System

Abstract

A system is provided.SOLUTION: The data processing system 10 includes means for receiving a voice input of a user and converting the voice input into voice data, means for transmitting the voice data to a server (data processing device 12), means for analyzing the voice data by the server (data processing device 12) and searching for corresponding information, means for transmitting the information searched by the server (data processing device 12) to a terminal (smart device 14), means for overlay-displaying the information received by the terminal (smart device 14) on a field of view of the user, means for capturing a motion of the user by a camera 42 and transmitting the captured motion to the server (data processing device 12), and means for analyzing the captured data by the server (data processing device 12) and identifying a progress or a recognition target.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] In recent years, many people have difficulty performing various tasks in their daily lives. Particularly in DIY projects, cooking, and other manual tasks, it is difficult to obtain the right information at the right time. This reduces work efficiency and wastes time. Furthermore, frequent references to smartphones or paper manuals to obtain information interrupt the work. There is a need to solve these issues and improve the efficiency of everyday tasks. [Means for solving the problem]

[0005] To solve the above problems, the present invention relates to a glasses-type wearable device equipped with AI. This device has a means for receiving a user's voice input and converting it into voice data, and a means for transmitting the voice data to a server. Furthermore, the server has a means for analyzing the voice data and searching for corresponding information, and a means for transmitting the searched information to the device.

[0006] The device has a means to overlay the received information on the user's field of view, and also has a means to capture the user's actions with a camera and send them to a server. The server has a means to analyze the captured data and identify the progress and recognized objects.

[0007] In addition, security is ensured by using encryption means when sending and receiving data, and privacy is protected by anonymizing users' personal information. Furthermore, advertising data is generated as a means of increasing revenue, and appropriate information is provided to users. This allows users to efficiently complete tasks and improve their daily lifestyles.

[0008] A "user" is a person who uses the system and interacts with it through voice input and visual information.

[0009] "Voice data" refers to data that receives voice input from a user and converts that voice into a digital format.

[0010] A "server" is a computer system that analyzes voice data, searches for and generates corresponding information, and transmits it to a terminal.

[0011] A "terminal" is a glasses-type wearable device worn by a user, and is hardware that receives voice input and displays visual information.

[0012] A "natural language processing module" is a software component that converts voice data into text data and understands and analyzes its content.

[0013] An "image recognition module" is a software component that analyzes image data captured by a camera and recognizes specific objects.

[0014] An "AR (Augmented Reality) display" is a combination of software and hardware that overlays digital information onto the physical world.

[0015] "Data encryption" is a method of converting data into cryptographic code so that the data being sent and received will not be leaked to third parties.

[0016] "Anonymization" is the process of removing or replacing identifying information from data so that a user's personal information cannot be identified.

[0017] "Advertising data" refers to marketing information generated to increase profits and is displayed to users. [Brief explanation of the drawings]

[0018] [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. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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, a 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), and an APU (Accelerated Processing Unit).

[0022] 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.

[0023] 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.

[0024] 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), Bluetooth (registered trademark), etc.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[0030] 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.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. 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 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] This invention relates to an AI-equipped wearable glasses-type device that improves the efficiency of users' daily tasks and makes it easier to obtain information. This system utilizes the user's voice input, visual information, and image recognition to assist with daily tasks such as DIY and cooking.

[0040] System configuration

[0041] 1. Glasses-type wearable device

[0042] The device accepts voice input and captures visual information with a camera, allowing users to operate it hands-free.

[0043] The device has a built-in function that automatically transmits voice data to a server, where the voice data is digitized using an encoder.

[0044] 2. Server

[0045] The server analyzes the voice data using a natural language processing module, converts the voice data into text, and searches for the required information.

[0046] The retrieved information is sent to the device. The server also processes the image data received from the device to identify the user's progress and recognition targets.

[0047] 3. Natural Language Processing Module

[0048] This is a module inside the server that converts voice data into text and understands the intent of commands and questions. For example, if a user says, "Tell me the next step," the module extracts the command "next step" and searches for the appropriate information.

[0049] 4. Image Recognition Module

[0050] This is a module inside the server that analyzes real-time image data sent from the device. When the user is working, it recognizes specific objects and progress from the captured images.

[0051] 5. AR display module

[0052] The device will then overlay the received information onto the user's field of vision, providing visual guidance on the location of parts and how to install screws when assembling furniture, for example.

[0053] System Operation

[0054] 1. Receiving and analyzing voice commands

[0055] The user gives a voice command such as "Tell me the next step." The device receives this voice and sends it to the server as voice data.

[0056] 2. Speech data analysis and information retrieval

[0057] The server analyzes the voice data using a natural language processing module and searches a database for corresponding information, such as cooking instructions or DIY steps.

[0058] 3. Transmission and Display of Information

[0059] The server sends the search results to the device, which then displays the information as an overlay in the user's field of view, and can also provide voice instructions.

[0060] 4. Checking work progress and providing guidance on next steps

[0061] As the user works, a camera captures their progress, and these image data are sent to a server, which uses an image recognition module to analyze their progress.

[0062] The server checks whether the next step has been completed and sends the next step to the terminal, which again overlays the information in the user's field of view and provides voice guidance.

[0063] Specific use cases

[0064] When cooking

[0065] 1. The user says, "Tell me what's in the fridge."

[0066] 2. The device sends the voice data to the server, which analyzes it and lists the contents of the refrigerator.

[0067] 3. The list is sent to the device and displayed in the user's field of view.

[0068] 4. When the user asks, "What recipe can I make with these ingredients?" the server searches for the recipe and displays it.

[0069] 5. The recipe steps are displayed in the user's field of vision and are guided by voice.

[0070] For DIY work

[0071] 1. The user speaks, "Tell me how to assemble furniture."

[0072] 2. The device sends the voice data to the server, which then searches for assembly instructions.

[0073] 3. The procedure is sent to the terminal and displayed in the user's field of view.

[0074] 4. As the user lines up the parts, a camera captures the situation and the server checks the progress.

[0075] 5. The next step is displayed in the user's field of view and is announced audibly.

[0076] As described above, the present invention provides specific embodiments for streamlining the user's daily work and significantly improving work efficiency.

[0077] The processing flow will be explained below.

[0078] Step 1:

[0079] The user gives a voice command such as "Tell me the next step." The device receives this voice command through a microphone and records it as voice data.

[0080] Step 2:

[0081] The terminal converts the voice data into a digital format using an encoder and transmits it to a server over the Internet.

[0082] Step 3:

[0083] The server passes the received voice data to a natural language processing module, which converts the voice data into text.

[0084] Step 4:

[0085] The server analyzes the text data and understands the command, "Tell me the next step." Based on this command, it searches the database for the necessary information.

[0086] Step 5:

[0087] The server generates search results and converts information about next steps into data packets and sends them to the terminal.

[0088] Step 6:

[0089] The device decodes the data packets received from the server and overlays them in the user's field of view as an AR display, with specific instructions on the next steps.

[0090] Step 7:

[0091] The user follows the displayed instructions to proceed with the work, and the progress of the work is captured in real time by a camera.

[0092] Step 8:

[0093] The device sends the captured image to the server, which contains the progress of the work.

[0094] Step 9:

[0095] The server uses an image recognition module to analyze the received image data and determine its progress and accuracy.

[0096] Step 10:

[0097] The server sends the analysis results to the terminal, and if the progress is correct, generates data instructing the next step.

[0098] Step 11:

[0099] The device receives instructions from the server and displays them as an overlay in the user's field of view as the next step, while simultaneously providing voice guidance for the next step.

[0100] Step 12:

[0101] This process is repeated until the user completes the task, at which point the system will provide a visual and audio notification that the task is complete.

[0102] The above is a concrete processing flow of the system program, which allows the user to work efficiently.

[0103] Example 1

[0104] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0105] With conventional technology, it was difficult to utilize users' voice input or visual information to assist with tasks. Furthermore, there was a lack of systems that could monitor the user's progress and provide appropriate instructions in real time. This resulted in inefficiencies in processes such as daily tasks, DIY, and cooking, and required users to spend time and effort looking up information.

[0106] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0107] In this invention, the server includes means for analyzing voice data with a natural language processing module and searching for corresponding information, means for analyzing captured data with an image recognition module and identifying progress and recognition targets, and means for transmitting the searched information to the terminal, thereby enabling the server to quickly search for information corresponding to the user's voice instructions and provide visual and audio guidance.

[0108] "Voice input" is a method by which a user communicates information or instructions to a system by speaking.

[0109] "Audio data" is data obtained by converting audio input into digital form.

[0110] A "server" is a central control unit that analyzes data and retrieves information.

[0111] A "natural language processing module" is a software component that converts voice data into text and analyzes the meaning of that text.

[0112] "Search means" is the function by which the server searches for appropriate information from the database.

[0113] A "terminal" is a glasses-type wearable device used by a user, which is a device for inputting voice and capturing visual information.

[0114] "Overlay display" is a method in which a terminal displays information superimposed on the user's field of view.

[0115] "Capture device" is a general term for cameras and sensors used to capture user movements and visual information.

[0116] An "image recognition module" is a software component that analyzes captured data to identify objects and progress.

[0117] "Voice guidance means" is a function that allows the terminal to convey instructions and information to the user by voice.

[0118] "Encryption means" refers to a technology that protects security by encrypting data contents when transmitting and receiving data.

[0119] "Anonymization means" refers to technology that converts a user's personal information into a form that cannot be identified.

[0120] The "advertising data generating means" is a function that creates data for displaying advertisements in order to increase profits.

[0121] This invention relates to an AI-equipped wearable glasses-type device that improves the efficiency of users' daily tasks and makes it easier to obtain information. This system utilizes the user's voice input, visual information, and image recognition to assist with daily tasks such as DIY and cooking.

[0122] The system includes the following components:

[0123] 1. Glasses-type wearable device

[0124] The device receives voice input and captures visual information with a camera, allowing the user to operate it hands-free. The device is equipped with a built-in function that automatically transmits voice data to a server, where it is digitized using an encoder. The device also includes an AR display module that overlays the received information onto the user's field of view. It also has a voice guidance function that provides necessary information to the user via voice.

[0125] 2. Server

[0126] The server receives the voice data and analyzes it using a natural language processing module. The analyzed voice data is converted into text and the required information is searched for in a database. The server also incorporates an image recognition module that understands the user's current task status and determines the next step. The server uses encryption methods to send and receive data to ensure security. Furthermore, the server also includes functions to anonymize users' personal information and generate advertising data as a means of increasing revenue.

[0127] Specific use cases

[0128] When cooking

[0129] 1. The user says, "Tell me what's in the fridge."

[0130] 2. The device sends the voice data to the server, which analyzes it and lists the contents of the refrigerator.

[0131] 3. The list is sent to the device and displayed in the user's field of view.

[0132] 4. When the user asks, "What recipe can I make with these ingredients?" the server searches for and displays the recipe.

[0133] 5. The recipe steps are displayed in the user's field of vision and are guided by voice.

[0134] For DIY work

[0135] 1. The user speaks, "Tell me how to assemble furniture."

[0136] 2. The device sends the voice data to the server, which then searches for assembly instructions.

[0137] 3. The procedure is sent to the terminal and displayed in the user's field of view.

[0138] 4. As the user lines up the parts, a camera captures the situation and the server checks the progress.

[0139] 5. The next step is displayed in the user's field of view and is announced audibly.

[0140] Prompt Sentence Examples

[0141] "Tell me the next step"

[0142] "Tell me what's in the fridge."

[0143] "Teach me how to assemble furniture"

[0144] In this way, the present invention can improve the efficiency of users' daily tasks, and specific embodiments can significantly improve the user experience. By implementing the present invention, users can receive immediate guidance using voice input and visual information, allowing them to perform daily tasks quickly and accurately.

[0145] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0146] Step 1: Receive voice instructions

[0147] The user gives a voice command such as "Tell me the next step." The device's microphone receives the voice input, and the voice data is digitized by an encoder. The digitized voice data is sent from the device to the server. The input is the voice command, and the output is the digitized voice data.

[0148] Step 2: Analyzing the audio data

[0149] The server receives the voice data, and the natural language processing module converts the data into text. The natural language processing module analyzes the commands from the text and extracts specific actions. The input is digitized voice data, and the output is the analyzed text and its commands.

[0150] Step 3: Finding information

[0151] The server queries a database based on the parsed text to find corresponding information, such as DIY instructions or cooking recipes. The input is the parsed text and extracted instructions, and the output is the retrieved related information.

[0152] Step 4: Submit your information

[0153] The server sends the search results back to the terminal. At this time, the security of the data is ensured using encryption. The input is the search result information, and the output is the information sent to the terminal in encrypted form.

[0154] Step 5: Information and navigation

[0155] The device decodes the received information and displays it as an overlay in the user's field of view using the AR display module. At the same time, the device uses a voice guidance means to communicate information and procedures to the user aloud. The input is encrypted information, and the output is the information overlaid in the field of view and voice guidance.

[0156] Step 6: Check the progress of your work

[0157] As the user works, the device's camera captures the progress in real time. The captured image data is sent from the device to the server. The input is the progress of the work, and the output is the captured image data.

[0158] Step 7: Progress analysis

[0159] The image recognition module analyzes the image data received by the server to identify the progress and the object to be recognized. For example, to confirm the position of parts in furniture assembly. The input is the captured image data, and the output is the analyzed progress and the recognized object information.

[0160] Step 8: Next steps

[0161] Based on the analysis results, the server sends the next step and necessary information back to the device. The next step received by the device is again overlaid in the user's field of view and guided by voice. The input is the analyzed progress and next step information, and the output is the next step displayed in the field of view and its voice guidance.

[0162] (Application example 1)

[0163] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0164] In today's brick-and-mortar stores, customers often find it difficult to find products and find detailed product information, reviews, and promotional information instantly. They also have limited means for effectively managing their shopping lists. This reduces shopping efficiency and impairs the customer experience. Furthermore, insufficient privacy practices raise concerns about the protection of personal information.

[0165] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0166] In this invention, the server includes a means for allowing a user to search for products in a store and visually providing location information for specific products, a means for displaying detailed product information and reviews based on a customer's voice command, and a means for acquiring location information from a proximity sensor in the store and automatically displaying promotional information. This allows customers to quickly find the products they need and obtain detailed information, improving shopping efficiency and satisfaction. Furthermore, the quality of the customer experience is improved by providing appropriate advertising information while protecting privacy.

[0167] "Voice input" is an input method in which a user verbally provides instructions or information through a microphone, which is then recognized and analyzed by the system.

[0168] "Voice data" refers to data that has been converted into digital form from a user's voice input.

[0169] A "server" is a central processing unit for analyzing voice data, searching for information, and processing data.

[0170] "Overlay display" is a display method in which a terminal presents information superimposed on the user's field of vision.

[0171] A "camera" is a device that captures the user's actions and environment in real time and converts them into video data.

[0172] "Capture data" refers to image and video data captured by a camera.

[0173] "Location information" is data relating to the location of a particular product.

[0174] "Detailed information" refers to information such as product specifications, descriptions, reviews, etc.

[0175] A "review" is information that describes a user's impressions and evaluations.

[0176] "Promotional Information" refers to information about discounts and special offers offered as part of sales promotion activities.

[0177] A "proximity sensor" is a device that detects the location of a user when they approach a specific product or area.

[0178] "Anonymization" is a method of processing personal information so that it cannot identify a specific individual.

[0179] "Advertising data" refers to promotional information generated for the purpose of increasing revenue.

[0180] This invention relates to a system that uses AI-equipped glasses-type wearable devices to improve customers' shopping experiences in brick-and-mortar stores. Specifically, it provides a means for customers to search for products through voice input and visually display detailed information, reviews, and promotional information about those products. The configuration and operation of the system are described in detail below.

[0181] System configuration

[0182] Glasses-type wearable device

[0183] The device receives voice input and captures visual information with a camera. The voice data is digitized and sent to a server. The device also has an AR display function, which overlays information on the user's field of view.

[0184] server

[0185] The server includes a number of analysis modules.

[0186] Natural language processing module: Uses the Google® Cloud Natural Language API to convert voice data into text and understand the intent of commands and questions.

[0187] Image recognition module: Uses OpenCV to analyze image data sent from the device and identify progress and recognition targets.

[0188] Database module: Access a database that provides real-time product location information, details, reviews, promotion information, etc.

[0189] Specific examples

[0190] The following is a usage scenario within a physical store:

[0191] 1. Product search and guidance:

[0192] The user speaks, "Where is the item XX?"

[0193] The voice data is sent to the server, and the natural language processing module extracts "XX product" as a search keyword.

[0194] The server retrieves the location information of the relevant product from the database and sends it to the terminal.

[0195] The device overlays real-time navigation information onto the user's field of view.

[0196] 2. Product details display:

[0197] The user picks up a product and says, "Show me reviews for this product."

[0198] The voice data is sent to the server, and a natural language processing module parses the command "Show me reviews."

[0199] The device's camera captures the product barcode and sends the image data to the server.

[0200] The image recognition module analyzes the barcode and identifies the corresponding product.

[0201] Review information is retrieved from the database and overlaid on the device's field of view using the device's AR display function.

[0202] 3. Display of Promotional Information:

[0203] When a user approaches a specific area, a proximity sensor detects their location.

[0204] The server retrieves promotional information about products in the relevant area from the database and transmits it to the terminal.

[0205] Promotional information is overlaid on the user's field of view.

[0206] Example prompt

[0207] Here are some examples of prompts to input to the generative AI model:

[0208] "Generate an application design that allows a user to search for a specific product in a store by voice, navigate to that product's location in an AR display, and visually present detailed information and reviews in AR."

[0209] This invention allows customers to quickly find the products they need and obtain detailed information, improving shopping efficiency and satisfaction. It also improves the quality of the customer experience by providing appropriate advertising information while protecting privacy. This invention significantly improves the shopping experience in physical stores.

[0210] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0211] Step 1:

[0212] The user speaks, "Where is the item XX?"

[0213] Input: User's voice command.

[0214] Output: Audio data.

[0215] Specific operation: The device's microphone captures the user's voice instructions and digitizes them as voice data.

[0216] Step 2:

[0217] The terminal transmits the voice data to the server.

[0218] Input: Digitized audio data.

[0219] Output: Notification of completion of transmission to the server.

[0220] Specific operation: The terminal's communication module encodes the voice data and sends it to the server.

[0221] Step 3:

[0222] The server analyzes the voice data, converts it into text using a natural language processing module, and extracts the intent.

[0223] Input: Audio data sent from the device.

[0224] Output: Data converted to text, intent extracted.

[0225] Specific operation: The Google Cloud Natural Language API on the server converts the voice data into text and extracts keywords (e.g., "product of XX").

[0226] Step 4:

[0227] The server retrieves the location information of the relevant product from the database.

[0228] Input: Extracted keywords (product names).

[0229] Output: Product location data.

[0230] Specific operation: The server accesses the database and obtains the location information of the corresponding product based on the product name.

[0231] Step 5:

[0232] The server sends the location data to the device.

[0233] Input: Location data.

[0234] Output: Notification of completion of transmission to the terminal.

[0235] Specific operation: The server's communication module encodes the location data and sends it to the device.

[0236] Step 6:

[0237] The device displays location information in an AR overlay on the user's field of view.

[0238] Input: Location data.

[0239] Output: Navigation information displayed in the user's field of view.

[0240] Specific operation: The device's AR display module visualizes location data and overlays it on the user's field of view in real time.

[0241] Step 7:

[0242] The user picks up a product and says, "Show me reviews for this product."

[0243] Input: User's voice command.

[0244] Output: Audio data.

[0245] Specific operation: The device's microphone captures the user's voice instructions and digitizes them as voice data.

[0246] Step 8:

[0247] The terminal transmits the voice data to the server.

[0248] Input: Digitized audio data.

[0249] Output: Notification of completion of transmission to the server.

[0250] Specific operation: The terminal's communication module encodes the voice data and sends it to the server.

[0251] Step 9:

[0252] The server analyzes the voice data, converts it into text using a natural language processing module, and extracts the intent.

[0253] Input: Audio data sent from the device.

[0254] Output: Data converted to text, intent extracted.

[0255] Specific operation: The Google Cloud Natural Language API on the server converts the voice data into text and extracts commands (e.g., "Show me reviews").

[0256] Step 10:

[0257] The user captures the product with a camera.

[0258] Input: Product image data.

[0259] Output: Capture data.

[0260] Specific operation: The device's camera captures the product barcode or image and digitizes it as image data.

[0261] Step 11:

[0262] The device sends the captured data to the server.

[0263] Input: Product image data.

[0264] Output: Notification of completion of transmission to the server.

[0265] Specific operation: The communication module of the terminal encodes the image data and sends it to the server.

[0266] Step 12:

[0267] The server analyzes the product barcode using an image recognition module and identifies the corresponding product from the database.

[0268] Input: Capture data.

[0269] Output: Identified product information.

[0270] Specific operation: OpenCV on the server analyzes the image data, reads the product barcode, and identifies the corresponding product.

[0271] Step 13:

[0272] The server retrieves the review information from the database.

[0273] Input: Identified product information.

[0274] Output: Review information data.

[0275] Specific operation: The server accesses the database and retrieves review information for the identified product.

[0276] Step 14:

[0277] The server transmits the review information to the terminal.

[0278] Input: Review information data.

[0279] Output: Notification of completion of transmission to the terminal.

[0280] Specific operation: The server's communication module encodes the review information data and transmits it to the terminal.

[0281] Step 15:

[0282] The device displays review information in an AR format overlaid on the user's field of vision.

[0283] Input: Review information data.

[0284] Output: Review information displayed to the user.

[0285] Specific operation: The device's AR display module visualizes review information data and overlays it in the user's field of view in real time.

[0286] Step 16:

[0287] When a user approaches a specific area, a proximity sensor detects their location.

[0288] Input: The user's location.

[0289] Output: Proximity detection data.

