system

Abstract

We provide the system. [Solution] A means of acquiring video data, A means of acquiring audio data, An analysis means for analyzing acquired video and audio data, A generation means for generating information based on the analysis results, A system that includes a means of presenting generated information to the user.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern times, the instant acquisition of information is an important factor, and there are limited ways to efficiently obtain information especially in situations where hands are occupied. Also, in overseas and unknown environments, means for quickly understanding different languages and character information are required. However, many conventional information acquisition devices block the field of view and have the problem that freely moving is restricted. Therefore, it is urgent to develop an information acquisition and presentation system that does not interfere with the user's field of view and does not require the use of hands.

Means for Solving the Problems

[0005] The present invention provides acquisition means for acquiring video data and audio data. The acquired data is analyzed, and the invention includes generation means for generating information based on the analysis results. This information is provided to the user via presentation means that is overlaid on one of the visual display units. Furthermore, by configuring translation means that translates audio data in real time and presents the translated information, it becomes possible to instantly understand information in different languages. In this way, rapid information acquisition and presentation can be achieved without obstructing the user's view.

[0006] "Acquisition means" refers to a function or device for collecting video data and audio data in real time.

[0007] "Analysis means" refers to a function or device that analyzes acquired data, performs identification and classification, and extracts meaning from that data.

[0008] "Generation means" refers to a function or device that generates new information or data useful to the user based on the analysis results.

[0009] "Presentation means" refers to a function or device for providing generated information to the user in a visual or auditory form.

[0010] "Translation means" refers to a function or device that converts acquired audio data into a different language in real time and presents it to the user.

[0011] A "visual display unit" is a display element that displays information in a portion of the user's field of vision, and is designed to avoid obstructing the user's view by displaying only a portion of the information. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2]This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0013] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0016] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0018] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applicable to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like.

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] As shown in Figure 1, the 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.

[0023] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0026] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0032] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0033] This invention is implemented as a next-generation wearable device for acquiring, analyzing, and presenting visual and auditory data. This device has the function of instantly acquiring and presenting necessary information without obstructing the individual user's field of vision.

[0034] Specifically, when a user wears a glasses-type device, the device acquires visual information of the surroundings using a camera and collects ambient sounds using a microphone. This acquired data is transmitted to a server in real time.

[0035] The server analyzes the received data using a high-performance AI model. For example, if a user is viewing a historical building, the server recognizes the image and retrieves relevant historical data and tourist information from its database. The analyzed information is generated in a format that the user can immediately understand.

[0036] The terminal displays important information received from the server overlaid on one of its visual display units. This allows the user to view the information without restricting their field of vision. Furthermore, the information can be read aloud as needed, allowing the user to perceive the information as well.

[0037] Furthermore, when a user encounters signs or directions from overseas, the device retrieves the text information and processes it on a server for translation. The translated result is then sent back to the device, allowing the user to receive the information in an easily understandable format.

[0038] This invention aims to reduce information gathering during tourist visits and language barriers during overseas travel, and to enable users to acquire and utilize information hands-free in their daily lives. In particular, it is expected to dramatically improve users' work efficiency.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The device powers on and begins continuously acquiring video data within its field of view via its camera. It also collects ambient audio through its microphone. This prepares the device to accumulate data about the user's viewing environment in real time.

[0042] Step 2:

[0043] The terminal transmits acquired video and audio data to the server in real time. This transmission is carried out through a secure communication protocol, ensuring data integrity and security.

[0044] Step 3:

[0045] The server analyzes the received data using an AI model. For video data, an object recognition algorithm is used to identify objects within the field of view, and for audio data, speech recognition technology is used to convert it into text.

[0046] Step 4:

[0047] The server retrieves relevant information from the database based on the analysis results. This includes descriptions and background information related to the identified object, as well as translations of any text found. The resulting information is then formatted appropriately for the user, and an information packet is generated.

[0048] Step 5:

[0049] The server sends information packets it has generated to the terminal. The terminal then uses overlay display technology to overlay the received information onto one of its visual display units, providing the information without obstructing the user's view.

[0050] Step 6:

[0051] Users can use the voice output function as needed to obtain information audibly through voice guidance from their device. This allows users to utilize information from both visual and auditory perspectives.

[0052] Step 7:

[0053] Once users have finished reviewing the information, they may enter feedback into their terminal, which is then sent to the server to contribute to system improvements. This helps to improve the accuracy of the system.

[0054] (Example 1)

[0055] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0056] Modern information gathering methods make it difficult for individual users to obtain information quickly and accurately in different environments. Furthermore, language differences and the sheer volume of information can make it time-consuming and laborious for users to utilize it effectively. Therefore, there is a need for systems that allow users to acquire information intuitively and efficiently, and to comfortably utilize information even in multicultural and multilingual environments.

[0057] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0058] In this invention, the server includes means for transmitting acquired video and audio data to a remote information processing device, means for analyzing the video and audio data using a large-scale learning model, and means for generating relevant information based on the analyzed data. This enables users to quickly acquire information appropriate to their environment in real time and to instantly understand information in different languages.

[0059] "Video data" refers to visual information acquired by cameras and other visual recording devices.

[0060] "Audio data" refers to auditory information acquired by microphones or other sound recording devices.

[0061] "Means of acquisition" refers to mechanisms or methods for electronically collecting specific data from the real world.

[0062] A "remote information processing device" refers to a computer system connected via a network for the purpose of receiving, analyzing, and processing data.

[0063] A "large-scale learning model" refers to an AI technology that uses machine learning algorithms to analyze complex patterns and features based on large amounts of data.

[0064] "Means of analysis" refers to the methods and processes used to process received data and extract meaningful information.

[0065] "Means of generating relevant information" refers to methods and processes for generating information useful to users based on analyzed data.

[0066] A "visual display device" refers to a display or projector used to visually present electronically generated information to a user.

[0067] "Means for presenting translation results" refers to methods or mechanisms for presenting translated information to the user visually or audibly.

[0068] This invention is a system for users to instantly acquire and analyze information about their surroundings through a glasses-type wearable device. When a user wears this device, the terminal uses a camera to acquire video data of the surroundings and a microphone to collect audio data. This data is transmitted in real time to a server, which is a remote information processing device.

[0069] The server analyzes the acquired video and audio data using high-performance, large-scale learning models. For example, a convolutional neural network (CNN) is used to analyze video data, and a natural language processing model is used to analyze audio data. This analysis generates relevant information tailored to the user's situation.

[0070] The generated information is overlaid on a visual display device in a user-friendly format. The display device is integrated into the clear lenses of the glasses and is designed not to obstruct the user's vision. Furthermore, the generated information is provided to the user via audio output as needed.

[0071] When a user encounters a sign or notice in a foreign language, the device retrieves the text information, which is then translated in real time by a server. The translated result is immediately presented to the user, removing information barriers in cross-cultural and cross-linguistic environments. In this process, the system operates quickly when the user enters a prompt such as, "Translate the content of this sign."

[0072] This invention aims to support users in easily utilizing information in everyday life and travel situations, and to significantly improve work efficiency.

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] The device, worn by the user as a pair of glasses, acquires ambient video data via a camera and simultaneously collects audio data via a microphone. The input is the user's visual and auditory environmental information, and the output is digital video and audio data. This data is acquired in real time and sent to the next processing step.

[0076] Step 2:

[0077] The terminal transmits the acquired video and audio data to the server. A fast and reliable communication protocol (e.g., HTTP / 2 or WebSocket) is used for this transmission. The input is the digital data generated in step 1, and the output is the raw data provided to the server.

[0078] Step 3:

[0079] The server processes the received video data using a convolutional neural network (CNN) to analyze its content. Audio data is converted to text using a natural language processing model. The input is the video and audio data sent in step 2, and the output is the analyzed visual and auditory information.

[0080] Step 4:

[0081] The server generates relevant information based on the analysis results using a large-scale learning model. For example, it retrieves detailed information about objects recognized from visual data from a database. The input is the analysis results obtained in step 3, and the output is information formatted in a way that is useful to the user.

[0082] Step 5:

[0083] The terminal overlays the generated information onto the user's glasses' visual display. This display is laid out so as not to obstruct the user's field of vision. Information can also be provided as audio. The input is the information obtained in step 4, and the output is the visual and auditory information presented to the user.

[0084] Step 6:

[0085] When a user recognizes a foreign sign or notice, the device acquires the text information and sends it to the server. The server receives the translation prompt and performs a real-time translation. The input is the text information the user sees, and the output is the translated content. The translation result is immediately sent back to the device and presented to the user.

[0086] (Application Example 1)

[0087] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0088] Conventional wearable devices have struggled to provide timely and appropriate visual and auditory information for everyday use, and have failed to improve the user experience, particularly in virtual environments for shopping and obtaining product information. Furthermore, the technology for quickly translating foreign language product information and presenting it in an easily understandable way for users has been insufficient.

[0089] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0090] In this invention, the server includes means for acquiring video information, means for acquiring audio information, and means for analyzing the acquired video and audio information. This makes it possible to instantly display detailed information about a product and its translation into a foreign language when a user views a product in a virtual environment using a smart device.

[0091] "Visual information" refers to real-world visual data, including visual content acquired through devices such as cameras.

[0092] "Auditory information" refers to auditory data, including ambient sounds and human speech, which is acquired through devices such as microphones.

[0093] "Means of analysis" refers to methods and techniques for processing acquired video and audio information and extracting meaningful data based on that information.

[0094] "Means of generating data" refers to the methods and technologies used to generate and present information necessary for users based on the results of analysis.

[0095] "Means for recognizing voice commands and performing interactions" refers to technology that enables accurate recognition of voice instructions from users and enables appropriate actions or responses based on those instructions.

[0096] "Displaying information overlaid on a visual display device" refers to a method of displaying digital information superimposed on the physical field of vision, and is a technique also known as overlay display.

[0097] "Translation" refers to the technology of converting acquired audio information into a different language and presenting it in a language format that the user can understand.

[0098] This invention provides a system that displays real-time information about products when a user wears smart glasses-type terminals and views products in a virtual mall. The system is implemented as follows:

[0099] First, the smart glasses acquire video information through their built-in camera. This video information is sent to a server to identify the product the user is viewing. The server uses the acquired video information to perform image recognition processing to identify the product. This process uses the OpenAI® API to identify the product and retrieve related information. In addition, voice information is collected by the microphone, and voice commands are recognized via the Google® Assistant API, enabling interaction based on the user's instructions.

