System

Abstract

An object of a system according to an embodiment is to enable a hearing-impaired person to visually grasp surrounding sound information.SOLUTION: A system according to an embodiment includes a directional microphone, a generation AI, and a display of smart glasses. The directional microphone collects acoustic data. The generation AI analyzes the acoustic signal collected by the directional microphone. The display of the smart glasses displays the result analyzed by the generation AI.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 technologies do not adequately provide hearing-impaired people with means to visually grasp surrounding sound information, and there is room for improvement.

[0005] The system according to the embodiment aims to enable hearing-impaired people to visually grasp surrounding sound information. [Means for solving the problem]

[0006] The system according to the embodiment includes a directional microphone, a generation AI, and a smartglasses display. The directional microphone collects acoustic data. The generation AI analyzes the acoustic data collected by the directional microphone. The smartglasses display displays the results of the analysis by the generation AI. [Effects of the Invention]

[0007] The system according to the embodiment can enable a hearing-impaired person to visually grasp surrounding sound information. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) The surrounding information visual transmission system according to an embodiment of the present invention is a system that enables hearing-impaired people to visually receive information about their surroundings. This system uses smart glasses equipped with multiple directional microphones, analyzes collected acoustic data using a generation AI, and displays the analysis results on the smart glasses. This allows hearing-impaired people to visually receive information about their surroundings, supporting communication with others and safety when out and about.

[0029] According to an embodiment, the ambient information visual transmission system includes a directional microphone, a generation AI, and a smartglasses display. The directional microphone collects acoustic data. For example, the directional microphone can concentrate on collecting sounds from a specific direction. Furthermore, the directional microphone can capture important sounds, such as the sound of a car coming from the front or a person's voice coming from the rear. The generation AI analyzes the acoustic data collected by the directional microphone. For example, the generation AI analyzes the type, direction, and distance of the sound to extract information important to the hearing impaired. The generation AI can analyze the acoustic data using a text generation AI (e.g., LLM) or a multimodal generation AI. The generation AI identifies, for example, the sound of a car engine, a human voice, an alarm sound, etc., and analyzes the direction and distance of each sound. The smartglasses display displays the results of the analysis by the generation AI. For example, the smartglasses display displays the type, direction, and distance of the sound. When a car is approaching from the front, the smartglasses display displays a car icon along with the distance. When a person is approaching from the rear, the smartglasses display displays a person icon along with the distance. As a result, the surrounding information visual transmission system according to the embodiment allows the hearing impaired person to visually receive surrounding information, for example, when a vehicle is approaching ahead or when a person is approaching from behind, and other important information can be visually grasped.

[0030] Directional microphones are placed in the front, back, left and right directions, and the position of the sound source can be determined by triangulation. Directional microphones are placed in the front, back, left and right directions, and the position of the sound source can be determined by triangulation. For example, we will increase the number of directional microphones installed in smart glasses and develop an algorithm to determine the position of the sound source with higher accuracy. This will enable the position of the sound source to be determined with high accuracy.

[0031] The directional microphone is customized to fit the shape of the user's head, maximizing the efficiency of collecting acoustic data. For example, 3D scanning technology can be used to analyze the shape of the user's head and design the optimal microphone placement, thereby maximizing the efficiency of collecting acoustic data.

[0032] The generating AI can analyze the acoustic data in real time and provide the user with the latest ambient information. The generating AI can, for example, analyze the acoustic data in real time and provide the user with the latest ambient information. For example, the generating AI can be used to update the analysis results of the acoustic data in real time and provide the user with the latest ambient information. This allows the user to be provided with the latest ambient information.

[0033] The generation AI can compare the results of the analysis of the acoustic data with the user's past behavioral history and display a predictive warning. For example, the generation AI can compare the results of the analysis of the acoustic data with the user's past behavioral history and display a predictive warning. For example, the generation AI can compare the results of the analysis of the acoustic data with the user's past behavioral history and display a predictive warning. In this way, by displaying a predictive warning, the safety of the user can be ensured.

[0034] Generative AI can integrate and analyze acoustic data and other sensor data to provide more multifaceted information about the surroundings. Generative AI can, for example, integrate and analyze acoustic data and other sensor data to provide more multifaceted information about the surroundings. For example, generative AI can be used to integrate and analyze acoustic data and other sensor data. This allows for more multifaceted information about the surroundings.

