System

Abstract

An object of a system according to an embodiment is to make it possible to use generated AI without blocking a hand or blocking a field of view.SOLUTION: A system according to an embodiment includes an eyeglass device, a voice input unit, and a display unit. The eyewear devices are equipped with a generating AI. The voice input unit receives a voice instruction from a user. The display unit displays information on the one lens on the basis of the instruction received by the voice input 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] With conventional technology, users had to operate a device such as a smartphone to use generative AI, which posed the problem of having to use their hands or blocking their view.

[0005] The system according to the embodiment aims to enable the use of generative AI without blocking hands or vision. [Means for solving the problem]

[0006] The system according to the embodiment includes an eyeglass device, a voice input unit, and a display unit. The eyeglass device is equipped with a generation AI. The voice input unit accepts voice instructions from a user. The display unit displays information on a lens of one eye based on the instructions accepted by the voice input unit. [Effects of the Invention]

[0007] The system according to the embodiment allows the user to use the generation AI without blocking their hands or their field of vision. [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 eyeglass device according to an embodiment of the present invention is a system equipped with generative AI functions, allowing users to use the functions anytime, anywhere. This system has functions such as digging deeper into the meaning of words, translating foreign language signs, and interpreting words in real time. Furthermore, the generative AI can be controlled by voice without operating a smartphone. Furthermore, since information is displayed on only one lens, it does not obstruct the user's hand or vision. This allows the eyeglass device to utilize the generative AI functions in any situation. For example, the user can translate foreign language signs while traveling or dig deeper into the meaning of words while working. Furthermore, the ability to obtain information via voice control without operating a smartphone improves convenience.

[0029] An eyeglass device according to an embodiment includes a generation AI, a voice input unit, and a display unit. The generation AI uses, for example, natural language processing or a machine learning algorithm to dig deeper into the meaning of words based on a user's voice instruction. The generation AI can also translate signs in foreign languages ​​and display the translation results. The generation AI can also interpret words in real time and display the interpretation results. The voice input unit accepts a user's voice instruction using, for example, a microphone or voice recognition technology. For example, when a user issues a voice instruction such as "Tell me the meaning of this word," the voice input unit accepts the instruction. The display unit displays information on one lens of the glasses using, for example, AR technology or display technology. For example, information analyzed by the generation AI is displayed on the lens of the glasses. This allows the user to use the functions of the generation AI based on voice instructions and display information on the lens of the glasses.

[0030] The generation AI can dig deeper into the meaning of words based on instructions received by the voice input unit and display related information on the display unit. For example, when a user inputs a specific word by voice, the generation AI analyzes the meaning of the word and provides related information. For example, if the user instructs the AI ​​to "tell me the meaning of this word," the generation AI will display the meaning of the word and related information in the lens of one eye. This allows the user to dig deeper into the meaning of words based on voice instructions and display related information.

[0031] The generation AI can translate signs in a foreign language based on instructions received by the voice input unit and display the translation results on the display unit. For example, when a user inputs a sign in a foreign language by voice, the generation AI analyzes the content of the sign and translates it into the user's native language. For example, if the user instructs the generation AI to "translate the content of this sign," the generation AI translates the content of the sign in real time and displays it in one of the lenses. This allows the user to translate signs in a foreign language based on voice instructions and display the translation results.

[0032] The generation AI can interpret words in real time based on instructions received by the voice input unit and display the interpretation results on the display unit. For example, when a user inputs a conversation in a foreign language by voice, the generation AI analyzes the content of the conversation and interprets it into the user's native language. For example, when the user instructs the generation AI to "interpret this conversation," the generation AI interprets the content of the conversation in real time and displays it in the lens of one eye. This allows the user to have words interpreted in real time based on voice instructions and display the interpretation results.

[0033] The generation AI can provide information such as the next schedule or weather forecast based on instructions received by the voice input unit and display it on the display unit. For example, when a user gives a voice command such as "Tell me my next schedule" or "Tell me the weather forecast," the generation AI provides information based on the command and displays it in the lens of one eye. This allows the user to receive and display information such as the next schedule or weather forecast based on their voice command.

[0034] The generative AI can dig deeper into the meaning of words based on instructions received through the voice input unit and display related historical background and cultural context on the display unit. For example, when a user inputs a specific word by voice, the generative AI provides not only the meaning of the word but also the related historical background and cultural context. For example, if the user inputs the word "revolution," the generative AI will display information about historical revolutionary examples and cultural influences in addition to the meaning of the word. This allows the user to dig deeper into the meaning of words and display related historical background and cultural context.

[0035] The generation AI can dig deeper into the meaning of words based on instructions received through the voice input unit and display related images and videos on the display unit. For example, when a user inputs a specific word by voice, the generation AI simultaneously displays related images and videos in addition to the meaning of the word. For example, if the user inputs the word "pyramid," the generation AI will display images of pyramids and videos of their construction process in addition to the meaning of the word. This allows the user to dig deeper into the meaning of words and display related images and videos.

[0036] Generative AI can dig deeper into the meaning of words based on instructions received through a voice input unit, and can be applied to creating educational materials and supporting student learning. For example, generative AI can apply its ability to dig deeper into word meanings to creating educational materials, automatically creating materials for teachers to use in class. For example, it can provide word meanings and background information related to specific topics. This can be applied to creating educational materials and supporting student learning.

[0037] The generation AI can translate signs in a foreign language based on instructions received by the voice input unit and display related background information and tourist information on the display unit. For example, when a user inputs a sign in a foreign language by voice, the generation AI not only translates the content of the sign, but also provides related background information and tourist information. For example, if the user instructs the generation AI to "translate the content of this sign," the generation AI will display the content of the sign as well as information about the history and tourist attractions of the location where the sign is installed. This allows the user to view related background information and tourist information in addition to the translation of the sign in a foreign language.

[0038] The generation AI can translate signs in foreign languages ​​based on instructions received by the voice input unit and suggest new related signs and information on the display unit based on past translation history. For example, the generation AI can automatically suggest new related signs and information based on the history of signs that the user has previously translated. For example, if the user instructs, "Translate the contents of this sign," the generation AI analyzes the past translation history and suggests new related signs and information. This allows the user to receive suggestions of new related signs and information based on the past translation history.

[0039] The generation AI can translate signs in foreign languages ​​based on instructions received through the voice input unit and be applied to explaining exhibits in museums and art galleries. For example, the generation AI can apply the sign translation function to explaining exhibits in museums and art galleries, providing information to visitors in multiple languages. For example, the description of an exhibit can be translated into multiple languages, and when a visitor gives a voice command, the generation AI translates the explanation and displays it in one of the lenses. This allows the user to receive explanations of exhibits in the museum or art galleries in multiple languages.