[0100] The obtained product information and recommended products are overlaid on the visual display using AR.js and presented directly in the user's field of view. This allows users to obtain additional information without obstructing their real-world vision. Furthermore, product information displayed in foreign languages ​​such as English is translated and presented to the user in their native language.

[0101] As a concrete example, when a user selects a dress in a fashion store within a virtual mall, smart glasses identify the dress and display information including price and reviews. When the user gives a voice command such as "Add this dress to cart," the system recognizes the instruction and performs the necessary action.

[0102] Examples of prompts to input into a generative AI model:

[0103] "Identify the product from the following images and retrieve and display the relevant market data, pricing information, and reviews for that product."

[0104] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0105] Step 1:

[0106] The device acquires surrounding video information using its camera. This acquired video information is used to clarify specific products or objects that the user is viewing. The input is real-world video, and the output is digitized visual data.

[0107] Step 2:

[0108] The device acquires voice information using a microphone. This voice information is primarily used to recognize the user's voice commands. The input is the user's voice, and the output is digitized voice data.

[0109] Step 3:

[0110] The terminal transmits the acquired video information to the server. By transferring the video data, it is used as input for further processing. The output triggers video analysis by the server.

[0111] Step 4:

[0112] The server processes the received video information using an AI model to identify products. This process utilizes the OpenAI API, which matches the data against a product database to identify the product. The input is digitized video data, and the output is the recognized product information.

[0113] Step 5:

[0114] The server retrieves relevant detailed data (e.g., price, reviews, inventory information) from the database based on the product information. The input is the recognized product information, and the output is a set of detailed data.

[0115] Step 6:

[0116] The server translates the retrieved information and converts it to the user's language if translation is required. The input is additional information (sometimes in a foreign language), and the output is the translated information.

[0117] Step 7:

[0118] The server sends the generated information to the terminal, which then displays that information as an overlay on its visual display device. AR.js is used here. The input is the translated additional information, and the output is a visual overlay displayed in the user's field of view.

[0119] Step 8:

[0120] The device uses the Google Assistant API to analyze acquired voice information and execute instructions based on the user's voice commands. The input is digitized voice data, and the output is an action within the system (e.g., executing the command "add to cart").

[0121] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0122] This invention is implemented as a next-generation wearable device that combines the ability to recognize user emotions and optimize information delivery based on those emotions. Its distinguishing feature is that it not only acquires and displays information, but also understands the user's emotional state and provides personalized information and interaction.

[0123] Specifically, when a user wears a glasses-type device, the device not only simply acquires video and ambient audio from the user's field of vision, but also has the function of analyzing the user's facial expressions from the video data. This data is transmitted to a server in real time and scrutinized by an emotion engine.

[0124] The server uses an emotion engine to analyze facial expressions and tone of voice to estimate the user's emotional state. For example, if the server determines that the user is excited about something, it will provide more relevant details. Conversely, when the user is calm, the server will adjust to present a deeper analysis.

[0125] This information is transmitted from the server to the terminal, just like with regular information delivery. The terminal then overlays this information on one of its visual display units. This method allows the user to access the necessary information without their field of vision being obstructed.

[0126] Furthermore, the acquired audio data is translated in real time, and the translation results may be filtered according to the user's emotions. In situations where the user is feeling stressed, the system can present translation results that focus on important context.

[0127] In this way, by dynamically changing the method of information delivery according to the user's current emotions, a more intuitive and natural interaction is achieved. This invention allows users to easily obtain a more personalized experience and promotes the optimal use of information according to the situation.

[0128] The following describes the processing flow.

[0129] Step 1:

[0130] The device starts up and simultaneously acquires video data from the user's field of view and audio data from the surroundings. The camera captures the scenery in front of the user, and the microphone captures the audio environment.

[0131] Step 2:

[0132] The device sends the acquired video data to the server. This video data includes frame information for recognizing facial expressions.

[0133] Step 3:

[0134] The server receives video data and analyzes the user's facial expressions using a facial recognition algorithm. It extracts facial expression data such as smiles, surprise, and pessimism to determine the user's emotional state.

[0135] Step 4:

[0136] The audio data is sent to a server, which uses speech recognition technology to convert it into text. Furthermore, an emotion engine is used to supplement the user's emotional state based on the tone and speed of the speech.

[0137] Step 5:

[0138] The server generates information to provide to the user based on the emotional information it analyzes. For example, if the user is excited, it prioritizes generating relevant entertainment information.

[0139] Step 6:

[0140] The generated information is overlaid on one of the terminal's visual display units. The user can view this information without their entire field of vision being obstructed.

[0141] Step 7:

[0142] The device will read out voice information as needed. It provides voice guidance optimized for the user's emotional state, offering intuitive and easy-to-understand explanations.

[0143] Step 8:

[0144] When a user provides feedback on the information, the device collects that feedback and sends it to the server. The server then uses this data to improve the overall system.

[0145] (Example 2)

[0146] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0147] Conventional information delivery systems present only fixed information without considering the user's emotional state, resulting in a limited user experience. Furthermore, they often include a lot of unnecessary visual and auditory information, making it difficult to efficiently provide only the information relevant to the user. This hinders users from making optimal use of information in accordance with their situation and emotions.

[0148] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0149] In this invention, the server includes means for acquiring video information, means for acquiring audio information, means for analyzing the acquired video and audio information, means for estimating the emotional state based on the analysis results, means for generating information according to the estimated emotional state, means for presenting the generated information to the user, means for displaying the information overlaid on a visual device, and means for immediately translating the acquired audio information and presenting the translation result. This enables the provision of information optimized based on the user's emotions, thereby improving the user experience.

[0150] "Visual information" refers to visual data acquired using cameras or other recording devices, including data about the user's surrounding environment and the user's own facial expressions.

[0151] "Audio information" refers to auditory data collected via microphones or other recording devices, including ambient sounds and user speech.

[0152] "Means of analysis" refers to a method or apparatus for processing video and audio information to recognize and extract specific features or patterns from it.

[0153] "Means for estimating emotional state" refers to a technology or device for predicting a user's emotional state based on analyzed video and audio information.

[0154] "Means for generating information" refers to a method or apparatus for creating or selecting information to be provided to a user based on an estimated emotional state.

[0155] "Means of presentation" refers to a method or apparatus for visually or audibly displaying or reproducing generated information to a user.

[0156] "Means of displaying information overlaid on a visual device" refers to a technology for displaying digital information on the screen of a device worn by a user, along with images of the real world that are visible as a background.

[0157] "Means for instantly translating and presenting the translation result" refers to a method or apparatus for rapidly converting audio information into another language and providing the translated content to the user.

[0158] This invention is implemented as a next-generation wearable system that recognizes the user's emotional state in real time and provides personalized information. This system acquires video and audio information via a glasses-type device worn by the user (hereinafter referred to as the "terminal"). The terminal has a built-in high-resolution camera and microphone and collects visual and auditory data through the user's activities.

[0159] The terminal uses highly accurate facial recognition software to analyze video information. For example, a common face recognition framework (e.g., OpenCV or Dlib) may be used. This allows the system to capture the user's facial feature points and make an initial determination of their emotional state. The acquired video and audio information is transmitted to the server via wireless communication.

[0160] The server uses the incoming data to perform a detailed analysis of the user's emotional state using a generative AI model (e.g., an emotion analysis model based on TENSORFLOW® or PyTorch). The server analyzes facial expressions and voice tone and generates corresponding emotion tags. Based on the analysis results, it also constructs optimized information using the generation method and sends it back to the terminal.

[0161] The terminal displays selected information as an overlay through hardware that overlays information sent from the server onto the user's field of view. This allows the user to view the necessary information without being visually obstructed by their surroundings.

[0162] As a concrete example, consider a scenario where a user visits a foreign tourist destination and obtains information. While the user views the tourist attraction through a glasses-type device, the device sends the image to a server, which performs emotion recognition. If the server determines that the user is showing an expression of admiration, it selects and provides detailed information about that tourist destination. Furthermore, if translation of surrounding audio information is necessary, the server instantly translates the audio information, filters the results on the device, and presents them to the user.

[0163] As an example of a prompt, if the user shows an excited expression towards a specific tourist destination, design an AI model that prioritizes and provides relevant information. By supplying this to the generating AI model, a more intuitive and personalized information delivery can be achieved.

[0164] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0165] Step 1:

[0166] When a user wears a glasses-type device, the terminal captures surrounding video and audio information. Its inputs include video data captured by a high-resolution camera and audio data recorded by a microphone. Specifically, the terminal collects this data in real time and immediately prepares to send it to a server.

[0167] Step 2:

[0168] The device analyzes collected video data using facial recognition software. The input is video data from the camera, and the output includes analyzed user facial features and preliminary emotion estimations. The operation involves using a general-purpose library like OpenCV to detect facial feature points and determine the initial emotional state (joy, anger, sadness, etc.).

[0169] Step 3:

[0170] The server receives analyzed video and audio data transmitted from the terminal. The input consists of feature point information and audio data, and the output is emotion tags that represent the user's detailed emotional state. The server uses a generative AI model to analyze subtle changes in facial expressions and voice tone, and the emotion engine precisely estimates the emotional state.

[0171] Step 4:

[0172] The server generates user-specific information based on estimated emotions. The input is emotion tags, and the output is customized informational content. Specifically, it selects the most relevant information from a set of emotion-based content and sends it to the device in a structured format.

[0173] Step 5:

[0174] The terminal displays information received from the server as an overlay on the user's field of view. The input is information content from the server, and the output is the information displayed on the user's field of view. Specifically, it overlays information onto the visual device through an application, allowing the user to obtain information while observing the actual environment.

[0175] Step 6:

[0176] The server translates audio data in real time and sends the results to the terminal. The input is audio data, and the output is translated text or audio. Specifically, it uses a language understanding library to convert the audio into another language, filters out important information, and provides it to the terminal in a format optimized for the user's situation.