[0035] The smart glasses display can display the analysis results as a 3D hologram, allowing the user to intuitively grasp the situation around them.The smart glasses display can, for example, display the analysis results as a 3D hologram, allowing the user to intuitively grasp the situation around them.For example, the smart glasses display can display the analysis results as a 3D hologram, allowing the user to intuitively grasp the situation around them.

[0036] The display of the smart glasses can dynamically display the analysis results in response to the movement of the user's line of sight, so that the necessary information is always within the field of view.The display of the smart glasses can dynamically display the analysis results in response to the movement of the user's line of sight, so that the necessary information is always within the field of view.For example, the display of the smart glasses can dynamically display the analysis results in response to the movement of the user's line of sight, so that the necessary information is always within the field of view.

[0037] Smart glasses can provide more detailed information about the surroundings by adding a camera and integrating and analyzing audio and video data.Smart glasses can provide more detailed information about the surroundings by adding a camera and integrating and analyzing audio and video data.For example, smart glasses can provide more detailed information about the surroundings by adding a camera and integrating and analyzing audio and video data.

[0038] The smart glasses are equipped with a vibration motor and can transmit warnings by vibration based on acoustic data.The smart glasses are equipped with, for example, a vibration motor and can transmit warnings by vibration based on acoustic data.For example, the smart glasses are equipped with a vibration motor and can transmit warnings by vibration based on acoustic data.This makes it possible to transmit warnings by vibration.

[0039] Generative AI can automatically translate the results of acoustic data analysis into different languages, building a system that can accommodate international users. Generative AI can, for example, automatically translate the results of acoustic data analysis into different languages, building a system that can accommodate international users. For example, generative AI can be used to build a system that automatically translates the results of acoustic data analysis into different languages. This makes it possible to build a system that can accommodate international users.

[0040] The smart glasses display can be equipped with an audio feedback function to provide the analysis results, making it possible to provide information both visually and audibly.The smart glasses display can be equipped with an audio feedback function to provide the analysis results, making it possible to provide information both visually and audibly.For example, the smart glasses display can be equipped with an audio feedback function to provide the analysis results, making it possible to provide information both visually and audibly.

[0041] The smart glasses display can link the analysis results with smartphones and tablets, allowing information to be shared across multiple devices.The smart glasses display can link the analysis results with smartphones and tablets, allowing information to be shared across multiple devices.For example, a function can be added to the smart glasses display to link the analysis results with smartphones and tablets, allowing information to be shared across multiple devices.

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

[0043] The surrounding information visual transmission system may include a gait analysis unit that analyzes the user's walking pattern. For example, the gait analysis unit may analyze the user's walking speed, stride length, and walking rhythm to detect abnormal walking patterns. This may enable a warning to be displayed if the user is likely to fall or if fatigue has accumulated. The gait analysis unit may also record the user's walking pattern and use the information for long-term health management. Furthermore, the gait analysis unit may compare the user's walking pattern with that of other users to evaluate the user's health condition.

[0044] The ambient information visual transmission system may include a heart rate monitoring unit that monitors the user's heart rate. For example, the heart rate monitoring unit may measure the user's heart rate in real time and detect abnormal heart rates. This may enable a warning to be displayed if the user is feeling stressed or unwell. The heart rate monitoring unit may also record the user's heart rate data and use the data for long-term health management. Furthermore, the heart rate monitoring unit may compare the user's heart rate data with that of other users to evaluate the user's health condition.

[0045] The ambient information visual transmission system may include an eye-gaze tracking unit that tracks the user's gaze. For example, the eye-gaze tracking unit may track the user's gaze movements in real time and prioritize displaying information related to the direction in which the user is focusing. This allows the user to quickly obtain the information they need. The eye-gaze tracking unit may also record the user's gaze data and analyze visual attention patterns. Furthermore, the eye-gaze tracking unit may compare the user's gaze data with that of other users to evaluate visual attention.

[0046] The ambient information visual transmission system may include a body temperature monitoring unit that monitors the user's body temperature. For example, the body temperature monitoring unit may measure the user's body temperature in real time and detect abnormal body temperatures. This may enable a warning to be displayed if the user has a fever or is feeling unwell. The body temperature monitoring unit may also record the user's body temperature data and use this data for long-term health management. Furthermore, the body temperature monitoring unit may compare the user's body temperature data with that of other users to evaluate the user's health condition.