[0290] Specific operation: The device's proximity sensor detects the user's position and generates proximity detection data.

[0291] Step 17:

[0292] The server retrieves the promotion information from the database and transmits it to the terminal.

[0293] Input: Proximity detection data.

[0294] Output: Promotion information data.

[0295] Specific operation: The server accesses the database, obtains promotion information for the relevant area, and sends it to the terminal.

[0296] Step 18:

[0297] The device displays promotional information in an AR overlay on the user's field of view.

[0298] Input: Promotion information data.

[0299] Output: Promotion information displayed in the user's field of view.

[0300] Specific operation: The device's AR display module visualizes promotional information data and overlays it in the user's field of view in real time.

[0301] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0302] This invention relates to an AI-equipped wearable eyeglasses that improves the efficiency of users' daily tasks and facilitates information acquisition. This system utilizes the user's voice input, visual information, and image recognition to assist with daily tasks such as DIY and cooking. Furthermore, the invention is equipped with an emotion engine that recognizes the user's emotions and optimizes the work experience based on those emotions.

[0303] System configuration

[0304] 1. Glasses-type wearable device

[0305] The device accepts voice input and captures visual information with a camera, allowing users to operate it hands-free.

[0306] The device has a built-in function that automatically transmits voice data to a server, where the voice data is digitized using an encoder.

[0307] 2. Server

[0308] The server analyzes the voice data using a natural language processing module, converts the voice data into text, and searches for the required information.

[0309] The retrieved information is sent to the device. The server also processes the image data received from the device to identify the user's progress and recognition targets.

[0310] The server is equipped with an emotion engine that can recognize the user's emotional state from their voice and image data.

[0311] 3. Natural Language Processing Module

[0312] This is a module inside the server that converts voice data into text and understands the intent of commands and questions. For example, if a user says, "Tell me the next step," the module extracts the command "next step" and searches for the appropriate information.

[0313] 4. Image Recognition Module

[0314] This is a module inside the server that analyzes real-time image data sent from the device. When the user is working, it recognizes specific objects and progress from the captured images.

[0315] 5. Emotion Engine

[0316] This is a module within the server that analyzes the user's voice and image data to recognize their emotional state, for example, determining whether the user is stressed or relaxed based on their tone of voice and facial expression.

[0317] 6. AR display module

[0318] The device will then overlay the received information onto the user's field of vision, providing visual guidance on the location of parts and how to install screws when assembling furniture, for example.

[0319] System Operation

[0320] 1. Receiving and analyzing voice commands

[0321] The user gives a voice command such as "Tell me the next step." The device receives this voice and sends it to the server as voice data.

[0322] 2. Speech data analysis and information retrieval

[0323] The server analyzes the voice data using a natural language processing module and searches a database for corresponding information, such as cooking instructions or DIY steps.

[0324] 3. Transmission and Display of Information

[0325] The server sends the search results to the device, which then displays the information as an overlay in the user's field of view, and can also provide voice instructions.

[0326] 4. Checking work progress and providing guidance on next steps

[0327] As the user works, a camera captures their progress, and these image data are sent to a server, which uses an image recognition module to analyze their progress.

[0328] The server checks whether the next step has been completed and sends the next step to the terminal, which again overlays the information in the user's field of view and provides voice guidance.

[0329] 5. Recognizing and regulating emotional states

[0330] The server uses the voice and image data to analyze the user's emotional state with an emotion engine. For example, if the user is feeling stressed, the server will recognize this.

[0331] Based on the user's emotional state, the server adjusts the next action: for example, if the user is feeling stressed, it guides them through steps to make the task less difficult.

[0332] Additionally, if the user is determined to be in a negative emotional state, the server will send encouraging messages or simple hints.

[0333] Specific use cases

[0334] When cooking

[0335] 1. The user says, "Tell me what's in the fridge."

[0336] 2. The device sends the voice data to the server, which analyzes it and lists the contents of the refrigerator.

[0337] 3. The list is sent to the device and displayed in the user's field of view.

[0338] 4. When the user asks, "What recipe can I make with these ingredients?" the server searches for the recipe and displays it.

[0339] 5. The recipe steps are displayed in the user's field of vision and are guided by voice.

[0340] 6. The server periodically analyzes the user's emotional state, and if the user is feeling stressed, it adjusts the difficulty of the recipe to be less difficult or starts with easier steps.

[0341] For DIY work

[0342] 1. The user speaks, "Tell me how to assemble furniture."

[0343] 2. The device sends the voice data to the server, which then searches for assembly instructions.

[0344] 3. The procedure is sent to the terminal and displayed in the user's field of view.

[0345] 4. As the user lines up the parts, a camera captures the situation and the server checks the progress.

[0346] 5. The next step is displayed in the user's field of view and is announced audibly.

[0347] 6. The server analyzes the user's emotional state and sends encouraging messages or provides simple explanations if the user is feeling confused or stressed.

[0348] As described above, the present invention provides specific embodiments for streamlining users' daily tasks and significantly improving work efficiency. Furthermore, the present invention can improve the user experience by recognizing the user's emotional state and providing optimal feedback based on that state.

[0349] The processing flow will be explained below.

[0350] Step 1:

[0351] The user gives a voice command such as "Tell me the next step." The device receives this voice command through the microphone and records it as audio data.

[0352] Step 2:

[0353] The device converts the recorded audio data into a digital format using an encoder and transmits it to a server via the Internet.

[0354] Step 3:

[0355] The server passes the received voice data to a natural language processing module, which converts the voice data into text.

[0356] Step 4:

[0357] The server analyzes the text data, understands the "next steps" instructions, and searches the database for the appropriate information.

[0358] Step 5:

[0359] The server converts the search results into data packets and transmits them to the terminal.

[0360] Step 6:

[0361] The device decodes the data packets received from the server and displays them as an AR overlay in the user's field of view, such as instructions on how to assemble furniture or cooking instructions.

[0362] Step 7:

[0363] The user follows the displayed instructions to proceed with the work. The device's camera captures the progress of the work and sends the image data to the server in real time.

[0364] Step 8:

[0365] The server uses an image recognition module to analyze the received image data and check the user's progress, for example, checking the correct placement of parts or the progress of cooking.

[0366] Step 9:

[0367] The server generates instruction data for the next step based on the analysis results and sends it to the terminal.

[0368] Step 10:

[0369] The device receives instruction data from the server and displays the next steps as an overlay in the user's field of vision. At the same time, it can also provide voice guidance for the next steps.

[0370] Step 11:

[0371] The server then passes the voice and image data to the emotion engine in parallel, which analyzes the user's emotional state, determining whether they are stressed or relaxed based on their voice tone and facial expression.

[0372] Step 12:

[0373] The server then uses the emotion engine's analysis to tailor the next steps to the user's emotional state. For example, if the user is feeling stressed, the server will suggest easier steps.

[0374] Step 13:

[0375] If the user is determined to be in a negative emotional state, the server generates and sends to the terminal encouraging messages and additional hints to make the task easier.

[0376] Step 14:

[0377] The device overlays encouraging messages and additional hints onto the user's field of vision and provides audio support.

[0378] Step 15:

[0379] This process is repeated until the user completes the task, at which point the system will provide a visual and audio notification that the task is complete.

[0380] The above is a concrete processing flow of a system incorporating an emotion engine. This flow allows users to work efficiently and also receives support according to their emotional state.

[0381] Example 2

[0382] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0383] Today's users need assistive technologies to help them efficiently complete their daily tasks. However, existing methods rely solely on voice instructions and visual information, lacking the ability to analyze and respond to the user's emotional state and progress in real time. Furthermore, they are unable to adequately address the stress and confusion users feel during the process, limiting their ability to improve work efficiency. Furthermore, the lack of encryption or anonymization of personal information during the transmission and reception of voice and image data raises security and privacy concerns.

[0384] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0385] In this invention, the server includes a means for analyzing voice data and searching for corresponding information, a means for analyzing captured data and identifying progress and recognition targets, and a means for analyzing the user's voice and image data and recognizing their emotional state, which makes it possible to grasp the user's emotional state and work progress in real time and adjust the next action based on that.

[0386] "Voice data" refers to data obtained by converting a user's voice into a digital signal.

[0387] A "server" is a computer system that processes and stores data over a network.

[0388] "Voice input" is the way a device receives spoken words or sounds from a user.

[0389] "Field of view overlay display" is a technology that displays information superimposed on the real image that the user is actually seeing.

[0390] A "camera" is a device for capturing video or images.

[0391] "Capture data" refers to image and video data captured or acquired by devices such as cameras.

[0392] "Progress" is a concept that indicates the progress and degree of achievement of a task or project.

[0393] A "recognition target" is a target or object that the system identifies and recognizes through analysis.

[0394] An "emotional state" is the state of a user's mood or emotions.

[0395] The "emotion engine" is a software module that analyzes the user's voice and image data to recognize their emotional state.

[0396] A "natural language processing module" is a software module that analyzes voice and text data to understand and process human language.

[0397] An "AR display module" is a software module that uses augmented reality technology to overlay information on the real world.

[0398] "Digitalization" is the process of converting analog data into a digital signal.

[0399] MODE FOR CARRYING OUT THE INVENTION

[0400] This invention relates to an AI-equipped wearable eyeglasses device that streamlines users' daily tasks and makes it easier to obtain information. In particular, it uses the user's voice input, visual information, and image recognition to assist with DIY tasks, cooking, and other tasks, and further optimizes the work experience using an emotion engine. This invention includes the following hardware and software components:

[0401] Hardware Configuration

[0402] 1. Glasses-type wearable device

[0403] Microphone: A device that captures audio input.

[0404] Camera: A device that captures visual information and acquires image data.

[0405] Encoder: A device that digitizes and compresses audio data.

[0406] AR display: A device that displays received information as an overlay on the user's field of vision.

[0407] Software Configuration

[0408] 1. Server

[0409] Natural language processing module: Software that converts voice data into text and understands the intent of commands and questions.

[0410] Database: Data storage for storing and retrieving necessary information.

[0411] Image Recognition Module: Software that analyzes captured image data to identify progress and recognized objects.

[0412] Emotion engine: Software that analyzes a user's voice and image data to recognize their emotional state.

[0413] Operating Procedure

[0414] When a user verbally commands, "Tell me what the next step is," the device's microphone captures the voice, and the digitized voice data is compressed by an encoder and sent to the server. The server's natural language processing module analyzes the voice data, converts it into text, and searches a database for appropriate information. This information is sent to the device and overlaid on the user's field of view via the AR display. The camera also captures the user's work progress in real time and sends it to the server, where an image recognition module analyzes the progress and identifies the next step.

[0415] Specific examples

[0416] When cooking

[0417] When the user says, "Tell me what's in the fridge," the device sends a voice message to the server, which then lists the contents of the fridge. The list is then sent to the device and displayed in the field of view. The user can then say, "What recipes can I make with these ingredients?" and the server will search for recipes and overlay the instructions in the field of view. The server analyzes the user's emotional state and adjusts the difficulty of the recipes if the user feels stressed.

[0418] For DIY work

[0419] When a user says, "Tell me how to assemble furniture," the device sends voice data to the server, which searches for assembly instructions. After the instructions are displayed in the field of view, a camera captures the placement of the parts, and the server analyzes the images to check the progress and display the next step. To ensure a comfortable working environment, the server monitors the user's emotional state and provides encouraging messages or simple explanations if the user is experiencing difficulty.

[0420] Prompt Sentence Examples

[0421] "Tell me a recipe I can make using ingredients in the fridge."

[0422] "Guide me through the next steps"

[0423] Please check the current progress

[0424] "Is there an easier way?"

[0425] In this way, the system can streamline users' daily tasks and improve their experience by providing optimal emotion-based feedback.

[0426] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0427] Step 1:

[0428] The user gives a voice command

[0429] Specific actions

[0430] The user gives a voice command, such as "Tell me what to do next." The device's microphone captures this voice.

[0431] Input: User's voice commands

[0432] Output: Audio data

[0433] Step 2:

[0434] Sending audio data

[0435] Specific actions

[0436] The device digitizes the captured audio using an encoder, compresses it, and then sends it to the server.

[0437] Input: Digitized and compressed audio data

[0438] Output: Audio data sent to the server

[0439] Step 3:

[0440] Analysis of audio data

[0441] Specific actions

[0442] The server passes the received voice data to a natural language processing module, which converts it into text, and extracts the intent of commands and questions from the voice data.

[0443] Input: Audio data sent to the server

[0444] Output: Parsed text data

[0445] Step 4:

[0446] Searching for information

[0447] Specific actions

[0448] The server's natural language processing module analyzes the text and then searches the database for the necessary information, such as cooking instructions or DIY steps.

[0449] Input: Parsed text data

[0450] Output: Search result information data

[0451] Step 5:

[0452] Sending information

[0453] Specific actions

[0454] The server transmits the search result information data to the terminal.

[0455] Input: Search result information data

[0456] Output: Information data sent to the terminal

[0457] Step 6:

[0458] Displaying Information

[0459] Specific actions

[0460] The device overlays the received information onto the user's field of view through an AR display module, and may also provide audio instructions using an audio output device.

[0461] Input: Information data sent to the terminal

[0462] Output: Information overlaid on the field of view

[0463] Step 7:

[0464] Work progress capture

[0465] Specific actions

[0466] As the user works, the device's camera captures their progress in real time.

[0467] Input: User's work progress

[0468] Output: Captured image data

[0469] Step 8:

[0470] Sending image data

[0471] Specific actions

[0472] The terminal transmits the captured image data to the server.

[0473] Input: Captured image data

[0474] Output: Image data sent to the server

[0475] Step 9:

[0476] Progress Analysis

[0477] Specific actions

[0478] The server's image recognition module analyzes the received image data and identifies the user's progress and the object to be recognized.

[0479] Input: Image data sent to the server

[0480] Output: Parsed progress information

[0481] Step 10:

[0482] Next step guidance

[0483] Specific actions

[0484] Based on the analyzed progress information, the server sends the next step to the device, which then overlays the received information onto the user's field of view and provides audio guidance.

[0485] Input: Parsed progress information

[0486] Output: Information data for next steps

[0487] Step 11:

[0488] Emotional state analysis

[0489] Specific actions

[0490] The server uses the voice data and image data to analyze the user's emotional state with an emotion engine, for example, by reading emotions from the user's tone of voice and facial expressions.

[0491] Input: Audio data, image data

[0492] Output: Parsed emotional state

[0493] Step 12:

[0494] Adjusting the next action

[0495] Specific actions

[0496] The server adjusts the next action based on the analyzed emotional state, for example, if the user is feeling stressed, it will guide them through steps to reduce the difficulty.

[0497] Input: Parsed emotional state

[0498] Output: A coordinated action plan

[0499] This will help users streamline their daily tasks and improve the user experience by providing optimal feedback based on emotions.

[0500] (Application example 2)

[0501] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0502] Problems faced by workers in modern factories and other workplaces include the complexity of work instructions, the cumbersome nature of progress management, and the impact of workers' emotional states on work efficiency. Conventional systems have difficulty managing this information centrally and providing real-time feedback, leading to reduced work efficiency and increased errors. The present invention aims to provide a new system that solves these problems and maximizes workers' work efficiency.

[0503] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0504] In this invention, the server includes means for receiving a user's voice input and converting it into voice data, means for transmitting the voice data to the server, means for the server to analyze the voice data and search for corresponding information, means for the server to transmit the searched information to the terminal, means for the terminal to overlay the information received on the user's field of view, means for capturing the user's actions with a camera and transmitting the captured data to the server, means for the server to analyze the captured data and identify progress and recognition targets, means for recognizing the user's emotional state using the captured data and voice data analyzed by the server, and means for adjusting the difficulty of work instructions and providing feedback based on the recognized emotional state. This allows the worker to obtain appropriate work information simply by giving voice instructions, and by checking progress and recognizing emotions with the camera, it becomes possible to optimize work efficiency in real time.

[0505] "Voice input" allows the system to recognize voice commands or questions uttered by the user as instructions.

[0506] "Voice data" refers to voice input converted into digital signals that can be used for analysis and retrieval.

[0507] The "server" is a central processing device that analyzes audio data and visual information and transmits the analysis results to the terminal.

[0508] A "terminal" refers to a wearable device that is worn by the user and displays information in the user's field of vision, and is responsible for exchanging audio and visual information.

[0509] "Visual information" refers to image and video data captured through cameras and other sensors.

[0510] A "camera" is a device that captures visual information and obtains images of a user's actions and environment.

[0511] "Capture data" refers to image and video data acquired from a visual sensor such as a camera.

[0512] "Analysis" refers to the process of extracting and processing specific information based on input voice data or captured data.

[0513] "Progress" is information that indicates the progress and degree of achievement of a task.

[0514] A "recognition target" is a specific object or action to be analyzed, and is identified through analysis.

[0515] "Emotional state" refers to the psychological state that can be read from the user's voice and facial expression, and includes stress, relaxation, etc.

[0516] "Feedback" refers to reactions such as encouraging messages or information on corrective work instructions provided to the user based on the analysis results.

[0517] "Difficulty" is an index that indicates the complexity of the task and the skill level required.

[0518] "Overlay display" refers to a method of displaying information superimposed on the user's field of vision, directly and visually conveying work instructions and progress status.

[0519] The system for implementing this invention includes a wearable terminal (smart glasses) worn by a user, a server, and a camera. The specific roles and operations of each element are described below.

[0520] Wearable devices

[0521] A wearable device receives voice input from the user and converts it into voice data. The device has a means of sending the converted voice data to a server. Voice recognition software such as the SpeechRecognition library is used to encode the voice data. The device also has a function for overlaying information received from the server onto the user's field of view. Specifically, it uses augmented reality (AR) technology to display instructions in a way that makes them easy for the user to see. Screen display and voice guidance on the device are handled by the ARDisplay module and speaker.

[0522] server

[0523] The server receives the voice data and analyzes it using a natural language processing module. The analyzed voice data is used to search for corresponding information. For example, a natural language processing library such as Python's Natural Language Toolkit (NLTK) is used. The server also has the function of analyzing the transmitted capture data and identifying the user's progress and recognition target. An image processing library such as OpenCV is used to analyze the capture data.

[0524] Next, the server contains an emotion engine that analyzes the user's voice and captured data to recognize their emotional state. The EmotionRecognition library is used to analyze the emotional state. For example, if the user is feeling stressed, the server determines this based on the analysis results. Based on the results, the server adjusts the difficulty of the work instructions and provides appropriate feedback. The entire process is carried out in real time.

[0525] camera

[0526] The camera is used to capture the user's actions and the surrounding situation. The captured data is sent to the server, where it is used to check the progress and identify the recognition target.

[0527] Specific examples

[0528] Receiving work orders

[0529] When the user speaks, "Tell me what to do next," the device sends the voice data to the server, which analyzes it, finds the appropriate work instructions, and displays them as an overlay in the user's field of view.

[0530] Progress check and feedback

[0531] While the task is in progress, the camera captures the user's movements and progress and sends them to the server. The server analyzes the captured images and checks the progress. If the server determines that the user is feeling stressed, it uses an emotion engine to analyze the user's state and provide appropriate feedback. For example, it displays instructions to reduce the difficulty of the task or an encouraging message.

[0532] Prompt Sentence Examples

[0533] Tell me what to do next

[0534] Check your progress

[0535] Work completed

[0536] Analyze your emotional state

[0537] Display an encouraging message

[0538] As described above, the present invention provides a system that allows the user to flexibly proceed with work based on simple voice instructions and visual information, thereby making it possible to improve work efficiency.

[0539] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0540] Step 1:

[0541] The user enters a voice command

[0542] The user issues a voice command, and the voice data is collected through the terminal's microphone.

[0543] Input: User's voice

[0544] Output: Audio data captured on the device

[0545] Specific operation: When the user says "Tell me what to do next," the device's microphone captures the voice.

[0546] Step 2:

[0547] Voice data is digitized and sent to the server

[0548] The terminal converts the collected voice into digital data and sends it to the server.

[0549] Input: Audio data

[0550] Output: Digital audio data sent to the server

[0551] Specific operation: The device's voice recognition module converts the speech into text, which is then sent to a server over the Internet.

[0552] Step 3:

[0553] Speech data analysis and information retrieval

[0554] The server receives the voice data, analyzes it using a natural language processing module, and retrieves corresponding information.

[0555] Input: Digital audio data

[0556] Output: Retrieved information

[0557] Specific operation: Natural language processing software (e.g., NLTK) on the server analyzes the text of the voice data and searches for the "next task."

[0558] Step 4:

[0559] Submit search results

[0560] The server transmits the retrieved information to the terminal.

[0561] Input: Searched information

[0562] Output: Search results sent to your device

[0563] Specific operation: The server divides the information into packets and sends them to the device's IP address.

[0564] Step 5:

[0565] Overlay display in the user's field of view

[0566] The terminal displays the received information as an overlay in the user's field of view.

[0567] Input: Search results received

[0568] Output: Work instructions displayed in the user's field of view

[0569] Specific operation: The AR display module of the wearable device receives text information and displays it over the user's field of view.

[0570] Step 6:

[0571] Camera capture of user's work progress

[0572] As the user works, the device's camera captures the progress and sends the image data to the server.

[0573] Input: User's work in progress

[0574] Output: Image data sent to the server

[0575] Specific operation: The device's camera takes images in real time and uploads the data to the server.

[0576] Step 7:

[0577] Analyzing image data and identifying progress

[0578] The server analyzes the captured image data and identifies the progress and the object of recognition.

[0579] Input: Captured image data

[0580] Output: Analysis results and progress information

[0581] Specific operation: Image recognition software (e.g., OpenCV) on the server analyzes the image and determines the progress of the work.

[0582] Step 8:

[0583] Recognition of emotional states

[0584] The server analyzes the audio and image data to recognize the user's emotional state.

[0585] Input: Audio and image data

[0586] Output: Perceived emotional state

[0587] Specific operation: The emotion recognition engine analyzes emotional states such as stress or relaxation from voice tone and facial expressions.