[0177] (Application Example 2)

[0178] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0179] Current information delivery systems provide information uniformly without considering the user's emotional state, making it difficult to present information optimized for individual user situations and moods. Furthermore, in online shopping, it's difficult to adjust and optimize product information according to the user's interests and emotions, thus hindering customer satisfaction. In this context, there is a need for technology that can recognize user emotions in real time and efficiently provide personalized information based on those emotions.

[0180] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0181] In this invention, the server includes a device for acquiring video data, a device for acquiring audio data, and a device for generating information based on the analysis results. This makes it possible to provide information based on the user's emotional state.

[0182] "Video data" refers to visually captured data used to obtain the user's facial expressions and movements.

[0183] "Voice data" refers to acoustic data collected to record the user's voice and surrounding sounds.

[0184] "Device" refers to hardware or software used to perform a specific function or process.

[0185] "Analysis" is the process of processing acquired data to estimate the emotional state of the user.

[0186] "Emotional state" refers to the user's current emotional and mood state.

[0187] An "information generating device" is a processing device that creates personalized information for users based on analyzed data.

[0188] "User" refers to an individual who uses the system to obtain information.

[0189] A "virtual commerce space" is an online marketplace where users can browse and purchase goods in a digital environment.

[0190] "Product information" refers to information that includes details and specifications related to a product or service.

[0191] A "visual display device" is a display device used to present visual information to a user.

[0192] To realize this invention, a glasses-type device worn by the user, a server, and a terminal that manages the virtual trading space must work together in coordination. First, the user uses the glasses-type device to acquire visual and audio data in real time. This data is transferred to the server via the internet. The server analyzes the user's facial expressions by using image recognition software, such as "Google Cloud AutoML Vision API" or "Amazon Rekognition," to process the visual data. It also applies speech recognition technology to the audio data to analyze the user's voice tone and keywords.

[0193] The server uses these analysis results to generate appropriate product or promotional information, employing a generative AI model that estimates the user's emotional state. This information is transmitted to a terminal managing the virtual commerce space and displayed on the user's glasses-type device in a form adjusted based on the user's emotions. At this time, relevant product information is overlaid on the visual display device, allowing the user to view the information without obstructing their vision.

[0194] For example, if the server determines that a user is excited by a particular product while exploring a virtual shopping space, that product will be highlighted, and promotional prices and detailed information about related products will be displayed in vivid colors. This allows users to enjoy a shopping experience that matches their emotions.

[0195] An example of a prompt message is: "Create a prompt message that analyzes the user's emotions from their facial expressions and voice, and generates product information that matches those emotions."

[0196] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0197] Step 1:

[0198] The system collects video and audio data from a device that captures the user's visual and audio data in real time while the user wears glasses. This provides basic data for recording the user's facial expressions and voice.

[0199] Step 2:

[0200] The user's glasses-type device transfers the collected video and audio data to the server. The server receives this data and prepares it for processing. It receives video and audio data as input and stores it in an analyzable format.

[0201] Step 3:

[0202] The server performs facial recognition on the video data using image recognition software. Specifically, it extracts emotional features from the user's facial expressions using tools such as the "Google Cloud AutoML Vision API." As a result of the data processing, an emotion index, such as smiles or surprise, is generated. The output is the emotion index.

[0203] Step 4:

[0204] The server processes audio data using speech recognition technology, analyzing voice tone and keywords. The user's voice tone and specific phrases are associated with their emotional state. Audio data is used as input, and the audio analysis results are obtained as output.

[0205] Step 5:

[0206] The server integrates the emotion index obtained in steps 3 and 4 with the voice analysis results and uses a generative AI model to estimate the user's emotional state. This performs data calculations to accurately identify the user's current emotions. The output is the emotional state.

[0207] Step 6:

[0208] The server generates appropriate product information within the virtual trading space based on the estimated emotional state of the user. Since the product information is customized according to the emotion, the input is the emotional state, and the output is customized product information.

[0209] Step 7:

[0210] The terminal overlays customized product information received from the server onto the user's glasses-type device. Specifically, it superimposes the necessary visual information onto one of the visual display devices. This allows the user to view product information that is relevant to their emotional state.

[0211] Step 8:

[0212] Users enjoy a shopping experience in a virtual commerce space based on the displayed product information. This enables interactions that are tailored to the user's emotions.

[0213] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0214] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0215] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0216] [Second Embodiment]

[0217] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0218] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0219] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0220] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0221] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0222] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0223] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0224] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0225] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0226] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0227] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0228] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0229] This invention is implemented as a next-generation wearable device for acquiring, analyzing, and presenting visual and auditory data. This device has the function of instantly acquiring and presenting necessary information without obstructing the individual user's field of vision.

[0230] Specifically, when a user wears a glasses-type device, the device acquires visual information of the surroundings using a camera and collects ambient sounds using a microphone. This acquired data is transmitted to a server in real time.

[0231] The server analyzes the received data using a high-performance AI model. For example, if a user is viewing a historical building, the server recognizes the image and retrieves relevant historical data and tourist information from its database. The analyzed information is generated in a format that the user can immediately understand.

[0232] The terminal displays important information received from the server overlaid on one of its visual display units. This allows the user to view the information without restricting their field of vision. Furthermore, the information can be read aloud as needed, allowing the user to perceive the information as well.

[0233] Furthermore, when a user encounters signs or directions from overseas, the device retrieves the text information and processes it on a server for translation. The translated result is then sent back to the device, allowing the user to receive the information in an easily understandable format.

[0234] This invention aims to reduce information gathering during tourist visits and language barriers during overseas travel, and to enable users to acquire and utilize information hands-free in their daily lives. In particular, it is expected to dramatically improve users' work efficiency.

[0235] The following describes the processing flow.

[0236] Step 1:

[0237] The device powers on and begins continuously acquiring video data within its field of view via its camera. It also collects ambient audio through its microphone. This prepares the device to accumulate data about the user's viewing environment in real time.

[0238] Step 2:

[0239] The terminal transmits acquired video and audio data to the server in real time. This transmission is carried out through a secure communication protocol, ensuring data integrity and security.

[0240] Step 3:

[0241] The server analyzes the received data using an AI model. For video data, an object recognition algorithm is used to identify objects within the field of view, and for audio data, speech recognition technology is used to convert it into text.

[0242] Step 4:

[0243] The server retrieves relevant information from the database based on the analysis results. This includes descriptions and background information related to the identified object, as well as translations of any text found. The resulting information is then formatted appropriately for the user, and an information packet is generated.

[0244] Step 5:

[0245] The server sends information packets it has generated to the terminal. The terminal then uses overlay display technology to overlay the received information onto one of its visual display units, providing the information without obstructing the user's view.

[0246] Step 6:

[0247] Users can use the voice output function as needed to obtain information audibly through voice guidance from their device. This allows users to utilize information from both visual and auditory perspectives.

[0248] Step 7:

[0249] Once users have finished reviewing the information, they may enter feedback into their terminal, which is then sent to the server to contribute to system improvements. This helps to improve the accuracy of the system.

[0250] (Example 1)

[0251] Next, we will describe Example 1. 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."

[0252] Modern information gathering methods make it difficult for individual users to obtain information quickly and accurately in different environments. Furthermore, language differences and the sheer volume of information can make it time-consuming and laborious for users to utilize it effectively. Therefore, there is a need for systems that allow users to acquire information intuitively and efficiently, and to comfortably utilize information even in multicultural and multilingual environments.

[0253] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0254] In this invention, the server includes means for transmitting acquired video and audio data to a remote information processing device, means for analyzing the video and audio data using a large-scale learning model, and means for generating relevant information based on the analyzed data. This enables users to quickly acquire information appropriate to their environment in real time and to instantly understand information in different languages.

[0255] "Video data" refers to visual information acquired by cameras and other visual recording devices.

[0256] "Audio data" refers to auditory information acquired by microphones or other sound recording devices.

[0257] "Means of acquisition" refers to mechanisms or methods for electronically collecting specific data from the real world.

[0258] A "remote information processing device" refers to a computer system connected via a network for the purpose of receiving, analyzing, and processing data.

[0259] A "large-scale learning model" refers to an AI technology that uses machine learning algorithms to analyze complex patterns and features based on large amounts of data.

[0260] "Means of analysis" refers to the methods and processes used to process received data and extract meaningful information.

[0261] "Means of generating relevant information" refers to methods and processes for generating information useful to users based on analyzed data.

[0262] A "visual display device" refers to a display or projector used to visually present electronically generated information to a user.

[0263] "Means for presenting translation results" refers to methods or mechanisms for presenting translated information to the user visually or audibly.

[0264] This invention is a system for users to instantly acquire and analyze information about their surroundings through a glasses-type wearable device. When a user wears this device, the terminal uses a camera to acquire video data of the surroundings and a microphone to collect audio data. This data is transmitted in real time to a server, which is a remote information processing device.

[0265] The server analyzes the acquired video and audio data using high-performance, large-scale learning models. For example, a convolutional neural network (CNN) is used to analyze video data, and a natural language processing model is used to analyze audio data. This analysis generates relevant information tailored to the user's situation.

[0266] The generated information is overlaid on a visual display device in a user-friendly format. The display device is integrated into the clear lenses of the glasses and is designed not to obstruct the user's vision. Furthermore, the generated information is provided to the user via audio output as needed.

[0267] When a user encounters a sign or notice in a foreign language, the device retrieves the text information, which is then translated in real time by a server. The translated result is immediately presented to the user, removing information barriers in cross-cultural and cross-linguistic environments. In this process, the system operates quickly when the user enters a prompt such as, "Translate the content of this sign."

[0268] This invention aims to support users in easily utilizing information in everyday life and travel situations, and to significantly improve work efficiency.

[0269] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0270] Step 1:

[0271] The device, worn by the user as a pair of glasses, acquires ambient video data via a camera and simultaneously collects audio data via a microphone. The input is the user's visual and auditory environmental information, and the output is digital video and audio data. This data is acquired in real time and sent to the next processing step.

[0272] Step 2:

[0273] The terminal transmits the acquired video and audio data to the server. A fast and reliable communication protocol (e.g., HTTP / 2 or WebSocket) is used for this transmission. The input is the digital data generated in step 1, and the output is the raw data provided to the server.