[0047] The ambient information visual transmission system may include a posture monitoring unit that monitors the user's posture. For example, the posture monitoring unit may measure the user's posture in real time and detect abnormal posture. This may result in a warning being displayed if the user maintains the same posture for a long period of time or if the user's posture is poor. The posture monitoring unit may also record the user's posture data and use it for long-term health management. Furthermore, the posture monitoring unit may compare the user's posture data with that of other users to evaluate their posture.

[0048] The ambient information visual transmission system may include a sleep monitoring unit that monitors the user's sleep patterns. For example, the sleep monitoring unit may analyze the user's sleep duration and sleep quality to detect abnormal sleep patterns. This may result in a warning being displayed if the user is not getting enough sleep or if the quality of their sleep is declining. The sleep monitoring unit may also record the user's sleep data and use it for long-term health management. Furthermore, the sleep monitoring unit may compare the user's sleep data with that of other users to evaluate their sleep state.

[0049] The processing flow of the first embodiment will be briefly explained below.

[0050] Step 1: A directional microphone collects acoustic data. For example, a directional microphone can focus on collecting sounds from a specific direction, ensuring that important sounds, such as the sound of a car in front or a person behind, are not missed. Step 2: The generative AI analyzes the acoustic data collected by the directional microphone. For example, the generative AI analyzes the type, direction, and distance of the sound to extract information important to the hearing impaired. The generative AI can analyze the acoustic data using text generation AI (e.g., LLM) or multimodal generative AI. The generative AI identifies sounds such as car engine sounds, human voices, and alarm sounds, and analyzes the direction and distance of each sound. Step 3: The smart glasses display shows the results of the analysis by the generative AI. For example, the smart glasses display shows the type, direction, and distance of the sound. If a car is approaching from the front, a car icon and the distance will be displayed, and if a person is approaching from behind, a person icon and the distance will be displayed.

[0051] (Example 2) The surrounding information visual transmission system according to an embodiment of the present invention is a system that enables hearing-impaired people to visually receive information about their surroundings. This system uses smart glasses equipped with multiple directional microphones, analyzes collected acoustic data using a generation AI, and displays the analysis results on the smart glasses. This allows hearing-impaired people to visually receive information about their surroundings, supporting communication with others and safety when out and about.

[0052] According to an embodiment, the ambient information visual transmission system includes a directional microphone, a generation AI, and a smartglasses display. The directional microphone collects acoustic data. For example, the directional microphone can concentrate on collecting sounds from a specific direction. Furthermore, the directional microphone can capture important sounds, such as the sound of a car coming from the front or a person's voice coming from the rear. The generation AI analyzes the acoustic data collected by the directional microphone. For example, the generation AI analyzes the type, direction, and distance of the sound to extract information important to the hearing impaired. The generation AI can analyze the acoustic data using a text generation AI (e.g., LLM) or a multimodal generation AI. The generation AI identifies, for example, the sound of a car engine, a human voice, an alarm sound, etc., and analyzes the direction and distance of each sound. The smartglasses display displays the results of the analysis by the generation AI. For example, the smartglasses display displays the type, direction, and distance of the sound. When a car is approaching from the front, the smartglasses display displays a car icon along with the distance. When a person is approaching from the rear, the smartglasses display displays a person icon along with the distance. As a result, the surrounding information visual transmission system according to the embodiment allows the hearing impaired person to visually receive surrounding information, for example, when a vehicle is approaching ahead or when a person is approaching from behind, and other important information can be visually grasped.

[0053] Directional microphones are placed in the front, back, left and right directions, and the position of the sound source can be determined by triangulation. Directional microphones are placed in the front, back, left and right directions, and the position of the sound source can be determined by triangulation. For example, we will increase the number of directional microphones installed in smart glasses and develop an algorithm to determine the position of the sound source with higher accuracy. This will enable the position of the sound source to be determined with high accuracy.

[0054] The directional microphone is customized to fit the shape of the user's head, maximizing the efficiency of collecting acoustic data. For example, 3D scanning technology can be used to analyze the shape of the user's head and design the optimal microphone placement, thereby maximizing the efficiency of collecting acoustic data.