[0588] Step 9:

[0589] Providing feedback based on emotional state

[0590] The server adjusts the difficulty of the work instructions based on the perceived emotional state and provides feedback.

[0591] Input: Perceived emotional state and progress information

[0592] Output: Tailored work instructions and encouraging messages

[0593] Specific operation: Based on the emotion recognition results, the server facilitates the next task or sends an encouraging message to the device, which is then overlaid on the device's field of vision.

[0594] The above is the specific flow of processing in this system.

[0595] 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.

[0596] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[0597] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0598] [Second embodiment]

[0599] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0600] 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.

[0601] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[0602] 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.

[0603] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0604] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0605] 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.

[0606] 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.

[0607] 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 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.

[0608] 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.

[0609] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0610] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0611] This invention relates to an AI-equipped wearable glasses-type device that improves the efficiency of users' daily tasks and makes it easier to obtain information. This system utilizes the user's voice input, visual information, and image recognition to assist with daily tasks such as DIY and cooking.

[0612] System configuration

[0613] 1. Glasses-type wearable device

[0614] The device accepts voice input and captures visual information with a camera, allowing users to operate it hands-free.

[0615] The device has a built-in function that automatically transmits voice data to a server, where the voice data is digitized using an encoder.

[0616] 2. Server

[0617] The server analyzes the voice data using a natural language processing module, converts the voice data into text, and searches for the required information.

[0618] The retrieved information is sent to the device. The server also processes the image data received from the device to identify the user's progress and recognition targets.

[0619] 3. Natural Language Processing Module

[0620] This is a module inside the server that converts voice data into text and understands the intent of commands and questions. For example, if a user says, "Tell me the next step," the module extracts the command "next step" and searches for the appropriate information.

[0621] 4. Image Recognition Module

[0622] This is a module inside the server that analyzes real-time image data sent from the device. When the user is working, it recognizes specific objects and progress from the captured images.

[0623] 5. AR display module

[0624] The device will then overlay the received information onto the user's field of vision, providing visual guidance on the location of parts and how to install screws when assembling furniture, for example.

[0625] System Operation

[0626] 1. Receiving and analyzing voice commands

[0627] The user gives a voice command such as "Tell me the next step." The device receives this voice and sends it to the server as voice data.

[0628] 2. Speech data analysis and information retrieval

[0629] The server analyzes the voice data using a natural language processing module and searches a database for corresponding information, such as cooking instructions or DIY steps.

[0630] 3. Transmission and Display of Information

[0631] The server sends the search results to the device, which then displays the information as an overlay in the user's field of view, and can also provide voice instructions.

[0632] 4. Checking work progress and providing guidance on next steps

[0633] As the user works, a camera captures their progress, and these image data are sent to a server, which uses an image recognition module to analyze their progress.

[0634] The server checks whether the next step has been completed and sends the next step to the terminal, which again overlays the information in the user's field of view and provides voice guidance.

[0635] Specific use cases

[0636] When cooking

[0637] 1. The user says, "Tell me what's in the fridge."

[0638] 2. The device sends the voice data to the server, which analyzes it and lists the contents of the refrigerator.

[0639] 3. The list is sent to the device and displayed in the user's field of view.

[0640] 4. When the user asks, "What recipe can I make with these ingredients?" the server searches for the recipe and displays it.

[0641] 5. The recipe steps are displayed in the user's field of vision and are guided by voice.

[0642] For DIY work

[0643] 1. The user speaks, "Tell me how to assemble furniture."

[0644] 2. The device sends the voice data to the server, which then searches for assembly instructions.

[0645] 3. The procedure is sent to the terminal and displayed in the user's field of view.

[0646] 4. As the user lines up the parts, a camera captures the situation and the server checks the progress.

[0647] 5. The next step is displayed in the user's field of view and is announced audibly.

[0648] As described above, the present invention provides specific embodiments for streamlining the user's daily work and significantly improving work efficiency.

[0649] The processing flow will be explained below.

[0650] Step 1:

[0651] The user gives a voice command such as "Tell me the next step." The device receives this voice command through a microphone and records it as voice data.

[0652] Step 2:

[0653] The terminal converts the voice data into a digital format using an encoder and transmits it to a server over the Internet.

[0654] Step 3:

[0655] The server passes the received voice data to a natural language processing module, which converts the voice data into text.

[0656] Step 4:

[0657] The server analyzes the text data and understands the command, "Tell me the next step." Based on this command, it searches the database for the necessary information.

[0658] Step 5:

[0659] The server generates search results and converts information about next steps into data packets and sends them to the terminal.

[0660] Step 6:

[0661] The device decodes the data packets received from the server and overlays them in the user's field of view as an AR display, with specific instructions on the next steps.

[0662] Step 7:

[0663] The user follows the displayed instructions to proceed with the work, and the progress of the work is captured in real time by a camera.

[0664] Step 8:

[0665] The device sends the captured image to the server, which contains the progress of the work.

[0666] Step 9:

[0667] The server uses an image recognition module to analyze the received image data and determine its progress and accuracy.

[0668] Step 10:

[0669] The server sends the analysis results to the terminal, and if the progress is correct, generates data instructing the next step.

[0670] Step 11:

[0671] The device receives instructions from the server and displays them as an overlay in the user's field of view as the next step, while simultaneously providing voice guidance for the next step.

[0672] Step 12:

[0673] This process is repeated until the user completes the task, at which point the system will provide a visual and audio notification that the task is complete.

[0674] The above is a concrete processing flow of the system program, which allows the user to work efficiently.

[0675] Example 1

[0676] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0677] With conventional technology, it was difficult to utilize users' voice input or visual information to assist with tasks. Furthermore, there was a lack of systems that could monitor the user's progress and provide appropriate instructions in real time. This resulted in inefficiencies in processes such as daily tasks, DIY, and cooking, and required users to spend time and effort looking up information.

[0678] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0679] In this invention, the server includes means for analyzing voice data with a natural language processing module and searching for corresponding information, means for analyzing captured data with an image recognition module and identifying progress and recognition targets, and means for transmitting the searched information to the terminal, thereby enabling the server to quickly search for information corresponding to the user's voice instructions and provide visual and audio guidance.

[0680] "Voice input" is a method by which a user communicates information or instructions to a system by speaking.

[0681] "Audio data" is data obtained by converting audio input into digital form.

[0682] A "server" is a central control unit that analyzes data and retrieves information.

[0683] A "natural language processing module" is a software component that converts voice data into text and analyzes the meaning of that text.

[0684] "Search means" is the function by which the server searches for appropriate information from the database.

[0685] A "terminal" is a glasses-type wearable device used by a user, which is a device for inputting voice and capturing visual information.

[0686] "Overlay display" is a method in which a terminal displays information superimposed on the user's field of view.

[0687] "Capture device" is a general term for cameras and sensors used to capture user movements and visual information.

[0688] An "image recognition module" is a software component that analyzes captured data to identify objects and progress.

[0689] "Voice guidance means" is a function that allows the terminal to convey instructions and information to the user by voice.

[0690] "Encryption means" refers to a technology that protects security by encrypting data contents when transmitting and receiving data.

[0691] "Anonymization means" refers to technology that converts a user's personal information into a form that cannot be identified.

[0692] The "advertising data generating means" is a function that creates data for displaying advertisements in order to increase profits.

[0693] This invention relates to an AI-equipped wearable glasses-type device that improves the efficiency of users' daily tasks and makes it easier to obtain information. This system utilizes the user's voice input, visual information, and image recognition to assist with daily tasks such as DIY and cooking.

[0694] The system includes the following components:

[0695] 1. Glasses-type wearable device

[0696] The device receives voice input and captures visual information with a camera, allowing the user to operate it hands-free. The device is equipped with a built-in function that automatically transmits voice data to a server, where it is digitized using an encoder. The device also includes an AR display module that overlays the received information onto the user's field of view. It also has a voice guidance function that provides necessary information to the user via voice.

[0697] 2. Server

[0698] The server receives the voice data and analyzes it using a natural language processing module. The analyzed voice data is converted into text and the required information is searched for in a database. The server also incorporates an image recognition module that understands the user's current task status and determines the next step. The server uses encryption methods to send and receive data to ensure security. Furthermore, the server also includes functions to anonymize users' personal information and generate advertising data as a means of increasing revenue.

[0699] Specific use cases

[0700] When cooking

[0701] 1. The user says, "Tell me what's in the fridge."

[0702] 2. The device sends the voice data to the server, which analyzes it and lists the contents of the refrigerator.

[0703] 3. The list is sent to the device and displayed in the user's field of view.

[0704] 4. When the user asks, "What recipe can I make with these ingredients?" the server searches for and displays the recipe.

[0705] 5. The recipe steps are displayed in the user's field of vision and are guided by voice.

[0706] For DIY work

[0707] 1. The user speaks, "Tell me how to assemble furniture."

[0708] 2. The device sends the voice data to the server, which then searches for assembly instructions.

[0709] 3. The procedure is sent to the terminal and displayed in the user's field of view.

[0710] 4. As the user lines up the parts, a camera captures the situation and the server checks the progress.

[0711] 5. The next step is displayed in the user's field of view and is announced audibly.

[0712] Prompt Sentence Examples

[0713] "Tell me the next step"

[0714] "Tell me what's in the fridge."

[0715] "Teach me how to assemble furniture"

[0716] In this way, the present invention can improve the efficiency of users' daily tasks, and specific embodiments can significantly improve the user experience. By implementing the present invention, users can receive immediate guidance using voice input and visual information, allowing them to perform daily tasks quickly and accurately.

[0717] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0718] Step 1: Receive voice instructions

[0719] The user gives a voice command such as "Tell me the next step." The device's microphone receives the voice input, and the voice data is digitized by an encoder. The digitized voice data is sent from the device to the server. The input is the voice command, and the output is the digitized voice data.

[0720] Step 2: Analyzing the audio data

[0721] The server receives the voice data, and the natural language processing module converts the data into text. The natural language processing module analyzes the commands from the text and extracts specific actions. The input is digitized voice data, and the output is the analyzed text and its commands.

[0722] Step 3: Finding information

[0723] The server queries a database based on the parsed text to find corresponding information, such as DIY instructions or cooking recipes. The input is the parsed text and extracted instructions, and the output is the retrieved related information.

[0724] Step 4: Submit your information

[0725] The server sends the search results back to the terminal. At this time, the security of the data is ensured using encryption. The input is the search result information, and the output is the information sent to the terminal in encrypted form.

[0726] Step 5: Information and navigation

[0727] The device decodes the received information and displays it as an overlay in the user's field of view using the AR display module. At the same time, the device uses a voice guidance means to communicate information and procedures to the user aloud. The input is encrypted information, and the output is the information overlaid in the field of view and voice guidance.

[0728] Step 6: Check the progress of your work

[0729] As the user works, the device's camera captures the progress in real time. The captured image data is sent from the device to the server. The input is the progress of the work, and the output is the captured image data.

[0730] Step 7: Progress analysis

[0731] The image recognition module analyzes the image data received by the server to identify the progress and the object to be recognized. For example, to confirm the position of parts in furniture assembly. The input is the captured image data, and the output is the analyzed progress and the recognized object information.

[0732] Step 8: Next steps

[0733] Based on the analysis results, the server sends the next step and necessary information back to the device. The next step received by the device is again overlaid in the user's field of view and guided by voice. The input is the analyzed progress and next step information, and the output is the next step displayed in the field of view and its voice guidance.

[0734] (Application example 1)

[0735] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0736] In today's brick-and-mortar stores, customers often find it difficult to find products and find detailed product information, reviews, and promotional information instantly. They also have limited means for effectively managing their shopping lists. This reduces shopping efficiency and impairs the customer experience. Furthermore, insufficient privacy practices raise concerns about the protection of personal information.

[0737] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0738] In this invention, the server includes a means for allowing a user to search for products in a store and visually providing location information for specific products, a means for displaying detailed product information and reviews based on a customer's voice command, and a means for acquiring location information from a proximity sensor in the store and automatically displaying promotional information. This allows customers to quickly find the products they need and obtain detailed information, improving shopping efficiency and satisfaction. Furthermore, the quality of the customer experience is improved by providing appropriate advertising information while protecting privacy.

[0739] "Voice input" is an input method in which a user verbally provides instructions or information through a microphone, which is then recognized and analyzed by the system.

[0740] "Voice data" refers to data that has been converted into digital form from a user's voice input.

[0741] A "server" is a central processing unit for analyzing voice data, searching for information, and processing data.

[0742] "Overlay display" is a display method in which a terminal presents information superimposed on the user's field of vision.

[0743] A "camera" is a device that captures the user's actions and environment in real time and converts them into video data.

[0744] "Capture data" refers to image and video data captured by a camera.

[0745] "Location information" is data relating to the location of a particular product.

[0746] "Detailed information" refers to information such as product specifications, descriptions, reviews, etc.

[0747] A "review" is information that describes a user's impressions and evaluations.

[0748] "Promotional Information" refers to information about discounts and special offers offered as part of sales promotion activities.

[0749] A "proximity sensor" is a device that detects the location of a user when they approach a specific product or area.

[0750] "Anonymization" is a method of processing personal information so that it cannot identify a specific individual.

[0751] "Advertising data" refers to promotional information generated for the purpose of increasing revenue.

[0752] This invention relates to a system that uses AI-equipped glasses-type wearable devices to improve customers' shopping experiences in brick-and-mortar stores. Specifically, it provides a means for customers to search for products through voice input and visually display detailed information, reviews, and promotional information about those products. The configuration and operation of the system are described in detail below.

[0753] System configuration

[0754] Glasses-type wearable device

[0755] The device receives voice input and captures visual information with a camera. The voice data is digitized and sent to a server. The device also has an AR display function, which overlays information on the user's field of view.

[0756] server

[0757] The server includes a number of analysis modules.

[0758] Natural language processing module: Uses the Google Cloud Natural Language API to convert voice data into text and understand the intent of commands and questions.

[0759] Image recognition module: Uses OpenCV to analyze image data sent from the device and identify progress and recognition targets.

[0760] Database module: Access a database that provides real-time product location information, details, reviews, promotion information, etc.

[0761] Specific examples

[0762] The following is a usage scenario within a physical store:

[0763] 1. Product search and guidance:

[0764] The user speaks, "Where is the item XX?"

[0765] The voice data is sent to the server, and the natural language processing module extracts "XX product" as a search keyword.

[0766] The server retrieves the location information of the relevant product from the database and sends it to the terminal.

[0767] The device overlays real-time navigation information onto the user's field of view.

[0768] 2. Product details display:

[0769] The user picks up a product and says, "Show me reviews for this product."

[0770] The voice data is sent to the server, and a natural language processing module parses the command "Show me reviews."

[0771] The device's camera captures the product barcode and sends the image data to the server.

[0772] The image recognition module analyzes the barcode and identifies the corresponding product.

[0773] Review information is retrieved from the database and overlaid on the device's field of view using the device's AR display function.

[0774] 3. Display of Promotional Information:

[0775] When a user approaches a specific area, a proximity sensor detects their location.

[0776] The server retrieves promotional information about products in the relevant area from the database and transmits it to the terminal.

[0777] Promotional information is overlaid on the user's field of view.

[0778] Example prompt

[0779] Here are some examples of prompts to input to the generative AI model:

[0780] "Generate an application design that allows a user to search for a specific product in a store by voice, navigate to that product's location in an AR display, and visually present detailed information and reviews in AR."

[0781] This invention allows customers to quickly find the products they need and obtain detailed information, improving shopping efficiency and satisfaction. It also improves the quality of the customer experience by providing appropriate advertising information while protecting privacy. This invention significantly improves the shopping experience in physical stores.

[0782] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0783] Step 1:

[0784] The user speaks, "Where is the item XX?"

[0785] Input: User's voice command.

[0786] Output: Audio data.

[0787] Specific operation: The device's microphone captures the user's voice instructions and digitizes them as voice data.

[0788] Step 2:

[0789] The terminal transmits the voice data to the server.

[0790] Input: Digitized audio data.

[0791] Output: Notification of completion of transmission to the server.

[0792] Specific operation: The terminal's communication module encodes the voice data and sends it to the server.

[0793] Step 3:

[0794] The server analyzes the voice data, converts it into text using a natural language processing module, and extracts the intent.

[0795] Input: Audio data sent from the device.

[0796] Output: Data converted to text, intent extracted.

[0797] Specific operation: The Google Cloud Natural Language API on the server converts the voice data into text and extracts keywords (e.g., "product of XX").

[0798] Step 4:

[0799] The server retrieves the location information of the relevant product from the database.

[0800] Input: Extracted keywords (product names).

[0801] Output: Product location data.

[0802] Specific operation: The server accesses the database and obtains the location information of the corresponding product based on the product name.

[0803] Step 5:

[0804] The server sends the location data to the device.

[0805] Input: Location data.

[0806] Output: Notification of completion of transmission to the terminal.

[0807] Specific operation: The server's communication module encodes the location data and sends it to the device.

[0808] Step 6:

[0809] The device displays location information in an AR overlay on the user's field of view.

[0810] Input: Location data.

[0811] Output: Navigation information displayed in the user's field of view.

[0812] Specific operation: The device's AR display module visualizes location data and overlays it on the user's field of view in real time.

[0813] Step 7:

[0814] The user picks up a product and says, "Show me reviews for this product."

[0815] Input: User's voice command.

[0816] Output: Audio data.

[0817] Specific operation: The device's microphone captures the user's voice instructions and digitizes them as voice data.

[0818] Step 8:

[0819] The terminal transmits the voice data to the server.

[0820] Input: Digitized audio data.

[0821] Output: Notification of completion of transmission to the server.

[0822] Specific operation: The terminal's communication module encodes the voice data and sends it to the server.

[0823] Step 9:

[0824] The server analyzes the voice data, converts it into text using a natural language processing module, and extracts the intent.

[0825] Input: Audio data sent from the device.

[0826] Output: Data converted to text, intent extracted.

[0827] Specific operation: The Google Cloud Natural Language API on the server converts the voice data into text and extracts commands (e.g., "Show me reviews").

[0828] Step 10:

[0829] The user captures the product with a camera.

[0830] Input: Product image data.

[0831] Output: Capture data.

[0832] Specific operation: The device's camera captures the product barcode or image and digitizes it as image data.

[0833] Step 11:

[0834] The device sends the captured data to the server.

[0835] Input: Product image data.

[0836] Output: Notification of completion of transmission to the server.

[0837] Specific operation: The communication module of the terminal encodes the image data and sends it to the server.

[0838] Step 12:

[0839] The server analyzes the product barcode using an image recognition module and identifies the corresponding product from the database.

[0840] Input: Capture data.

[0841] Output: Identified product information.

[0842] Specific operation: OpenCV on the server analyzes the image data, reads the product barcode, and identifies the corresponding product.

[0843] Step 13:

[0844] The server retrieves the review information from the database.

[0845] Input: Identified product information.

[0846] Output: Review information data.

[0847] Specific operation: The server accesses the database and retrieves review information for the identified product.

[0848] Step 14:

[0849] The server transmits the review information to the terminal.

[0850] Input: Review information data.

[0851] Output: Notification of completion of transmission to the terminal.

[0852] Specific operation: The server's communication module encodes the review information data and transmits it to the terminal.

[0853] Step 15:

[0854] The device displays review information in an AR format overlaid on the user's field of vision.

[0855] Input: Review information data.

[0856] Output: Review information displayed to the user.

[0857] Specific operation: The device's AR display module visualizes review information data and overlays it in the user's field of view in real time.

[0858] Step 16:

[0859] When a user approaches a specific area, a proximity sensor detects their location.

[0860] Input: The user's location.

[0861] Output: Proximity detection data.

[0862] Specific operation: The device's proximity sensor detects the user's position and generates proximity detection data.

[0863] Step 17:

[0864] The server retrieves the promotion information from the database and transmits it to the terminal.

[0865] Input: Proximity detection data.

[0866] Output: Promotion information data.

[0867] Specific operation: The server accesses the database, obtains promotion information for the relevant area, and sends it to the terminal.

[0868] Step 18:

[0869] The device displays promotional information in an AR overlay on the user's field of view.

[0870] Input: Promotion information data.

[0871] Output: Promotion information displayed in the user's field of view.

[0872] Specific operation: The device's AR display module visualizes promotional information data and overlays it in the user's field of view in real time.

[0873] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0874] This invention relates to an AI-equipped wearable eyeglasses that improves the efficiency of users' daily tasks and facilitates information acquisition. This system utilizes the user's voice input, visual information, and image recognition to assist with daily tasks such as DIY and cooking. Furthermore, the invention is equipped with an emotion engine that recognizes the user's emotions and optimizes the work experience based on those emotions.

[0875] System configuration

[0876] 1. Glasses-type wearable device

[0877] The device accepts voice input and captures visual information with a camera, allowing users to operate it hands-free.

[0878] The device has a built-in function that automatically transmits voice data to a server, where the voice data is digitized using an encoder.

[0879] 2. Server

[0880] The server analyzes the voice data using a natural language processing module, converts the voice data into text, and searches for the required information.

[0881] The retrieved information is sent to the device. The server also processes the image data received from the device to identify the user's progress and recognition targets.

[0882] The server is equipped with an emotion engine that can recognize the user's emotional state from their voice and image data.

[0883] 3. Natural Language Processing Module

[0884] This is a module inside the server that converts voice data into text and understands the intent of commands and questions. For example, if a user says, "Tell me the next step," the module extracts the command "next step" and searches for the appropriate information.

[0885] 4. Image Recognition Module

[0886] This is a module inside the server that analyzes real-time image data sent from the device. When the user is working, it recognizes specific objects and progress from the captured images.

[0887] 5. Emotion Engine

[0888] This is a module within the server that analyzes the user's voice and image data to recognize their emotional state, for example, determining whether the user is stressed or relaxed based on their tone of voice and facial expression.