[0274] Step 3:

[0275] The server processes the received video data using a convolutional neural network (CNN) to analyze its content. Audio data is converted to text using a natural language processing model. The input is the video and audio data sent in step 2, and the output is the analyzed visual and auditory information.

[0276] Step 4:

[0277] The server generates relevant information based on the analysis results using a large-scale learning model. For example, detailed information about the objects recognized from the visual data is retrieved from the database. The input is the analysis result obtained in Step 3, and the output is information arranged in a format beneficial to the user.

[0278] Step 5:

[0279] The terminal overlays and displays the generated information on the visual display device of the user's glasses. This display is laid out so as not to obstruct the user's field of vision. Also, the information can be provided as audio. The input is the information obtained in Step 4, and the output is the visual and auditory information presented to the user.

[0280] Step 6:

[0281] When the user recognizes an overseas sign or guidance, the terminal acquires the character information and transmits it to the server. The server receives the translation prompt sentence and performs real-time translation. The input is the character information seen by the user, and the output is the translated content. The translation result is immediately sent back to the terminal and presented to the user.

[0282] (Application Example 1)

[0283] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0284] Conventional wearable devices have difficulty in immediately and appropriately presenting visual and auditory information when used by users in their daily lives, and particularly in improving the user experience in shopping and obtaining product information in a virtual environment. Also, the technology for quickly translating foreign language product information and presenting it in an easy-to-understand manner to users was insufficient.

[0285] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 1 is realized by the following means.

[0286] In this invention, the server includes means for acquiring video information, means for acquiring audio information, and means for analyzing the acquired video information and audio information. Thereby, when the user views a product in a virtual environment using a smart device, it becomes possible to immediately present detailed information about the product and the translation result in a foreign language.

[0287] "Video information" refers to real visual data and includes visual content acquired through devices such as cameras.

[0288] "Audio information" refers to auditory data including environmental sounds and human speech and is acquired through devices such as microphones.

[0289] "Means for analyzing" refers to methods and technologies for processing the acquired video information and audio information and extracting meaningful data based on them.

[0290] "Means for generating data" refers to methods and technologies used to generate and present information necessary for the user based on the analyzed results.

[0291] "Means for recognizing voice commands and performing interactions" means a technology that enables accurate recognition of voice instructions from the user and appropriate actions and responses based on them.

[0292] "Display over a visual display device" refers to a method of displaying digital information by superimposing it on the physical visual field and is a technology also called overlay display.

[0293] "Translate" refers to a technology that converts the acquired audio information into a different language and presents it in a language form understandable to the user.

[0294] This invention provides a system that displays real-time information about products when a user wears smart glasses-type terminals and views products in a virtual mall. The system is implemented as follows:

[0295] First, the smart glasses acquire video information through their built-in camera. This video information is sent to a server to identify the product the user is viewing. The server uses the acquired video information to perform image recognition processing to identify the product. This process uses the OpenAI API to identify the product and retrieve related information. In addition, voice information is collected by the microphone, and voice commands are recognized via the Google Assistant API, allowing for interaction based on the user's instructions.

[0296] The obtained product information and recommended products are overlaid on the visual display using AR.js and presented directly in the user's field of view. This allows users to obtain additional information without obstructing their real-world vision. Furthermore, product information displayed in foreign languages ​​such as English is translated and presented to the user in their native language.

[0297] As a concrete example, when a user selects a dress in a fashion store within a virtual mall, smart glasses identify the dress and display information including price and reviews. When the user gives a voice command such as "Add this dress to cart," the system recognizes the instruction and performs the necessary action.

[0298] Examples of prompts to input into a generative AI model:

[0299] "Identify the product from the following images and retrieve and display the relevant market data, pricing information, and reviews for that product."

[0300] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0301] Step 1:

[0302] The terminal acquires surrounding video information with a camera. This acquired video information is used to clarify the specific products or objects that the user is viewing. The input is the actual video, and digitized visual data is obtained as the output.

[0303] Step 2:

[0304] The terminal acquires audio information with a microphone. This audio information is mainly used to recognize the user's voice commands. The input is the voice from the user, and digitized audio data is obtained as the output.

[0305] Step 3:

[0306] The terminal transmits the acquired video information to the server. By transferring the video data, the data is used as an input for further processing. The output triggers video analysis by the server.

[0307] Step 4:

[0308] The server processes the received video information using an AI model to identify the product. In this process, the OpenAI API is used, and the product is identified by comparing it with the product database. The input is the digitized video data, and the output is the recognized product information.

[0309] Step 5:

[0310] The server obtains related detailed data (e.g., price, review, inventory information) from the database based on the product information. The input is the recognized product information, and the output is a set of detailed data.

[0311] Step 6:

[0312] The server translates the retrieved information and converts it to the user's language if translation is required. The input is additional information (sometimes in a foreign language), and the output is the translated information.

[0313] Step 7:

[0314] The server sends the generated information to the terminal, which then displays that information as an overlay on its visual display device. AR.js is used here. The input is the translated additional information, and the output is a visual overlay displayed in the user's field of view.

[0315] Step 8:

[0316] The device uses the Google Assistant API to analyze acquired voice information and execute instructions based on the user's voice commands. The input is digitized voice data, and the output is an action within the system (e.g., executing the command "add to cart").

[0317] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0318] This invention is implemented as a next-generation wearable device that combines the ability to recognize user emotions and optimize information delivery based on those emotions. Its distinguishing feature is that it not only acquires and displays information, but also understands the user's emotional state and provides personalized information and interaction.

[0319] Specifically, when a user wears a glasses-type device, the device not only simply acquires video and ambient audio from the user's field of vision, but also has the function of analyzing the user's facial expressions from the video data. This data is transmitted to a server in real time and scrutinized by an emotion engine.

[0320] The server uses an emotion engine to analyze facial expressions and tone of voice to estimate the user's emotional state. For example, if the server determines that the user is excited about something, it will provide more relevant details. Conversely, when the user is calm, the server will adjust to present a deeper analysis.

[0321] This information is transmitted from the server to the terminal, just like with regular information delivery. The terminal then overlays this information on one of its visual display units. This method allows the user to access the necessary information without their field of vision being obstructed.

[0322] Furthermore, the acquired audio data is translated in real time, and the translation results may be filtered according to the user's emotions. In situations where the user is feeling stressed, the system can present translation results that focus on important context.

[0323] In this way, by dynamically changing the method of information delivery according to the user's current emotions, a more intuitive and natural interaction is achieved. This invention allows users to easily obtain a more personalized experience and promotes the optimal use of information according to the situation.

[0324] The following describes the processing flow.

[0325] Step 1:

[0326] The device starts up and simultaneously acquires video data from the user's field of view and audio data from the surroundings. The camera captures the scenery in front of the user, and the microphone captures the audio environment.

[0327] Step 2:

[0328] The device sends the acquired video data to the server. This video data includes frame information for recognizing facial expressions.

[0329] Step 3:

[0330] The server receives video data and analyzes the user's facial expressions using a facial recognition algorithm. It extracts facial expression data such as smiles, surprise, and pessimism to determine the user's emotional state.

[0331] Step 4:

[0332] The audio data is sent to a server, which uses speech recognition technology to convert it into text. Furthermore, an emotion engine is used to supplement the user's emotional state based on the tone and speed of the speech.

[0333] Step 5:

[0334] The server generates information to provide to the user based on the emotional information it analyzes. For example, if the user is excited, it prioritizes generating relevant entertainment information.

[0335] Step 6:

[0336] The generated information is overlaid on one of the terminal's visual display units. The user can view this information without their entire field of vision being obstructed.

[0337] Step 7:

[0338] The device will read out voice information as needed. It provides voice guidance optimized for the user's emotional state, offering intuitive and easy-to-understand explanations.

[0339] Step 8:

[0340] When a user provides feedback on the information, the device collects that feedback and sends it to the server. The server then uses this data to improve the overall system.

[0341] (Example 2)

[0342] Next, we will describe Example 2. 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".

[0343] Conventional information delivery systems present only fixed information without considering the user's emotional state, resulting in a limited user experience. Furthermore, they often include a lot of unnecessary visual and auditory information, making it difficult to efficiently provide only the information relevant to the user. This hinders users from making optimal use of information in accordance with their situation and emotions.

[0344] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0345] In this invention, the server includes means for acquiring video information, means for acquiring audio information, means for analyzing the acquired video and audio information, means for estimating the emotional state based on the analysis results, means for generating information according to the estimated emotional state, means for presenting the generated information to the user, means for displaying the information overlaid on a visual device, and means for immediately translating the acquired audio information and presenting the translation result. This enables the provision of information optimized based on the user's emotions, thereby improving the user experience.

[0346] "Visual information" refers to visual data acquired using cameras or other recording devices, including data about the user's surrounding environment and the user's own facial expressions.

[0347] "Audio information" refers to auditory data collected via microphones or other recording devices, including ambient sounds and user speech.

[0348] "Means of analysis" refers to a method or apparatus for processing video and audio information to recognize and extract specific features or patterns from it.

[0349] "Means for estimating emotional state" refers to a technology or device for predicting a user's emotional state based on analyzed video and audio information.

[0350] "Means for generating information" refers to a method or apparatus for creating or selecting information to be provided to a user based on an estimated emotional state.

[0351] "Means of presentation" refers to a method or apparatus for visually or audibly displaying or reproducing generated information to a user.

[0352] "Means of displaying information overlaid on a visual device" refers to a technology for displaying digital information on the screen of a device worn by a user, along with images of the real world that are visible as a background.

[0353] "Means for instantly translating and presenting the translation result" refers to a method or apparatus for rapidly converting audio information into another language and providing the translated content to the user.

[0354] This invention is implemented as a next-generation wearable system that recognizes the user's emotional state in real time and provides personalized information. This system acquires video and audio information via a glasses-type device worn by the user (hereinafter referred to as the "terminal"). The terminal has a built-in high-resolution camera and microphone and collects visual and auditory data through the user's activities.

[0355] The terminal uses highly accurate facial recognition software to analyze video information. For example, a common face recognition framework (e.g., OpenCV or Dlib) may be used. This allows the system to capture the user's facial feature points and make an initial determination of their emotional state. The acquired video and audio information is transmitted to the server via wireless communication.

