System

Abstract

An object of a system according to an embodiment is to smoothly perform communication between people who speak different languages.SOLUTION: A system according to an embodiment includes a noise cancelling unit, a translating unit, and a 3D audio unit. The noise canceling unit cancels external sound. The translation unit translates the voice canceled by the noise canceling unit. The 3D audio unit spatially reproduces the voice translated by the translating unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has had the problem of making it difficult for people who speak different languages ​​to communicate smoothly.

[0005] The system according to the embodiment aims to facilitate smooth communication between people who speak different languages. [Means for solving the problem]

[0006] The system according to the embodiment includes a noise canceling unit, a translation unit, and a 3D audio unit. The noise canceling unit cancels external sounds. The translation unit translates the sounds canceled by the noise canceling unit. The 3D audio unit spatially reproduces the sounds translated by the translation unit. [Effects of the Invention]

[0007] The system according to the embodiment enables smooth communication between people who speak different languages. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

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

[0028] (Example 1) The machine-translating audio glasses system according to an embodiment of the present invention is a system that cancels external sounds using active noise canceling technology, translates them using a generation AI, and spatially reproduces them using 3D audio technology, thereby providing users with a natural conversation experience.

[0029] An automatic translation audio glasses system according to an embodiment includes a noise canceling unit, a translation unit, and a 3D audio unit. The noise canceling unit cancels external sounds. For example, the noise canceling unit uses active noise canceling technology to analyze external sounds in real time and generate anti-phase sound waves to cancel the noise. The noise canceling unit can also use passive noise canceling technology to physically block out sounds. The noise canceling unit also uses a generation AI to optimize the noise canceling process and provide an optimal audio environment for the user. The translation unit translates the sounds canceled by the noise canceling unit. For example, the translation unit uses a generation AI to analyze external sounds in real time and translate them instantly. The generation AI converts input speech into text using speech recognition technology and translates the text. The translated text is then converted back into speech and provided to the user. The generation AI performs translation using a text generation AI (e.g., LLM). The generation AI can also use multimodal generation AI to analyze and translate both speech and text. The 3D audio unit spatially reproduces the speech translated by the translation unit. For example, the 3D audio unit uses 3D audio technology to make the translated speech sound like it's coming from a spatially accurate location. The 3D audio unit can also use binaural audio technology to reproduce speech in three dimensions. The 3D audio unit can also dynamically adjust the direction of speech according to the user's head movement. This allows the automatic translation audio glasses system according to the embodiment to provide a natural conversation experience to the user. For example, as the user moves their head, the direction of speech changes accordingly. This allows the user to experience the conversation as if the other person were speaking in their own language.

[0030] The noise canceling unit can automatically optimize the noise canceling effect according to the surrounding environmental sounds. For example, the noise canceling unit analyzes the surrounding environmental sounds in real time and automatically optimizes the noise canceling effect. For example, the noise canceling intensity is lowered in a quiet environment and increased in a noisy environment. The noise canceling unit also incorporates a system that adjusts the noise canceling settings according to changes in the environmental sounds. For example, the noise canceling effect is optimized based on the type and volume of the environmental sounds. This allows the user to receive the optimal audio environment by optimizing the noise canceling effect according to the surrounding environmental sounds.

[0031] The translation unit can learn the user's past conversation history and provide individually optimized translations. The translation unit, for example, learns the user's past conversation history and provides individually optimized translations. For example, it learns the user's frequently used phrases and technical terms and reflects them in the translation results. The translation unit also introduces a system that learns the user's conversation patterns and language habits and improves translation accuracy. For example, it analyzes the user's past conversation history and provides individually optimized translations. The translation unit also develops an application that learns the user's past conversation history. The user provides their conversation history through the app, and the translation is optimized based on that data. In this way, translation accuracy can be improved by learning the user's past conversation history.

[0032] The 3D audio unit can dynamically adjust the direction of the sound according to the user's head movement. For example, the 3D audio unit analyzes the user's head movement in real time and dynamically adjusts the direction of the sound. For example, when the user moves their head, the direction of the sound changes accordingly. The 3D audio unit also introduces a system that dynamically adjusts the direction of the sound using a sensor that detects the user's head movement. For example, when the user turns their head, the direction of the sound changes accordingly. The 3D audio unit also develops an application that dynamically adjusts the direction of the sound based on the user's head movement. The user detects their head movement through the app and adjusts the sound based on that data. This allows the direction of the sound to be dynamically adjusted according to the user's head movement, providing a more natural sound experience.

[0033] The noise canceling unit can ensure that important sounds are not missed by emphasizing specific frequency bands. For example, the noise canceling unit can ensure that important sounds (e.g., alarm sounds) are not missed by emphasizing specific frequency bands. For example, a setting to emphasize alarm sounds or warning sounds can be added. The noise canceling unit can also introduce a system that ensures that important sounds are not missed by emphasizing specific frequency bands. For example, human voices or alarm sounds can be emphasized even during noise cancellation. The noise canceling unit can also develop an application that emphasizes specific frequency bands. The user can set important sounds through the app and have those frequency bands emphasized. This makes it possible to ensure that important sounds are not missed by emphasizing specific frequency bands.