[0889] 6. AR display module

[0890] The device will then overlay the received information onto the user's field of vision, providing visual guidance on the location of parts and how to install screws when assembling furniture, for example.

[0891] System Operation

[0892] 1. Receiving and analyzing voice commands

[0893] The user gives a voice command such as "Tell me the next step." The device receives this voice and sends it to the server as voice data.

[0894] 2. Speech data analysis and information retrieval

[0895] The server analyzes the voice data using a natural language processing module and searches a database for corresponding information, such as cooking instructions or DIY steps.

[0896] 3. Transmission and Display of Information

[0897] The server sends the search results to the device, which then displays the information as an overlay in the user's field of view, and can also provide voice instructions.

[0898] 4. Checking work progress and providing guidance on next steps

[0899] As the user works, a camera captures their progress, and these image data are sent to a server, which uses an image recognition module to analyze their progress.

[0900] The server checks whether the next step has been completed and sends the next step to the terminal, which again overlays the information in the user's field of view and provides voice guidance.

[0901] 5. Recognizing and regulating emotional states

[0902] The server uses the voice and image data to analyze the user's emotional state with an emotion engine. For example, if the user is feeling stressed, the server will recognize this.

[0903] Based on the user's emotional state, the server adjusts the next action: for example, if the user is feeling stressed, it guides them through steps to make the task less difficult.

[0904] Additionally, if the user is determined to be in a negative emotional state, the server will send encouraging messages or simple hints.

[0905] Specific use cases

[0906] When cooking

[0907] 1. The user says, "Tell me what's in the fridge."

[0908] 2. The device sends the voice data to the server, which analyzes it and lists the contents of the refrigerator.

[0909] 3. The list is sent to the device and displayed in the user's field of view.

[0910] 4. When the user asks, "What recipe can I make with these ingredients?" the server searches for the recipe and displays it.

[0911] 5. The recipe steps are displayed in the user's field of vision and are guided by voice.

[0912] 6. The server periodically analyzes the user's emotional state, and if the user is feeling stressed, it adjusts the difficulty of the recipe to be less difficult or starts with easier steps.

[0913] For DIY work

[0914] 1. The user speaks, "Tell me how to assemble furniture."

[0915] 2. The device sends the voice data to the server, which then searches for assembly instructions.

[0916] 3. The procedure is sent to the terminal and displayed in the user's field of view.

[0917] 4. As the user lines up the parts, a camera captures the situation and the server checks the progress.

[0918] 5. The next step is displayed in the user's field of view and is announced audibly.

[0919] 6. The server analyzes the user's emotional state and sends encouraging messages or provides simple explanations if the user is feeling confused or stressed.

[0920] As described above, the present invention provides specific embodiments for streamlining users' daily tasks and significantly improving work efficiency. Furthermore, the present invention can improve the user experience by recognizing the user's emotional state and providing optimal feedback based on that state.

[0921] The processing flow will be explained below.

[0922] Step 1:

[0923] The user gives a voice command such as "Tell me the next step." The device receives this voice command through the microphone and records it as audio data.

[0924] Step 2:

[0925] The device converts the recorded audio data into a digital format using an encoder and transmits it to a server via the Internet.

[0926] Step 3:

[0927] The server passes the received voice data to a natural language processing module, which converts the voice data into text.

[0928] Step 4:

[0929] The server analyzes the text data, understands the "next steps" instructions, and searches the database for the appropriate information.

[0930] Step 5:

[0931] The server converts the search results into data packets and transmits them to the terminal.

[0932] Step 6:

[0933] The device decodes the data packets received from the server and displays them as an AR overlay in the user's field of view, such as instructions on how to assemble furniture or cooking instructions.

[0934] Step 7:

[0935] The user follows the displayed instructions to proceed with the work. The device's camera captures the progress of the work and sends the image data to the server in real time.

[0936] Step 8:

[0937] The server uses an image recognition module to analyze the received image data and check the user's progress, for example, checking the correct placement of parts or the progress of cooking.

[0938] Step 9:

[0939] The server generates instruction data for the next step based on the analysis results and sends it to the terminal.

[0940] Step 10:

[0941] The device receives instruction data from the server and displays the next steps as an overlay in the user's field of vision. At the same time, it can also provide voice guidance for the next steps.

[0942] Step 11:

[0943] The server then passes the voice and image data to the emotion engine in parallel, which analyzes the user's emotional state, determining whether they are stressed or relaxed based on their voice tone and facial expression.

[0944] Step 12:

[0945] The server then uses the emotion engine's analysis to tailor the next steps to the user's emotional state. For example, if the user is feeling stressed, the server will suggest easier steps.

[0946] Step 13:

[0947] If the user is determined to be in a negative emotional state, the server generates and sends to the terminal encouraging messages and additional hints to make the task easier.

[0948] Step 14:

[0949] The device overlays encouraging messages and additional hints onto the user's field of vision and provides audio support.

[0950] Step 15:

[0951] This process is repeated until the user completes the task, at which point the system will provide a visual and audio notification that the task is complete.

[0952] The above is a concrete processing flow of a system incorporating an emotion engine. This flow allows users to work efficiently and also receives support according to their emotional state.

[0953] Example 2

[0954] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0955] Today's users need assistive technologies to help them efficiently complete their daily tasks. However, existing methods rely solely on voice instructions and visual information, lacking the ability to analyze and respond to the user's emotional state and progress in real time. Furthermore, they are unable to adequately address the stress and confusion users feel during the process, limiting their ability to improve work efficiency. Furthermore, the lack of encryption or anonymization of personal information during the transmission and reception of voice and image data raises security and privacy concerns.

[0956] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0957] In this invention, the server includes a means for analyzing voice data and searching for corresponding information, a means for analyzing captured data and identifying progress and recognition targets, and a means for analyzing the user's voice and image data and recognizing their emotional state, which makes it possible to grasp the user's emotional state and work progress in real time and adjust the next action based on that.

[0958] "Voice data" refers to data obtained by converting a user's voice into a digital signal.

[0959] A "server" is a computer system that processes and stores data over a network.

[0960] "Voice input" is the way a device receives spoken words or sounds from a user.

[0961] "Field of view overlay display" is a technology that displays information superimposed on the real image that the user is actually seeing.

[0962] A "camera" is a device for capturing video or images.

[0963] "Capture data" refers to image and video data captured or acquired by devices such as cameras.

[0964] "Progress" is a concept that indicates the progress and degree of achievement of a task or project.

[0965] A "recognition target" is a target or object that the system identifies and recognizes through analysis.

[0966] An "emotional state" is the state of a user's mood or emotions.

[0967] The "emotion engine" is a software module that analyzes the user's voice and image data to recognize their emotional state.

[0968] A "natural language processing module" is a software module that analyzes voice and text data to understand and process human language.

[0969] An "AR display module" is a software module that uses augmented reality technology to overlay information on the real world.

[0970] "Digitalization" is the process of converting analog data into a digital signal.

[0971] MODE FOR CARRYING OUT THE INVENTION

[0972] This invention relates to an AI-equipped wearable eyeglasses device that streamlines users' daily tasks and makes it easier to obtain information. In particular, it uses the user's voice input, visual information, and image recognition to assist with DIY tasks, cooking, and other tasks, and further optimizes the work experience using an emotion engine. This invention includes the following hardware and software components:

[0973] Hardware Configuration

[0974] 1. Glasses-type wearable device

[0975] Microphone: A device that captures audio input.

[0976] Camera: A device that captures visual information and acquires image data.

[0977] Encoder: A device that digitizes and compresses audio data.

[0978] AR display: A device that displays received information as an overlay on the user's field of vision.

[0979] Software Configuration

[0980] 1. Server

[0981] Natural language processing module: Software that converts voice data into text and understands the intent of commands and questions.

[0982] Database: Data storage for storing and retrieving necessary information.

[0983] Image Recognition Module: Software that analyzes captured image data to identify progress and recognized objects.

[0984] Emotion engine: Software that analyzes a user's voice and image data to recognize their emotional state.

[0985] Operating Procedure

[0986] When a user verbally commands, "Tell me what the next step is," the device's microphone captures the voice, and the digitized voice data is compressed by an encoder and sent to the server. The server's natural language processing module analyzes the voice data, converts it into text, and searches a database for appropriate information. This information is sent to the device and overlaid on the user's field of view via the AR display. The camera also captures the user's work progress in real time and sends it to the server, where an image recognition module analyzes the progress and identifies the next step.

[0987] Specific examples

[0988] When cooking

[0989] When the user says, "Tell me what's in the fridge," the device sends a voice message to the server, which then lists the contents of the fridge. The list is then sent to the device and displayed in the field of view. The user can then say, "What recipes can I make with these ingredients?" and the server will search for recipes and overlay the instructions in the field of view. The server analyzes the user's emotional state and adjusts the difficulty of the recipes if the user feels stressed.

[0990] For DIY work

[0991] When a user says, "Tell me how to assemble furniture," the device sends voice data to the server, which searches for assembly instructions. After the instructions are displayed in the field of view, a camera captures the placement of the parts, and the server analyzes the images to check the progress and display the next step. To ensure a comfortable working environment, the server monitors the user's emotional state and provides encouraging messages or simple explanations if the user is experiencing difficulty.

[0992] Prompt Sentence Examples

[0993] "Tell me a recipe I can make using ingredients in the fridge."

[0994] "Guide me through the next steps"

[0995] Please check the current progress

[0996] "Is there an easier way?"

[0997] In this way, the system can streamline users' daily tasks and improve their experience by providing optimal emotion-based feedback.

[0998] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0999] Step 1:

[1000] The user gives a voice command

[1001] Specific actions

[1002] The user gives a voice command, such as "Tell me what to do next." The device's microphone captures this voice.

[1003] Input: User's voice commands

[1004] Output: Audio data

[1005] Step 2:

[1006] Sending audio data

[1007] Specific actions

[1008] The device digitizes the captured audio using an encoder, compresses it, and then sends it to the server.

[1009] Input: Digitized and compressed audio data

[1010] Output: Audio data sent to the server

[1011] Step 3:

[1012] Analysis of audio data

[1013] Specific actions

[1014] The server passes the received voice data to a natural language processing module, which converts it into text, and extracts the intent of commands and questions from the voice data.

[1015] Input: Audio data sent to the server

[1016] Output: Parsed text data

[1017] Step 4:

[1018] Searching for information

[1019] Specific actions

[1020] The server's natural language processing module analyzes the text and then searches the database for the necessary information, such as cooking instructions or DIY steps.

[1021] Input: Parsed text data

[1022] Output: Search result information data

[1023] Step 5:

[1024] Sending information

[1025] Specific actions

[1026] The server transmits the search result information data to the terminal.

[1027] Input: Search result information data

[1028] Output: Information data sent to the terminal

[1029] Step 6:

[1030] Displaying Information

[1031] Specific actions

[1032] The device overlays the received information onto the user's field of view through an AR display module, and may also provide audio instructions using an audio output device.

[1033] Input: Information data sent to the terminal

[1034] Output: Information overlaid on the field of view

[1035] Step 7:

[1036] Work progress capture

[1037] Specific actions

[1038] As the user works, the device's camera captures their progress in real time.

[1039] Input: User's work progress

[1040] Output: Captured image data

[1041] Step 8:

[1042] Sending image data

[1043] Specific actions

[1044] The terminal transmits the captured image data to the server.

[1045] Input: Captured image data

[1046] Output: Image data sent to the server

[1047] Step 9:

[1048] Progress Analysis

[1049] Specific actions

[1050] The server's image recognition module analyzes the received image data and identifies the user's progress and the object to be recognized.

[1051] Input: Image data sent to the server

[1052] Output: Parsed progress information

[1053] Step 10:

[1054] Next step guidance

[1055] Specific actions

[1056] Based on the analyzed progress information, the server sends the next step to the device, which then overlays the received information onto the user's field of view and provides audio guidance.

[1057] Input: Parsed progress information

[1058] Output: Information data for next steps

[1059] Step 11:

[1060] Emotional state analysis

[1061] Specific actions

[1062] The server uses the voice data and image data to analyze the user's emotional state with an emotion engine, for example, by reading emotions from the user's tone of voice and facial expressions.

[1063] Input: Audio data, image data

[1064] Output: Parsed emotional state

[1065] Step 12:

[1066] Adjusting the next action

[1067] Specific actions

[1068] The server adjusts the next action based on the analyzed emotional state, for example, if the user is feeling stressed, it will guide them through steps to reduce the difficulty.

[1069] Input: Parsed emotional state

[1070] Output: A coordinated action plan

[1071] This will help users streamline their daily tasks and improve the user experience by providing optimal feedback based on emotions.

[1072] (Application example 2)

[1073] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1074] Problems faced by workers in modern factories and other workplaces include the complexity of work instructions, the cumbersome nature of progress management, and the impact of workers' emotional states on work efficiency. Conventional systems have difficulty managing this information centrally and providing real-time feedback, leading to reduced work efficiency and increased errors. The present invention aims to provide a new system that solves these problems and maximizes workers' work efficiency.

[1075] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1076] In this invention, the server includes means for receiving a user's voice input and converting it into voice data, means for transmitting the voice data to the server, means for the server to analyze the voice data and search for corresponding information, means for the server to transmit the searched information to the terminal, means for the terminal to overlay the information received on the user's field of view, means for capturing the user's actions with a camera and transmitting the captured data to the server, means for the server to analyze the captured data and identify progress and recognition targets, means for recognizing the user's emotional state using the captured data and voice data analyzed by the server, and means for adjusting the difficulty of work instructions and providing feedback based on the recognized emotional state. This allows the worker to obtain appropriate work information simply by giving voice instructions, and by checking progress and recognizing emotions with the camera, it becomes possible to optimize work efficiency in real time.

[1077] "Voice input" allows the system to recognize voice commands or questions uttered by the user as instructions.

[1078] "Voice data" refers to voice input converted into digital signals that can be used for analysis and retrieval.

[1079] The "server" is a central processing device that analyzes audio data and visual information and transmits the analysis results to the terminal.

[1080] A "terminal" refers to a wearable device that is worn by the user and displays information in the user's field of vision, and is responsible for exchanging audio and visual information.

[1081] "Visual information" refers to image and video data captured through cameras and other sensors.

[1082] A "camera" is a device that captures visual information and obtains images of a user's actions and environment.

[1083] "Capture data" refers to image and video data acquired from a visual sensor such as a camera.

[1084] "Analysis" refers to the process of extracting and processing specific information based on input voice data or captured data.

[1085] "Progress" is information that indicates the progress and degree of achievement of a task.

[1086] A "recognition target" is a specific object or action to be analyzed, and is identified through analysis.

[1087] "Emotional state" refers to the psychological state that can be read from the user's voice and facial expression, and includes stress, relaxation, etc.

[1088] "Feedback" refers to reactions such as encouraging messages or information on corrective work instructions provided to the user based on the analysis results.

[1089] "Difficulty" is an index that indicates the complexity of the task and the skill level required.

[1090] "Overlay display" refers to a method of displaying information superimposed on the user's field of vision, directly and visually conveying work instructions and progress status.

[1091] The system for implementing this invention includes a wearable terminal (smart glasses) worn by a user, a server, and a camera. The specific roles and operations of each element are described below.

[1092] Wearable devices

[1093] A wearable device receives voice input from the user and converts it into voice data. The device has a means of sending the converted voice data to a server. Voice recognition software such as the SpeechRecognition library is used to encode the voice data. The device also has a function for overlaying information received from the server onto the user's field of view. Specifically, it uses augmented reality (AR) technology to display instructions in a way that makes them easy for the user to see. Screen display and voice guidance on the device are handled by the ARDisplay module and speaker.

[1094] server

[1095] The server receives the voice data and analyzes it using a natural language processing module. The analyzed voice data is used to search for corresponding information. For example, a natural language processing library such as Python's Natural Language Toolkit (NLTK) is used. The server also has the function of analyzing the transmitted capture data and identifying the user's progress and recognition target. An image processing library such as OpenCV is used to analyze the capture data.

[1096] Next, the server contains an emotion engine that analyzes the user's voice and captured data to recognize their emotional state. The EmotionRecognition library is used to analyze the emotional state. For example, if the user is feeling stressed, the server determines this based on the analysis results. Based on the results, the server adjusts the difficulty of the work instructions and provides appropriate feedback. The entire process is carried out in real time.

[1097] camera

[1098] The camera is used to capture the user's actions and the surrounding situation. The captured data is sent to the server, where it is used to check the progress and identify the recognition target.

[1099] Specific examples

[1100] Receiving work orders

[1101] When the user speaks, "Tell me what to do next," the device sends the voice data to the server, which analyzes it, finds the appropriate work instructions, and displays them as an overlay in the user's field of view.

[1102] Progress check and feedback

[1103] While the task is in progress, the camera captures the user's movements and progress and sends them to the server. The server analyzes the captured images and checks the progress. If the server determines that the user is feeling stressed, it uses an emotion engine to analyze the user's state and provide appropriate feedback. For example, it displays instructions to reduce the difficulty of the task or an encouraging message.

[1104] Prompt Sentence Examples

[1105] Tell me what to do next

[1106] Check your progress

[1107] Work completed

[1108] Analyze your emotional state

[1109] Display an encouraging message

[1110] As described above, the present invention provides a system that allows the user to flexibly proceed with work based on simple voice instructions and visual information, thereby making it possible to improve work efficiency.

[1111] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1112] Step 1:

[1113] The user enters a voice command

[1114] The user issues a voice command, and the voice data is collected through the terminal's microphone.

[1115] Input: User's voice

[1116] Output: Audio data captured on the device

[1117] Specific operation: When the user says "Tell me what to do next," the device's microphone captures the voice.

[1118] Step 2:

[1119] Voice data is digitized and sent to the server

[1120] The terminal converts the collected voice into digital data and sends it to the server.

[1121] Input: Audio data

[1122] Output: Digital audio data sent to the server

[1123] Specific operation: The device's voice recognition module converts the speech into text, which is then sent to a server over the Internet.

[1124] Step 3:

[1125] Speech data analysis and information retrieval

[1126] The server receives the voice data, analyzes it using a natural language processing module, and retrieves corresponding information.

[1127] Input: Digital audio data

[1128] Output: Retrieved information

[1129] Specific operation: Natural language processing software (e.g., NLTK) on the server analyzes the text of the voice data and searches for the "next task."

[1130] Step 4:

[1131] Submit search results

[1132] The server transmits the retrieved information to the terminal.

[1133] Input: Searched information

[1134] Output: Search results sent to your device

[1135] Specific operation: The server divides the information into packets and sends them to the device's IP address.

[1136] Step 5:

[1137] Overlay display in the user's field of view

[1138] The terminal displays the received information as an overlay in the user's field of view.

[1139] Input: Search results received

[1140] Output: Work instructions displayed in the user's field of view

[1141] Specific operation: The AR display module of the wearable device receives text information and displays it over the user's field of view.

[1142] Step 6:

[1143] Camera capture of user's work progress

[1144] As the user works, the device's camera captures the progress and sends the image data to the server.

[1145] Input: User's work in progress

[1146] Output: Image data sent to the server

[1147] Specific operation: The device's camera takes images in real time and uploads the data to the server.

[1148] Step 7:

[1149] Analyzing image data and identifying progress

[1150] The server analyzes the captured image data and identifies the progress and the object of recognition.

[1151] Input: Captured image data

[1152] Output: Analysis results and progress information

[1153] Specific operation: Image recognition software (e.g., OpenCV) on the server analyzes the image and determines the progress of the work.

[1154] Step 8:

[1155] Recognition of emotional states

[1156] The server analyzes the audio and image data to recognize the user's emotional state.

[1157] Input: Audio and image data

[1158] Output: Perceived emotional state

[1159] Specific operation: The emotion recognition engine analyzes emotional states such as stress or relaxation from voice tone and facial expressions.

[1160] Step 9:

[1161] Providing feedback based on emotional state

[1162] The server adjusts the difficulty of the work instructions based on the perceived emotional state and provides feedback.

[1163] Input: Perceived emotional state and progress information

[1164] Output: Tailored work instructions and encouraging messages

[1165] Specific operation: Based on the emotion recognition results, the server facilitates the next task or sends an encouraging message to the device, which is then overlaid on the device's field of vision.

[1166] The above is the specific flow of processing in this system.

[1167] 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.

[1168] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[1169] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1170] [Third embodiment]

[1171] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1172] 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.

[1173] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[1174] 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.

[1175] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1176] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1177] 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.

[1178] 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.

[1179] 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 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.

[1180] 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.

[1181] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1182] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1183] This invention relates to an AI-equipped wearable glasses-type device that improves the efficiency of users' daily tasks and makes it easier to obtain information. This system utilizes the user's voice input, visual information, and image recognition to assist with daily tasks such as DIY and cooking.

[1184] System configuration

[1185] 1. Glasses-type wearable device

[1186] The device accepts voice input and captures visual information with a camera, allowing users to operate it hands-free.

[1187] The device has a built-in function that automatically transmits voice data to a server, where the voice data is digitized using an encoder.

[1188] 2. Server

[1189] The server analyzes the voice data using a natural language processing module, converts the voice data into text, and searches for the required information.

[1190] The retrieved information is sent to the device. The server also processes the image data received from the device to identify the user's progress and recognition targets.

[1191] 3. Natural Language Processing Module

[1192] This is a module inside the server that converts voice data into text and understands the intent of commands and questions. For example, if a user says, "Tell me the next step," the module extracts the command "next step" and searches for the appropriate information.

[1193] 4. Image Recognition Module

[1194] This is a module inside the server that analyzes real-time image data sent from the device. When the user is working, it recognizes specific objects and progress from the captured images.

[1195] 5. AR display module

[1196] The device will then overlay the received information onto the user's field of vision, providing visual guidance on the location of parts and how to install screws when assembling furniture, for example.