[0040] The generative AI can interpret words in real time based on instructions received through the voice input unit and display background information and cultural context of the conversation on the display unit. For example, when a user inputs a conversation in a foreign language by voice, the generative AI not only interprets the content of the conversation but also provides related background information and cultural context. For example, if a user instructs the AI ​​to "interpret this conversation," the generative AI will display the content of the conversation as well as the background and cultural information of the conversation. This allows the user to view the background information and cultural context of the conversation.

[0041] The generation AI can interpret words in real time based on instructions received by the voice input unit and suggest new related conversations or topics on the display unit based on past interpretation history. For example, the generation AI can automatically suggest new related conversations or topics based on the history of conversations that the user has interpreted in the past. For example, if the user instructs, "Interpret this conversation," the generation AI analyzes the past interpretation history and suggests new related conversations or topics. As a result, the user is suggested new related conversations or topics based on the past interpretation history.

[0042] The generative AI can interpret words in real time based on instructions received through the voice input unit, and can be applied to multilingual communication at business meetings and international conferences. For example, the generative AI can apply its real-time interpretation function to multilingual communication at business meetings and international conferences, and when participants give voice instructions, the conversation is interpreted in real time and displayed in one of the lenses. For example, if a user gives the instruction "Interpret the contents of this meeting," the generative AI will interpret and display the contents of the meeting in real time. This will support users in multilingual communication at business meetings and international conferences.

[0043] The generative AI can interpret words in real time based on instructions received by the voice input unit, and can be applied to multilingual support in medical settings. For example, the generative AI can apply its real-time interpretation function to multilingual support in medical settings, supporting communication between patients and medical staff. For example, when a patient instructs, "Please explain these symptoms," the generative AI will interpret the explanation in real time and convey it to the medical staff. This will support users in multilingual support in medical settings.

[0044] The generation AI can provide information such as the next schedule or weather forecast based on instructions received by the voice input unit, and can provide related new information or suggestions on the display unit based on past instruction history. For example, when a user issues a voice instruction, the generation AI automatically provides related new information or suggestions based on the past instruction history. For example, if the user instructs, "Tell me what's next on my schedule," the generation AI analyzes the past schedule history and displays related new schedules or suggestions. This allows the user to be provided with related new information or suggestions based on the past instruction history.

[0045] The generation AI provides information such as the next schedule or weather forecast based on instructions received by the voice input unit, and can learn the user's voice characteristics and speaking style to improve the accuracy of voice operation. For example, when a user issues a command by voice, the generation AI learns the user's voice characteristics and speaking style to improve the accuracy of voice operation. For example, if the user commands, "Tell me my next schedule," the generation AI analyzes the user's voice characteristics and understands the command more accurately. This allows the generation AI to learn the user's voice characteristics and speaking style and improve the accuracy of voice operation.

[0046] The generating AI provides information such as the next schedule or weather forecast based on instructions received by the voice input unit, and can be applied to operating smart devices and controlling home appliances in the home. For example, the generating AI applies voice operation functionality to operating smart devices in the home, controlling the device when the user gives a voice command. For example, if the user commands "Turn on the lights," the generating AI will turn on the lights. This helps the user operate smart devices and control home appliances in the home.

[0047] The generation AI provides information such as the next schedule or weather forecast based on instructions received by the voice input unit, and can be applied to in-vehicle systems and navigation systems. For example, the generation AI applies voice operation functions to in-vehicle systems and navigation systems to provide information and assist with operation while driving. For example, if you instruct the system to "tell me where the next gas station is," the generation AI will display the nearest gas station. This will assist the user in operating the in-vehicle system or navigation system.

[0048] The generative AI can customize the device design to suit the user's facial shape and eyesight based on instructions received by the voice input unit. The generative AI, for example, builds a system that allows the device design to be customized to suit the user's facial shape and eyesight. For example, when a user instructs, "Customize this device," the generative AI analyzes the user's facial shape and eyesight and provides the optimal design. This allows the device design to be customized to suit the user's facial shape and eyesight.

[0049] The generation AI can apply a design that does not obstruct the user's hands or obstruct the view to providing information during sports or outdoor activities based on instructions received through the voice input unit. For example, the generation AI applies a design that does not obstruct the user's hands or obstruct the view to providing information during sports or outdoor activities, and when the user gives a voice command, the information is displayed on the lens of one eye. For example, if the user gives the command "Tell me the next checkpoint," the generation AI will display that information. This provides support for the user in receiving information during sports or outdoor activities.

[0050] The generation AI can stylishly improve the design of a device based on instructions received by the voice input unit so that it can also be used as a fashion item. For example, the generation AI builds a system that stylishly improves the design of a device so that it can also be used as a fashion item. For example, when a user instructs, "Make this device stylish," the generation AI changes the design. As a result, the user's device is stylishly improved so that it can also be used as a fashion item.

[0051] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0052] The eyeglass device includes a generation AI, a voice input unit, and a display unit. The generation AI, for example, uses natural language processing or machine learning algorithms to dig deeper into the meaning of words based on the user's voice instructions. The generation AI can also, for example, translate signs in foreign languages ​​and display the translation results. The generation AI can also, for example, interpret words in real time and display the translation results. The voice input unit accepts the user's voice instructions using, for example, a microphone or voice recognition technology. For example, when a user vocally instructs, "Tell me the meaning of this word," the voice input unit accepts the instruction. The display unit displays information on one lens using, for example, AR technology or display technology. For example, information analyzed by the generation AI is displayed on one lens. This allows the user to use the generation AI's functions based on the voice instructions and display information on the other lens. Furthermore, the generation AI can provide detailed geographical information about a specific location based on the user's voice instructions. For example, when a user instructs, "Tell me the history of this place," the generation AI displays information about the location's historical background and tourist attractions. This allows the user to obtain detailed information about the places visited during their trip. The generation AI can also provide recipes and cooking methods for specific dishes based on the user's voice instructions. For example, if the user says, "Tell me how to make this dish," the generation AI will display the recipe and cooking method for that dish. This allows the user to obtain the information necessary to cook the dish. The generation AI can also provide the rules and tactics of specific sports based on the user's voice instructions. For example, if the user says, "Tell me the rules of this sport," the generation AI will display the rules and tactics of that sport. This allows the user to obtain the information necessary to enjoy sports.