[0034] The 3D audio unit can spatially separate the voices of multiple speakers, allowing multiple conversations to be heard simultaneously. For example, the 3D audio unit can spatially separate the voices of multiple speakers, allowing multiple conversations to be heard simultaneously. For example, during a conference, the voices of multiple speakers can be heard from different directions. The 3D audio unit also develops a system that incorporates 3D audio technology to spatially separate the voices of multiple speakers. For example, when multiple conversations are taking place simultaneously, the voices of each speaker can be heard from different directions. The 3D audio unit also develops an application that spatially separates the voices of multiple speakers. The user sets the voice of each speaker through the app, and the voices are separated based on that data. This makes it possible to spatially separate the voices of multiple speakers, allowing multiple conversations to be heard simultaneously.

[0035] The noise canceling unit can be made to be switchable on / off with a specific voice command. For example, the noise canceling unit can be operated with a voice command such as "noise canceling on" or "noise canceling off." Furthermore, a system is introduced for the noise canceling unit that enables the noise canceling function to be switched on / off using a voice command. For example, the user changes the noise canceling settings by giving voice instructions. Furthermore, an application is developed that enables the noise canceling unit to be switched on / off with a specific voice command. The user sets a voice command through the app and operates the noise canceling with that command. This allows the noise canceling to be switched on / off with a specific voice command, improving user convenience.

[0036] The translation unit can display the translated text as subtitles in real time. For example, the translation unit displays the translated text as subtitles in real time. For example, the translated text is displayed as subtitles on the lenses of the glasses during a conversation. The translation unit also implements a system for displaying translated text as subtitles in real time. For example, it translates what a user is saying in real time and displays the text as subtitles. The translation unit also develops an application for displaying translated text as subtitles in real time. The user can check the translated text through the app, and the text is displayed on the glasses. In this way, the translated text can be displayed as subtitles in real time, providing the user with visual translation information.

[0037] The 3D audio unit can also be applied to the playback of music and entertainment content, enhancing the sense of realism. The 3D audio unit can also be applied to the playback of music and entertainment content, enhancing the sense of realism. For example, music can be played in 3D audio, providing a live concert-like experience. The 3D audio unit will also develop systems that incorporate 3D audio technology into the playback of music and entertainment content. For example, the audio from movies and games can be played in 3D audio, enhancing the sense of realism. The 3D audio unit will also develop applications that use 3D audio technology to optimize the playback of music and entertainment content. Users can adjust audio settings through the app to enhance the sense of realism. This allows the application of 3D audio technology to the playback of music and entertainment content to enhance the sense of realism.

[0038] The noise canceling unit can automatically adjust the noise canceling effect according to the user's activity. The noise canceling unit automatically adjusts the noise canceling effect according to the user's activity (e.g., walking, driving). For example, the noise canceling intensity is lowered while walking and increased while driving. The noise canceling unit also incorporates a system that analyzes the user's activity in real time and automatically adjusts the noise canceling effect. For example, the noise canceling settings are changed when the user is exercising. The noise canceling unit also develops an application that automatically adjusts the noise canceling effect based on the user's activity. The user inputs their activity through the app, and the noise canceling settings are optimized based on that data. This makes it possible to provide an optimal audio environment by automatically adjusting the noise canceling effect according to the user's activity.

[0039] The translation unit can switch between formal and informal translation results according to the user's preferences. For example, the translation unit switches between formal and informal translation results according to the user's preferences. For example, it provides formal translations in business situations and informal translations in casual situations. The translation unit also introduces a system that switches between formal and informal translation results according to the user's preferences. For example, it adjusts the tone of the translation based on the preferences set by the user. The translation unit also develops an application that switches between formal and informal translation results according to the user's preferences. The user sets their preferences through the app, and the translation is optimized based on that data. This makes it possible to provide more appropriate translations by switching between formal and informal translation results according to the user's preferences.

[0040] The noise canceling unit can automatically adjust sound quality based on the shape of the user's ears. For example, the noise canceling unit detects the shape of the user's ears using a sensor and adjusts the speaker's sound quality in real time based on that data. For example, it automatically adjusts the balance of high and low frequencies according to the shape of the ears. The noise canceling unit also incorporates a system that 3D scans the shape of the ears and optimizes the speaker's acoustic characteristics based on that data. For example, it customizes the speaker's sound quality based on the shape of the ears. The noise canceling unit also develops an application that automatically adjusts sound quality based on the shape of the user's ears. The user scans the shape of their ears through the app and sends that data to the glasses to optimize the sound quality. This automatically adjusts sound quality based on the shape of the user's ears, providing an optimal audio environment.