[1197] System Operation

[1198] 1. Receiving and analyzing voice commands

[1199] The user gives a voice command such as "Tell me the next step." The device receives this voice and sends it to the server as voice data.

[1200] 2. Speech data analysis and information retrieval

[1201] The server analyzes the voice data using a natural language processing module and searches a database for corresponding information, such as cooking instructions or DIY steps.

[1202] 3. Transmission and Display of Information

[1203] The server sends the search results to the device, which then displays the information as an overlay in the user's field of view, and can also provide voice instructions.

[1204] 4. Checking work progress and providing guidance on next steps

[1205] As the user works, a camera captures their progress, and these image data are sent to a server, which uses an image recognition module to analyze their progress.

[1206] The server checks whether the next step has been completed and sends the next step to the terminal, which again overlays the information in the user's field of view and provides voice guidance.

[1207] Specific use cases

[1208] When cooking

[1209] 1. The user says, "Tell me what's in the fridge."

[1210] 2. The device sends the voice data to the server, which analyzes it and lists the contents of the refrigerator.

[1211] 3. The list is sent to the device and displayed in the user's field of view.

[1212] 4. When the user asks, "What recipe can I make with these ingredients?" the server searches for the recipe and displays it.

[1213] 5. The recipe steps are displayed in the user's field of vision and are guided by voice.

[1214] For DIY work

[1215] 1. The user speaks, "Tell me how to assemble furniture."

[1216] 2. The device sends the voice data to the server, which then searches for assembly instructions.

[1217] 3. The procedure is sent to the terminal and displayed in the user's field of view.

[1218] 4. As the user lines up the parts, a camera captures the situation and the server checks the progress.

[1219] 5. The next step is displayed in the user's field of view and is announced audibly.

[1220] As described above, the present invention provides specific embodiments for streamlining the user's daily work and significantly improving work efficiency.

[1221] The processing flow will be explained below.

[1222] Step 1:

[1223] The user gives a voice command such as "Tell me the next step." The device receives this voice command through a microphone and records it as voice data.

[1224] Step 2:

[1225] The terminal converts the voice data into a digital format using an encoder and transmits it to a server over the Internet.

[1226] Step 3:

[1227] The server passes the received voice data to a natural language processing module, which converts the voice data into text.

[1228] Step 4:

[1229] The server analyzes the text data and understands the command, "Tell me the next step." Based on this command, it searches the database for the necessary information.

[1230] Step 5:

[1231] The server generates search results and converts information about next steps into data packets and sends them to the terminal.

[1232] Step 6:

[1233] The device decodes the data packets received from the server and overlays them in the user's field of view as an AR display, with specific instructions on the next steps.

[1234] Step 7:

[1235] The user follows the displayed instructions to proceed with the work, and the progress of the work is captured in real time by a camera.

[1236] Step 8:

[1237] The device sends the captured image to the server, which contains the progress of the work.

[1238] Step 9:

[1239] The server uses an image recognition module to analyze the received image data and determine its progress and accuracy.

[1240] Step 10:

[1241] The server sends the analysis results to the terminal, and if the progress is correct, generates data instructing the next step.

[1242] Step 11:

[1243] The device receives instructions from the server and displays them as an overlay in the user's field of view as the next step, while simultaneously providing voice guidance for the next step.

[1244] Step 12:

[1245] This process is repeated until the user completes the task, at which point the system will provide a visual and audio notification that the task is complete.

[1246] The above is a concrete processing flow of the system program, which allows the user to work efficiently.

[1247] Example 1

[1248] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1249] With conventional technology, it was difficult to utilize users' voice input or visual information to assist with tasks. Furthermore, there was a lack of systems that could monitor the user's progress and provide appropriate instructions in real time. This resulted in inefficiencies in processes such as daily tasks, DIY, and cooking, and required users to spend time and effort looking up information.

[1250] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1251] In this invention, the server includes means for analyzing voice data with a natural language processing module and searching for corresponding information, means for analyzing captured data with an image recognition module and identifying progress and recognition targets, and means for transmitting the searched information to the terminal, thereby enabling the server to quickly search for information corresponding to the user's voice instructions and provide visual and audio guidance.

[1252] "Voice input" is a method by which a user communicates information or instructions to a system by speaking.

[1253] "Audio data" is data obtained by converting audio input into digital form.

[1254] A "server" is a central control unit that analyzes data and retrieves information.

[1255] A "natural language processing module" is a software component that converts voice data into text and analyzes the meaning of that text.

[1256] "Search means" is the function by which the server searches for appropriate information from the database.

[1257] A "terminal" is a glasses-type wearable device used by a user, which is a device for inputting voice and capturing visual information.

[1258] "Overlay display" is a method in which a terminal displays information superimposed on the user's field of view.

[1259] "Capture device" is a general term for cameras and sensors used to capture user movements and visual information.

[1260] An "image recognition module" is a software component that analyzes captured data to identify objects and progress.

[1261] "Voice guidance means" is a function that allows the terminal to convey instructions and information to the user by voice.

[1262] "Encryption means" refers to a technology that protects security by encrypting data contents when transmitting and receiving data.

[1263] "Anonymization means" refers to technology that converts a user's personal information into a form that cannot be identified.

[1264] The "advertising data generating means" is a function that creates data for displaying advertisements in order to increase profits.

[1265] This invention relates to an AI-equipped wearable glasses-type device that improves the efficiency of users' daily tasks and makes it easier to obtain information. This system utilizes the user's voice input, visual information, and image recognition to assist with daily tasks such as DIY and cooking.

[1266] The system includes the following components:

[1267] 1. Glasses-type wearable device

[1268] The device receives voice input and captures visual information with a camera, allowing the user to operate it hands-free. The device is equipped with a built-in function that automatically transmits voice data to a server, where it is digitized using an encoder. The device also includes an AR display module that overlays the received information onto the user's field of view. It also has a voice guidance function that provides necessary information to the user via voice.

[1269] 2. Server

[1270] The server receives the voice data and analyzes it using a natural language processing module. The analyzed voice data is converted into text and the required information is searched for in a database. The server also incorporates an image recognition module that understands the user's current task status and determines the next step. The server uses encryption methods to send and receive data to ensure security. Furthermore, the server also includes functions to anonymize users' personal information and generate advertising data as a means of increasing revenue.

[1271] Specific use cases

[1272] When cooking

[1273] 1. The user says, "Tell me what's in the fridge."

[1274] 2. The device sends the voice data to the server, which analyzes it and lists the contents of the refrigerator.

[1275] 3. The list is sent to the device and displayed in the user's field of view.

[1276] 4. When the user asks, "What recipe can I make with these ingredients?" the server searches for and displays the recipe.

[1277] 5. The recipe steps are displayed in the user's field of vision and are guided by voice.

[1278] For DIY work

[1279] 1. The user speaks, "Tell me how to assemble furniture."

[1280] 2. The device sends the voice data to the server, which then searches for assembly instructions.

[1281] 3. The procedure is sent to the terminal and displayed in the user's field of view.

[1282] 4. As the user lines up the parts, a camera captures the situation and the server checks the progress.

[1283] 5. The next step is displayed in the user's field of view and is announced audibly.

[1284] Prompt Sentence Examples

[1285] "Tell me the next step"

[1286] "Tell me what's in the fridge."

[1287] "Teach me how to assemble furniture"

[1288] In this way, the present invention can improve the efficiency of users' daily tasks, and specific embodiments can significantly improve the user experience. By implementing the present invention, users can receive immediate guidance using voice input and visual information, allowing them to perform daily tasks quickly and accurately.

[1289] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1290] Step 1: Receive voice instructions

[1291] The user gives a voice command such as "Tell me the next step." The device's microphone receives the voice input, and the voice data is digitized by an encoder. The digitized voice data is sent from the device to the server. The input is the voice command, and the output is the digitized voice data.

[1292] Step 2: Analyzing the audio data

[1293] The server receives the voice data, and the natural language processing module converts the data into text. The natural language processing module analyzes the commands from the text and extracts specific actions. The input is digitized voice data, and the output is the analyzed text and its commands.

[1294] Step 3: Finding information

[1295] The server queries a database based on the parsed text to find corresponding information, such as DIY instructions or cooking recipes. The input is the parsed text and extracted instructions, and the output is the retrieved related information.

[1296] Step 4: Submit your information

[1297] The server sends the search results back to the terminal. At this time, the security of the data is ensured using encryption. The input is the search result information, and the output is the information sent to the terminal in encrypted form.

[1298] Step 5: Information and navigation

[1299] The device decodes the received information and displays it as an overlay in the user's field of view using the AR display module. At the same time, the device uses a voice guidance means to communicate information and procedures to the user aloud. The input is encrypted information, and the output is the information overlaid in the field of view and voice guidance.

[1300] Step 6: Check the progress of your work

[1301] As the user works, the device's camera captures the progress in real time. The captured image data is sent from the device to the server. The input is the progress of the work, and the output is the captured image data.

[1302] Step 7: Progress analysis

[1303] The image recognition module analyzes the image data received by the server to identify the progress and the object to be recognized. For example, to confirm the position of parts in furniture assembly. The input is the captured image data, and the output is the analyzed progress and the recognized object information.

[1304] Step 8: Next steps

[1305] Based on the analysis results, the server sends the next step and necessary information back to the device. The next step received by the device is again overlaid in the user's field of view and guided by voice. The input is the analyzed progress and next step information, and the output is the next step displayed in the field of view and its voice guidance.

[1306] (Application example 1)

[1307] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1308] In today's brick-and-mortar stores, customers often find it difficult to find products and find detailed product information, reviews, and promotional information instantly. They also have limited means for effectively managing their shopping lists. This reduces shopping efficiency and impairs the customer experience. Furthermore, insufficient privacy practices raise concerns about the protection of personal information.

[1309] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1310] In this invention, the server includes a means for allowing a user to search for products in a store and visually providing location information for specific products, a means for displaying detailed product information and reviews based on a customer's voice command, and a means for acquiring location information from a proximity sensor in the store and automatically displaying promotional information. This allows customers to quickly find the products they need and obtain detailed information, improving shopping efficiency and satisfaction. Furthermore, the quality of the customer experience is improved by providing appropriate advertising information while protecting privacy.

[1311] "Voice input" is an input method in which a user verbally provides instructions or information through a microphone, which is then recognized and analyzed by the system.

[1312] "Voice data" refers to data that has been converted into digital form from a user's voice input.

[1313] A "server" is a central processing unit for analyzing voice data, searching for information, and processing data.

[1314] "Overlay display" is a display method in which a terminal presents information superimposed on the user's field of vision.

[1315] A "camera" is a device that captures the user's actions and environment in real time and converts them into video data.

[1316] "Capture data" refers to image and video data captured by a camera.

[1317] "Location information" is data relating to the location of a particular product.

[1318] "Detailed information" refers to information such as product specifications, descriptions, reviews, etc.

[1319] A "review" is information that describes a user's impressions and evaluations.

[1320] "Promotional Information" refers to information about discounts and special offers offered as part of sales promotion activities.

[1321] A "proximity sensor" is a device that detects the location of a user when they approach a specific product or area.

[1322] "Anonymization" is a method of processing personal information so that it cannot identify a specific individual.

[1323] "Advertising data" refers to promotional information generated for the purpose of increasing revenue.

[1324] This invention relates to a system that uses AI-equipped glasses-type wearable devices to improve customers' shopping experiences in brick-and-mortar stores. Specifically, it provides a means for customers to search for products through voice input and visually display detailed information, reviews, and promotional information about those products. The configuration and operation of the system are described in detail below.

[1325] System configuration

[1326] Glasses-type wearable device

[1327] The device receives voice input and captures visual information with a camera. The voice data is digitized and sent to a server. The device also has an AR display function, which overlays information on the user's field of view.

[1328] server

[1329] The server includes a number of analysis modules.

[1330] Natural language processing module: Uses the Google Cloud Natural Language API to convert voice data into text and understand the intent of commands and questions.

[1331] Image recognition module: Uses OpenCV to analyze image data sent from the device and identify progress and recognition targets.

[1332] Database module: Access a database that provides real-time product location information, details, reviews, promotion information, etc.

[1333] Specific examples

[1334] The following is a usage scenario within a physical store:

[1335] 1. Product search and guidance:

[1336] The user speaks, "Where is the item XX?"

[1337] The voice data is sent to the server, and the natural language processing module extracts "XX product" as a search keyword.

[1338] The server retrieves the location information of the relevant product from the database and sends it to the terminal.

[1339] The device overlays real-time navigation information onto the user's field of view.

[1340] 2. Product details display:

[1341] The user picks up a product and says, "Show me reviews for this product."

[1342] The voice data is sent to the server, and a natural language processing module parses the command "Show me reviews."

[1343] The device's camera captures the product barcode and sends the image data to the server.

[1344] The image recognition module analyzes the barcode and identifies the corresponding product.

[1345] Review information is retrieved from the database and overlaid on the device's field of view using the device's AR display function.

[1346] 3. Display of Promotional Information:

[1347] When a user approaches a specific area, a proximity sensor detects their location.

[1348] The server retrieves promotional information about products in the relevant area from the database and transmits it to the terminal.

[1349] Promotional information is overlaid on the user's field of view.

[1350] Example prompt

[1351] Here are some examples of prompts to input to the generative AI model:

[1352] "Generate an application design that allows a user to search for a specific product in a store by voice, navigate to that product's location in an AR display, and visually present detailed information and reviews in AR."

[1353] This invention allows customers to quickly find the products they need and obtain detailed information, improving shopping efficiency and satisfaction. It also improves the quality of the customer experience by providing appropriate advertising information while protecting privacy. This invention significantly improves the shopping experience in physical stores.

[1354] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1355] Step 1:

[1356] The user speaks, "Where is the item XX?"

[1357] Input: User's voice command.

[1358] Output: Audio data.

[1359] Specific operation: The device's microphone captures the user's voice instructions and digitizes them as voice data.

[1360] Step 2:

[1361] The terminal transmits the voice data to the server.

[1362] Input: Digitized audio data.

[1363] Output: Notification of completion of transmission to the server.

[1364] Specific operation: The terminal's communication module encodes the voice data and sends it to the server.

[1365] Step 3:

[1366] The server analyzes the voice data, converts it into text using a natural language processing module, and extracts the intent.

[1367] Input: Audio data sent from the device.

[1368] Output: Data converted to text, intent extracted.

[1369] Specific operation: The Google Cloud Natural Language API on the server converts the voice data into text and extracts keywords (e.g., "product of XX").

[1370] Step 4:

[1371] The server retrieves the location information of the relevant product from the database.

[1372] Input: Extracted keywords (product names).

[1373] Output: Product location data.

[1374] Specific operation: The server accesses the database and obtains the location information of the corresponding product based on the product name.

[1375] Step 5:

[1376] The server sends the location data to the device.

[1377] Input: Location data.

[1378] Output: Notification of completion of transmission to the terminal.

[1379] Specific operation: The server's communication module encodes the location data and sends it to the device.

[1380] Step 6:

[1381] The device displays location information in an AR overlay on the user's field of view.

[1382] Input: Location data.

[1383] Output: Navigation information displayed in the user's field of view.

[1384] Specific operation: The device's AR display module visualizes location data and overlays it on the user's field of view in real time.

[1385] Step 7:

[1386] The user picks up a product and says, "Show me reviews for this product."

[1387] Input: User's voice command.

[1388] Output: Audio data.

[1389] Specific operation: The device's microphone captures the user's voice instructions and digitizes them as voice data.

[1390] Step 8:

[1391] The terminal transmits the voice data to the server.

[1392] Input: Digitized audio data.

[1393] Output: Notification of completion of transmission to the server.

[1394] Specific operation: The terminal's communication module encodes the voice data and sends it to the server.

[1395] Step 9:

[1396] The server analyzes the voice data, converts it into text using a natural language processing module, and extracts the intent.

[1397] Input: Audio data sent from the device.

[1398] Output: Data converted to text, intent extracted.

[1399] Specific operation: The Google Cloud Natural Language API on the server converts the voice data into text and extracts commands (e.g., "Show me reviews").

[1400] Step 10:

[1401] The user captures the product with a camera.

[1402] Input: Product image data.

[1403] Output: Capture data.

[1404] Specific operation: The device's camera captures the product barcode or image and digitizes it as image data.

[1405] Step 11:

[1406] The device sends the captured data to the server.

[1407] Input: Product image data.

[1408] Output: Notification of completion of transmission to the server.

[1409] Specific operation: The communication module of the terminal encodes the image data and sends it to the server.

[1410] Step 12:

[1411] The server analyzes the product barcode using an image recognition module and identifies the corresponding product from the database.

[1412] Input: Capture data.

[1413] Output: Identified product information.

[1414] Specific operation: OpenCV on the server analyzes the image data, reads the product barcode, and identifies the corresponding product.

[1415] Step 13:

[1416] The server retrieves the review information from the database.

[1417] Input: Identified product information.

[1418] Output: Review information data.

[1419] Specific operation: The server accesses the database and retrieves review information for the identified product.

[1420] Step 14:

[1421] The server transmits the review information to the terminal.

[1422] Input: Review information data.

[1423] Output: Notification of completion of transmission to the terminal.

[1424] Specific operation: The server's communication module encodes the review information data and transmits it to the terminal.

[1425] Step 15:

[1426] The device displays review information in an AR format overlaid on the user's field of vision.

[1427] Input: Review information data.

[1428] Output: Review information displayed to the user.

[1429] Specific operation: The device's AR display module visualizes review information data and overlays it in the user's field of view in real time.

[1430] Step 16:

[1431] When a user approaches a specific area, a proximity sensor detects their location.

[1432] Input: The user's location.

[1433] Output: Proximity detection data.

[1434] Specific operation: The device's proximity sensor detects the user's position and generates proximity detection data.

[1435] Step 17:

[1436] The server retrieves the promotion information from the database and transmits it to the terminal.

[1437] Input: Proximity detection data.

[1438] Output: Promotion information data.

[1439] Specific operation: The server accesses the database, obtains promotion information for the relevant area, and sends it to the terminal.

[1440] Step 18:

[1441] The device displays promotional information in an AR overlay on the user's field of view.

[1442] Input: Promotion information data.

[1443] Output: Promotion information displayed in the user's field of view.

[1444] Specific operation: The device's AR display module visualizes promotional information data and overlays it in the user's field of view in real time.

[1445] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1446] This invention relates to an AI-equipped wearable eyeglasses that improves the efficiency of users' daily tasks and facilitates information acquisition. This system utilizes the user's voice input, visual information, and image recognition to assist with daily tasks such as DIY and cooking. Furthermore, the invention is equipped with an emotion engine that recognizes the user's emotions and optimizes the work experience based on those emotions.

[1447] System configuration

[1448] 1. Glasses-type wearable device

[1449] The device accepts voice input and captures visual information with a camera, allowing users to operate it hands-free.

[1450] The device has a built-in function that automatically transmits voice data to a server, where the voice data is digitized using an encoder.

[1451] 2. Server

[1452] The server analyzes the voice data using a natural language processing module, converts the voice data into text, and searches for the required information.

[1453] The retrieved information is sent to the device. The server also processes the image data received from the device to identify the user's progress and recognition targets.

[1454] The server is equipped with an emotion engine that can recognize the user's emotional state from their voice and image data.

[1455] 3. Natural Language Processing Module

[1456] This is a module inside the server that converts voice data into text and understands the intent of commands and questions. For example, if a user says, "Tell me the next step," the module extracts the command "next step" and searches for the appropriate information.

[1457] 4. Image Recognition Module

[1458] This is a module inside the server that analyzes real-time image data sent from the device. When the user is working, it recognizes specific objects and progress from the captured images.

[1459] 5. Emotion Engine

[1460] This is a module within the server that analyzes the user's voice and image data to recognize their emotional state, for example, determining whether the user is stressed or relaxed based on their tone of voice and facial expression.

[1461] 6. AR display module

[1462] The device will then overlay the received information onto the user's field of vision, providing visual guidance on the location of parts and how to install screws when assembling furniture, for example.

[1463] System Operation

[1464] 1. Receiving and analyzing voice commands

[1465] The user gives a voice command such as "Tell me the next step." The device receives this voice and sends it to the server as voice data.

[1466] 2. Speech data analysis and information retrieval

[1467] The server analyzes the voice data using a natural language processing module and searches a database for corresponding information, such as cooking instructions or DIY steps.

[1468] 3. Transmission and Display of Information

[1469] The server sends the search results to the device, which then displays the information as an overlay in the user's field of view, and can also provide voice instructions.

[1470] 4. Checking work progress and providing guidance on next steps

[1471] As the user works, a camera captures their progress, and these image data are sent to a server, which uses an image recognition module to analyze their progress.

[1472] The server checks whether the next step has been completed and sends the next step to the terminal, which again overlays the information in the user's field of view and provides voice guidance.

[1473] 5. Recognizing and regulating emotional states

[1474] The server uses the voice and image data to analyze the user's emotional state with an emotion engine. For example, if the user is feeling stressed, the server will recognize this.

[1475] Based on the user's emotional state, the server adjusts the next action: for example, if the user is feeling stressed, it guides them through steps to make the task less difficult.

[1476] Additionally, if the user is determined to be in a negative emotional state, the server will send encouraging messages or simple hints.

[1477] Specific use cases

[1478] When cooking

[1479] 1. The user says, "Tell me what's in the fridge."

[1480] 2. The device sends the voice data to the server, which analyzes it and lists the contents of the refrigerator.

[1481] 3. The list is sent to the device and displayed in the user's field of view.

[1482] 4. When the user asks, "What recipe can I make with these ingredients?" the server searches for the recipe and displays it.

[1483] 5. The recipe steps are displayed in the user's field of vision and are guided by voice.

[1484] 6. The server periodically analyzes the user's emotional state, and if the user is feeling stressed, it adjusts the difficulty of the recipe to be less difficult or starts with easier steps.

[1485] For DIY work

[1486] 1. The user speaks, "Tell me how to assemble furniture."