[0055] The generating AI can analyze the acoustic data in real time and provide the user with the latest ambient information. The generating AI can, for example, analyze the acoustic data in real time and provide the user with the latest ambient information. For example, the generating AI can be used to update the analysis results of the acoustic data in real time and provide the user with the latest ambient information. This allows the user to be provided with the latest ambient information.

[0056] The generation AI can compare the results of the analysis of the acoustic data with the user's past behavioral history and display a predictive warning. For example, the generation AI can compare the results of the analysis of the acoustic data with the user's past behavioral history and display a predictive warning. For example, the generation AI can compare the results of the analysis of the acoustic data with the user's past behavioral history and display a predictive warning. In this way, by displaying a predictive warning, the safety of the user can be ensured.

[0057] Generative AI can integrate and analyze acoustic data and other sensor data to provide more multifaceted information about the surroundings. Generative AI can, for example, integrate and analyze acoustic data and other sensor data to provide more multifaceted information about the surroundings. For example, generative AI can be used to integrate and analyze acoustic data and other sensor data. This allows for more multifaceted information about the surroundings.

[0058] The smart glasses display can display the analysis results as a 3D hologram, allowing the user to intuitively grasp the situation around them.The smart glasses display can, for example, display the analysis results as a 3D hologram, allowing the user to intuitively grasp the situation around them.For example, the smart glasses display can display the analysis results as a 3D hologram, allowing the user to intuitively grasp the situation around them.

[0059] The display of the smart glasses can dynamically display the analysis results in response to the movement of the user's line of sight, so that the necessary information is always within the field of view.The display of the smart glasses can dynamically display the analysis results in response to the movement of the user's line of sight, so that the necessary information is always within the field of view.For example, the display of the smart glasses can dynamically display the analysis results in response to the movement of the user's line of sight, so that the necessary information is always within the field of view.

[0060] The smart glasses display can use an emotion estimation function to select a display method according to the user's emotional state and provide visual feedback to reduce stress. The smart glasses display can use, for example, an emotion estimation function to select a display method according to the user's emotional state and provide visual feedback to reduce stress. For example, the emotion estimation function can be used to select a display method according to the user's emotional state. This enables visual feedback to reduce stress for the user.

[0061] Smart glasses can provide more detailed information about the surroundings by adding a camera and integrating and analyzing audio and video data.Smart glasses can provide more detailed information about the surroundings by adding a camera and integrating and analyzing audio and video data.For example, smart glasses can provide more detailed information about the surroundings by adding a camera and integrating and analyzing audio and video data.

[0062] The smart glasses are equipped with a vibration motor and can transmit warnings by vibration based on acoustic data.The smart glasses are equipped with, for example, a vibration motor and can transmit warnings by vibration based on acoustic data.For example, the smart glasses are equipped with a vibration motor and can transmit warnings by vibration based on acoustic data.This makes it possible to transmit warnings by vibration.

[0063] Generative AI can automatically translate the results of acoustic data analysis into different languages, building a system that can accommodate international users. Generative AI can, for example, automatically translate the results of acoustic data analysis into different languages, building a system that can accommodate international users. For example, generative AI can be used to build a system that automatically translates the results of acoustic data analysis into different languages. This makes it possible to build a system that can accommodate international users.

[0064] The generation AI can use the emotion estimation function to analyze what emotion a user feels in response to a specific sound, and optimize the analysis algorithm for the acoustic data based on the results. The generation AI can, for example, use the emotion estimation function to analyze what emotion a user feels in response to a specific sound, and optimize the analysis algorithm for the acoustic data based on the results. For example, the generation AI can use the emotion estimation function to analyze what emotion a user feels in response to a specific sound, and optimize the analysis algorithm for the acoustic data based on the results.

[0065] The smart glasses display can be equipped with an audio feedback function to provide the analysis results, making it possible to provide information both visually and audibly.The smart glasses display can be equipped with an audio feedback function to provide the analysis results, making it possible to provide information both visually and audibly.For example, the smart glasses display can be equipped with an audio feedback function to provide the analysis results, making it possible to provide information both visually and audibly.