[0041] The translation unit can perform translation in real time by utilizing a low-latency network. The translation unit, for example, performs translation in real time by utilizing a low-latency network. For example, translated audio is provided in real time during a video call. The translation unit also introduces a system that performs translation in real time during a video call by utilizing a low-latency network. For example, translated text is displayed as subtitles during a call. The translation unit also develops an application that performs translation in real time by utilizing a low-latency network. The user can check the translated audio and text during a video call through the app. In this way, smooth conversations can be achieved by performing translation in real time by utilizing a low-latency network.

[0042] The 3D audio unit can dynamically adjust the direction of the sound according to the user's head movement. For example, the 3D audio unit analyzes the user's head movement in real time and dynamically adjusts the direction of the sound. For example, when the user moves their head, the direction of the sound changes accordingly. The 3D audio unit also introduces a system that dynamically adjusts the direction of the sound using a sensor that detects the user's head movement. For example, when the user turns their head, the direction of the sound changes accordingly. The 3D audio unit also develops an application that dynamically adjusts the direction of the sound based on the user's head movement. The user detects their head movement through the app and adjusts the sound based on that data. This allows the direction of the sound to be dynamically adjusted according to the user's head movement, providing a more natural sound experience.

[0043] The noise canceling unit can ensure that important sounds are not missed by emphasizing specific frequency bands. For example, the noise canceling unit can ensure that important sounds (e.g., alarm sounds) are not missed by emphasizing specific frequency bands. For example, a setting to emphasize alarm sounds or warning sounds can be added. The noise canceling unit can also introduce a system that ensures that important sounds are not missed by emphasizing specific frequency bands. For example, human voices or alarm sounds can be emphasized even during noise cancellation. The noise canceling unit can also develop an application that emphasizes specific frequency bands. The user can set important sounds through the app and have those frequency bands emphasized. This makes it possible to ensure that important sounds are not missed by emphasizing specific frequency bands.

[0044] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0045] The noise canceling unit can emphasize specific frequency bands to ensure that important sounds are not missed. For example, a setting will be added to emphasize alarm sounds and warning sounds. The noise canceling unit will also introduce a system that emphasizes specific frequency bands to ensure that important sounds are not missed. For example, human voices and alarm sounds will be emphasized even when noise is canceled. The noise canceling unit will also develop an application that emphasizes specific frequency bands. The user will set important sounds through the app and emphasize those frequency bands. This will ensure that important sounds are not missed by emphasizing specific frequency bands.

[0046] The translation department can learn the user's past conversation history and provide individually optimized translations. For example, it can learn the user's frequently used phrases and technical terms and reflect them in the translation results. The translation department also introduces a system that learns the user's conversation patterns and language habits and improves translation accuracy. For example, it can analyze the user's past conversation history and provide individually optimized translations. The translation department also develops an application that learns the user's past conversation history. The user provides their conversation history through the app, and translations are optimized based on that data. In this way, translation accuracy can be improved by learning the user's past conversation history.

[0047] The 3D audio division can spatially separate the voices of multiple speakers, allowing multiple conversations to be heard simultaneously. For example, during a conference, the voices of multiple speakers can be heard from different directions. The 3D audio division will also develop a system that incorporates 3D audio technology to spatially separate the voices of multiple speakers. For example, when multiple conversations are taking place simultaneously, the voices of each speaker can be heard from different directions. The 3D audio division will also develop an application that spatially separates the voices of multiple speakers. Users set the voice of each speaker through the app, and the voices are separated based on that data. This spatial separation makes it possible to hear multiple conversations simultaneously.

[0048] The noise canceling unit can automatically adjust sound quality based on the shape of the user's ears. For example, it can detect the shape of the user's ears with a sensor and adjust the speaker's sound quality in real time based on that data. For example, it can automatically adjust the balance of high and low frequencies according to the shape of the ears. The noise canceling unit also incorporates a system that 3D scans the shape of the ears and optimizes the acoustic characteristics of the speakers based on that data. For example, it can customize the sound quality of the speakers based on the shape of the ears. The noise canceling unit will also develop an application that automatically adjusts sound quality based on the shape of the user's ears. The user scans the shape of their ears through the app and sends that data to the glasses to optimize the sound quality. This makes it possible to provide the optimal audio environment by automatically adjusting the sound quality based on the shape of the user's ears.

[0049] The translation department can perform translation in real time by utilizing a low-latency network. For example, translated audio can be provided in real time during a video call. The translation department also introduces a system that performs translation in real time during a video call by utilizing a low-latency network. For example, translated text can be displayed as subtitles during a call. The translation department also develops an application that performs translation in real time by utilizing a low-latency network. Users can check the translated audio and text during a video call through the app. This allows for smooth conversations by performing translation in real time by utilizing a low-latency network.