[1487] 2. The device sends the voice data to the server, which then searches for assembly instructions.

[1488] 3. The procedure is sent to the terminal and displayed in the user's field of view.

[1489] 4. As the user lines up the parts, a camera captures the situation and the server checks the progress.

[1490] 5. The next step is displayed in the user's field of view and is announced audibly.

[1491] 6. The server analyzes the user's emotional state and sends encouraging messages or provides simple explanations if the user is feeling confused or stressed.

[1492] As described above, the present invention provides specific embodiments for streamlining users' daily tasks and significantly improving work efficiency. Furthermore, the present invention can improve the user experience by recognizing the user's emotional state and providing optimal feedback based on that state.

[1493] The processing flow will be explained below.

[1494] Step 1:

[1495] The user gives a voice command such as "Tell me the next step." The device receives this voice command through the microphone and records it as audio data.

[1496] Step 2:

[1497] The device converts the recorded audio data into a digital format using an encoder and transmits it to a server via the Internet.

[1498] Step 3:

[1499] The server passes the received voice data to a natural language processing module, which converts the voice data into text.

[1500] Step 4:

[1501] The server analyzes the text data, understands the "next steps" instructions, and searches the database for the appropriate information.

[1502] Step 5:

[1503] The server converts the search results into data packets and transmits them to the terminal.

[1504] Step 6:

[1505] The device decodes the data packets received from the server and displays them as an AR overlay in the user's field of view, such as instructions on how to assemble furniture or cooking instructions.

[1506] Step 7:

[1507] The user follows the displayed instructions to proceed with the work. The device's camera captures the progress of the work and sends the image data to the server in real time.

[1508] Step 8:

[1509] The server uses an image recognition module to analyze the received image data and check the user's progress, for example, checking the correct placement of parts or the progress of cooking.

[1510] Step 9:

[1511] The server generates instruction data for the next step based on the analysis results and sends it to the terminal.

[1512] Step 10:

[1513] The device receives instruction data from the server and displays the next steps as an overlay in the user's field of vision. At the same time, it can also provide voice guidance for the next steps.

[1514] Step 11:

[1515] The server then passes the voice and image data to the emotion engine in parallel, which analyzes the user's emotional state, determining whether they are stressed or relaxed based on their voice tone and facial expression.

[1516] Step 12:

[1517] The server then uses the emotion engine's analysis to tailor the next steps to the user's emotional state. For example, if the user is feeling stressed, the server will suggest easier steps.

[1518] Step 13:

[1519] If the user is determined to be in a negative emotional state, the server generates and sends to the terminal encouraging messages and additional hints to make the task easier.

[1520] Step 14:

[1521] The device overlays encouraging messages and additional hints onto the user's field of vision and provides audio support.

[1522] Step 15:

[1523] This process is repeated until the user completes the task, at which point the system will provide a visual and audio notification that the task is complete.

[1524] The above is a concrete processing flow of a system incorporating an emotion engine. This flow allows users to work efficiently and also receives support according to their emotional state.

[1525] Example 2

[1526] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1527] Today's users need assistive technologies to help them efficiently complete their daily tasks. However, existing methods rely solely on voice instructions and visual information, lacking the ability to analyze and respond to the user's emotional state and progress in real time. Furthermore, they are unable to adequately address the stress and confusion users feel during the process, limiting their ability to improve work efficiency. Furthermore, the lack of encryption or anonymization of personal information during the transmission and reception of voice and image data raises security and privacy concerns.

[1528] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1529] In this invention, the server includes a means for analyzing voice data and searching for corresponding information, a means for analyzing captured data and identifying progress and recognition targets, and a means for analyzing the user's voice and image data and recognizing their emotional state, which makes it possible to grasp the user's emotional state and work progress in real time and adjust the next action based on that.

[1530] "Voice data" refers to data obtained by converting a user's voice into a digital signal.

[1531] A "server" is a computer system that processes and stores data over a network.

[1532] "Voice input" is the way a device receives spoken words or sounds from a user.

[1533] "Field of view overlay display" is a technology that displays information superimposed on the real image that the user is actually seeing.

[1534] A "camera" is a device for capturing video or images.

[1535] "Capture data" refers to image and video data captured or acquired by devices such as cameras.

[1536] "Progress" is a concept that indicates the progress and degree of achievement of a task or project.

[1537] A "recognition target" is a target or object that the system identifies and recognizes through analysis.

[1538] An "emotional state" is the state of a user's mood or emotions.

[1539] The "emotion engine" is a software module that analyzes the user's voice and image data to recognize their emotional state.

[1540] A "natural language processing module" is a software module that analyzes voice and text data to understand and process human language.

[1541] An "AR display module" is a software module that uses augmented reality technology to overlay information on the real world.

[1542] "Digitalization" is the process of converting analog data into a digital signal.

[1543] MODE FOR CARRYING OUT THE INVENTION

[1544] This invention relates to an AI-equipped wearable eyeglasses device that streamlines users' daily tasks and makes it easier to obtain information. In particular, it uses the user's voice input, visual information, and image recognition to assist with DIY tasks, cooking, and other tasks, and further optimizes the work experience using an emotion engine. This invention includes the following hardware and software components:

[1545] Hardware Configuration

[1546] 1. Glasses-type wearable device

[1547] Microphone: A device that captures audio input.

[1548] Camera: A device that captures visual information and acquires image data.

[1549] Encoder: A device that digitizes and compresses audio data.

[1550] AR display: A device that displays received information as an overlay on the user's field of vision.

[1551] Software Configuration

[1552] 1. Server

[1553] Natural language processing module: Software that converts voice data into text and understands the intent of commands and questions.

[1554] Database: Data storage for storing and retrieving necessary information.

[1555] Image Recognition Module: Software that analyzes captured image data to identify progress and recognized objects.

[1556] Emotion engine: Software that analyzes a user's voice and image data to recognize their emotional state.

[1557] Operating Procedure

[1558] When a user verbally commands, "Tell me what the next step is," the device's microphone captures the voice, and the digitized voice data is compressed by an encoder and sent to the server. The server's natural language processing module analyzes the voice data, converts it into text, and searches a database for appropriate information. This information is sent to the device and overlaid on the user's field of view via the AR display. The camera also captures the user's work progress in real time and sends it to the server, where an image recognition module analyzes the progress and identifies the next step.

[1559] Specific examples

[1560] When cooking

[1561] When the user says, "Tell me what's in the fridge," the device sends a voice message to the server, which then lists the contents of the fridge. The list is then sent to the device and displayed in the field of view. The user can then say, "What recipes can I make with these ingredients?" and the server will search for recipes and overlay the instructions in the field of view. The server analyzes the user's emotional state and adjusts the difficulty of the recipes if the user feels stressed.

[1562] For DIY work

[1563] When a user says, "Tell me how to assemble furniture," the device sends voice data to the server, which searches for assembly instructions. After the instructions are displayed in the field of view, a camera captures the placement of the parts, and the server analyzes the images to check the progress and display the next step. To ensure a comfortable working environment, the server monitors the user's emotional state and provides encouraging messages or simple explanations if the user is experiencing difficulty.

[1564] Prompt Sentence Examples

[1565] "Tell me a recipe I can make using ingredients in the fridge."

[1566] "Guide me through the next steps"

[1567] Please check the current progress

[1568] "Is there an easier way?"

[1569] In this way, the system can streamline users' daily tasks and improve their experience by providing optimal emotion-based feedback.

[1570] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1571] Step 1:

[1572] The user gives a voice command

[1573] Specific actions

[1574] The user gives a voice command, such as "Tell me what to do next." The device's microphone captures this voice.

[1575] Input: User's voice commands

[1576] Output: Audio data

[1577] Step 2:

[1578] Sending audio data

[1579] Specific actions

[1580] The device digitizes the captured audio using an encoder, compresses it, and then sends it to the server.

[1581] Input: Digitized and compressed audio data

[1582] Output: Audio data sent to the server

[1583] Step 3:

[1584] Analysis of audio data

[1585] Specific actions

[1586] The server passes the received voice data to a natural language processing module, which converts it into text, and extracts the intent of commands and questions from the voice data.

[1587] Input: Audio data sent to the server

[1588] Output: Parsed text data

[1589] Step 4:

[1590] Searching for information

[1591] Specific actions

[1592] The server's natural language processing module analyzes the text and then searches the database for the necessary information, such as cooking instructions or DIY steps.

[1593] Input: Parsed text data

[1594] Output: Search result information data

[1595] Step 5:

[1596] Sending information

[1597] Specific actions

[1598] The server transmits the search result information data to the terminal.

[1599] Input: Search result information data

[1600] Output: Information data sent to the terminal

[1601] Step 6:

[1602] Displaying Information

[1603] Specific actions

[1604] The device overlays the received information onto the user's field of view through an AR display module, and may also provide audio instructions using an audio output device.

[1605] Input: Information data sent to the terminal

[1606] Output: Information overlaid on the field of view

[1607] Step 7:

[1608] Work progress capture

[1609] Specific actions

[1610] As the user works, the device's camera captures their progress in real time.

[1611] Input: User's work progress

[1612] Output: Captured image data

[1613] Step 8:

[1614] Sending image data

[1615] Specific actions

[1616] The terminal transmits the captured image data to the server.

[1617] Input: Captured image data

[1618] Output: Image data sent to the server

[1619] Step 9:

[1620] Progress Analysis

[1621] Specific actions

[1622] The server's image recognition module analyzes the received image data and identifies the user's progress and the object to be recognized.

[1623] Input: Image data sent to the server

[1624] Output: Parsed progress information

[1625] Step 10:

[1626] Next step guidance

[1627] Specific actions

[1628] Based on the analyzed progress information, the server sends the next step to the device, which then overlays the received information onto the user's field of view and provides audio guidance.

[1629] Input: Parsed progress information

[1630] Output: Information data for next steps

[1631] Step 11:

[1632] Emotional state analysis

[1633] Specific actions

[1634] The server uses the voice data and image data to analyze the user's emotional state with an emotion engine, for example, by reading emotions from the user's tone of voice and facial expressions.

[1635] Input: Audio data, image data

[1636] Output: Parsed emotional state

[1637] Step 12:

[1638] Adjusting the next action

[1639] Specific actions

[1640] The server adjusts the next action based on the analyzed emotional state, for example, if the user is feeling stressed, it will guide them through steps to reduce the difficulty.

[1641] Input: Parsed emotional state

[1642] Output: A coordinated action plan

[1643] This will help users streamline their daily tasks and improve the user experience by providing optimal feedback based on emotions.

[1644] (Application example 2)

[1645] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1646] Problems faced by workers in modern factories and other workplaces include the complexity of work instructions, the cumbersome nature of progress management, and the impact of workers' emotional states on work efficiency. Conventional systems have difficulty managing this information centrally and providing real-time feedback, leading to reduced work efficiency and increased errors. The present invention aims to provide a new system that solves these problems and maximizes workers' work efficiency.

[1647] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1648] In this invention, the server includes means for receiving a user's voice input and converting it into voice data, means for transmitting the voice data to the server, means for the server to analyze the voice data and search for corresponding information, means for the server to transmit the searched information to the terminal, means for the terminal to overlay the information received on the user's field of view, means for capturing the user's actions with a camera and transmitting the captured data to the server, means for the server to analyze the captured data and identify progress and recognition targets, means for recognizing the user's emotional state using the captured data and voice data analyzed by the server, and means for adjusting the difficulty of work instructions and providing feedback based on the recognized emotional state. This allows the worker to obtain appropriate work information simply by giving voice instructions, and by checking progress and recognizing emotions with the camera, it becomes possible to optimize work efficiency in real time.

[1649] "Voice input" allows the system to recognize voice commands or questions uttered by the user as instructions.

[1650] "Voice data" refers to voice input converted into digital signals that can be used for analysis and retrieval.

[1651] The "server" is a central processing device that analyzes audio data and visual information and transmits the analysis results to the terminal.

[1652] A "terminal" refers to a wearable device that is worn by the user and displays information in the user's field of vision, and is responsible for exchanging audio and visual information.

[1653] "Visual information" refers to image and video data captured through cameras and other sensors.

[1654] A "camera" is a device that captures visual information and obtains images of a user's actions and environment.

[1655] "Capture data" refers to image and video data acquired from a visual sensor such as a camera.

[1656] "Analysis" refers to the process of extracting and processing specific information based on input voice data or captured data.

[1657] "Progress" is information that indicates the progress and degree of achievement of a task.

[1658] A "recognition target" is a specific object or action to be analyzed, and is identified through analysis.

[1659] "Emotional state" refers to the psychological state that can be read from the user's voice and facial expression, and includes stress, relaxation, etc.

[1660] "Feedback" refers to reactions such as encouraging messages or information on corrective work instructions provided to the user based on the analysis results.

[1661] "Difficulty" is an index that indicates the complexity of the task and the skill level required.

[1662] "Overlay display" refers to a method of displaying information superimposed on the user's field of vision, directly and visually conveying work instructions and progress status.

[1663] The system for implementing this invention includes a wearable terminal (smart glasses) worn by a user, a server, and a camera. The specific roles and operations of each element are described below.

[1664] Wearable devices

[1665] A wearable device receives voice input from the user and converts it into voice data. The device has a means of sending the converted voice data to a server. Voice recognition software such as the SpeechRecognition library is used to encode the voice data. The device also has a function for overlaying information received from the server onto the user's field of view. Specifically, it uses augmented reality (AR) technology to display instructions in a way that makes them easy for the user to see. Screen display and voice guidance on the device are handled by the ARDisplay module and speaker.

[1666] server

[1667] The server receives the voice data and analyzes it using a natural language processing module. The analyzed voice data is used to search for corresponding information. For example, a natural language processing library such as Python's Natural Language Toolkit (NLTK) is used. The server also has the function of analyzing the transmitted capture data and identifying the user's progress and recognition target. An image processing library such as OpenCV is used to analyze the capture data.

[1668] Next, the server contains an emotion engine that analyzes the user's voice and captured data to recognize their emotional state. The EmotionRecognition library is used to analyze the emotional state. For example, if the user is feeling stressed, the server determines this based on the analysis results. Based on the results, the server adjusts the difficulty of the work instructions and provides appropriate feedback. The entire process is carried out in real time.

[1669] camera

[1670] The camera is used to capture the user's actions and the surrounding situation. The captured data is sent to the server, where it is used to check the progress and identify the recognition target.

[1671] Specific examples

[1672] Receiving work orders

[1673] When the user speaks, "Tell me what to do next," the device sends the voice data to the server, which analyzes it, finds the appropriate work instructions, and displays them as an overlay in the user's field of view.

[1674] Progress check and feedback

[1675] While the task is in progress, the camera captures the user's movements and progress and sends them to the server. The server analyzes the captured images and checks the progress. If the server determines that the user is feeling stressed, it uses an emotion engine to analyze the user's state and provide appropriate feedback. For example, it displays instructions to reduce the difficulty of the task or an encouraging message.

[1676] Prompt Sentence Examples

[1677] Tell me what to do next

[1678] Check your progress

[1679] Work completed

[1680] Analyze your emotional state

[1681] Display an encouraging message

[1682] As described above, the present invention provides a system that allows the user to flexibly proceed with work based on simple voice instructions and visual information, thereby making it possible to improve work efficiency.

[1683] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1684] Step 1:

[1685] The user enters a voice command

[1686] The user issues a voice command, and the voice data is collected through the terminal's microphone.

[1687] Input: User's voice

[1688] Output: Audio data captured on the device

[1689] Specific operation: When the user says "Tell me what to do next," the device's microphone captures the voice.

[1690] Step 2:

[1691] Voice data is digitized and sent to the server

[1692] The terminal converts the collected voice into digital data and sends it to the server.

[1693] Input: Audio data

[1694] Output: Digital audio data sent to the server

[1695] Specific operation: The device's voice recognition module converts the speech into text, which is then sent to a server over the Internet.

[1696] Step 3:

[1697] Speech data analysis and information retrieval

[1698] The server receives the voice data, analyzes it using a natural language processing module, and retrieves corresponding information.

[1699] Input: Digital audio data

[1700] Output: Retrieved information

[1701] Specific operation: Natural language processing software (e.g., NLTK) on the server analyzes the text of the voice data and searches for the "next task."

[1702] Step 4:

[1703] Submit search results

[1704] The server transmits the retrieved information to the terminal.

[1705] Input: Searched information

[1706] Output: Search results sent to your device

[1707] Specific operation: The server divides the information into packets and sends them to the device's IP address.

[1708] Step 5:

[1709] Overlay display in the user's field of view

[1710] The terminal displays the received information as an overlay in the user's field of view.

[1711] Input: Search results received

[1712] Output: Work instructions displayed in the user's field of view

[1713] Specific operation: The AR display module of the wearable device receives text information and displays it over the user's field of view.

[1714] Step 6:

[1715] Camera capture of user's work progress

[1716] As the user works, the device's camera captures the progress and sends the image data to the server.

[1717] Input: User's work in progress

[1718] Output: Image data sent to the server

[1719] Specific operation: The device's camera takes images in real time and uploads the data to the server.

[1720] Step 7:

[1721] Analyzing image data and identifying progress

[1722] The server analyzes the captured image data and identifies the progress and the object of recognition.

[1723] Input: Captured image data

[1724] Output: Analysis results and progress information

[1725] Specific operation: Image recognition software (e.g., OpenCV) on the server analyzes the image and determines the progress of the work.

[1726] Step 8:

[1727] Recognition of emotional states

[1728] The server analyzes the audio and image data to recognize the user's emotional state.

[1729] Input: Audio and image data

[1730] Output: Perceived emotional state

[1731] Specific operation: The emotion recognition engine analyzes emotional states such as stress or relaxation from voice tone and facial expressions.

[1732] Step 9:

[1733] Providing feedback based on emotional state

[1734] The server adjusts the difficulty of the work instructions based on the perceived emotional state and provides feedback.

[1735] Input: Perceived emotional state and progress information

[1736] Output: Tailored work instructions and encouraging messages

[1737] Specific operation: Based on the emotion recognition results, the server facilitates the next task or sends an encouraging message to the device, which is then overlaid on the device's field of vision.

[1738] The above is the specific flow of processing in this system.

[1739] 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.

[1740] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[1741] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1742] [Fourth embodiment]

[1743] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1744] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1745] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[1746] 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.

[1747] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1748] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1749] 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.

[1750] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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.

[1751] 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.

[1752] 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 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.

[1753] 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.

[1754] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1755] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1756] This invention relates to an AI-equipped wearable glasses-type device that improves the efficiency of users' daily tasks and makes it easier to obtain information. This system utilizes the user's voice input, visual information, and image recognition to assist with daily tasks such as DIY and cooking.

[1757] System configuration

[1758] 1. Glasses-type wearable device

[1759] The device accepts voice input and captures visual information with a camera, allowing users to operate it hands-free.

[1760] The device has a built-in function that automatically transmits voice data to a server, where the voice data is digitized using an encoder.

[1761] 2. Server

[1762] The server analyzes the voice data using a natural language processing module, converts the voice data into text, and searches for the required information.

[1763] The retrieved information is sent to the device. The server also processes the image data received from the device to identify the user's progress and recognition targets.

[1764] 3. Natural Language Processing Module

[1765] This is a module inside the server that converts voice data into text and understands the intent of commands and questions. For example, if a user says, "Tell me the next step," the module extracts the command "next step" and searches for the appropriate information.

[1766] 4. Image Recognition Module

[1767] This is a module inside the server that analyzes real-time image data sent from the device. When the user is working, it recognizes specific objects and progress from the captured images.

[1768] 5. AR display module

[1769] The device will then overlay the received information onto the user's field of vision, providing visual guidance on the location of parts and how to install screws when assembling furniture, for example.

[1770] System Operation

[1771] 1. Receiving and analyzing voice commands

[1772] The user gives a voice command such as "Tell me the next step." The device receives this voice and sends it to the server as voice data.

[1773] 2. Speech data analysis and information retrieval

[1774] The server analyzes the voice data using a natural language processing module and searches a database for corresponding information, such as cooking instructions or DIY steps.

[1775] 3. Transmission and Display of Information

[1776] The server sends the search results to the device, which then displays the information as an overlay in the user's field of view, and can also provide voice instructions.

[1777] 4. Checking work progress and providing guidance on next steps

[1778] As the user works, a camera captures their progress, and these image data are sent to a server, which uses an image recognition module to analyze their progress.

[1779] The server checks whether the next step has been completed and sends the next step to the terminal, which again overlays the information in the user's field of view and provides voice guidance.

[1780] Specific use cases

[1781] When cooking

[1782] 1. The user says, "Tell me what's in the fridge."

[1783] 2. The device sends the voice data to the server, which analyzes it and lists the contents of the refrigerator.

[1784] 3. The list is sent to the device and displayed in the user's field of view.

[1785] 4. When the user asks, "What recipe can I make with these ingredients?" the server searches for the recipe and displays it.

[1786] 5. The recipe steps are displayed in the user's field of vision and are guided by voice.

[1787] For DIY work

[1788] 1. The user speaks, "Tell me how to assemble furniture."

[1789] 2. The device sends the voice data to the server, which then searches for assembly instructions.

[1790] 3. The procedure is sent to the terminal and displayed in the user's field of view.

[1791] 4. As the user lines up the parts, a camera captures the situation and the server checks the progress.

[1792] 5. The next step is displayed in the user's field of view and is announced audibly.

[1793] As described above, the present invention provides specific embodiments for streamlining the user's daily work and significantly improving work efficiency.

[1794] The processing flow will be explained below.

[1795] Step 1:

[1796] The user gives a voice command such as "Tell me the next step." The device receives this voice command through a microphone and records it as voice data.

[1797] Step 2:

[1798] The terminal converts the voice data into a digital format using an encoder and transmits it to a server over the Internet.

[1799] Step 3:

[1800] The server passes the received voice data to a natural language processing module, which converts the voice data into text.