[0053] The generation AI can dig deeper into the meaning of words based on instructions received through the voice input unit and display related information on the display unit. For example, when a user inputs a specific word via voice, the generation AI analyzes the meaning of the word and provides related information. For example, when the user instructs, "Tell me the meaning of this word," the generation AI displays the meaning of the word and related information in one eye lens. This allows the user to dig deeper into the meaning of words and display related information based on the voice instruction. Furthermore, the generation AI can provide literary works and poems related to specific words based on the user's voice instruction. For example, when a user instructs, "Tell me poems that use this word," the generation AI displays poems and literary works that include the word. This allows the user to dig deeper into the meaning of words and enjoy related literary works and poetry. The generation AI can also provide scientific research and papers related to specific words based on the user's voice instruction. For example, when a user instructs, "Tell me research on this word," the generation AI displays scientific research and papers related to the word. This allows the user to dig deeper into the meaning of words and obtain related scientific information. Furthermore, the generative AI can provide music and lyrics related to specific words based on the user's voice instructions. For example, if a user says, "Tell me a song that uses this word," the generative AI will display lyrics and music that include that word. This allows users to dig deeper into the meaning of the word and enjoy related music and lyrics.

[0054] The generation AI can translate foreign-language signs based on instructions received through the voice input unit and display the translation results on the display unit. For example, when a user voice-inputs a foreign-language sign, the generation AI analyzes the sign's content and translates it into the user's native language. For example, when a user instructs the generation AI to "translate the contents of this sign," the generation AI translates the sign's content in real time and displays it in one eye lens. This allows the user to translate foreign-language signs based on voice instructions and display the translation results. Furthermore, the generation AI can provide historical background and cultural context related to specific signs based on the user's voice instructions. For example, when a user instructs the generation AI to "tell me the background of this sign," the generation AI displays the historical background and cultural context related to the sign. This allows the user to not only understand the sign's content, but also its background and cultural meaning. The generation AI can also provide tourist information and geographical information related to specific signs based on the user's voice instructions. For example, when a user instructs the generation AI to "tell me the location of this sign," the generation AI displays tourist information and geographical information about the location of the sign. This allows users to not only understand the sign's content, but also obtain information about its location. Furthermore, the generation AI can provide event information and schedules related to a specific sign based on the user's voice instructions. For example, if a user says, "Tell me about the events on this sign," the generation AI will display event information and schedules related to that sign. This allows users to not only understand the sign's content, but also obtain information about the events.

[0055] The generation AI can interpret words in real time based on instructions received through the voice input unit and display the interpretation results on the display unit. For example, when a user speaks a conversation in a foreign language, the generation AI analyzes the content of the conversation and translates it into the user's native language. For example, when the user instructs "Interpret this conversation," the generation AI interprets the content of the conversation in real time and displays it in one eye lens. This allows the user to interpret words in real time based on their voice instructions and display the interpretation results. Furthermore, the generation AI can provide cultural background and customs related to a specific conversation based on the user's voice instructions. For example, when a user instructs "Tell me the background of this conversation," the generation AI displays cultural background and customs related to the conversation. This allows the user to not only understand the content of the conversation but also its background and cultural meaning. The generation AI can also provide historical examples and episodes related to a specific conversation based on the user's voice instructions. For example, when a user instructs "Tell me the history of this conversation," the generation AI displays historical examples and episodes related to the conversation. This allows the user to not only understand the content of the conversation but also its historical background. Furthermore, the generative AI can provide business and economic information related to a specific conversation based on the user's voice instructions. For example, if the user says, "Tell me the business information about this conversation," the generative AI will display the business and economic information related to that conversation. This allows the user to not only understand the content of the conversation, but also its business and economic meaning.

[0056] The generation AI can provide information such as the next appointment or weather forecast based on instructions received by the voice input unit and display it on the display unit. For example, when a user vocally instructs the generation AI to "tell me about my next appointment" or "tell me the weather forecast," the generation AI provides information based on the instruction and displays it on one eye lens. This allows the user to receive and display information such as the next appointment or weather forecast based on the voice instruction. Furthermore, the generation AI can provide traffic information and route guidance related to a specific appointment based on the user's voice instruction. For example, when a user instructs the generation AI to "tell me the route to the location of my next appointment," the generation AI displays traffic information and route guidance to that location. This allows the user to obtain the information needed to head to the next appointment. The generation AI can also provide weather information and weather forecast related to a specific appointment based on the user's voice instruction. For example, when a user instructs the generation AI to "tell me the weather at the location of my next appointment," the generation AI displays the weather information and weather forecast for that location. This allows the user to obtain the weather information needed to head to the next appointment. Furthermore, the generation AI can provide event information and schedules related to a specific appointment based on the user's voice instruction. For example, if a user says, "Tell me about the next scheduled event," the AI ​​will display the event information and schedule related to that event, allowing the user to obtain the event information they need when heading to their next appointment.

[0057] The generative AI can dig deeper into the meaning of words based on instructions received through the voice input unit and display related historical background and cultural context on the display unit. For example, when a user inputs a specific word via voice, the generative AI provides not only the meaning of the word but also the related historical background and cultural context. For example, if the user inputs the word "revolution," the generative AI displays information about historical revolutionary examples and their cultural influences in addition to the meaning of the word. This allows the user to dig deeper into the meaning of the word and view related historical background and cultural context. Furthermore, the generative AI can provide literary works and poems related to a specific word based on the user's voice instructions. For example, if a user instructs the AI ​​to "tell me poems that use this word," the AI ​​displays poems and literary works that include the word. This allows the user to dig deeper into the meaning of the word and enjoy related literary works and poetry. The generative AI can also provide scientific research and papers related to a specific word based on the user's voice instructions. For example, if a user instructs the AI ​​to "tell me research on this word," the AI ​​displays scientific research and papers related to the word. This allows the user to dig deeper into the meaning of the word and obtain related scientific information. Furthermore, the generative AI can provide music and lyrics related to specific words based on the user's voice instructions. For example, if a user says, "Tell me a song that uses this word," the generative AI will display lyrics and music that include that word. This allows users to dig deeper into the meaning of the word and enjoy related music and lyrics.

[0058] The generation AI can dig deeper into the meaning of words based on instructions received through the voice input unit and display related images and videos on the display unit. For example, when a user inputs a specific word by voice, the generation AI simultaneously displays related images and videos in addition to the meaning of the word. For example, if the user inputs the word "pyramid," the generation AI displays images of pyramids and videos of their construction process in addition to the meaning of the word. This allows the user to dig deeper into the meaning of the word and view related images and videos. Furthermore, the generation AI can provide artworks and photos related to specific words based on the user's voice instructions. For example, when a user instructs the generation AI to "tell me about art related to this word," the generation AI displays artworks and photos related to the word. This allows the user to dig deeper into the meaning of the word and enjoy related artworks and photos. The generation AI can also provide videos of scientific experiments and demonstrations related to specific words based on the user's voice instructions. For example, when a user instructs the generation AI to "tell me about experiments related to this word," the generation AI displays videos of scientific experiments and demonstrations related to the word. This allows users to dig deeper into the meaning of words and obtain related scientific information. Furthermore, the generative AI can also provide historical footage or documentaries related to specific words based on the user's voice instructions. For example, if a user says, "Tell me historical footage related to this word," the generative AI will display historical footage or documentaries related to that word. This allows users to dig deeper into the meaning of words and obtain related historical information.