[0050] The 3D audio division will also apply this technology to the playback of music and entertainment content, enhancing the sense of realism. For example, music can be played in 3D audio, providing a live concert-like experience. The 3D audio division will also develop systems that incorporate 3D audio technology into the playback of music and entertainment content. For example, the audio from movies and games can be played in 3D audio, enhancing the sense of realism. The 3D audio division will also develop applications that use 3D audio technology to optimize the playback of music and entertainment content. Users can adjust audio settings through the app to enhance the sense of realism. This will enable the application of 3D audio technology to the playback of music and entertainment content to enhance the sense of realism.

[0051] The noise canceling unit can be made to be switchable on / off with a specific voice command. For example, it can be operated with a voice command such as "noise canceling on" or "noise canceling off." In addition, a system can be introduced for the noise canceling unit that allows the noise canceling function to be switched on / off using a voice command. For example, the user can change the noise canceling settings by giving voice instructions. In addition, an application can be developed that allows the noise canceling unit to be switched on / off with a specific voice command. The user sets a voice command through the app and operates the noise canceling with that command. This can improve user convenience by switching noise canceling on / off with a specific voice command.

[0052] The processing flow of the first embodiment will be briefly explained below.

[0053] Step 1: The noise canceling unit cancels external sounds. For example, active noise canceling technology can be used to analyze external sounds in real time and generate anti-phase sound waves to cancel the noise. Passive noise canceling technology can also be used to physically block out sound. Furthermore, generative AI can be used to optimize the noise canceling process and provide the user with the optimal audio environment. Step 2: The translation unit translates the audio canceled by the noise canceling unit. For example, it uses a generation AI to analyze external audio in real time and translate it instantly. The generation AI uses speech recognition technology to convert the input audio into text and translates that text. The translated text is converted back into audio and provided to the user. The generation AI performs the translation using a text generation AI (for example, LLM). It is also possible to use a multimodal generation AI to analyze and translate both audio and text. Step 3: The 3D audio unit spatially reproduces the audio translated by the translation unit. For example, 3D audio technology can be used to ensure the translated audio is heard from a spatially accurate location. Binaural audio technology can also be used to reproduce the audio in three dimensions. The audio direction can also be dynamically adjusted according to the user's head movement. This allows the user to experience the other person speaking in their own language.

[0054] (Example 2) The machine-translating audio glasses system according to an embodiment of the present invention is a system that cancels external sounds using active noise canceling technology, translates them using a generation AI, and spatially reproduces them using 3D audio technology, thereby providing users with a natural conversation experience.

[0055] An automatic translation audio glasses system according to an embodiment includes a noise canceling unit, a translation unit, and a 3D audio unit. The noise canceling unit cancels external sounds. For example, the noise canceling unit uses active noise canceling technology to analyze external sounds in real time and generate anti-phase sound waves to cancel the noise. The noise canceling unit can also use passive noise canceling technology to physically block out sounds. The noise canceling unit also uses a generation AI to optimize the noise canceling process and provide an optimal audio environment for the user. The translation unit translates the sounds canceled by the noise canceling unit. For example, the translation unit uses a generation AI to analyze external sounds in real time and translate them instantly. The generation AI converts input speech into text using speech recognition technology and translates the text. The translated text is then converted back into speech and provided to the user. The generation AI performs translation using a text generation AI (e.g., LLM). The generation AI can also use multimodal generation AI to analyze and translate both speech and text. The 3D audio unit spatially reproduces the speech translated by the translation unit. For example, the 3D audio unit uses 3D audio technology to make the translated speech sound like it's coming from a spatially accurate location. The 3D audio unit can also use binaural audio technology to reproduce speech in three dimensions. The 3D audio unit can also dynamically adjust the direction of speech according to the user's head movement. This allows the automatic translation audio glasses system according to the embodiment to provide a natural conversation experience to the user. For example, as the user moves their head, the direction of speech changes accordingly. This allows the user to experience the conversation as if the other person were speaking in their own language.

[0056] The noise canceling unit can automatically optimize the noise canceling effect according to the surrounding environmental sounds. For example, the noise canceling unit analyzes the surrounding environmental sounds in real time and automatically optimizes the noise canceling effect. For example, the noise canceling intensity is lowered in a quiet environment and increased in a noisy environment. The noise canceling unit also incorporates a system that adjusts the noise canceling settings according to changes in the environmental sounds. For example, the noise canceling effect is optimized based on the type and volume of the environmental sounds. This allows the user to receive the optimal audio environment by optimizing the noise canceling effect according to the surrounding environmental sounds.

[0057] The translation unit can learn the user's past conversation history and provide individually optimized translations. The translation unit, for example, learns the user's past conversation history and provides individually optimized translations. For example, it learns the user's frequently used phrases and technical terms and reflects them in the translation results. The translation unit also introduces a system that learns the user's conversation patterns and language habits and improves translation accuracy. For example, it analyzes the user's past conversation history and provides individually optimized translations. The translation unit also develops an application that learns the user's past conversation history. The user provides their conversation history through the app, and the translation is optimized based on that data. In this way, translation accuracy can be improved by learning the user's past conversation history.