[1801] Step 4:

[1802] The server analyzes the text data and understands the command, "Tell me the next step." Based on this command, it searches the database for the necessary information.

[1803] Step 5:

[1804] The server generates search results and converts information about next steps into data packets and sends them to the terminal.

[1805] Step 6:

[1806] The device decodes the data packets received from the server and overlays them in the user's field of view as an AR display, with specific instructions on the next steps.

[1807] Step 7:

[1808] The user follows the displayed instructions to proceed with the work, and the progress of the work is captured in real time by a camera.

[1809] Step 8:

[1810] The device sends the captured image to the server, which contains the progress of the work.

[1811] Step 9:

[1812] The server uses an image recognition module to analyze the received image data and determine its progress and accuracy.

[1813] Step 10:

[1814] The server sends the analysis results to the terminal, and if the progress is correct, generates data instructing the next step.

[1815] Step 11:

[1816] The device receives instructions from the server and displays them as an overlay in the user's field of view as the next step, while simultaneously providing voice guidance for the next step.

[1817] Step 12:

[1818] This process is repeated until the user completes the task, at which point the system will provide a visual and audio notification that the task is complete.

[1819] The above is a concrete processing flow of the system program, which allows the user to work efficiently.

[1820] Example 1

[1821] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1822] With conventional technology, it was difficult to utilize users' voice input or visual information to assist with tasks. Furthermore, there was a lack of systems that could monitor the user's progress and provide appropriate instructions in real time. This resulted in inefficiencies in processes such as daily tasks, DIY, and cooking, and required users to spend time and effort looking up information.

[1823] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1824] In this invention, the server includes means for analyzing voice data with a natural language processing module and searching for corresponding information, means for analyzing captured data with an image recognition module and identifying progress and recognition targets, and means for transmitting the searched information to the terminal, thereby enabling the server to quickly search for information corresponding to the user's voice instructions and provide visual and audio guidance.

[1825] "Voice input" is a method by which a user communicates information or instructions to a system by speaking.

[1826] "Audio data" is data obtained by converting audio input into digital form.

[1827] A "server" is a central control unit that analyzes data and retrieves information.

[1828] A "natural language processing module" is a software component that converts voice data into text and analyzes the meaning of that text.

[1829] "Search means" is the function by which the server searches for appropriate information from the database.

[1830] A "terminal" is a glasses-type wearable device used by a user, which is a device for inputting voice and capturing visual information.

[1831] "Overlay display" is a method in which a terminal displays information superimposed on the user's field of view.

[1832] "Capture device" is a general term for cameras and sensors used to capture user movements and visual information.

[1833] An "image recognition module" is a software component that analyzes captured data to identify objects and progress.

[1834] "Voice guidance means" is a function that allows the terminal to convey instructions and information to the user by voice.

[1835] "Encryption means" refers to a technology that protects security by encrypting data contents when transmitting and receiving data.

[1836] "Anonymization means" refers to technology that converts a user's personal information into a form that cannot be identified.

[1837] The "advertising data generating means" is a function that creates data for displaying advertisements in order to increase profits.

[1838] This invention relates to an AI-equipped wearable glasses-type device that improves the efficiency of users' daily tasks and makes it easier to obtain information. This system utilizes the user's voice input, visual information, and image recognition to assist with daily tasks such as DIY and cooking.

[1839] The system includes the following components:

[1840] 1. Glasses-type wearable device

[1841] The device receives voice input and captures visual information with a camera, allowing the user to operate it hands-free. The device is equipped with a built-in function that automatically transmits voice data to a server, where it is digitized using an encoder. The device also includes an AR display module that overlays the received information onto the user's field of view. It also has a voice guidance function that provides necessary information to the user via voice.

[1842] 2. Server

[1843] The server receives the voice data and analyzes it using a natural language processing module. The analyzed voice data is converted into text and the required information is searched for in a database. The server also incorporates an image recognition module that understands the user's current task status and determines the next step. The server uses encryption methods to send and receive data to ensure security. Furthermore, the server also includes functions to anonymize users' personal information and generate advertising data as a means of increasing revenue.

[1844] Specific use cases

[1845] When cooking

[1846] 1. The user says, "Tell me what's in the fridge."

[1847] 2. The device sends the voice data to the server, which analyzes it and lists the contents of the refrigerator.

[1848] 3. The list is sent to the device and displayed in the user's field of view.

[1849] 4. When the user asks, "What recipe can I make with these ingredients?" the server searches for and displays the recipe.

[1850] 5. The recipe steps are displayed in the user's field of vision and are guided by voice.

[1851] For DIY work

[1852] 1. The user speaks, "Tell me how to assemble furniture."

[1853] 2. The device sends the voice data to the server, which then searches for assembly instructions.

[1854] 3. The procedure is sent to the terminal and displayed in the user's field of view.

[1855] 4. As the user lines up the parts, a camera captures the situation and the server checks the progress.

[1856] 5. The next step is displayed in the user's field of view and is announced audibly.

[1857] Prompt Sentence Examples

[1858] "Tell me the next step"

[1859] "Tell me what's in the fridge."

[1860] "Teach me how to assemble furniture"

[1861] In this way, the present invention can improve the efficiency of users' daily tasks, and specific embodiments can significantly improve the user experience. By implementing the present invention, users can receive immediate guidance using voice input and visual information, allowing them to perform daily tasks quickly and accurately.

[1862] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1863] Step 1: Receive voice instructions

[1864] The user gives a voice command such as "Tell me the next step." The device's microphone receives the voice input, and the voice data is digitized by an encoder. The digitized voice data is sent from the device to the server. The input is the voice command, and the output is the digitized voice data.

[1865] Step 2: Analyzing the audio data

[1866] The server receives the voice data, and the natural language processing module converts the data into text. The natural language processing module analyzes the commands from the text and extracts specific actions. The input is digitized voice data, and the output is the analyzed text and its commands.

[1867] Step 3: Finding information

[1868] The server queries a database based on the parsed text to find corresponding information, such as DIY instructions or cooking recipes. The input is the parsed text and extracted instructions, and the output is the retrieved related information.

[1869] Step 4: Submit your information

[1870] The server sends the search results back to the terminal. At this time, the security of the data is ensured using encryption. The input is the search result information, and the output is the information sent to the terminal in encrypted form.

[1871] Step 5: Information and navigation

[1872] The device decodes the received information and displays it as an overlay in the user's field of view using the AR display module. At the same time, the device uses a voice guidance means to communicate information and procedures to the user aloud. The input is encrypted information, and the output is the information overlaid in the field of view and voice guidance.

[1873] Step 6: Check the progress of your work

[1874] As the user works, the device's camera captures the progress in real time. The captured image data is sent from the device to the server. The input is the progress of the work, and the output is the captured image data.

[1875] Step 7: Progress analysis

[1876] The image recognition module analyzes the image data received by the server to identify the progress and the object to be recognized. For example, to confirm the position of parts in furniture assembly. The input is the captured image data, and the output is the analyzed progress and the recognized object information.

[1877] Step 8: Next steps

[1878] Based on the analysis results, the server sends the next step and necessary information back to the device. The next step received by the device is again overlaid in the user's field of view and guided by voice. The input is the analyzed progress and next step information, and the output is the next step displayed in the field of view and its voice guidance.

[1879] (Application example 1)

[1880] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1881] In today's brick-and-mortar stores, customers often find it difficult to find products and find detailed product information, reviews, and promotional information instantly. They also have limited means for effectively managing their shopping lists. This reduces shopping efficiency and impairs the customer experience. Furthermore, insufficient privacy practices raise concerns about the protection of personal information.

[1882] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1883] In this invention, the server includes a means for allowing a user to search for products in a store and visually providing location information for specific products, a means for displaying detailed product information and reviews based on a customer's voice command, and a means for acquiring location information from a proximity sensor in the store and automatically displaying promotional information. This allows customers to quickly find the products they need and obtain detailed information, improving shopping efficiency and satisfaction. Furthermore, the quality of the customer experience is improved by providing appropriate advertising information while protecting privacy.

[1884] "Voice input" is an input method in which a user verbally provides instructions or information through a microphone, which is then recognized and analyzed by the system.

[1885] "Voice data" refers to data that has been converted into digital form from a user's voice input.

[1886] A "server" is a central processing unit for analyzing voice data, searching for information, and processing data.

[1887] "Overlay display" is a display method in which a terminal presents information superimposed on the user's field of vision.

[1888] A "camera" is a device that captures the user's actions and environment in real time and converts them into video data.

[1889] "Capture data" refers to image and video data captured by a camera.

[1890] "Location information" is data relating to the location of a particular product.

[1891] "Detailed information" refers to information such as product specifications, descriptions, reviews, etc.

[1892] A "review" is information that describes a user's impressions and evaluations.

[1893] "Promotional Information" refers to information about discounts and special offers offered as part of sales promotion activities.

[1894] A "proximity sensor" is a device that detects the location of a user when they approach a specific product or area.

[1895] "Anonymization" is a method of processing personal information so that it cannot identify a specific individual.

[1896] "Advertising data" refers to promotional information generated for the purpose of increasing revenue.

[1897] This invention relates to a system that uses AI-equipped glasses-type wearable devices to improve customers' shopping experiences in brick-and-mortar stores. Specifically, it provides a means for customers to search for products through voice input and visually display detailed information, reviews, and promotional information about those products. The configuration and operation of the system are described in detail below.

[1898] System configuration

[1899] Glasses-type wearable device

[1900] The device receives voice input and captures visual information with a camera. The voice data is digitized and sent to a server. The device also has an AR display function, which overlays information on the user's field of view.

[1901] server

[1902] The server includes a number of analysis modules.

[1903] Natural language processing module: Uses the Google Cloud Natural Language API to convert voice data into text and understand the intent of commands and questions.

[1904] Image recognition module: Uses OpenCV to analyze image data sent from the device and identify progress and recognition targets.

[1905] Database module: Access a database that provides real-time product location information, details, reviews, promotion information, etc.

[1906] Specific examples

[1907] The following is a usage scenario within a physical store:

[1908] 1. Product search and guidance:

[1909] The user speaks, "Where is the item XX?"

[1910] The voice data is sent to the server, and the natural language processing module extracts "XX product" as a search keyword.

[1911] The server retrieves the location information of the relevant product from the database and sends it to the terminal.

[1912] The device overlays real-time navigation information onto the user's field of view.

[1913] 2. Product details display:

[1914] The user picks up a product and says, "Show me reviews for this product."

[1915] The voice data is sent to the server, and a natural language processing module parses the command "Show me reviews."

[1916] The device's camera captures the product barcode and sends the image data to the server.

[1917] The image recognition module analyzes the barcode and identifies the corresponding product.

[1918] Review information is retrieved from the database and overlaid on the device's field of view using the device's AR display function.

[1919] 3. Display of Promotional Information:

[1920] When a user approaches a specific area, a proximity sensor detects their location.

[1921] The server retrieves promotional information about products in the relevant area from the database and transmits it to the terminal.

[1922] Promotional information is overlaid on the user's field of view.

[1923] Example prompt

[1924] Here are some examples of prompts to input to the generative AI model:

[1925] "Generate an application design that allows a user to search for a specific product in a store by voice, navigate to that product's location in an AR display, and visually present detailed information and reviews in AR."

[1926] This invention allows customers to quickly find the products they need and obtain detailed information, improving shopping efficiency and satisfaction. It also improves the quality of the customer experience by providing appropriate advertising information while protecting privacy. This invention significantly improves the shopping experience in physical stores.

[1927] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1928] Step 1:

[1929] The user speaks, "Where is the item XX?"

[1930] Input: User's voice command.

[1931] Output: Audio data.

[1932] Specific operation: The device's microphone captures the user's voice instructions and digitizes them as voice data.

[1933] Step 2:

[1934] The terminal transmits the voice data to the server.

[1935] Input: Digitized audio data.

[1936] Output: Notification of completion of transmission to the server.

[1937] Specific operation: The terminal's communication module encodes the voice data and sends it to the server.

[1938] Step 3:

[1939] The server analyzes the voice data, converts it into text using a natural language processing module, and extracts the intent.

[1940] Input: Audio data sent from the device.

[1941] Output: Data converted to text, intent extracted.

[1942] Specific operation: The Google Cloud Natural Language API on the server converts the voice data into text and extracts keywords (e.g., "product of XX").

[1943] Step 4:

[1944] The server retrieves the location information of the relevant product from the database.

[1945] Input: Extracted keywords (product names).

[1946] Output: Product location data.

[1947] Specific operation: The server accesses the database and obtains the location information of the corresponding product based on the product name.

[1948] Step 5:

[1949] The server sends the location data to the device.

[1950] Input: Location data.

[1951] Output: Notification of completion of transmission to the terminal.

[1952] Specific operation: The server's communication module encodes the location data and sends it to the device.

[1953] Step 6:

[1954] The device displays location information in an AR overlay on the user's field of view.

[1955] Input: Location data.

[1956] Output: Navigation information displayed in the user's field of view.

[1957] Specific operation: The device's AR display module visualizes location data and overlays it on the user's field of view in real time.

[1958] Step 7:

[1959] The user picks up a product and says, "Show me reviews for this product."

[1960] Input: User's voice command.

[1961] Output: Audio data.

[1962] Specific operation: The device's microphone captures the user's voice instructions and digitizes them as voice data.

[1963] Step 8:

[1964] The terminal transmits the voice data to the server.

[1965] Input: Digitized audio data.

[1966] Output: Notification of completion of transmission to the server.

[1967] Specific operation: The terminal's communication module encodes the voice data and sends it to the server.

[1968] Step 9:

[1969] The server analyzes the voice data, converts it into text using a natural language processing module, and extracts the intent.

[1970] Input: Audio data sent from the device.

[1971] Output: Data converted to text, intent extracted.

[1972] Specific operation: The Google Cloud Natural Language API on the server converts the voice data into text and extracts commands (e.g., "Show me reviews").

[1973] Step 10:

[1974] The user captures the product with a camera.

[1975] Input: Product image data.

[1976] Output: Capture data.

[1977] Specific operation: The device's camera captures the product barcode or image and digitizes it as image data.

[1978] Step 11:

[1979] The device sends the captured data to the server.

[1980] Input: Product image data.

[1981] Output: Notification of completion of transmission to the server.

[1982] Specific operation: The communication module of the terminal encodes the image data and sends it to the server.

[1983] Step 12:

[1984] The server analyzes the product barcode using an image recognition module and identifies the corresponding product from the database.

[1985] Input: Capture data.

[1986] Output: Identified product information.

[1987] Specific operation: OpenCV on the server analyzes the image data, reads the product barcode, and identifies the corresponding product.

[1988] Step 13:

[1989] The server retrieves the review information from the database.

[1990] Input: Identified product information.

[1991] Output: Review information data.

[1992] Specific operation: The server accesses the database and retrieves review information for the identified product.

[1993] Step 14:

[1994] The server transmits the review information to the terminal.

[1995] Input: Review information data.

[1996] Output: Notification of completion of transmission to the terminal.

[1997] Specific operation: The server's communication module encodes the review information data and transmits it to the terminal.

[1998] Step 15:

[1999] The device displays review information in an AR format overlaid on the user's field of vision.

[2000] Input: Review information data.

[2001] Output: Review information displayed to the user.

[2002] Specific operation: The device's AR display module visualizes review information data and overlays it in the user's field of view in real time.

[2003] Step 16:

[2004] When a user approaches a specific area, a proximity sensor detects their location.

[2005] Input: The user's location.

[2006] Output: Proximity detection data.

[2007] Specific operation: The device's proximity sensor detects the user's position and generates proximity detection data.

[2008] Step 17:

[2009] The server retrieves the promotion information from the database and transmits it to the terminal.

[2010] Input: Proximity detection data.

[2011] Output: Promotion information data.

[2012] Specific operation: The server accesses the database, obtains promotion information for the relevant area, and sends it to the terminal.

[2013] Step 18:

[2014] The device displays promotional information in an AR overlay on the user's field of view.

[2015] Input: Promotion information data.

[2016] Output: Promotion information displayed in the user's field of view.

[2017] Specific operation: The device's AR display module visualizes promotional information data and overlays it in the user's field of view in real time.

[2018] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2019] This invention relates to an AI-equipped wearable eyeglasses that improves the efficiency of users' daily tasks and facilitates information acquisition. This system utilizes the user's voice input, visual information, and image recognition to assist with daily tasks such as DIY and cooking. Furthermore, the invention is equipped with an emotion engine that recognizes the user's emotions and optimizes the work experience based on those emotions.

[2020] System configuration

[2021] 1. Glasses-type wearable device

[2022] The device accepts voice input and captures visual information with a camera, allowing users to operate it hands-free.

[2023] The device has a built-in function that automatically transmits voice data to a server, where the voice data is digitized using an encoder.

[2024] 2. Server

[2025] The server analyzes the voice data using a natural language processing module, converts the voice data into text, and searches for the required information.

[2026] The retrieved information is sent to the device. The server also processes the image data received from the device to identify the user's progress and recognition targets.

[2027] The server is equipped with an emotion engine that can recognize the user's emotional state from their voice and image data.

[2028] 3. Natural Language Processing Module

[2029] This is a module inside the server that converts voice data into text and understands the intent of commands and questions. For example, if a user says, "Tell me the next step," the module extracts the command "next step" and searches for the appropriate information.

[2030] 4. Image Recognition Module

[2031] This is a module inside the server that analyzes real-time image data sent from the device. When the user is working, it recognizes specific objects and progress from the captured images.

[2032] 5. Emotion Engine

[2033] This is a module within the server that analyzes the user's voice and image data to recognize their emotional state, for example, determining whether the user is stressed or relaxed based on their tone of voice and facial expression.

[2034] 6. AR display module

[2035] The device will then overlay the received information onto the user's field of vision, providing visual guidance on the location of parts and how to install screws when assembling furniture, for example.

[2036] System Operation

[2037] 1. Receiving and analyzing voice commands

[2038] The user gives a voice command such as "Tell me the next step." The device receives this voice and sends it to the server as voice data.

[2039] 2. Speech data analysis and information retrieval

[2040] The server analyzes the voice data using a natural language processing module and searches a database for corresponding information, such as cooking instructions or DIY steps.

[2041] 3. Transmission and Display of Information

[2042] The server sends the search results to the device, which then displays the information as an overlay in the user's field of view, and can also provide voice instructions.

[2043] 4. Checking work progress and providing guidance on next steps

[2044] As the user works, a camera captures their progress, and these image data are sent to a server, which uses an image recognition module to analyze their progress.

[2045] The server checks whether the next step has been completed and sends the next step to the terminal, which again overlays the information in the user's field of view and provides voice guidance.

[2046] 5. Recognizing and regulating emotional states

[2047] The server uses the voice and image data to analyze the user's emotional state with an emotion engine. For example, if the user is feeling stressed, the server will recognize this.

[2048] Based on the user's emotional state, the server adjusts the next action: for example, if the user is feeling stressed, it guides them through steps to make the task less difficult.

[2049] Additionally, if the user is determined to be in a negative emotional state, the server will send encouraging messages or simple hints.

[2050] Specific use cases

[2051] When cooking

[2052] 1. The user says, "Tell me what's in the fridge."

[2053] 2. The device sends the voice data to the server, which analyzes it and lists the contents of the refrigerator.

[2054] 3. The list is sent to the device and displayed in the user's field of view.

[2055] 4. When the user asks, "What recipe can I make with these ingredients?" the server searches for the recipe and displays it.

[2056] 5. The recipe steps are displayed in the user's field of vision and are guided by voice.

[2057] 6. The server periodically analyzes the user's emotional state, and if the user is feeling stressed, it adjusts the difficulty of the recipe to be less difficult or starts with easier steps.

[2058] For DIY work

[2059] 1. The user speaks, "Tell me how to assemble furniture."

[2060] 2. The device sends the voice data to the server, which then searches for assembly instructions.

[2061] 3. The procedure is sent to the terminal and displayed in the user's field of view.

[2062] 4. As the user lines up the parts, a camera captures the situation and the server checks the progress.

[2063] 5. The next step is displayed in the user's field of view and is announced audibly.

[2064] 6. The server analyzes the user's emotional state and sends encouraging messages or provides simple explanations if the user is feeling confused or stressed.

[2065] As described above, the present invention provides specific embodiments for streamlining users' daily tasks and significantly improving work efficiency. Furthermore, the present invention can improve the user experience by recognizing the user's emotional state and providing optimal feedback based on that state.

[2066] The processing flow will be explained below.

[2067] Step 1:

[2068] The user gives a voice command such as "Tell me the next step." The device receives this voice command through the microphone and records it as audio data.

[2069] Step 2:

[2070] The device converts the recorded audio data into a digital format using an encoder and transmits it to a server via the Internet.

[2071] Step 3:

[2072] The server passes the received voice data to a natural language processing module, which converts the voice data into text.

[2073] Step 4:

[2074] The server analyzes the text data, understands the "next steps" instructions, and searches the database for the appropriate information.

[2075] Step 5:

[2076] The server converts the search results into data packets and transmits them to the terminal.

[2077] Step 6:

[2078] The device decodes the data packets received from the server and displays them as an AR overlay in the user's field of view, such as instructions on how to assemble furniture or cooking instructions.

[2079] Step 7:

[2080] The user follows the displayed instructions to proceed with the work. The device's camera captures the progress of the work and sends the image data to the server in real time.

[2081] Step 8:

[2082] The server uses an image recognition module to analyze the received image data and check the user's progress, for example, checking the correct placement of parts or the progress of cooking.

[2083] Step 9:

[2084] The server generates instruction data for the next step based on the analysis results and sends it to the terminal.

[2085] Step 10:

[2086] The device receives instruction data from the server and displays the next steps as an overlay in the user's field of vision. At the same time, it can also provide voice guidance for the next steps.

[2087] Step 11:

[2088] The server then passes the voice and image data to the emotion engine in parallel, which analyzes the user's emotional state, determining whether they are stressed or relaxed based on their voice tone and facial expression.