[0059] Generative AI can dig deeper into the meaning of words based on instructions received through a voice input unit, making it applicable to creating educational materials and supporting student learning. For example, generative AI can apply its word digging capabilities to creating educational materials, automatically creating materials for teachers to use in class. For example, it can provide the meanings and background information of words related to specific topics. This can be applied to creating educational materials and supporting student learning. Furthermore, when a student voice-inputs a specific word, generative AI can automatically generate quizzes and questions related to that word. For example, if a student instructs the system to "make a quiz about this word," the generative AI can display quizzes and questions related to that word. This allows students to enjoy learning. Furthermore, when a student voice-inputs a specific word, generative AI can provide video lessons or online courses related to that word. For example, if a student instructs the system to "teach me a video lesson about this word," the generative AI can display video lessons or online courses related to that word. This allows students to progress through their studies at their own pace. Furthermore, when a student voice-inputs a specific word, generative AI can provide ideas for experiments or projects related to that word. For example, when a student says, "Tell me an experiment related to this word," the generative AI will display ideas for experiments and projects related to that word, allowing students to deepen their understanding through hands-on learning.

[0060] The processing flow of the first embodiment will be briefly explained below.

[0061] Step 1: The voice input unit receives a voice instruction from the user using a microphone and voice recognition technology. For example, if the user gives a voice instruction such as "Tell me the meaning of this word," the voice input unit receives the instruction. Step 2: The generative AI uses natural language processing and machine learning algorithms to dig deeper into the meaning of words based on the user's voice commands. The generative AI can also translate signs in foreign languages ​​and display the translation results. The generative AI can also interpret words in real time and display the translation results. Step 3: The display unit uses AR technology and display technology to display information on one of the lenses. For example, information analyzed by the generation AI is displayed on one of the lenses. This allows the user to use the generation AI's functions based on voice instructions to display information on one of the lenses.

[0062] (Example 2) The eyeglass device according to an embodiment of the present invention is a system equipped with generative AI functions, allowing users to use the functions anytime, anywhere. This system has functions such as digging deeper into the meaning of words, translating foreign language signs, and interpreting words in real time. Furthermore, the generative AI can be controlled by voice without operating a smartphone. Furthermore, since information is displayed on only one lens, it does not obstruct the user's hand or vision. This allows the eyeglass device to utilize the generative AI functions in any situation. For example, the user can translate foreign language signs while traveling or dig deeper into the meaning of words while working. Furthermore, the ability to obtain information via voice control without operating a smartphone improves convenience.

[0063] An eyeglass device according to an embodiment includes a generation AI, a voice input unit, and a display unit. The generation AI uses, for example, natural language processing or a machine learning algorithm to dig deeper into the meaning of words based on a user's voice instruction. The generation AI can also translate signs in foreign languages ​​and display the translation results. The generation AI can also interpret words in real time and display the interpretation results. The voice input unit accepts a user's voice instruction using, for example, a microphone or voice recognition technology. For example, when a user issues a voice instruction such as "Tell me the meaning of this word," the voice input unit accepts the instruction. The display unit displays information on one lens of the glasses using, for example, AR technology or display technology. For example, information analyzed by the generation AI is displayed on the lens of the glasses. This allows the user to use the functions of the generation AI based on voice instructions and display information on the lens of the glasses.

[0064] The generation AI can dig deeper into the meaning of words based on instructions received by the voice input unit and display related information on the display unit. For example, when a user inputs a specific word by voice, the generation AI analyzes the meaning of the word and provides related information. For example, if the user instructs the AI ​​to "tell me the meaning of this word," the generation AI will display the meaning of the word and related information in the lens of one eye. This allows the user to dig deeper into the meaning of words based on voice instructions and display related information.

[0065] The generation AI can translate signs in a foreign language based on instructions received by the voice input unit and display the translation results on the display unit. For example, when a user inputs a sign in a foreign language by voice, the generation AI analyzes the content of the sign and translates it into the user's native language. For example, if the user instructs the generation AI to "translate the content of this sign," the generation AI translates the content of the sign in real time and displays it in one of the lenses. This allows the user to translate signs in a foreign language based on voice instructions and display the translation results.

[0066] The generation AI can interpret words in real time based on instructions received by the voice input unit and display the interpretation results on the display unit. For example, when a user inputs a conversation in a foreign language by voice, the generation AI analyzes the content of the conversation and interprets it into the user's native language. For example, when the user instructs the generation AI to "interpret this conversation," the generation AI interprets the content of the conversation in real time and displays it in the lens of one eye. This allows the user to have words interpreted in real time based on voice instructions and display the interpretation results.

[0067] The generation AI can provide information such as the next schedule or weather forecast based on instructions received by the voice input unit and display it on the display unit. For example, when a user gives a voice command such as "Tell me my next schedule" or "Tell me the weather forecast," the generation AI provides information based on the command and displays it in the lens of one eye. This allows the user to receive and display information such as the next schedule or weather forecast based on their voice command.

[0068] The generation AI can infer emotions based on instructions received by the voice input unit and display related information on the display unit based on those emotions. For example, when a user inputs a specific word by voice, the generation AI infers the emotion associated with that word and calculates an emotion score. For example, if a user inputs the word "love," the generation AI analyzes the emotion associated with that word, and if the emotion is strong, it prioritizes displaying related positive information. This allows related information to be displayed based on the user's emotions.

[0069] The generative AI can dig deeper into the meaning of words based on instructions received through the voice input unit and display related historical background and cultural context on the display unit. For example, when a user inputs a specific word by voice, the generative AI provides not only the meaning of the word but also the related historical background and cultural context. For example, if the user inputs the word "revolution," the generative AI will display information about historical revolutionary examples and cultural influences in addition to the meaning of the word. This allows the user to dig deeper into the meaning of words and display related historical background and cultural context.

[0070] The generation AI can dig deeper into the meaning of words based on instructions received through the voice input unit and display related images and videos on the display unit. For example, when a user inputs a specific word by voice, the generation AI simultaneously displays related images and videos in addition to the meaning of the word. For example, if the user inputs the word "pyramid," the generation AI will display images of pyramids and videos of their construction process in addition to the meaning of the word. This allows the user to dig deeper into the meaning of words and display related images and videos.