[0058] The 3D audio unit can dynamically adjust the direction of the sound according to the user's head movement. For example, the 3D audio unit analyzes the user's head movement in real time and dynamically adjusts the direction of the sound. For example, when the user moves their head, the direction of the sound changes accordingly. The 3D audio unit also introduces a system that dynamically adjusts the direction of the sound using a sensor that detects the user's head movement. For example, when the user turns their head, the direction of the sound changes accordingly. The 3D audio unit also develops an application that dynamically adjusts the direction of the sound based on the user's head movement. The user detects their head movement through the app and adjusts the sound based on that data. This allows the direction of the sound to be dynamically adjusted according to the user's head movement, providing a more natural sound experience.

[0059] The noise canceling unit can ensure that important sounds are not missed by emphasizing specific frequency bands. For example, the noise canceling unit can ensure that important sounds (e.g., alarm sounds) are not missed by emphasizing specific frequency bands. For example, a setting to emphasize alarm sounds or warning sounds can be added. The noise canceling unit can also introduce a system that ensures that important sounds are not missed by emphasizing specific frequency bands. For example, human voices or alarm sounds can be emphasized even during noise cancellation. The noise canceling unit can also develop an application that emphasizes specific frequency bands. The user can set important sounds through the app and have those frequency bands emphasized. This makes it possible to ensure that important sounds are not missed by emphasizing specific frequency bands.

[0060] The translation unit can reflect the speaker's emotions and tone in the translated audio. For example, the translation unit reflects the speaker's emotions and tone in the translated audio. For example, if the speaker is happy, the translated audio will be played in a happy tone. The translation unit also introduces a system that analyzes the speaker's emotions and tone in real time and reflects them in the translated audio. For example, if the speaker is angry, the translated audio will be played in an angry tone. The translation unit also develops an application that reflects the speaker's emotions and tone in the translated audio. The user inputs their emotional state through the app, and the translated audio is optimized based on that data. This allows the speaker's emotions and tone to be reflected in the translated audio, providing a more natural conversation experience.

[0061] The 3D audio unit can spatially separate the voices of multiple speakers, allowing multiple conversations to be heard simultaneously. For example, the 3D audio unit can spatially separate the voices of multiple speakers, allowing multiple conversations to be heard simultaneously. For example, during a conference, the voices of multiple speakers can be heard from different directions. The 3D audio unit also develops a system that incorporates 3D audio technology to spatially separate the voices of multiple speakers. For example, when multiple conversations are taking place simultaneously, the voices of each speaker can be heard from different directions. The 3D audio unit also develops an application that spatially separates the voices of multiple speakers. The user sets the voice of each speaker through the app, and the voices are separated based on that data. This makes it possible to spatially separate the voices of multiple speakers, allowing multiple conversations to be heard simultaneously.

[0062] The noise canceling unit can adjust the noise canceling intensity according to the user's stress level using an emotion estimation function. The noise canceling unit, for example, uses the emotion estimation function to adjust the noise canceling intensity according to the user's stress level. For example, if the user is feeling stressed, the noise canceling intensity is increased. The noise canceling unit also incorporates a system that analyzes the user's stress level in real time and adjusts the noise canceling intensity according to the user's emotion. For example, if the user is relaxed, the noise canceling intensity is reduced. The noise canceling unit also develops an application that uses the emotion estimation function to adjust the noise canceling intensity based on the user's stress level. The user inputs their stress level through the app, and the noise canceling settings are optimized based on that data. This allows the noise canceling intensity to be adjusted according to the user's stress level, providing the user with an optimal audio environment.

[0063] The translation unit uses an emotion estimation function to provide translation results that correspond to the user's emotional state, thereby conveying emotional nuances. The translation unit, for example, uses the emotion estimation function to provide translation results that correspond to the user's emotional state, thereby conveying emotional nuances. For example, if the user is sad, the translation results will reflect that emotion. The translation unit also introduces a system that analyzes the user's emotional state in real time and provides translation results that correspond to the emotion. For example, if the user is excited, the translation results will reflect that emotion. The translation unit also develops an application that uses the emotion estimation function to provide translation results based on the user's emotional state. The user inputs their emotional state through the app, and the translation is optimized based on that data. This makes it possible to convey emotional nuances by providing translation results that correspond to the user's emotional state.

[0064] The noise canceling unit can be made to be switchable on / off with a specific voice command. For example, the noise canceling unit can be operated with a voice command such as "noise canceling on" or "noise canceling off." Furthermore, a system is introduced for the noise canceling unit that enables the noise canceling function to be switched on / off using a voice command. For example, the user changes the noise canceling settings by giving voice instructions. Furthermore, an application is developed that enables the noise canceling unit to be switched on / off with a specific voice command. The user sets a voice command through the app and operates the noise canceling with that command. This allows the noise canceling to be switched on / off with a specific voice command, improving user convenience.