[0356] The server uses the incoming data to perform a detailed analysis of the user's emotional state using a generative AI model (e.g., an emotion analysis model based on TensorFlow or PyTorch). The server analyzes facial expressions and voice tone and generates corresponding emotion tags. Based on the analysis results, it also constructs optimized information using the generative means and sends it back to the terminal.

[0357] The terminal displays selected information as an overlay through hardware that overlays information sent from the server onto the user's field of view. This allows the user to view the necessary information without being visually obstructed by their surroundings.

[0358] As a concrete example, consider a scenario where a user visits a foreign tourist destination and obtains information. While the user views the tourist attraction through a glasses-type device, the device sends the image to a server, which performs emotion recognition. If the server determines that the user is showing an expression of admiration, it selects and provides detailed information about that tourist destination. Furthermore, if translation of surrounding audio information is necessary, the server instantly translates the audio information, filters the results on the device, and presents them to the user.

[0359] As an example of a prompt, if the user shows an excited expression towards a specific tourist destination, design an AI model that prioritizes and provides relevant information. By supplying this to the generating AI model, a more intuitive and personalized information delivery can be achieved.

[0360] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0361] Step 1:

[0362] When a user wears a glasses-type device, the terminal captures surrounding video and audio information. Its inputs include video data captured by a high-resolution camera and audio data recorded by a microphone. Specifically, the terminal collects this data in real time and immediately prepares to send it to a server.

[0363] Step 2:

[0364] The device analyzes collected video data using facial recognition software. The input is video data from the camera, and the output includes analyzed user facial features and preliminary emotion estimations. The operation involves using a general-purpose library like OpenCV to detect facial feature points and determine the initial emotional state (joy, anger, sadness, etc.).

[0365] Step 3:

[0366] The server receives analyzed video and audio data transmitted from the terminal. The input consists of feature point information and audio data, and the output is emotion tags that represent the user's detailed emotional state. The server uses a generative AI model to analyze subtle changes in facial expressions and voice tone, and the emotion engine precisely estimates the emotional state.

[0367] Step 4:

[0368] The server generates user-specific information based on estimated emotions. The input is emotion tags, and the output is customized informational content. Specifically, it selects the most relevant information from a set of emotion-based content and sends it to the device in a structured format.

[0369] Step 5:

[0370] The terminal displays information received from the server as an overlay on the user's field of view. The input is information content from the server, and the output is the information displayed on the user's field of view. Specifically, it overlays information onto the visual device through an application, allowing the user to obtain information while observing the actual environment.

[0371] Step 6:

[0372] The server translates audio data in real time and sends the results to the terminal. The input is audio data, and the output is translated text or audio. Specifically, it uses a language understanding library to convert the audio into another language, filters out important information, and provides it to the terminal in a format optimized for the user's situation.

[0373] (Application Example 2)

[0374] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0375] Current information delivery systems provide information uniformly without considering the user's emotional state, making it difficult to present information optimized for individual user situations and moods. Furthermore, in online shopping, it's difficult to adjust and optimize product information according to the user's interests and emotions, thus hindering customer satisfaction. In this context, there is a need for technology that can recognize user emotions in real time and efficiently provide personalized information based on those emotions.

[0376] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0377] In this invention, the server includes a device for acquiring video data, a device for acquiring audio data, and a device for generating information based on the analysis results. This makes it possible to provide information based on the user's emotional state.

[0378] "Video data" refers to visually captured data used to obtain the user's facial expressions and movements.

[0379] "Voice data" refers to acoustic data collected to record the user's voice and surrounding sounds.

[0380] "Device" refers to hardware or software used to perform a specific function or process.

[0381] "Analysis" is the process of processing acquired data to estimate the emotional state of the user.

[0382] "Emotional state" refers to the user's current emotional and mood state.

[0383] An "information generating device" is a processing device that creates personalized information for users based on analyzed data.

[0384] "User" refers to an individual who uses the system to obtain information.

[0385] A "virtual commerce space" is an online marketplace where users can browse and purchase goods in a digital environment.

[0386] "Product information" refers to information that includes details and specifications related to a product or service.

[0387] A "visual display device" is a display device used to present visual information to a user.

[0388] To realize this invention, a glasses-type device worn by the user, a server, and a terminal that manages the virtual trading space must work together in coordination. First, the user uses the glasses-type device to acquire visual and audio data in real time. This data is transferred to the server via the internet. The server analyzes the user's facial expressions by using image recognition software, such as "Google Cloud AutoML Vision API" or "Amazon Rekognition," to process the visual data. It also applies speech recognition technology to the audio data to analyze the user's voice tone and keywords.

[0389] The server uses these analysis results to generate appropriate product or promotional information, employing a generative AI model that estimates the user's emotional state. This information is transmitted to a terminal managing the virtual commerce space and displayed on the user's glasses-type device in a form adjusted based on the user's emotions. At this time, relevant product information is overlaid on the visual display device, allowing the user to view the information without obstructing their vision.

[0390] For example, if the server determines that a user is excited by a particular product while exploring a virtual shopping space, that product will be highlighted, and promotional prices and detailed information about related products will be displayed in vivid colors. This allows users to enjoy a shopping experience that matches their emotions.

[0391] An example of a prompt message is: "Create a prompt message that analyzes the user's emotions from their facial expressions and voice, and generates product information that matches those emotions."

[0392] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0393] Step 1:

[0394] The system collects video and audio data from a device that captures the user's visual and audio data in real time while the user wears glasses. This provides basic data for recording the user's facial expressions and voice.

[0395] Step 2:

[0396] The user's glasses-type device transfers the collected video and audio data to the server. The server receives this data and prepares it for processing. It receives video and audio data as input and stores it in an analyzable format.

[0397] Step 3:

[0398] The server performs facial recognition on the video data using image recognition software. Specifically, it extracts emotional features from the user's facial expressions using tools such as the "Google Cloud AutoML Vision API." As a result of the data processing, an emotion index, such as smiles or surprise, is generated. The output is the emotion index.

[0399] Step 4:

[0400] The server processes audio data using speech recognition technology, analyzing voice tone and keywords. The user's voice tone and specific phrases are associated with their emotional state. Audio data is used as input, and the audio analysis results are obtained as output.

[0401] Step 5:

[0402] The server integrates the emotion index obtained in steps 3 and 4 with the voice analysis results and uses a generative AI model to estimate the user's emotional state. This performs data calculations to accurately identify the user's current emotions. The output is the emotional state.

[0403] Step 6:

[0404] The server generates appropriate product information within the virtual trading space based on the estimated emotional state of the user. Since the product information is customized according to the emotion, the input is the emotional state, and the output is customized product information.

[0405] Step 7:

[0406] The terminal overlays customized product information received from the server onto the user's glasses-type device. Specifically, it superimposes the necessary visual information onto one of the visual display devices. This allows the user to view product information that is relevant to their emotional state.

[0407] Step 8:

[0408] Users enjoy a shopping experience in a virtual commerce space based on the displayed product information. This enables interactions that are tailored to the user's emotions.

[0409] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0410] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0411] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0412] [Third Embodiment]

[0413] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0414] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0415] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0416] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0417] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0418] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0419] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0420] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0421] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0422] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0423] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0424] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0425] This invention is implemented as a next-generation wearable device for acquiring, analyzing, and presenting visual and auditory data. This device has the function of instantly acquiring and presenting necessary information without obstructing the individual user's field of vision.

[0426] Specifically, when a user wears a glasses-type device, the device acquires visual information of the surroundings using a camera and collects ambient sounds using a microphone. This acquired data is transmitted to a server in real time.

[0427] The server analyzes the received data using a high-performance AI model. For example, if a user is viewing a historical building, the server recognizes the image and retrieves relevant historical data and tourist information from its database. The analyzed information is generated in a format that the user can immediately understand.

[0428] The terminal displays important information received from the server overlaid on one of its visual display units. This allows the user to view the information without restricting their field of vision. Furthermore, the information can be read aloud as needed, allowing the user to perceive the information as well.

[0429] Furthermore, when a user encounters signs or directions from overseas, the device retrieves the text information and processes it on a server for translation. The translated result is then sent back to the device, allowing the user to receive the information in an easily understandable format.

[0430] This invention aims to reduce information gathering during tourist visits and language barriers during overseas travel, and to enable users to acquire and utilize information hands-free in their daily lives. In particular, it is expected to dramatically improve users' work efficiency.

[0431] The following describes the processing flow.

[0432] Step 1:

[0433] The device powers on and begins continuously acquiring video data within its field of view via its camera. It also collects ambient audio through its microphone. This prepares the device to accumulate data about the user's viewing environment in real time.

[0434] Step 2:

[0435] The terminal transmits acquired video and audio data to the server in real time. This transmission is carried out through a secure communication protocol, ensuring data integrity and security.

[0436] Step 3:

[0437] The server analyzes the received data using an AI model. For video data, an object recognition algorithm is used to identify objects within the field of view, and for audio data, speech recognition technology is used to convert it into text.

[0438] Step 4:

[0439] The server retrieves relevant information from the database based on the analysis results. This includes descriptions and background information related to the identified object, as well as translations of any text found. The resulting information is then formatted appropriately for the user, and an information packet is generated.

[0440] Step 5:

[0441] The server sends information packets it has generated to the terminal. The terminal then uses overlay display technology to overlay the received information onto one of its visual display units, providing the information without obstructing the user's view.

[0442] Step 6:

[0443] Users can use the voice output function as needed to obtain information audibly through voice guidance from their device. This allows users to utilize information from both visual and auditory perspectives.

[0444] Step 7:

[0445] Once users have finished reviewing the information, they may enter feedback into their terminal, which is then sent to the server to contribute to system improvements. This helps to improve the accuracy of the system.

[0446] (Example 1)

[0447] Next, we will describe Example 1. 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."

[0448] Modern information gathering methods make it difficult for individual users to obtain information quickly and accurately in different environments. Furthermore, language differences and the sheer volume of information can make it time-consuming and laborious for users to utilize it effectively. Therefore, there is a need for systems that allow users to acquire information intuitively and efficiently, and to comfortably utilize information even in multicultural and multilingual environments.