[0066] The smart glasses display can link the analysis results with smartphones and tablets, allowing information to be shared across multiple devices.The smart glasses display can link the analysis results with smartphones and tablets, allowing information to be shared across multiple devices.For example, a function can be added to the smart glasses display to link the analysis results with smartphones and tablets, allowing information to be shared across multiple devices.

[0067] The generation AI can use the emotion estimation function to analyze what emotions a user has toward specific information and customize the display content based on the results. The generation AI can, for example, use the emotion estimation function to analyze what emotions a user has toward specific information and customize the display content based on the results. For example, the generation AI can use the emotion estimation function to analyze what emotions a user has toward specific information and customize the display content based on the results.

[0068] The generation AI can use the emotion estimation function to provide analysis results according to the user's emotional state and provide acoustic feedback to reduce stress.The generation AI can use the emotion estimation function to provide analysis results according to the user's emotional state and provide acoustic feedback to reduce stress.For example, the generation AI can use the emotion estimation function to provide analysis results according to the user's emotional state.This makes it possible to provide acoustic feedback to reduce stress for the user.

[0069] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0070] The surrounding information visual transmission system may include a gait analysis unit that analyzes the user's walking pattern. For example, the gait analysis unit may analyze the user's walking speed, stride length, and walking rhythm to detect abnormal walking patterns. This may enable a warning to be displayed if the user is likely to fall or if fatigue has accumulated. The gait analysis unit may also record the user's walking pattern and use the information for long-term health management. Furthermore, the gait analysis unit may compare the user's walking pattern with that of other users to evaluate the user's health condition.

[0071] The ambient information visual transmission system may include a heart rate monitoring unit that monitors the user's heart rate. For example, the heart rate monitoring unit may measure the user's heart rate in real time and detect abnormal heart rates. This may enable a warning to be displayed if the user is feeling stressed or unwell. The heart rate monitoring unit may also record the user's heart rate data and use the data for long-term health management. Furthermore, the heart rate monitoring unit may compare the user's heart rate data with that of other users to evaluate the user's health condition.

[0072] The ambient information visual transmission system may include an emotion analysis unit that estimates the user's emotion and customizes the analysis results of the audio data based on the estimated emotion. For example, the emotion analysis unit estimates the user's emotion from the user's facial expression, voice, heart rate, etc., and displays a concise analysis result if the user is relaxed. Conversely, if the user is nervous, detailed analysis results can be displayed to increase the user's sense of security. The emotion analysis unit can also record the user's emotion data and monitor long-term changes in emotion. Furthermore, the emotion analysis unit can compare the user's emotion data with that of other users to evaluate the user's emotional state.

[0073] The ambient information visual transmission system may include an eye-gaze tracking unit that tracks the user's gaze. For example, the eye-gaze tracking unit may track the user's gaze movements in real time and prioritize displaying information related to the direction in which the user is focusing. This allows the user to quickly obtain the information they need. The eye-gaze tracking unit may also record the user's gaze data and analyze visual attention patterns. Furthermore, the eye-gaze tracking unit may compare the user's gaze data with that of other users to evaluate visual attention.

[0074] The ambient information visual transmission system may include a warning adjustment unit that estimates the user's emotions and adjusts the warning display method based on the estimated emotions. For example, if the user is feeling stressed, the warning adjustment unit may display the warning in a calm color or shape. Conversely, if the user is relaxed, the warning may be displayed in an emphasizing color or shape to attract the user's attention. The warning adjustment unit may also record the user's emotional data and optimize the warning display method. Furthermore, the warning adjustment unit may compare the user's emotional data with that of other users and evaluate the warning display method.

[0075] The ambient information visual transmission system may include a body temperature monitoring unit that monitors the user's body temperature. For example, the body temperature monitoring unit may measure the user's body temperature in real time and detect abnormal body temperatures. This may enable a warning to be displayed if the user has a fever or is feeling unwell. The body temperature monitoring unit may also record the user's body temperature data and use this data for long-term health management. Furthermore, the body temperature monitoring unit may compare the user's body temperature data with that of other users to evaluate the user's health condition.

[0076] The ambient information visual transmission system may include an emotion optimization unit that estimates a user's emotion and optimizes an analysis algorithm for audio data based on the estimated emotion. For example, the emotion optimization unit may analyze how the user feels about a particular sound and adjust the analysis algorithm for audio data based on the analysis results. This reduces sounds that the user finds unpleasant and provides a comfortable audio environment. The emotion optimization unit may also record the user's emotion data and use it to improve the analysis algorithm. Furthermore, the emotion optimization unit may compare the user's emotion data with that of other users and evaluate the analysis algorithm.