[0065] The translation unit can display the translated text as subtitles in real time. For example, the translation unit displays the translated text as subtitles in real time. For example, the translated text is displayed as subtitles on the lenses of the glasses during a conversation. The translation unit also implements a system for displaying translated text as subtitles in real time. For example, it translates what a user is saying in real time and displays the text as subtitles. The translation unit also develops an application for displaying translated text as subtitles in real time. The user can check the translated text through the app, and the text is displayed on the glasses. In this way, the translated text can be displayed as subtitles in real time, providing the user with visual translation information.

[0066] The 3D audio unit can also be applied to the playback of music and entertainment content, enhancing the sense of realism. The 3D audio unit can also be applied to the playback of music and entertainment content, enhancing the sense of realism. For example, music can be played in 3D audio, providing a live concert-like experience. The 3D audio unit will also develop systems that incorporate 3D audio technology into the playback of music and entertainment content. For example, the audio from movies and games can be played in 3D audio, enhancing the sense of realism. The 3D audio unit will also develop applications that use 3D audio technology to optimize the playback of music and entertainment content. Users can adjust audio settings through the app to enhance the sense of realism. This allows the application of 3D audio technology to the playback of music and entertainment content to enhance the sense of realism.

[0067] The noise canceling unit can automatically adjust the noise canceling effect according to the user's activity. The noise canceling unit automatically adjusts the noise canceling effect according to the user's activity (e.g., walking, driving). For example, the noise canceling intensity is lowered while walking and increased while driving. The noise canceling unit also incorporates a system that analyzes the user's activity in real time and automatically adjusts the noise canceling effect. For example, the noise canceling settings are changed when the user is exercising. The noise canceling unit also develops an application that automatically adjusts the noise canceling effect based on the user's activity. The user inputs their activity through the app, and the noise canceling settings are optimized based on that data. This makes it possible to provide an optimal audio environment by automatically adjusting the noise canceling effect according to the user's activity.

[0068] The translation unit can switch between formal and informal translation results according to the user's preferences. For example, the translation unit switches between formal and informal translation results according to the user's preferences. For example, it provides formal translations in business situations and informal translations in casual situations. The translation unit also introduces a system that switches between formal and informal translation results according to the user's preferences. For example, it adjusts the tone of the translation based on the preferences set by the user. The translation unit also develops an application that switches between formal and informal translation results according to the user's preferences. The user sets their preferences through the app, and the translation is optimized based on that data. This makes it possible to provide more appropriate translations by switching between formal and informal translation results according to the user's preferences.

[0069] The 3D audio unit can use the emotion estimation function to play natural and environmental sounds in 3D audio when the user is relaxing. For example, the 3D audio unit uses the emotion estimation function to play natural and environmental sounds in 3D audio when the user is relaxing. For example, when it detects that the user is relaxed, it plays the sounds of waves and wind in 3D audio. The 3D audio unit also introduces a system that analyzes the user's emotional state in real time and plays natural and environmental sounds in 3D audio when the user is relaxing. For example, when the user is relaxing, it plays the sounds of a forest or rain in 3D audio. The 3D audio unit also develops an application that uses the emotion estimation function to play natural and environmental sounds in 3D audio based on the user's relaxation state. The user inputs their relaxation state through the app, and the sound is played based on that data. This allows the user to enjoy a more comfortable audio environment by playing natural and environmental sounds in 3D audio when they are relaxing.

[0070] The noise canceling unit can automatically adjust sound quality based on the shape of the user's ears. For example, the noise canceling unit detects the shape of the user's ears using a sensor and adjusts the speaker's sound quality in real time based on that data. For example, it automatically adjusts the balance of high and low frequencies according to the shape of the ears. The noise canceling unit also incorporates a system that 3D scans the shape of the ears and optimizes the speaker's acoustic characteristics based on that data. For example, it customizes the speaker's sound quality based on the shape of the ears. The noise canceling unit also develops an application that automatically adjusts sound quality based on the shape of the user's ears. The user scans the shape of their ears through the app and sends that data to the glasses to optimize the sound quality. This automatically adjusts sound quality based on the shape of the user's ears, providing an optimal audio environment.

[0071] The translation unit can perform translation in real time by utilizing a low-latency network. The translation unit, for example, performs translation in real time by utilizing a low-latency network. For example, translated audio is provided in real time during a video call. The translation unit also introduces a system that performs translation in real time during a video call by utilizing a low-latency network. For example, translated text is displayed as subtitles during a call. The translation unit also develops an application that performs translation in real time by utilizing a low-latency network. The user can check the translated audio and text during a video call through the app. In this way, smooth conversations can be achieved by performing translation in real time by utilizing a low-latency network.