[0449] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0450] In this invention, the server includes means for transmitting acquired video and audio data to a remote information processing device, means for analyzing the video and audio data using a large-scale learning model, and means for generating relevant information based on the analyzed data. This enables users to quickly acquire information appropriate to their environment in real time and to instantly understand information in different languages.

[0451] "Video data" refers to visual information acquired by cameras and other visual recording devices.

[0452] "Audio data" refers to auditory information acquired by microphones or other sound recording devices.

[0453] "Means of acquisition" refers to mechanisms or methods for electronically collecting specific data from the real world.

[0454] A "remote information processing device" refers to a computer system connected via a network for the purpose of receiving, analyzing, and processing data.

[0455] A "large-scale learning model" refers to an AI technology that uses machine learning algorithms to analyze complex patterns and features based on large amounts of data.

[0456] "Means of analysis" refers to the methods and processes used to process received data and extract meaningful information.

[0457] "Means of generating relevant information" refers to methods and processes for generating information useful to users based on analyzed data.

[0458] A "visual display device" refers to a display or projector used to visually present electronically generated information to a user.

[0459] "Means for presenting translation results" refers to methods or mechanisms for presenting translated information to the user visually or audibly.

[0460] This invention is a system for users to instantly acquire and analyze information about their surroundings through a glasses-type wearable device. When a user wears this device, the terminal uses a camera to acquire video data of the surroundings and a microphone to collect audio data. This data is transmitted in real time to a server, which is a remote information processing device.

[0461] The server analyzes the acquired video and audio data using high-performance, large-scale learning models. For example, a convolutional neural network (CNN) is used to analyze video data, and a natural language processing model is used to analyze audio data. This analysis generates relevant information tailored to the user's situation.

[0462] The generated information is overlaid on a visual display device in a user-friendly format. The display device is integrated into the clear lenses of the glasses and is designed not to obstruct the user's vision. Furthermore, the generated information is provided to the user via audio output as needed.

[0463] When a user encounters a sign or notice in a foreign language, the device retrieves the text information, which is then translated in real time by a server. The translated result is immediately presented to the user, removing information barriers in cross-cultural and cross-linguistic environments. In this process, the system operates quickly when the user enters a prompt such as, "Translate the content of this sign."

[0464] This invention aims to support users in easily utilizing information in everyday life and travel situations, and to significantly improve work efficiency.

[0465] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0466] Step 1:

[0467] The device, worn by the user as a pair of glasses, acquires ambient video data via a camera and simultaneously collects audio data via a microphone. The input is the user's visual and auditory environmental information, and the output is digital video and audio data. This data is acquired in real time and sent to the next processing step.

[0468] Step 2:

[0469] The terminal transmits the acquired video and audio data to the server. A fast and reliable communication protocol (e.g., HTTP / 2 or WebSocket) is used for this transmission. The input is the digital data generated in step 1, and the output is the raw data provided to the server.

[0470] Step 3:

[0471] The server processes the received video data using a convolutional neural network (CNN) to analyze its content. Audio data is converted to text using a natural language processing model. The input is the video and audio data sent in step 2, and the output is the analyzed visual and auditory information.

[0472] Step 4:

[0473] The server generates relevant information based on the analysis results using a large-scale learning model. For example, it retrieves detailed information about objects recognized from visual data from a database. The input is the analysis results obtained in step 3, and the output is information formatted in a way that is useful to the user.

[0474] Step 5:

[0475] The terminal overlays the generated information onto the user's glasses' visual display. This display is laid out so as not to obstruct the user's field of vision. Information can also be provided as audio. The input is the information obtained in step 4, and the output is the visual and auditory information presented to the user.

[0476] Step 6:

[0477] When a user recognizes a foreign sign or notice, the device acquires the text information and sends it to the server. The server receives the translation prompt and performs a real-time translation. The input is the text information the user sees, and the output is the translated content. The translation result is immediately sent back to the device and presented to the user.

[0478] (Application Example 1)

[0479] Next, we will explain Application Example 1. In the following explanation, 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."

[0480] Conventional wearable devices have struggled to provide timely and appropriate visual and auditory information for everyday use, and have failed to improve the user experience, particularly in virtual environments for shopping and obtaining product information. Furthermore, the technology for quickly translating foreign language product information and presenting it in an easily understandable way for users has been insufficient.

[0481] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0482] In this invention, the server includes means for acquiring video information, means for acquiring audio information, and means for analyzing the acquired video and audio information. This makes it possible to instantly display detailed information about a product and its translation into a foreign language when a user views a product in a virtual environment using a smart device.

[0483] "Visual information" refers to real-world visual data, including visual content acquired through devices such as cameras.

[0484] "Auditory information" refers to auditory data, including ambient sounds and human speech, which is acquired through devices such as microphones.

[0485] "Means of analysis" refers to methods and techniques for processing acquired video and audio information and extracting meaningful data based on that information.

[0486] "Means of generating data" refers to the methods and technologies used to generate and present information necessary for users based on the results of analysis.

[0487] "Means for recognizing voice commands and performing interactions" refers to technology that enables accurate recognition of voice instructions from users and enables appropriate actions or responses based on those instructions.

[0488] "Displaying information overlaid on a visual display device" refers to a method of displaying digital information superimposed on the physical field of vision, and is a technique also known as overlay display.

[0489] "Translation" refers to the technology of converting acquired audio information into a different language and presenting it in a language format that the user can understand.

[0490] This invention provides a system that displays real-time information about products when a user wears smart glasses-type terminals and views products in a virtual mall. The system is implemented as follows:

[0491] First, the smart glasses acquire video information through their built-in camera. This video information is sent to a server to identify the product the user is viewing. The server uses the acquired video information to perform image recognition processing to identify the product. This process uses the OpenAI API to identify the product and retrieve related information. In addition, voice information is collected by the microphone, and voice commands are recognized via the Google Assistant API, allowing for interaction based on the user's instructions.

[0492] The obtained product information and recommended products are overlaid on the visual display using AR.js and presented directly in the user's field of view. This allows users to obtain additional information without obstructing their real-world vision. Furthermore, product information displayed in foreign languages ​​such as English is translated and presented to the user in their native language.

[0493] As a concrete example, when a user selects a dress in a fashion store within a virtual mall, smart glasses identify the dress and display information including price and reviews. When the user gives a voice command such as "Add this dress to cart," the system recognizes the instruction and performs the necessary action.

[0494] Examples of prompts to input into a generative AI model:

[0495] "Identify the product from the following images and retrieve and display the relevant market data, pricing information, and reviews for that product."

[0496] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0497] Step 1:

[0498] The device acquires surrounding video information using its camera. This acquired video information is used to clarify specific products or objects that the user is viewing. The input is real-world video, and the output is digitized visual data.

[0499] Step 2:

[0500] The device acquires voice information using a microphone. This voice information is primarily used to recognize the user's voice commands. The input is the user's voice, and the output is digitized voice data.

[0501] Step 3:

[0502] The terminal transmits the acquired video information to the server. By transferring the video data, it is used as input for further processing. The output triggers video analysis by the server.

[0503] Step 4:

[0504] The server processes the received video information using an AI model to identify products. This process utilizes the OpenAI API, which matches the data against a product database to identify the product. The input is digitized video data, and the output is the recognized product information.

[0505] Step 5:

[0506] The server retrieves relevant detailed data (e.g., price, reviews, inventory information) from the database based on the product information. The input is the recognized product information, and the output is a set of detailed data.

[0507] Step 6:

[0508] The server translates the retrieved information and converts it to the user's language if translation is required. The input is additional information (sometimes in a foreign language), and the output is the translated information.

[0509] Step 7:

[0510] The server sends the generated information to the terminal, which then displays that information as an overlay on its visual display device. AR.js is used here. The input is the translated additional information, and the output is a visual overlay displayed in the user's field of view.

[0511] Step 8:

[0512] The device uses the Google Assistant API to analyze acquired voice information and execute instructions based on the user's voice commands. The input is digitized voice data, and the output is an action within the system (e.g., executing the command "add to cart").

[0513] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0514] This invention is implemented as a next-generation wearable device that combines the ability to recognize user emotions and optimize information delivery based on those emotions. Its distinguishing feature is that it not only acquires and displays information, but also understands the user's emotional state and provides personalized information and interaction.

[0515] Specifically, when a user wears a glasses-type device, the device not only simply acquires video and ambient audio from the user's field of vision, but also has the function of analyzing the user's facial expressions from the video data. This data is transmitted to a server in real time and scrutinized by an emotion engine.

[0516] The server uses an emotion engine to analyze facial expressions and tone of voice to estimate the user's emotional state. For example, if the server determines that the user is excited about something, it will provide more relevant details. Conversely, when the user is calm, the server will adjust to present a deeper analysis.

[0517] This information is transmitted from the server to the terminal, just like with regular information delivery. The terminal then overlays this information on one of its visual display units. This method allows the user to access the necessary information without their field of vision being obstructed.

[0518] Furthermore, the acquired audio data is translated in real time, and the translation results may be filtered according to the user's emotions. In situations where the user is feeling stressed, the system can present translation results that focus on important context.

[0519] In this way, by dynamically changing the method of information delivery according to the user's current emotions, a more intuitive and natural interaction is achieved. This invention allows users to easily obtain a more personalized experience and promotes the optimal use of information according to the situation.

[0520] The following describes the processing flow.

[0521] Step 1:

[0522] The device starts up and simultaneously acquires video data from the user's field of view and audio data from the surroundings. The camera captures the scenery in front of the user, and the microphone captures the audio environment.

[0523] Step 2:

[0524] The device sends the acquired video data to the server. This video data includes frame information for recognizing facial expressions.

[0525] Step 3:

[0526] The server receives video data and analyzes the user's facial expressions using a facial recognition algorithm. It extracts facial expression data such as smiles, surprise, and pessimism to determine the user's emotional state.

[0527] Step 4:

[0528] The audio data is sent to a server, which uses speech recognition technology to convert it into text. Furthermore, an emotion engine is used to supplement the user's emotional state based on the tone and speed of the speech.

[0529] Step 5:

[0530] The server generates information to provide to the user based on the emotional information it analyzes. For example, if the user is excited, it prioritizes generating relevant entertainment information.

[0531] Step 6:

[0532] The generated information is overlaid on one of the terminal's visual display units. The user can view this information without their entire field of vision being obstructed.