[2089] Step 12:

[2090] The server then uses the emotion engine's analysis to tailor the next steps to the user's emotional state. For example, if the user is feeling stressed, the server will suggest easier steps.

[2091] Step 13:

[2092] If the user is determined to be in a negative emotional state, the server generates and sends to the terminal encouraging messages and additional hints to make the task easier.

[2093] Step 14:

[2094] The device overlays encouraging messages and additional hints onto the user's field of vision and provides audio support.

[2095] Step 15:

[2096] This process is repeated until the user completes the task, at which point the system will provide a visual and audio notification that the task is complete.

[2097] The above is a concrete processing flow of a system incorporating an emotion engine. This flow allows users to work efficiently and also receives support according to their emotional state.

[2098] Example 2

[2099] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2100] Today's users need assistive technologies to help them efficiently complete their daily tasks. However, existing methods rely solely on voice instructions and visual information, lacking the ability to analyze and respond to the user's emotional state and progress in real time. Furthermore, they are unable to adequately address the stress and confusion users feel during the process, limiting their ability to improve work efficiency. Furthermore, the lack of encryption or anonymization of personal information during the transmission and reception of voice and image data raises security and privacy concerns.

[2101] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2102] In this invention, the server includes a means for analyzing voice data and searching for corresponding information, a means for analyzing captured data and identifying progress and recognition targets, and a means for analyzing the user's voice and image data and recognizing their emotional state, which makes it possible to grasp the user's emotional state and work progress in real time and adjust the next action based on that.

[2103] "Voice data" refers to data obtained by converting a user's voice into a digital signal.

[2104] A "server" is a computer system that processes and stores data over a network.

[2105] "Voice input" is the way a device receives spoken words or sounds from a user.

[2106] "Field of view overlay display" is a technology that displays information superimposed on the real image that the user is actually seeing.

[2107] A "camera" is a device for capturing video or images.

[2108] "Capture data" refers to image and video data captured or acquired by devices such as cameras.

[2109] "Progress" is a concept that indicates the progress and degree of achievement of a task or project.

[2110] A "recognition target" is a target or object that the system identifies and recognizes through analysis.

[2111] An "emotional state" is the state of a user's mood or emotions.

[2112] The "emotion engine" is a software module that analyzes the user's voice and image data to recognize their emotional state.

[2113] A "natural language processing module" is a software module that analyzes voice and text data to understand and process human language.

[2114] An "AR display module" is a software module that uses augmented reality technology to overlay information on the real world.

[2115] "Digitalization" is the process of converting analog data into a digital signal.

[2116] MODE FOR CARRYING OUT THE INVENTION

[2117] This invention relates to an AI-equipped wearable eyeglasses device that streamlines users' daily tasks and makes it easier to obtain information. In particular, it uses the user's voice input, visual information, and image recognition to assist with DIY tasks, cooking, and other tasks, and further optimizes the work experience using an emotion engine. This invention includes the following hardware and software components:

[2118] Hardware Configuration

[2119] 1. Glasses-type wearable device

[2120] Microphone: A device that captures audio input.

[2121] Camera: A device that captures visual information and acquires image data.

[2122] Encoder: A device that digitizes and compresses audio data.

[2123] AR display: A device that displays received information as an overlay on the user's field of vision.

[2124] Software Configuration

[2125] 1. Server

[2126] Natural language processing module: Software that converts voice data into text and understands the intent of commands and questions.

[2127] Database: Data storage for storing and retrieving necessary information.

[2128] Image Recognition Module: Software that analyzes captured image data to identify progress and recognized objects.

[2129] Emotion engine: Software that analyzes a user's voice and image data to recognize their emotional state.

[2130] Operating Procedure

[2131] When a user verbally commands, "Tell me what the next step is," the device's microphone captures the voice, and the digitized voice data is compressed by an encoder and sent to the server. The server's natural language processing module analyzes the voice data, converts it into text, and searches a database for appropriate information. This information is sent to the device and overlaid on the user's field of view via the AR display. The camera also captures the user's work progress in real time and sends it to the server, where an image recognition module analyzes the progress and identifies the next step.

[2132] Specific examples

[2133] When cooking

[2134] When the user says, "Tell me what's in the fridge," the device sends a voice message to the server, which then lists the contents of the fridge. The list is then sent to the device and displayed in the field of view. The user can then say, "What recipes can I make with these ingredients?" and the server will search for recipes and overlay the instructions in the field of view. The server analyzes the user's emotional state and adjusts the difficulty of the recipes if the user feels stressed.

[2135] For DIY work

[2136] When a user says, "Tell me how to assemble furniture," the device sends voice data to the server, which searches for assembly instructions. After the instructions are displayed in the field of view, a camera captures the placement of the parts, and the server analyzes the images to check the progress and display the next step. To ensure a comfortable working environment, the server monitors the user's emotional state and provides encouraging messages or simple explanations if the user is experiencing difficulty.

[2137] Prompt Sentence Examples

[2138] "Tell me a recipe I can make using ingredients in the fridge."

[2139] "Guide me through the next steps"

[2140] Please check the current progress

[2141] "Is there an easier way?"

[2142] In this way, the system can streamline users' daily tasks and improve their experience by providing optimal emotion-based feedback.

[2143] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2144] Step 1:

[2145] The user gives a voice command

[2146] Specific actions

[2147] The user gives a voice command, such as "Tell me what to do next." The device's microphone captures this voice.

[2148] Input: User's voice commands

[2149] Output: Audio data

[2150] Step 2:

[2151] Sending audio data

[2152] Specific actions

[2153] The device digitizes the captured audio using an encoder, compresses it, and then sends it to the server.

[2154] Input: Digitized and compressed audio data

[2155] Output: Audio data sent to the server

[2156] Step 3:

[2157] Analysis of audio data

[2158] Specific actions

[2159] The server passes the received voice data to a natural language processing module, which converts it into text, and extracts the intent of commands and questions from the voice data.

[2160] Input: Audio data sent to the server

[2161] Output: Parsed text data

[2162] Step 4:

[2163] Searching for information

[2164] Specific actions

[2165] The server's natural language processing module analyzes the text and then searches the database for the necessary information, such as cooking instructions or DIY steps.

[2166] Input: Parsed text data

[2167] Output: Search result information data

[2168] Step 5:

[2169] Sending information

[2170] Specific actions

[2171] The server transmits the search result information data to the terminal.

[2172] Input: Search result information data

[2173] Output: Information data sent to the terminal

[2174] Step 6:

[2175] Displaying Information

[2176] Specific actions

[2177] The device overlays the received information onto the user's field of view through an AR display module, and may also provide audio instructions using an audio output device.

[2178] Input: Information data sent to the terminal

[2179] Output: Information overlaid on the field of view

[2180] Step 7:

[2181] Work progress capture

[2182] Specific actions

[2183] As the user works, the device's camera captures their progress in real time.

[2184] Input: User's work progress

[2185] Output: Captured image data

[2186] Step 8:

[2187] Sending image data

[2188] Specific actions

[2189] The terminal transmits the captured image data to the server.

[2190] Input: Captured image data

[2191] Output: Image data sent to the server

[2192] Step 9:

[2193] Progress Analysis

[2194] Specific actions

[2195] The server's image recognition module analyzes the received image data and identifies the user's progress and the object to be recognized.

[2196] Input: Image data sent to the server

[2197] Output: Parsed progress information

[2198] Step 10:

[2199] Next step guidance

[2200] Specific actions

[2201] Based on the analyzed progress information, the server sends the next step to the device, which then overlays the received information onto the user's field of view and provides audio guidance.

[2202] Input: Parsed progress information

[2203] Output: Information data for next steps

[2204] Step 11:

[2205] Emotional state analysis

[2206] Specific actions

[2207] The server uses the voice data and image data to analyze the user's emotional state with an emotion engine, for example, by reading emotions from the user's tone of voice and facial expressions.

[2208] Input: Audio data, image data

[2209] Output: Parsed emotional state

[2210] Step 12:

[2211] Adjusting the next action

[2212] Specific actions

[2213] The server adjusts the next action based on the analyzed emotional state, for example, if the user is feeling stressed, it will guide them through steps to reduce the difficulty.

[2214] Input: Parsed emotional state

[2215] Output: A coordinated action plan

[2216] This will help users streamline their daily tasks and improve the user experience by providing optimal feedback based on emotions.

[2217] (Application example 2)

[2218] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2219] Problems faced by workers in modern factories and other workplaces include the complexity of work instructions, the cumbersome nature of progress management, and the impact of workers' emotional states on work efficiency. Conventional systems have difficulty managing this information centrally and providing real-time feedback, leading to reduced work efficiency and increased errors. The present invention aims to provide a new system that solves these problems and maximizes workers' work efficiency.

[2220] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2221] In this invention, the server includes means for receiving a user's voice input and converting it into voice data, means for transmitting the voice data to the server, means for the server to analyze the voice data and search for corresponding information, means for the server to transmit the searched information to the terminal, means for the terminal to overlay the information received on the user's field of view, means for capturing the user's actions with a camera and transmitting the captured data to the server, means for the server to analyze the captured data and identify progress and recognition targets, means for recognizing the user's emotional state using the captured data and voice data analyzed by the server, and means for adjusting the difficulty of work instructions and providing feedback based on the recognized emotional state. This allows the worker to obtain appropriate work information simply by giving voice instructions, and by checking progress and recognizing emotions with the camera, it becomes possible to optimize work efficiency in real time.

[2222] "Voice input" allows the system to recognize voice commands or questions uttered by the user as instructions.

[2223] "Voice data" refers to voice input converted into digital signals that can be used for analysis and retrieval.

[2224] The "server" is a central processing device that analyzes audio data and visual information and transmits the analysis results to the terminal.

[2225] A "terminal" refers to a wearable device that is worn by the user and displays information in the user's field of vision, and is responsible for exchanging audio and visual information.

[2226] "Visual information" refers to image and video data captured through cameras and other sensors.

[2227] A "camera" is a device that captures visual information and obtains images of a user's actions and environment.

[2228] "Capture data" refers to image and video data acquired from a visual sensor such as a camera.

[2229] "Analysis" refers to the process of extracting and processing specific information based on input voice data or captured data.

[2230] "Progress" is information that indicates the progress and degree of achievement of a task.

[2231] A "recognition target" is a specific object or action to be analyzed, and is identified through analysis.

[2232] "Emotional state" refers to the psychological state that can be read from the user's voice and facial expression, and includes stress, relaxation, etc.

[2233] "Feedback" refers to reactions such as encouraging messages or information on corrective work instructions provided to the user based on the analysis results.

[2234] "Difficulty" is an index that indicates the complexity of the task and the skill level required.

[2235] "Overlay display" refers to a method of displaying information superimposed on the user's field of vision, directly and visually conveying work instructions and progress status.

[2236] The system for implementing this invention includes a wearable terminal (smart glasses) worn by a user, a server, and a camera. The specific roles and operations of each element are described below.

[2237] Wearable devices

[2238] A wearable device receives voice input from the user and converts it into voice data. The device has a means of sending the converted voice data to a server. Voice recognition software such as the SpeechRecognition library is used to encode the voice data. The device also has a function for overlaying information received from the server onto the user's field of view. Specifically, it uses augmented reality (AR) technology to display instructions in a way that makes them easy for the user to see. Screen display and voice guidance on the device are handled by the ARDisplay module and speaker.

[2239] server

[2240] The server receives the voice data and analyzes it using a natural language processing module. The analyzed voice data is used to search for corresponding information. For example, a natural language processing library such as Python's Natural Language Toolkit (NLTK) is used. The server also has the function of analyzing the transmitted capture data and identifying the user's progress and recognition target. An image processing library such as OpenCV is used to analyze the capture data.

[2241] Next, the server contains an emotion engine that analyzes the user's voice and captured data to recognize their emotional state. The EmotionRecognition library is used to analyze the emotional state. For example, if the user is feeling stressed, the server determines this based on the analysis results. Based on the results, the server adjusts the difficulty of the work instructions and provides appropriate feedback. The entire process is carried out in real time.

[2242] camera

[2243] The camera is used to capture the user's actions and the surrounding situation. The captured data is sent to the server, where it is used to check the progress and identify the recognition target.

[2244] Specific examples

[2245] Receiving work orders

[2246] When the user speaks, "Tell me what to do next," the device sends the voice data to the server, which analyzes it, finds the appropriate work instructions, and displays them as an overlay in the user's field of view.

[2247] Progress check and feedback

[2248] While the task is in progress, the camera captures the user's movements and progress and sends them to the server. The server analyzes the captured images and checks the progress. If the server determines that the user is feeling stressed, it uses an emotion engine to analyze the user's state and provide appropriate feedback. For example, it displays instructions to reduce the difficulty of the task or an encouraging message.

[2249] Prompt Sentence Examples

[2250] Tell me what to do next

[2251] Check your progress

[2252] Work completed

[2253] Analyze your emotional state

[2254] Display an encouraging message

[2255] As described above, the present invention provides a system that allows the user to flexibly proceed with work based on simple voice instructions and visual information, thereby making it possible to improve work efficiency.

[2256] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2257] Step 1:

[2258] The user enters a voice command

[2259] The user issues a voice command, and the voice data is collected through the terminal's microphone.

[2260] Input: User's voice

[2261] Output: Audio data captured on the device

[2262] Specific operation: When the user says "Tell me what to do next," the device's microphone captures the voice.

[2263] Step 2:

[2264] Voice data is digitized and sent to the server

[2265] The terminal converts the collected voice into digital data and sends it to the server.

[2266] Input: Audio data

[2267] Output: Digital audio data sent to the server

[2268] Specific operation: The device's voice recognition module converts the speech into text, which is then sent to a server over the Internet.

[2269] Step 3:

[2270] Speech data analysis and information retrieval

[2271] The server receives the voice data, analyzes it using a natural language processing module, and retrieves corresponding information.

[2272] Input: Digital audio data

[2273] Output: Retrieved information

[2274] Specific operation: Natural language processing software (e.g., NLTK) on the server analyzes the text of the voice data and searches for the "next task."

[2275] Step 4:

[2276] Submit search results

[2277] The server transmits the retrieved information to the terminal.

[2278] Input: Searched information

[2279] Output: Search results sent to your device

[2280] Specific operation: The server divides the information into packets and sends them to the device's IP address.

[2281] Step 5:

[2282] Overlay display in the user's field of view

[2283] The terminal displays the received information as an overlay in the user's field of view.

[2284] Input: Search results received

[2285] Output: Work instructions displayed in the user's field of view

[2286] Specific operation: The AR display module of the wearable device receives text information and displays it over the user's field of view.

[2287] Step 6:

[2288] Camera capture of user's work progress

[2289] As the user works, the device's camera captures the progress and sends the image data to the server.

[2290] Input: User's work in progress

[2291] Output: Image data sent to the server

[2292] Specific operation: The device's camera takes images in real time and uploads the data to the server.

[2293] Step 7:

[2294] Analyzing image data and identifying progress

[2295] The server analyzes the captured image data and identifies the progress and the object of recognition.

[2296] Input: Captured image data

[2297] Output: Analysis results and progress information

[2298] Specific operation: Image recognition software (e.g., OpenCV) on the server analyzes the image and determines the progress of the work.

[2299] Step 8:

[2300] Recognition of emotional states

[2301] The server analyzes the audio and image data to recognize the user's emotional state.

[2302] Input: Audio and image data

[2303] Output: Perceived emotional state

[2304] Specific operation: The emotion recognition engine analyzes emotional states such as stress or relaxation from voice tone and facial expressions.

[2305] Step 9:

[2306] Providing feedback based on emotional state

[2307] The server adjusts the difficulty of the work instructions based on the perceived emotional state and provides feedback.

[2308] Input: Perceived emotional state and progress information

[2309] Output: Tailored work instructions and encouraging messages

[2310] Specific operation: Based on the emotion recognition results, the server facilitates the next task or sends an encouraging message to the device, which is then overlaid on the device's field of vision.

[2311] The above is the specific flow of processing in this system.

[2312] 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.

[2313] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[2314] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2315] 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.

[2316] FIG. 9 is a diagram illustrating 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 actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect 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.

[2317] 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.

[2318] 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).

[2319] 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 indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, 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 indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2320] 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."

[2321] 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.

[2322] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2323] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2324] 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.

[2325] 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.

[2326] 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.

[2327] The hardware resource for executing a specific process can be any of the following processors: An example of a processor 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. Another example of a processor is 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.

[2328] The hardware resource that executes the specific processing 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 processing may be a single processor.

[2329] 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.

[2330] 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.

[2331] 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.

[2332] 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.

[2333] The following is further disclosed regarding the above embodiment.

[2334] (Claim 1)

[2335] means for receiving a user's voice input and converting it into voice data;

[2336] means for transmitting audio data to a server;

[2337] A means for the server to analyze the voice data and search for corresponding information;

[2338] means for transmitting the searched information by the server to the terminal;

[2339] means for overlaying and displaying the information received by the terminal in the user's field of view;

[2340] A means for capturing user actions with a camera and transmitting the captured actions to a server;

[2341] A system including a means for the server to analyze the captured data and identify progress and recognized objects.

[2342] (Claim 2)

[2343] 2. The system according to claim 1, wherein encryption means is used in transmitting and receiving data.

[2344] (Claim 3)

[2345] 10. The system of claim 1, including a server that anonymizes personal information of users and generates advertising data as a revenue generating means.

[2346] "Example 1"

[2347] (Claim 1)

[2348] means for receiving a user's voice input and converting it into voice data;

[2349] means for transmitting audio data to a server;

[2350] A means for the server to analyze the voice data using a natural language processing module and search for corresponding information;

[2351] means for transmitting the searched information by the server to the terminal;

[2352] means for overlaying and displaying the information received by the terminal in the user's field of view;

[2353] A means for capturing user actions with a capture device and transmitting the captured actions to a server;

[2354] The server analyzes the captured data using an image recognition module to identify the progress and the object of recognition.

[2355] A means for the device to provide audible guidance on overlaid information

[2356] A system including:

[2357] (Claim 2)

[2358] 2. The system according to claim 1, wherein encryption means is used in transmitting and receiving data.

[2359] (Claim 3)

[2360] 10. The system of claim 1, including a server that anonymizes personal information of users and generates advertising data as a revenue generating means.

[2361] "Application Example 1"

[2362] (Claim 1)

[2363] means for receiving a user's voice input and converting it into voice data;

[2364] means for transmitting audio data to a server;

[2365] A means for the server to analyze the voice data and search for corresponding information;

[2366] means for transmitting the searched information by the server to the terminal;

[2367] means for overlaying and displaying the information received by the terminal in the user's field of view;

[2368] A means for capturing user actions with a camera and transmitting the captured actions to a server;

[2369] A means for the server to analyze the captured data and identify the progress and recognition target;

[2370] A means for users to search for products in a store and visually provide location information of specific products;

[2371] A means for displaying detailed product information and reviews based on a customer's voice command;

[2372] A method to acquire location information from proximity sensors in the store and automatically display promotional information;

[2373] A system including:

[2374] (Claim 2)

[2375] 2. The system according to claim 1, wherein encryption means is used in transmitting and receiving data.

[2376] (Claim 3)

[2377] 10. The system of claim 1, including a server that anonymizes personal information of users and generates advertising data as a revenue generating means.

[2378] "Example 2: Combining Emotion Engines"

[2379] (Claim 1)

[2380] means for receiving a user's voice input and converting it into voice data;

[2381] means for transmitting audio data to a server;

[2382] A means for the server to analyze the voice data and search for corresponding information;

[2383] means for transmitting the searched information by the server to the terminal;

[2384] means for overlaying and displaying the information received by the terminal in the user's field of view;

[2385] A means for capturing user actions with a camera and transmitting the captured actions to a server;

[2386] A means for the server to analyze the captured data and identify the progress and recognition target;

[2387] means for analyzing the user's voice and image data to recognize the user's emotional state;

[2388] The system includes a means for adjusting a next action based on the emotional state.

[2389] (Claim 2)

[2390] 2. The system according to claim 1, wherein encryption means is used in transmitting and receiving data.

[2391] (Claim 3)

[2392] 10. The system of claim 1, including a server that anonymizes personal information of users and generates advertising data as a revenue generating means.

[2393] "Application example 2 when combining emotion engines"

[2394] (Claim 1)

[2395] means for receiving a user's voice input and converting it into voice data;

[2396] means for transmitting audio data to a server;

[2397] A means for the server to analyze the voice data and search for corresponding information;

[2398] means for transmitting the searched information by the server to the terminal;

[2399] means for overlaying and displaying the information received by the terminal in the user's field of view;

[2400] A means for capturing user actions with a camera and transmitting the captured actions to a server;

[2401] A means for the server to analyze the captured data and identify the progress and recognition target;

[2402] means for recognizing the emotional state of the user using the captured data and the voice data analyzed by the server;

[2403] The system includes a means for adjusting the difficulty of work instructions and providing feedback based on the perceived emotional state.

[2404] (Claim 2)

[2405] 2. The system according to claim 1, wherein encryption means is used in transmitting and receiving data.

[2406] (Claim 3)

[2407] 10. The system of claim 1, including a server that anonymizes personal information of users and generates advertising data as a revenue generating means. [Explanation of symbols]

[2408] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving a user's voice input and converting it into voice data; means for transmitting audio data to a server; A means for the server to analyze the voice data and search for corresponding information; means for transmitting the searched information by the server to the terminal; means for overlaying and displaying the information received by the terminal in the user's field of view; A means for capturing user actions with a camera and transmitting the captured actions to a server; A system including a means for the server to analyze the captured data and identify progress and recognized objects.

2. 2. The system according to claim 1, wherein encryption means is used in transmitting and receiving data.

3. 10. The system of claim 1, further comprising a server that anonymizes personal information of users and generates advertising data as a revenue generating means.

Images