[0071] Generative AI can dig deeper into the meaning of words based on instructions received through a voice input unit, and can be applied to creating educational materials and supporting student learning. For example, generative AI can apply its ability to dig deeper into word meanings to creating educational materials, automatically creating materials for teachers to use in class. For example, it can provide word meanings and background information related to specific topics. This can be applied to creating educational materials and supporting student learning.

[0072] The generation AI can estimate emotions based on instructions received by the voice input unit and display related information on the display unit to elicit positive emotions. For example, when a user inputs a specific word by voice, the generation AI estimates the emotion associated with that word and provides related information to elicit positive emotions. For example, if the word "challenge" is input, the generation AI will display success stories and encouraging messages related to that word. This allows the system to provide related information to elicit positive emotions in the user.

[0073] The generation AI can translate signs in a foreign language based on instructions received by the voice input unit, estimate emotions, and adjust the translation results. For example, when a user inputs a sign in a foreign language by voice, the generation AI estimates the emotion toward the sign's content and adjusts the translation results based on the emotion score. For example, if a user instructs the generation AI to "translate the content of this sign," the generation AI analyzes the emotion toward the sign's content and provides a positive translation result if the emotion is strongly positive. This allows the generation AI to adjust the translation results based on the user's emotions.

[0074] The generation AI can translate signs in a foreign language based on instructions received by the voice input unit and display related background information and tourist information on the display unit. For example, when a user inputs a sign in a foreign language by voice, the generation AI not only translates the content of the sign, but also provides related background information and tourist information. For example, if the user instructs the generation AI to "translate the content of this sign," the generation AI will display the content of the sign as well as information about the history and tourist attractions of the location where the sign is installed. This allows the user to view related background information and tourist information in addition to the translation of the sign in a foreign language.

[0075] The generation AI can translate signs in foreign languages ​​based on instructions received by the voice input unit and suggest new related signs and information on the display unit based on past translation history. For example, the generation AI can automatically suggest new related signs and information based on the history of signs that the user has previously translated. For example, if the user instructs, "Translate the contents of this sign," the generation AI analyzes the past translation history and suggests new related signs and information. This allows the user to receive suggestions of new related signs and information based on the past translation history.

[0076] The generation AI can translate signs in foreign languages ​​based on instructions received through the voice input unit and be applied to explaining exhibits in museums and art galleries. For example, the generation AI can apply the sign translation function to explaining exhibits in museums and art galleries, providing information to visitors in multiple languages. For example, the description of an exhibit can be translated into multiple languages, and when a visitor gives a voice command, the generation AI translates the explanation and displays it in one of the lenses. This allows the user to receive explanations of exhibits in the museum or art galleries in multiple languages.

[0077] The generation AI can translate signs in a foreign language based on instructions received by the voice input unit, estimate emotions, and display related information on the display unit to elicit positive emotions. For example, when a user inputs a sign in a foreign language by voice, the generation AI estimates emotions regarding the sign's content and provides related information to elicit positive emotions. For example, if the user instructs the generation AI to "translate the content of this sign," the generation AI displays positive information related to the sign's content. This makes it possible to provide related information to elicit positive emotions in the user.

[0078] The generation AI can interpret words in real time based on instructions received by the voice input unit and estimate emotions to adjust the interpretation results. For example, when a user inputs a conversation in a foreign language by voice, the generation AI estimates the emotions toward the content of the conversation and adjusts the interpretation results based on the emotion score. For example, if the user instructs "Interpret this conversation," the generation AI analyzes the emotions toward the content of the conversation and provides a positive interpretation result if the positive emotions are strong. This allows the interpretation results to be adjusted based on the user's emotions.

[0079] The generative AI can interpret words in real time based on instructions received through the voice input unit and display background information and cultural context of the conversation on the display unit. For example, when a user inputs a conversation in a foreign language by voice, the generative AI not only interprets the content of the conversation but also provides related background information and cultural context. For example, if a user instructs the AI ​​to "interpret this conversation," the generative AI will display the content of the conversation as well as the background and cultural information of the conversation. This allows the user to view the background information and cultural context of the conversation.

[0080] The generation AI can interpret words in real time based on instructions received by the voice input unit and suggest new related conversations or topics on the display unit based on past interpretation history. For example, the generation AI can automatically suggest new related conversations or topics based on the history of conversations that the user has interpreted in the past. For example, if the user instructs, "Interpret this conversation," the generation AI analyzes the past interpretation history and suggests new related conversations or topics. As a result, the user is suggested new related conversations or topics based on the past interpretation history.

[0081] The generative AI can interpret words in real time based on instructions received through the voice input unit, and can be applied to multilingual communication at business meetings and international conferences. For example, the generative AI can apply its real-time interpretation function to multilingual communication at business meetings and international conferences, and when participants give voice instructions, the conversation is interpreted in real time and displayed in one of the lenses. For example, if a user gives the instruction "Interpret the contents of this meeting," the generative AI will interpret and display the contents of the meeting in real time. This will support users in multilingual communication at business meetings and international conferences.

[0082] The generative AI can interpret words in real time based on instructions received by the voice input unit, and can be applied to multilingual support in medical settings. For example, the generative AI can apply its real-time interpretation function to multilingual support in medical settings, supporting communication between patients and medical staff. For example, when a patient instructs, "Please explain these symptoms," the generative AI will interpret the explanation in real time and convey it to the medical staff. This will support users in multilingual support in medical settings.

[0083] The generation AI can interpret words in real time based on instructions received by the voice input unit, estimate emotions, and display relevant information on the display unit to elicit positive emotions. For example, when a user inputs a conversation in a foreign language by voice, the generation AI estimates emotions regarding the content of the conversation and provides relevant information to elicit positive emotions. For example, if the user instructs the AI ​​to "interpret this conversation," the generation AI will display positive information related to the content of the conversation. This makes it possible to provide relevant information to elicit positive emotions in the user.

[0084] The generative AI can provide information such as the next schedule or weather forecast based on instructions received through the voice input unit, and can estimate emotions and adjust responses accordingly. For example, when a user gives a command by voice, the generative AI estimates the emotion associated with the command and adjusts the response based on the emotion score. For example, if the user says, "Tell me what my next schedule is," the generative AI will analyze the user's emotion and respond in a brighter tone if the emotion is strongly positive. This allows the response to be adjusted based on the user's emotion.