[0072] The 3D audio unit can dynamically adjust the direction of the sound according to the user's head movement. For example, the 3D audio unit analyzes the user's head movement in real time and dynamically adjusts the direction of the sound. For example, when the user moves their head, the direction of the sound changes accordingly. The 3D audio unit also introduces a system that dynamically adjusts the direction of the sound using a sensor that detects the user's head movement. For example, when the user turns their head, the direction of the sound changes accordingly. The 3D audio unit also develops an application that dynamically adjusts the direction of the sound based on the user's head movement. The user detects their head movement through the app and adjusts the sound based on that data. This allows the direction of the sound to be dynamically adjusted according to the user's head movement, providing a more natural sound experience.

[0073] The noise canceling unit can ensure that important sounds are not missed by emphasizing specific frequency bands. For example, the noise canceling unit can ensure that important sounds (e.g., alarm sounds) are not missed by emphasizing specific frequency bands. For example, a setting to emphasize alarm sounds or warning sounds can be added. The noise canceling unit can also introduce a system that ensures that important sounds are not missed by emphasizing specific frequency bands. For example, human voices or alarm sounds can be emphasized even during noise cancellation. The noise canceling unit can also develop an application that emphasizes specific frequency bands. The user can set important sounds through the app and have those frequency bands emphasized. This makes it possible to ensure that important sounds are not missed by emphasizing specific frequency bands.

[0074] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0075] The noise canceling unit can emphasize specific frequency bands to ensure that important sounds are not missed. For example, a setting will be added to emphasize alarm sounds and warning sounds. The noise canceling unit will also introduce a system that emphasizes specific frequency bands to ensure that important sounds are not missed. For example, human voices and alarm sounds will be emphasized even when noise is canceled. The noise canceling unit will also develop an application that emphasizes specific frequency bands. The user will set important sounds through the app and emphasize those frequency bands. This will ensure that important sounds are not missed by emphasizing specific frequency bands.

[0076] The translation department can learn the user's past conversation history and provide individually optimized translations. For example, it can learn the user's frequently used phrases and technical terms and reflect them in the translation results. The translation department also introduces a system that learns the user's conversation patterns and language habits and improves translation accuracy. For example, it can analyze the user's past conversation history and provide individually optimized translations. The translation department also develops an application that learns the user's past conversation history. The user provides their conversation history through the app, and translations are optimized based on that data. In this way, translation accuracy can be improved by learning the user's past conversation history.

[0077] The 3D audio division can spatially separate the voices of multiple speakers, allowing multiple conversations to be heard simultaneously. For example, during a conference, the voices of multiple speakers can be heard from different directions. The 3D audio division will also develop a system that incorporates 3D audio technology to spatially separate the voices of multiple speakers. For example, when multiple conversations are taking place simultaneously, the voices of each speaker can be heard from different directions. The 3D audio division will also develop an application that spatially separates the voices of multiple speakers. Users set the voice of each speaker through the app, and the voices are separated based on that data. This spatial separation makes it possible to hear multiple conversations simultaneously.

[0078] The noise canceling unit can use the emotion estimation function to adjust the noise canceling intensity according to the user's stress level. For example, if the user is feeling stressed, the noise canceling intensity is increased. The noise canceling unit also introduces a system that analyzes the user's stress level in real time and adjusts the noise canceling intensity according to the user's emotion. For example, if the user is relaxed, the noise canceling intensity is reduced. The noise canceling unit also develops an application that uses the emotion estimation function to adjust the noise canceling intensity based on the user's stress level. The user inputs their stress level through the app, and the noise canceling settings are optimized based on that data. This allows the noise canceling intensity to be adjusted according to the user's stress level, providing the user with the optimal audio environment.

[0079] The translation department uses an emotion estimation function to provide translation results that correspond to the user's emotional state, allowing for the conveyance of emotional nuances. For example, if the user is sad, the translation results will reflect that emotion. The translation department also introduces a system that analyzes the user's emotional state in real time and provides translation results that correspond to that emotion. For example, if the user is excited, the translation results will reflect that emotion. The translation department also develops an application that uses the emotion estimation function to provide translation results based on the user's emotional state. The user inputs their emotional state through the app, and the translation is optimized based on that data. This allows for the conveyance of emotional nuances by providing translation results that correspond to the user's emotional state.

[0080] The 3D audio unit uses the emotion estimation function to play natural and environmental sounds in 3D audio when the user is relaxing. For example, if the system detects that the user is relaxed, it will play the sounds of waves and wind in 3D audio. The 3D audio unit also introduces a system that analyzes the user's emotional state in real time and plays natural and environmental sounds in 3D audio when the user is relaxing. For example, it will play the sounds of a forest or rain in 3D audio when the user is relaxing. The 3D audio unit also uses the emotion estimation function to develop an application that plays natural and environmental sounds in 3D audio based on the user's relaxation state. The user inputs their relaxation state through the app, and the app plays sounds based on that data. This allows the system to play natural and environmental sounds in 3D audio when the user is relaxing, providing a more comfortable audio environment.