[0077] The ambient information visual transmission system may include a posture monitoring unit that monitors the user's posture. For example, the posture monitoring unit may measure the user's posture in real time and detect abnormal posture. This may result in a warning being displayed if the user maintains the same posture for a long period of time or if the user's posture is poor. The posture monitoring unit may also record the user's posture data and use it for long-term health management. Furthermore, the posture monitoring unit may compare the user's posture data with that of other users to evaluate their posture.

[0078] The ambient information visual transmission system may include an emotion filtering unit that estimates a user's emotion and filters audio data based on the estimated emotion. For example, if the user is feeling stressed, the emotion filtering unit may filter out specific sounds to reduce stress. Conversely, if the user is relaxed, the emotion filtering unit may emphasize specific sounds to maintain relaxation. The emotion filtering unit may also record the user's emotion data and use the data to improve the filtering algorithm. Furthermore, the emotion filtering unit may compare the user's emotion data with that of other users to evaluate the filtering algorithm.

[0079] The ambient information visual transmission system may include a sleep monitoring unit that monitors the user's sleep patterns. For example, the sleep monitoring unit may analyze the user's sleep duration and sleep quality to detect abnormal sleep patterns. This may result in a warning being displayed if the user is not getting enough sleep or if the quality of their sleep is declining. The sleep monitoring unit may also record the user's sleep data and use it for long-term health management. Furthermore, the sleep monitoring unit may compare the user's sleep data with that of other users to evaluate their sleep state.

[0080] The processing flow of the second embodiment will be briefly explained below.

[0081] Step 1: A directional microphone collects acoustic data. For example, a directional microphone can focus on collecting sounds from a specific direction, ensuring that important sounds, such as the sound of a car in front or a person behind, are not missed. Step 2: The generative AI analyzes the acoustic data collected by the directional microphone. For example, the generative AI analyzes the type, direction, and distance of the sound to extract information important to the hearing impaired. The generative AI can analyze the acoustic data using text generation AI (e.g., LLM) or multimodal generative AI. The generative AI identifies sounds such as car engine sounds, human voices, and alarm sounds, and analyzes the direction and distance of each sound. Step 3: The smart glasses display shows the results of the analysis by the generative AI. For example, the smart glasses display shows the type, direction, and distance of the sound. If a car is approaching from the front, a car icon and the distance will be displayed, and if a person is approaching from behind, a person icon and the distance will be displayed.

[0082] 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.

[0083] 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.

[0084] 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.

[0085] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0086] 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.

[0087] 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.

[0088] 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.

[0089] 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.

[0090] 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).

[0091] 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.

[0092] 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.

[0093] 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.

[0094] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0095] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0101] 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.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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).

[0106] 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.

[0107] 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.

[0108] 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.

[0109] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0110] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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).

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0126] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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).

[0135] 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.

[0136] 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."

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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]

[0149] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. Equipped with multiple directional microphones, A generation AI that analyzes the acoustic data collected by the directional microphone; A display of smart glasses that displays the results analyzed by the generation AI. A system characterized by:

2. The directional microphone is Located in the front, rear, left and right directions, Identifying the location of the sound source by triangulation 2. The system of claim 1.

3. The generated AI is The acoustic data is integrated with other sensor data for analysis; Providing more comprehensive information about the surrounding area 2. The system of claim 1.

4. The display of the smart glasses The analysis results are displayed as a 3D hologram. Allowing users to intuitively understand their surroundings 2. The system of claim 1.

5. The display of the smart glasses Select a display method according to the user's emotional state, Providing visual feedback to reduce stress 2. The system of claim 1.

6. The smart glasses include: Add a camera, By integrating and analyzing the audio data and video data, Provides more detailed information about surroundings 2. The system of claim 1.

7. The generated AI is Analyze how users feel about specific sounds, Based on the results, the analysis algorithm for the acoustic data is optimized.

2. The system of claim 1.

8. The generated AI is Provides analysis results according to the user's emotional state, Provides acoustic feedback to reduce stress 2. The system of claim 1.

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