[0085] The generation AI can provide information such as the next schedule or weather forecast based on instructions received by the voice input unit, and can provide related new information or suggestions on the display unit based on past instruction history. For example, when a user issues a voice instruction, the generation AI automatically provides related new information or suggestions based on the past instruction history. For example, if the user instructs, "Tell me what's next on my schedule," the generation AI analyzes the past schedule history and displays related new schedules or suggestions. This allows the user to be provided with related new information or suggestions based on the past instruction history.

[0086] The generation AI provides information such as the next schedule or weather forecast based on instructions received by the voice input unit, and can learn the user's voice characteristics and speaking style to improve the accuracy of voice operation. For example, when a user issues a command by voice, the generation AI learns the user's voice characteristics and speaking style to improve the accuracy of voice operation. For example, if the user commands, "Tell me my next schedule," the generation AI analyzes the user's voice characteristics and understands the command more accurately. This allows the generation AI to learn the user's voice characteristics and speaking style and improve the accuracy of voice operation.

[0087] The generating AI provides information such as the next schedule or weather forecast based on instructions received by the voice input unit, and can be applied to operating smart devices and controlling home appliances in the home. For example, the generating AI applies voice operation functionality to operating smart devices in the home, controlling the device when the user gives a voice command. For example, if the user commands "Turn on the lights," the generating AI will turn on the lights. This helps the user operate smart devices and control home appliances in the home.

[0088] The generation AI provides information such as the next schedule or weather forecast based on instructions received by the voice input unit, and can be applied to in-vehicle systems and navigation systems. For example, the generation AI applies voice operation functions to in-vehicle systems and navigation systems to provide information and assist with operation while driving. For example, if you instruct the system to "tell me where the next gas station is," the generation AI will display the nearest gas station. This will assist the user in operating the in-vehicle system or navigation system.

[0089] The generation AI can provide information such as the next schedule or weather forecast based on instructions received by the voice input unit, and can estimate emotions and display related information on the display unit to elicit positive emotions. For example, when a user gives a voice instruction, the generation AI estimates the emotion associated with the instruction and provides related information to elicit positive emotions. For example, if the instruction is "Tell me my next schedule," the generation AI analyzes the user's emotions, and if the positive emotion is strong, it displays related positive information. This makes it possible to provide related information to elicit positive emotions from the user.

[0090] The generation AI can analyze the emotions felt while using the device based on instructions received through the voice input unit, and adjust the design and display content based on those emotions. For example, the generation AI can estimate the emotions felt by the user while using the device, and adjust the design and display content based on those emotions. For example, if the user instructs, "Change this design," the generation AI will analyze the user's emotions, and if the user's emotions are strong, it will display a brighter design. This makes it possible to adjust the design and display content based on the user's emotions.

[0091] The generative AI can customize the device design to suit the user's facial shape and eyesight based on instructions received by the voice input unit. The generative AI, for example, builds a system that allows the device design to be customized to suit the user's facial shape and eyesight. For example, when a user instructs, "Customize this device," the generative AI analyzes the user's facial shape and eyesight and provides the optimal design. This allows the device design to be customized to suit the user's facial shape and eyesight.

[0092] The generation AI can apply a design that does not obstruct the user's hands or obstruct the view to providing information during sports or outdoor activities based on instructions received through the voice input unit. For example, the generation AI applies a design that does not obstruct the user's hands or obstruct the view to providing information during sports or outdoor activities, and when the user gives a voice command, the information is displayed on the lens of one eye. For example, if the user gives the command "Tell me the next checkpoint," the generation AI will display that information. This provides support for the user in receiving information during sports or outdoor activities.

[0093] The generation AI can stylishly improve the design of a device based on instructions received by the voice input unit so that it can also be used as a fashion item. For example, the generation AI builds a system that stylishly improves the design of a device so that it can also be used as a fashion item. For example, when a user instructs, "Make this device stylish," the generation AI changes the design. As a result, the user's device is stylishly improved so that it can also be used as a fashion item.

[0094] The generation AI can analyze the emotions felt while using the device based on instructions received by the voice input unit and display relevant information on the display unit to elicit positive emotions. The generation AI, for example, estimates the emotions felt by the user while using the device and provides relevant information to elicit positive emotions based on those emotions. For example, if the user instructs "change this information," the generation AI analyzes the user's emotions and displays related positive information if the positive emotions are strong. This makes it possible to provide relevant information to elicit positive emotions from the user.

[0095] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0096] The eyeglass device includes a generation AI, a voice input unit, and a display unit. The generation AI, for example, uses natural language processing or machine learning algorithms to dig deeper into the meaning of words based on the user's voice instructions. The generation AI can also, for example, translate signs in foreign languages ​​and display the translation results. The generation AI can also, for example, interpret words in real time and display the translation results. The voice input unit accepts the user's voice instructions using, for example, a microphone or voice recognition technology. For example, when a user vocally instructs, "Tell me the meaning of this word," the voice input unit accepts the instruction. The display unit displays information on one lens using, for example, AR technology or display technology. For example, information analyzed by the generation AI is displayed on one lens. This allows the user to use the generation AI's functions based on the voice instructions and display information on the other lens. Furthermore, the generation AI can provide detailed geographical information about a specific location based on the user's voice instructions. For example, when a user instructs, "Tell me the history of this place," the generation AI displays information about the location's historical background and tourist attractions. This allows the user to obtain detailed information about the places visited during their trip. The generation AI can also provide recipes and cooking methods for specific dishes based on the user's voice instructions. For example, if the user says, "Tell me how to make this dish," the generation AI will display the recipe and cooking method for that dish. This allows the user to obtain the information necessary to cook the dish. The generation AI can also provide the rules and tactics of specific sports based on the user's voice instructions. For example, if the user says, "Tell me the rules of this sport," the generation AI will display the rules and tactics of that sport. This allows the user to obtain the information necessary to enjoy sports.

[0097] The generation AI can dig deeper into the meaning of words based on instructions received through the voice input unit and display related information on the display unit. For example, when a user inputs a specific word via voice, the generation AI analyzes the meaning of the word and provides related information. For example, when the user instructs, "Tell me the meaning of this word," the generation AI displays the meaning of the word and related information in one eye lens. This allows the user to dig deeper into the meaning of words and display related information based on the voice instruction. Furthermore, the generation AI can provide literary works and poems related to specific words based on the user's voice instruction. For example, when a user instructs, "Tell me poems that use this word," the generation AI displays poems and literary works that include the word. This allows the user to dig deeper into the meaning of words and enjoy related literary works and poetry. The generation AI can also provide scientific research and papers related to specific words based on the user's voice instruction. For example, when a user instructs, "Tell me research on this word," the generation AI displays scientific research and papers related to the word. This allows the user to dig deeper into the meaning of words and obtain related scientific information. Furthermore, the generative AI can provide music and lyrics related to specific words based on the user's voice instructions. For example, if a user says, "Tell me a song that uses this word," the generative AI will display lyrics and music that include that word. This allows users to dig deeper into the meaning of the word and enjoy related music and lyrics.

