreshing effect can be provided. Furthermore, using the emotion estimation function, when the user is concentrating, audio content to improve concentration can be provided. In this way, the audio glasses system can provide audio content according to the user's emotional state and support relaxation and concentration.

[0075] The audio glasses system can also analyze the user's emotional state and provide appropriate feedback. For example, using the emotion estimation function, it can display an encouraging message when the user is feeling positive. It can also use the emotion estimation function to provide advice on how to relax when the user is feeling negative. It can also use the emotion estimation function to suggest breathing exercises or relaxation techniques to reduce stress when the user is feeling stressed. This allows the audio glasses system to provide feedback according to the user's emotional state and support mental health.

[0076] The audio glasses system can also analyze the user's emotional state and suggest appropriate exercises. For example, using the emotion estimation function, when a user is feeling stressed, it can suggest relaxing yoga or stretching. Also, using the emotion estimation function, when a user is feeling energetic, it can suggest cardio exercises or running. Furthermore, using the emotion estimation function, it can suggest light walking or relaxation exercises when a user is tired. In this way, the audio glasses system can suggest exercises according to the user's emotional state and support a healthy lifestyle.

[0077] The audio glasses system can also analyze the user's emotional state and provide appropriate learning content. For example, by using the emotion estimation function, when the user is relaxed, it can provide content that allows the user to learn while relaxing. Also, by using the emotion estimation function, it can provide learning content that helps the user to improve their concentration when they are concentrating. Furthermore, by using the emotion estimation function, it can provide light learning content or content to refresh the user when they are tired. In this way, the audio glasses system can provide learning content that suits the user's emotional state and support effective learning.

[0078] The audio glasses system can further analyze the user's emotional state and suggest an appropriate communication method. For example, by using the emotion estimation function, when the user is nervous, a communication method to help the user relax can be suggested. Also, by using the emotion estimation function, when the user is angry, a communication method to help the user calm down can be suggested. Furthermore, by using the emotion estimation function, when the user is sad, a communication method to comfort the user can be suggested. In this way, the audio glasses system can suggest a communication method according to the user's emotional state and support smooth communication.

[0079] The audio glasses system can further analyze the user's visual information and provide visual feedback. For example, the audio glasses system can analyze the visual information to highlight the color or shape of the object the user is looking at. The audio glasses system can also analyze the visual information to display detailed information about the object the user is looking at. The audio glasses system can also analyze the visual information to provide relevant information about the object the user is looking at. In this way, the audio glasses system can utilize the user's visual information to provide a richer visual experience.

[0080] The audio glasses system can further analyze the user's voice commands and support voice operations. For example, it can analyze the voice commands and perform the operations instructed by the user. It can also analyze the voice commands and provide information requested by the user. It can also analyze the voice commands and automatically perform tasks set by the user. In this way, the audio glasses system can utilize the user's voice commands to provide a more convenient operation experience.

[0081] The processing flow of the second embodiment will be briefly explained below.

[0082] Step 1: The audio amplifier amplifies the sound. For example, the audio amplifier analyzes the surrounding sounds and amplifies only the necessary sounds. It can also emphasize and amplify specific frequency bands, and amplify sounds according to the user's hearing characteristics. Step 2: The viewpoint recognition unit recognizes the user's viewpoint. For example, it identifies the user's viewpoint using eye tracking technology. It can also recognize the user's viewpoint using a camera, and identify the object the user is focusing on. Step 3: The translation unit translates the speech in different languages. For example, it can translate speech in different languages ​​in real time and translate it into the user's native language. It can also output the translated speech. Step 4: The subtitle display unit converts the audio into text and displays it. For example, it can convert audio into text in real time and display the text in the user's field of view. It can also analyze the subtitle data to provide supplemental information.

[0083] 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.

[0084] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0085] 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.

[0086] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0087] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0088] 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.

[0089] 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.

[0090] 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.

[0091] 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).

[0092] 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.

[0093] 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.

[0094] 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.

[0095] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0096] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0097] 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.

[0098] 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.

[0099] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0100] 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.

[0101] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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).

[0107] 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.

[0108] 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.

[0109] 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.

[0110] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0111] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0112] 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.

[0113] 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.

[0114] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0115] 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.

[0116] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0117] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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).

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0127] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0128] 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.

[0129] 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.

[0130] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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).

[0136] 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.

[0137] 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."

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0150] 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. an audio amplifier unit that amplifies audio; a viewpoint recognition unit that recognizes a viewpoint of a user; a translation unit that translates audio between different languages; A subtitle display unit converts the audio into text and displays it. A system characterized by:

2. The audio amplifier unit Analyzes surrounding sounds and adjusts specific frequency bands in real time to optimize them to the user's hearing characteristics.

2. The system of claim 1.

3. The viewpoint recognition unit Providing detailed information on the subject of the user's attention in real time 2. The system of claim 1.

4. The translation unit The speech in the different languages ​​is translated in real time and output in the user's native language.

2. The system of claim 1.

5. The subtitle display unit Converting the speech into text in real time and displaying it in the user's field of view 2. The system of claim 1.

6. The audio amplifier unit Automatically adjust the tone and volume of the audio according to the emotional state of the user.

2. The system of claim 1.

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