[0533] Step 7:

[0534] The device will read out voice information as needed. It provides voice guidance optimized for the user's emotional state, offering intuitive and easy-to-understand explanations.

[0535] Step 8:

[0536] When a user provides feedback on the information, the device collects that feedback and sends it to the server. The server then uses this data to improve the overall system.

[0537] (Example 2)

[0538] Next, we will describe Example 2. 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."

[0539] Conventional information delivery systems present only fixed information without considering the user's emotional state, resulting in a limited user experience. Furthermore, they often include a lot of unnecessary visual and auditory information, making it difficult to efficiently provide only the information relevant to the user. This hinders users from making optimal use of information in accordance with their situation and emotions.

[0540] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0541] In this invention, the server includes means for acquiring video information, means for acquiring audio information, means for analyzing the acquired video and audio information, means for estimating the emotional state based on the analysis results, means for generating information according to the estimated emotional state, means for presenting the generated information to the user, means for displaying the information overlaid on a visual device, and means for immediately translating the acquired audio information and presenting the translation result. This enables the provision of information optimized based on the user's emotions, thereby improving the user experience.

[0542] "Visual information" refers to visual data acquired using cameras or other recording devices, including data about the user's surrounding environment and the user's own facial expressions.

[0543] "Audio information" refers to auditory data collected via microphones or other recording devices, including ambient sounds and user speech.

[0544] "Means of analysis" refers to a method or apparatus for processing video and audio information to recognize and extract specific features or patterns from it.

[0545] "Means for estimating emotional state" refers to a technology or device for predicting a user's emotional state based on analyzed video and audio information.

[0546] "Means for generating information" refers to a method or apparatus for creating or selecting information to be provided to a user based on an estimated emotional state.

[0547] "Means of presentation" refers to a method or apparatus for visually or audibly displaying or reproducing generated information to a user.

[0548] "Means of displaying information overlaid on a visual device" refers to a technology for displaying digital information on the screen of a device worn by a user, along with images of the real world that are visible as a background.

[0549] "Means for instantly translating and presenting the translation result" refers to a method or apparatus for rapidly converting audio information into another language and providing the translated content to the user.

[0550] This invention is implemented as a next-generation wearable system that recognizes the user's emotional state in real time and provides personalized information. This system acquires video and audio information via a glasses-type device worn by the user (hereinafter referred to as the "terminal"). The terminal has a built-in high-resolution camera and microphone and collects visual and auditory data through the user's activities.

[0551] The terminal uses highly accurate facial recognition software to analyze video information. For example, a common face recognition framework (e.g., OpenCV or Dlib) may be used. This allows the system to capture the user's facial feature points and make an initial determination of their emotional state. The acquired video and audio information is transmitted to the server via wireless communication.

[0552] The server uses the incoming data to perform a detailed analysis of the user's emotional state using a generative AI model (e.g., an emotion analysis model based on TensorFlow or PyTorch). The server analyzes facial expressions and voice tone and generates corresponding emotion tags. Based on the analysis results, it also constructs optimized information using the generative means and sends it back to the terminal.

[0553] The terminal displays selected information as an overlay through hardware that overlays information sent from the server onto the user's field of view. This allows the user to view the necessary information without being visually obstructed by their surroundings.

[0554] As a concrete example, consider a scenario where a user visits a foreign tourist destination and obtains information. While the user views the tourist attraction through a glasses-type device, the device sends the image to a server, which performs emotion recognition. If the server determines that the user is showing an expression of admiration, it selects and provides detailed information about that tourist destination. Furthermore, if translation of surrounding audio information is necessary, the server instantly translates the audio information, filters the results on the device, and presents them to the user.

[0555] As an example of a prompt, if the user shows an excited expression towards a specific tourist destination, design an AI model that prioritizes and provides relevant information. By supplying this to the generating AI model, a more intuitive and personalized information delivery can be achieved.

[0556] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0557] Step 1:

[0558] When a user wears a glasses-type device, the terminal captures surrounding video and audio information. Its inputs include video data captured by a high-resolution camera and audio data recorded by a microphone. Specifically, the terminal collects this data in real time and immediately prepares to send it to a server.

[0559] Step 2:

[0560] The device analyzes collected video data using facial recognition software. The input is video data from the camera, and the output includes analyzed user facial features and preliminary emotion estimations. The operation involves using a general-purpose library like OpenCV to detect facial feature points and determine the initial emotional state (joy, anger, sadness, etc.).

[0561] Step 3:

[0562] The server receives analyzed video and audio data transmitted from the terminal. The input consists of feature point information and audio data, and the output is emotion tags that represent the user's detailed emotional state. The server uses a generative AI model to analyze subtle changes in facial expressions and voice tone, and the emotion engine precisely estimates the emotional state.

[0563] Step 4:

[0564] The server generates user-specific information based on estimated emotions. The input is emotion tags, and the output is customized informational content. Specifically, it selects the most relevant information from a set of emotion-based content and sends it to the device in a structured format.

[0565] Step 5:

[0566] The terminal displays information received from the server as an overlay on the user's field of view. The input is information content from the server, and the output is the information displayed on the user's field of view. Specifically, it overlays information onto the visual device through an application, allowing the user to obtain information while observing the actual environment.

[0567] Step 6:

[0568] The server translates audio data in real time and sends the results to the terminal. The input is audio data, and the output is translated text or audio. Specifically, it uses a language understanding library to convert the audio into another language, filters out important information, and provides it to the terminal in a format optimized for the user's situation.

[0569] (Application Example 2)

[0570] Next, we will explain application example 2. In the following explanation, 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."

[0571] Current information delivery systems provide information uniformly without considering the user's emotional state, making it difficult to present information optimized for individual user situations and moods. Furthermore, in online shopping, it's difficult to adjust and optimize product information according to the user's interests and emotions, thus hindering customer satisfaction. In this context, there is a need for technology that can recognize user emotions in real time and efficiently provide personalized information based on those emotions.

[0572] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0573] In this invention, the server includes a device for acquiring video data, a device for acquiring audio data, and a device for generating information based on the analysis results. This makes it possible to provide information based on the user's emotional state.

[0574] "Video data" refers to visually captured data used to obtain the user's facial expressions and movements.

[0575] "Voice data" refers to acoustic data collected to record the user's voice and surrounding sounds.

[0576] "Device" refers to hardware or software used to perform a specific function or process.

[0577] "Analysis" is the process of processing acquired data to estimate the emotional state of the user.

[0578] "Emotional state" refers to the user's current emotional and mood state.

[0579] An "information generating device" is a processing device that creates personalized information for users based on analyzed data.

[0580] "User" refers to an individual who uses the system to obtain information.

[0581] A "virtual commerce space" is an online marketplace where users can browse and purchase goods in a digital environment.

[0582] "Product information" refers to information that includes details and specifications related to a product or service.

[0583] A "visual display device" is a display device used to present visual information to a user.

[0584] To realize this invention, a glasses-type device worn by the user, a server, and a terminal that manages the virtual trading space must work together in coordination. First, the user uses the glasses-type device to acquire visual and audio data in real time. This data is transferred to the server via the internet. The server analyzes the user's facial expressions by using image recognition software, such as "Google Cloud AutoML Vision API" or "Amazon Rekognition," to process the visual data. It also applies speech recognition technology to the audio data to analyze the user's voice tone and keywords.

[0585] The server uses these analysis results to generate appropriate product or promotional information, employing a generative AI model that estimates the user's emotional state. This information is transmitted to a terminal managing the virtual commerce space and displayed on the user's glasses-type device in a form adjusted based on the user's emotions. At this time, relevant product information is overlaid on the visual display device, allowing the user to view the information without obstructing their vision.

[0586] For example, if the server determines that a user is excited by a particular product while exploring a virtual shopping space, that product will be highlighted, and promotional prices and detailed information about related products will be displayed in vivid colors. This allows users to enjoy a shopping experience that matches their emotions.

[0587] An example of a prompt message is: "Create a prompt message that analyzes the user's emotions from their facial expressions and voice, and generates product information that matches those emotions."

[0588] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0589] Step 1:

[0590] The system collects video and audio data from a device that captures the user's visual and audio data in real time while the user wears glasses. This provides basic data for recording the user's facial expressions and voice.

[0591] Step 2:

[0592] The user's glasses-type device transfers the collected video and audio data to the server. The server receives this data and prepares it for processing. It receives video and audio data as input and stores it in an analyzable format.

[0593] Step 3:

[0594] The server performs facial recognition on the video data using image recognition software. Specifically, it extracts emotional features from the user's facial expressions using tools such as the "Google Cloud AutoML Vision API." As a result of the data processing, an emotion index, such as smiles or surprise, is generated. The output is the emotion index.

[0595] Step 4:

[0596] The server processes audio data using speech recognition technology, analyzing voice tone and keywords. The user's voice tone and specific phrases are associated with their emotional state. Audio data is used as input, and the audio analysis results are obtained as output.

[0597] Step 5:

[0598] The server integrates the emotion index obtained in steps 3 and 4 with the voice analysis results and uses a generative AI model to estimate the user's emotional state. This performs data calculations to accurately identify the user's current emotions. The output is the emotional state.

[0599] Step 6:

[0600] The server generates appropriate product information within the virtual trading space based on the estimated emotional state of the user. Since the product information is customized according to the emotion, the input is the emotional state, and the output is customized product information.

[0601] Step 7:

[0602] The terminal overlays customized product information received from the server onto the user's glasses-type device. Specifically, it superimposes the necessary visual information onto one of the visual display devices. This allows the user to view product information that is relevant to their emotional state.

[0603] Step 8:

[0604] Users enjoy a shopping experience in a virtual commerce space based on the displayed product information. This enables interactions that are tailored to the user's emotions.

[0605] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0606] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0607] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0608] [Fourth Embodiment]

[0609] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0610] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0611] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0612] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0613] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0614] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0615] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0616] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0617] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0618] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0619] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0620] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0621] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0622] This invention is implemented as a next-generation wearable device for acquiring, analyzing, and presenting visual and auditory data. This device has the function of instantly acquiring and presenting necessary information without obstructing the individual user's field of vision.