[0098] The generation AI can translate foreign-language signs based on instructions received through the voice input unit and display the translation results on the display unit. For example, when a user voice-inputs a foreign-language sign, the generation AI analyzes the sign's content and translates it into the user's native language. For example, when a user instructs the generation AI to "translate the contents of this sign," the generation AI translates the sign's content in real time and displays it in one eye lens. This allows the user to translate foreign-language signs based on voice instructions and display the translation results. Furthermore, the generation AI can provide historical background and cultural context related to specific signs based on the user's voice instructions. For example, when a user instructs the generation AI to "tell me the background of this sign," the generation AI displays the historical background and cultural context related to the sign. This allows the user to not only understand the sign's content, but also its background and cultural meaning. The generation AI can also provide tourist information and geographical information related to specific signs based on the user's voice instructions. For example, when a user instructs the generation AI to "tell me the location of this sign," the generation AI displays tourist information and geographical information about the location of the sign. This allows users to not only understand the sign's content, but also obtain information about its location. Furthermore, the generation AI can provide event information and schedules related to a specific sign based on the user's voice instructions. For example, if a user says, "Tell me about the events on this sign," the generation AI will display event information and schedules related to that sign. This allows users to not only understand the sign's content, but also obtain information about the events.

[0099] The generation AI can interpret words in real time based on instructions received through the voice input unit and display the interpretation results on the display unit. For example, when a user speaks a conversation in a foreign language, the generation AI analyzes the content of the conversation and translates it into the user's native language. For example, when the user instructs "Interpret this conversation," the generation AI interprets the content of the conversation in real time and displays it in one eye lens. This allows the user to interpret words in real time based on their voice instructions and display the interpretation results. Furthermore, the generation AI can provide cultural background and customs related to a specific conversation based on the user's voice instructions. For example, when a user instructs "Tell me the background of this conversation," the generation AI displays cultural background and customs related to the conversation. This allows the user to not only understand the content of the conversation but also its background and cultural meaning. The generation AI can also provide historical examples and episodes related to a specific conversation based on the user's voice instructions. For example, when a user instructs "Tell me the history of this conversation," the generation AI displays historical examples and episodes related to the conversation. This allows the user to not only understand the content of the conversation but also its historical background. Furthermore, the generative AI can provide business and economic information related to a specific conversation based on the user's voice instructions. For example, if the user says, "Tell me the business information about this conversation," the generative AI will display the business and economic information related to that conversation. This allows the user to not only understand the content of the conversation, but also its business and economic meaning.

[0100] The generation AI can provide information such as the next appointment or weather forecast based on instructions received by the voice input unit and display it on the display unit. For example, when a user vocally instructs the generation AI to "tell me about my next appointment" or "tell me the weather forecast," the generation AI provides information based on the instruction and displays it on one eye lens. This allows the user to receive and display information such as the next appointment or weather forecast based on the voice instruction. Furthermore, the generation AI can provide traffic information and route guidance related to a specific appointment based on the user's voice instruction. For example, when a user instructs the generation AI to "tell me the route to the location of my next appointment," the generation AI displays traffic information and route guidance to that location. This allows the user to obtain the information needed to head to the next appointment. The generation AI can also provide weather information and weather forecast related to a specific appointment based on the user's voice instruction. For example, when a user instructs the generation AI to "tell me the weather at the location of my next appointment," the generation AI displays the weather information and weather forecast for that location. This allows the user to obtain the weather information needed to head to the next appointment. Furthermore, the generation AI can provide event information and schedules related to a specific appointment based on the user's voice instruction. For example, if a user says, "Tell me about the next scheduled event," the AI ​​will display the event information and schedule related to that event, allowing the user to obtain the event information they need when heading to their next appointment.

[0101] The generation AI can estimate emotions based on instructions received by the voice input unit and display related information on the display unit based on those emotions. For example, when a user inputs a specific word by voice, the generation AI estimates the emotion associated with that word and calculates an emotion score. For example, if a user inputs the word "love," the generation AI analyzes the emotion associated with that word and prioritizes displaying related positive information if the emotion is strong. This allows related information to be displayed based on the user's emotions. Furthermore, the generation AI can also provide encouraging messages or quotes related to specific words based on the user's emotions. For example, if a user inputs the word "challenge," the generation AI displays encouraging messages or quotes related to that word. This allows the user to obtain information that elicits positive emotions. The generation AI can also provide music or videos related to specific words based on the user's emotions. For example, if a user inputs the word "happy," the generation AI displays positive music or videos related to that word. This allows the user to obtain information that elicits positive emotions. Furthermore, the generation AI can provide art or photos related to specific words based on the user's emotions. For example, if a user types in the word "beautiful," the generative AI will display beautiful art and photos related to that word, providing users with information to evoke positive emotions.

[0102] The generative AI can dig deeper into the meaning of words based on instructions received through the voice input unit and display related historical background and cultural context on the display unit. For example, when a user inputs a specific word via voice, the generative AI provides not only the meaning of the word but also the related historical background and cultural context. For example, if the user inputs the word "revolution," the generative AI displays information about historical revolutionary examples and their cultural influences in addition to the meaning of the word. This allows the user to dig deeper into the meaning of the word and view related historical background and cultural context. Furthermore, the generative AI can provide literary works and poems related to a specific word based on the user's voice instructions. For example, if a user instructs the AI ​​to "tell me poems that use this word," the AI ​​displays poems and literary works that include the word. This allows the user to dig deeper into the meaning of the word and enjoy related literary works and poetry. The generative AI can also provide scientific research and papers related to a specific word based on the user's voice instructions. For example, if a user instructs the AI ​​to "tell me research on this word," the AI ​​displays scientific research and papers related to the word. This allows the user to dig deeper into the meaning of the word and obtain related scientific information. Furthermore, the generative AI can provide music and lyrics related to specific words based on the user's voice instructions. For example, if a user says, "Tell me a song that uses this word," the generative AI will display lyrics and music that include that word. This allows users to dig deeper into the meaning of the word and enjoy related music and lyrics.