[0081] The noise canceling unit can automatically adjust sound quality based on the shape of the user's ears. For example, it can detect the shape of the user's ears with a sensor and adjust the speaker's sound quality in real time based on that data. For example, it can automatically adjust the balance of high and low frequencies according to the shape of the ears. The noise canceling unit also incorporates a system that 3D scans the shape of the ears and optimizes the acoustic characteristics of the speakers based on that data. For example, it can customize the sound quality of the speakers based on the shape of the ears. The noise canceling unit will also develop an application that automatically adjusts sound quality based on the shape of the user's ears. The user scans the shape of their ears through the app and sends that data to the glasses to optimize the sound quality. This makes it possible to provide the optimal audio environment by automatically adjusting the sound quality based on the shape of the user's ears.

[0082] The translation department can perform translation in real time by utilizing a low-latency network. For example, translated audio can be provided in real time during a video call. The translation department also introduces a system that performs translation in real time during a video call by utilizing a low-latency network. For example, translated text can be displayed as subtitles during a call. The translation department also develops an application that performs translation in real time by utilizing a low-latency network. Users can check the translated audio and text during a video call through the app. This allows for smooth conversations by performing translation in real time by utilizing a low-latency network.

[0083] The 3D audio division will also apply this technology to the playback of music and entertainment content, enhancing the sense of realism. For example, music can be played in 3D audio, providing a live concert-like experience. The 3D audio division will also develop systems that incorporate 3D audio technology into the playback of music and entertainment content. For example, the audio from movies and games can be played in 3D audio, enhancing the sense of realism. The 3D audio division will also develop applications that use 3D audio technology to optimize the playback of music and entertainment content. Users can adjust audio settings through the app to enhance the sense of realism. This will enable the application of 3D audio technology to the playback of music and entertainment content to enhance the sense of realism.

[0084] The noise canceling unit can be made to be switchable on / off with a specific voice command. For example, it can be operated with a voice command such as "noise canceling on" or "noise canceling off." In addition, a system can be introduced for the noise canceling unit that allows the noise canceling function to be switched on / off using a voice command. For example, the user can change the noise canceling settings by giving voice instructions. In addition, an application can be developed that allows the noise canceling unit to be switched on / off with a specific voice command. The user sets a voice command through the app and operates the noise canceling with that command. This can improve user convenience by switching noise canceling on / off with a specific voice command.

[0085] The processing flow of the second embodiment will be briefly explained below.

[0086] Step 1: The noise canceling unit cancels external sounds. For example, active noise canceling technology can be used to analyze external sounds in real time and generate anti-phase sound waves to cancel the noise. Passive noise canceling technology can also be used to physically block out sound. Furthermore, generative AI can be used to optimize the noise canceling process and provide the user with the optimal audio environment. Step 2: The translation unit translates the audio canceled by the noise canceling unit. For example, it uses a generation AI to analyze external audio in real time and translate it instantly. The generation AI uses speech recognition technology to convert the input audio into text and translates that text. The translated text is converted back into audio and provided to the user. The generation AI performs the translation using a text generation AI (for example, LLM). It is also possible to use a multimodal generation AI to analyze and translate both audio and text. Step 3: The 3D audio unit spatially reproduces the audio translated by the translation unit. For example, 3D audio technology can be used to ensure the translated audio is heard from a spatially accurate location. Binaural audio technology can also be used to reproduce the audio in three dimensions. The audio direction can also be dynamically adjusted according to the user's head movement. This allows the user to experience the other person speaking in their own language.

[0087] 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.

[0088] 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.

[0089] 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.

[0090] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0091] 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.

[0092] 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.

[0093] 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.

[0094] 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.

[0095] 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).

[0096] 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.

[0097] 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.

[0098] 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.

[0099] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0100] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0101] 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.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0106] 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.

[0107] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0108] The 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.

[0109] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0110] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0111] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0112] Fig. 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.

[0113] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0114] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0115] In the headset type terminal 314, 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 headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0116] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0117] The specific processing unit 290 transmits the result of the specific processing to the 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.

[0118] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt 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.

[0119] 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.

[0120] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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).

[0126] 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.

[0127] 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.

[0128] 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.

[0129] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0130] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0131] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0132] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0133] The specific processing unit 290 transmits the result of the specific processing to the 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.

[0134] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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).

[0140] 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.

[0141] 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."

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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]

[0154] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A noise canceling unit that cancels external sounds, a translation unit that translates the voice canceled by the noise canceling unit; a 3D audio unit that spatially reproduces the audio translated by the translation unit; A system characterized by:

2. The noise canceling unit Automatically optimizes noise cancellation according to the surrounding environment 2. The system of claim 1.

3. The translation unit Learns the user's past conversation history and provides individually optimized translations 2. The system of claim 1.

4. The 3D audio unit Dynamically adjusting the direction of the audio according to the user's head movements 2. The system of claim 1.

5. The noise canceling unit Emphasizes specific frequency bands to ensure you don't miss important audio 2. The system of claim 1.

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