[0103] The generation AI can dig deeper into the meaning of words based on instructions received through the voice input unit and display related images and videos on the display unit. For example, when a user inputs a specific word by voice, the generation AI simultaneously displays related images and videos in addition to the meaning of the word. For example, if the user inputs the word "pyramid," the generation AI displays images of pyramids and videos of their construction process in addition to the meaning of the word. This allows the user to dig deeper into the meaning of the word and view related images and videos. Furthermore, the generation AI can provide artworks and photos related to specific words based on the user's voice instructions. For example, when a user instructs the generation AI to "tell me about art related to this word," the generation AI displays artworks and photos related to the word. This allows the user to dig deeper into the meaning of the word and enjoy related artworks and photos. The generation AI can also provide videos of scientific experiments and demonstrations related to specific words based on the user's voice instructions. For example, when a user instructs the generation AI to "tell me about experiments related to this word," the generation AI displays videos of scientific experiments and demonstrations related to the word. This allows users to dig deeper into the meaning of words and obtain related scientific information. Furthermore, the generative AI can also provide historical footage or documentaries related to specific words based on the user's voice instructions. For example, if a user says, "Tell me historical footage related to this word," the generative AI will display historical footage or documentaries related to that word. This allows users to dig deeper into the meaning of words and obtain related historical information.

[0104] Generative AI can dig deeper into the meaning of words based on instructions received through a voice input unit, making it applicable to creating educational materials and supporting student learning. For example, generative AI can apply its word digging capabilities to creating educational materials, automatically creating materials for teachers to use in class. For example, it can provide the meanings and background information of words related to specific topics. This can be applied to creating educational materials and supporting student learning. Furthermore, when a student voice-inputs a specific word, generative AI can automatically generate quizzes and questions related to that word. For example, if a student instructs the system to "make a quiz about this word," the generative AI can display quizzes and questions related to that word. This allows students to enjoy learning. Furthermore, when a student voice-inputs a specific word, generative AI can provide video lessons or online courses related to that word. For example, if a student instructs the system to "teach me a video lesson about this word," the generative AI can display video lessons or online courses related to that word. This allows students to progress through their studies at their own pace. Furthermore, when a student voice-inputs a specific word, generative AI can provide ideas for experiments or projects related to that word. For example, when a student says, "Tell me an experiment related to this word," the generative AI will display ideas for experiments and projects related to that word, allowing students to deepen their understanding through hands-on learning.

[0105] The generation AI can estimate emotions based on instructions received by the voice input unit and display related information for eliciting positive emotions on the display unit. For example, when a user inputs a specific word by voice, the generation AI estimates the emotion associated with that word and provides related information for eliciting positive emotions. For example, if a user inputs the word "challenge," the generation AI displays success stories and encouraging messages related to that word. This provides related information for eliciting positive emotions in the user. Furthermore, the generation AI can provide positive music and videos related to specific words based on the user's emotions. For example, if a user inputs the word "happy," the generation AI displays positive music and videos related to that word. This allows the user to obtain information for eliciting positive emotions. The generation AI can also provide positive art and photos related to specific words based on the user's emotions. For example, if a user inputs the word "beautiful," the generation AI displays beautiful art and photos related to that word. This allows the user to obtain information for eliciting positive emotions. Furthermore, the generation AI can provide positive literature and poetry related to specific words based on the user's emotions. For example, if a user inputs the word "love," the generation AI displays positive literature and poetry related to that word. This allows the user to obtain information that will elicit positive emotions.

[0106] The generation AI can translate foreign language signs based on instructions received by the voice input unit and adjust the translation results by estimating emotions. For example, when a user voice-inputs a foreign language sign, the generation AI estimates the emotion toward the sign's content and adjusts the translation results based on the emotion score. For example, if a user instructs, "Translate the content of this sign," the generation AI analyzes the emotion toward the sign's content and provides a positive translation result if the emotion is strong. This allows the translation results to be adjusted based on the user's emotions. Furthermore, the generation AI can also provide positive information and messages related to a specific sign based on the user's emotions. For example, if a user instructs, "Translate the content of this sign," the generation AI displays positive information and messages related to the sign. This allows the user to obtain information that elicits positive emotions. The generation AI can also provide positive tourist information and geographical information related to a specific sign based on the user's emotions. For example, if a user instructs, "Tell me where this sign is," the generation AI displays positive tourist information and geographical information about the location of the sign. This allows the user to obtain information that elicits positive emotions. Furthermore, the generative AI can provide positive event information and schedules related to a specific sign based on the user's emotions. For example, if a user says, "Tell me about the events on this sign," the generative AI will display positive event information and schedules related to that sign. This allows the user to obtain information that will elicit positive emotions.

[0107] The processing flow of the second embodiment will be briefly explained below.

[0108] Step 1: The voice input unit receives a voice instruction from the user using a microphone and voice recognition technology. For example, if the user gives a voice instruction such as "Tell me the meaning of this word," the voice input unit receives the instruction. Step 2: The generative AI uses natural language processing and machine learning algorithms to dig deeper into the meaning of words based on the user's voice commands. The generative AI can also translate signs in foreign languages ​​and display the translation results. The generative AI can also interpret words in real time and display the translation results. Step 3: The display unit uses AR technology and display technology to display information on one of the lenses. For example, information analyzed by the generation AI is displayed on one of the lenses. This allows the user to use the generation AI's functions based on voice instructions to display information on one of the lenses.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0113] 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.

[0114] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0115] The 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.

[0116] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0117] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (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).

[0118] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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).

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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).

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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).

[0162] 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.

[0163] 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."

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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.

[0171] 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.

[0172] 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.

[0173] 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.

[0174] 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.

[0175] 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]

[0176] 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 glasses device equipped with generative AI, a voice input unit that accepts voice instructions from a user; a display unit that displays information on the lens of one eye based on an instruction received by the voice input unit; A system characterized by:

2. The generated AI is The meaning of words is dug up based on instructions received by the voice input unit, and related images and videos are displayed on the display unit.

2. The system of claim 1.

3. The generated AI is Translates signs in a foreign language based on instructions received by the voice input unit, estimates emotions, and adjusts the translation result.

2. The system of claim 1.

4. The generated AI is The speech is interpreted in real time based on the instruction received by the voice input unit, and the emotion is estimated to adjust the interpretation result.

2. The system of claim 1.

5. The generated AI is Providing information such as upcoming schedules and weather forecasts based on instructions received by the voice input unit, and adjusting responses by estimating emotions 2. The system of claim 1.

6. The generated AI is Analyzing emotions felt while using the device based on instructions received by the voice input unit, and adjusting the design and display content based on the emotions.

2. The system of claim 1.

7. The generated AI is An emotion is estimated based on an instruction received by the voice input unit, and related information is displayed on the display unit based on the emotion.

2. The system of claim 1.

8. The generated AI is An emotion is estimated based on an instruction received by the voice input unit, and related information for eliciting a positive emotion is displayed on the display unit.

2. The system of claim 1.

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