[0623] Specifically, when a user wears a glasses-type device, the device acquires visual information of the surroundings using a camera and collects ambient sounds using a microphone. This acquired data is transmitted to a server in real time.

[0624] The server analyzes the received data using a high-performance AI model. For example, if a user is viewing a historical building, the server recognizes the image and retrieves relevant historical data and tourist information from its database. The analyzed information is generated in a format that the user can immediately understand.

[0625] The terminal displays important information received from the server overlaid on one of its visual display units. This allows the user to view the information without restricting their field of vision. Furthermore, the information can be read aloud as needed, allowing the user to perceive the information as well.

[0626] Furthermore, when a user encounters signs or directions from overseas, the device retrieves the text information and processes it on a server for translation. The translated result is then sent back to the device, allowing the user to receive the information in an easily understandable format.

[0627] This invention aims to reduce information gathering during tourist visits and language barriers during overseas travel, and to enable users to acquire and utilize information hands-free in their daily lives. In particular, it is expected to dramatically improve users' work efficiency.

[0628] The following describes the processing flow.

[0629] Step 1:

[0630] The device powers on and begins continuously acquiring video data within its field of view via its camera. It also collects ambient audio through its microphone. This prepares the device to accumulate data about the user's viewing environment in real time.

[0631] Step 2:

[0632] The terminal transmits acquired video and audio data to the server in real time. This transmission is carried out through a secure communication protocol, ensuring data integrity and security.

[0633] Step 3:

[0634] The server analyzes the received data using an AI model. For video data, an object recognition algorithm is used to identify objects within the field of view, and for audio data, speech recognition technology is used to convert it into text.

[0635] Step 4:

[0636] The server retrieves relevant information from the database based on the analysis results. This includes descriptions and background information related to the identified object, as well as translations of any text found. The resulting information is then formatted appropriately for the user, and an information packet is generated.

[0637] Step 5:

[0638] The server sends information packets it has generated to the terminal. The terminal then uses overlay display technology to overlay the received information onto one of its visual display units, providing the information without obstructing the user's view.

[0639] Step 6:

[0640] Users can use the voice output function as needed to obtain information audibly through voice guidance from their device. This allows users to utilize information from both visual and auditory perspectives.

[0641] Step 7:

[0642] Once users have finished reviewing the information, they may enter feedback into their terminal, which is then sent to the server to contribute to system improvements. This helps to improve the accuracy of the system.

[0643] (Example 1)

[0644] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0645] Modern information gathering methods make it difficult for individual users to obtain information quickly and accurately in different environments. Furthermore, language differences and the sheer volume of information can make it time-consuming and laborious for users to utilize it effectively. Therefore, there is a need for systems that allow users to acquire information intuitively and efficiently, and to comfortably utilize information even in multicultural and multilingual environments.

[0646] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0647] In this invention, the server includes means for transmitting acquired video and audio data to a remote information processing device, means for analyzing the video and audio data using a large-scale learning model, and means for generating relevant information based on the analyzed data. This enables users to quickly acquire information appropriate to their environment in real time and to instantly understand information in different languages.

[0648] "Video data" refers to visual information acquired by cameras and other visual recording devices.

[0649] "Audio data" refers to auditory information acquired by microphones or other sound recording devices.

[0650] "Means of acquisition" refers to mechanisms or methods for electronically collecting specific data from the real world.

[0651] A "remote information processing device" refers to a computer system connected via a network for the purpose of receiving, analyzing, and processing data.

[0652] A "large-scale learning model" refers to an AI technology that uses machine learning algorithms to analyze complex patterns and features based on large amounts of data.

[0653] "Means of analysis" refers to the methods and processes used to process received data and extract meaningful information.

[0654] "Means of generating relevant information" refers to methods and processes for generating information useful to users based on analyzed data.

[0655] A "visual display device" refers to a display or projector used to visually present electronically generated information to a user.

[0656] "Means for presenting translation results" refers to methods or mechanisms for presenting translated information to the user visually or audibly.

[0657] This invention is a system for users to instantly acquire and analyze information about their surroundings through a glasses-type wearable device. When a user wears this device, the terminal uses a camera to acquire video data of the surroundings and a microphone to collect audio data. This data is transmitted in real time to a server, which is a remote information processing device.

[0658] The server analyzes the acquired video and audio data using high-performance, large-scale learning models. For example, a convolutional neural network (CNN) is used to analyze video data, and a natural language processing model is used to analyze audio data. This analysis generates relevant information tailored to the user's situation.

[0659] The generated information is overlaid on a visual display device in a user-friendly format. The display device is integrated into the clear lenses of the glasses and is designed not to obstruct the user's vision. Furthermore, the generated information is provided to the user via audio output as needed.

[0660] When a user encounters a sign or notice in a foreign language, the device retrieves the text information, which is then translated in real time by a server. The translated result is immediately presented to the user, removing information barriers in cross-cultural and cross-linguistic environments. In this process, the system operates quickly when the user enters a prompt such as, "Translate the content of this sign."

[0661] This invention aims to support users in easily utilizing information in everyday life and travel situations, and to significantly improve work efficiency.

[0662] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0663] Step 1:

[0664] The device, worn by the user as a pair of glasses, acquires ambient video data via a camera and simultaneously collects audio data via a microphone. The input is the user's visual and auditory environmental information, and the output is digital video and audio data. This data is acquired in real time and sent to the next processing step.

[0665] Step 2:

[0666] The terminal transmits the acquired video and audio data to the server. A fast and reliable communication protocol (e.g., HTTP / 2 or WebSocket) is used for this transmission. The input is the digital data generated in step 1, and the output is the raw data provided to the server.

[0667] Step 3:

[0668] The server processes the received video data using a convolutional neural network (CNN) to analyze its content. Audio data is converted to text using a natural language processing model. The input is the video and audio data sent in step 2, and the output is the analyzed visual and auditory information.

[0669] Step 4:

[0670] The server generates relevant information based on the analysis results using a large-scale learning model. For example, it retrieves detailed information about objects recognized from visual data from a database. The input is the analysis results obtained in step 3, and the output is information formatted in a way that is useful to the user.

[0671] Step 5:

[0672] The terminal overlays the generated information onto the user's glasses' visual display. This display is laid out so as not to obstruct the user's field of vision. Information can also be provided as audio. The input is the information obtained in step 4, and the output is the visual and auditory information presented to the user.

[0673] Step 6:

[0674] When a user recognizes a foreign sign or notice, the device acquires the text information and sends it to the server. The server receives the translation prompt and performs a real-time translation. The input is the text information the user sees, and the output is the translated content. The translation result is immediately sent back to the device and presented to the user.

[0675] (Application Example 1)

[0676] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0677] Conventional wearable devices have struggled to provide timely and appropriate visual and auditory information for everyday use, and have failed to improve the user experience, particularly in virtual environments for shopping and obtaining product information. Furthermore, the technology for quickly translating foreign language product information and presenting it in an easily understandable way for users has been insufficient.

[0678] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0679] In this invention, the server includes means for acquiring video information, means for acquiring audio information, and means for analyzing the acquired video and audio information. This makes it possible to instantly display detailed information about a product and its translation into a foreign language when a user views a product in a virtual environment using a smart device.

[0680] "Visual information" refers to real-world visual data, including visual content acquired through devices such as cameras.

[0681] "Auditory information" refers to auditory data, including ambient sounds and human speech, which is acquired through devices such as microphones.

[0682] "Means of analysis" refers to methods and techniques for processing acquired video and audio information and extracting meaningful data based on that information.

[0683] "Means of generating data" refers to the methods and technologies used to generate and present information necessary for users based on the results of analysis.

[0684] "Means for recognizing voice commands and performing interactions" refers to technology that enables accurate recognition of voice instructions from users and enables appropriate actions or responses based on those instructions.

[0685] "Displaying information overlaid on a visual display device" refers to a method of displaying digital information superimposed on the physical field of vision, and is a technique also known as overlay display.

[0686] "Translation" refers to the technology of converting acquired audio information into a different language and presenting it in a language format that the user can understand.

[0687] This invention provides a system that displays real-time information about products when a user wears smart glasses-type terminals and views products in a virtual mall. The system is implemented as follows:

[0688] First, the smart glasses acquire video information through their built-in camera. This video information is sent to a server to identify the product the user is viewing. The server uses the acquired video information to perform image recognition processing to identify the product. This process uses the OpenAI API to identify the product and retrieve related information. In addition, voice information is collected by the microphone, and voice commands are recognized via the Google Assistant API, allowing for interaction based on the user's instructions.

[0689] The obtained product information and recommended products are overlaid on the visual display using AR.js and presented directly in the user's field of view. This allows users to obtain additional information without obstructing their real-world vision. Furthermore, product information displayed in foreign languages ​​such as English is translated and presented to the user in their native language.

[0690] As a concrete example, when a user selects a dress in a fashion store within a virtual mall, smart glasses identify the dress and display information including price and reviews. When the user gives a voice command such as "Add this dress to cart," the system recognizes the instruction and performs the necessary action.

[0691] Examples of prompts to input into a generative AI model:

[0692] "Identify the product from the following images and retrieve and display the relevant market data, pricing information, and reviews for that product."

[0693] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0694] Step 1:

[0695] The device acquires surrounding video information using its camera. This acquired video information is used to clarify specific products or objects that the user is viewing. The input is real-world video, and the output is digitized visual data.

[0696] Step 2:

[0697] The device acquires voice information using a microphone. This voice information is primarily used to recognize the user's voice commands. The input is the user's voice, and the output is digitized voice data.

[0698] Step 3:

[0699] The terminal transmits the acquired video information to the server. By transferring the video data, it is used as input for further processing. The output triggers video analysis by the server.

[0700] Step 4:

[0701] The server processes the received video information using an AI model to identify products. This process utilizes the OpenAI API, which matches the data against a product database to identify the product. The input is digitized video data, and the output is the recognized product information.

[0702] Step 5:

[0703] The server retrieves relevant detailed data (e.g., price, reviews, inventory information) from the database based on the product information. The input is the recognized product information, and the output is a set of detailed data.

[0704] Step 6:

[0705] The server translates the retrieved information and converts it to the user's language if translation is required. The input is additional information (sometimes in a foreign language), and the output is the translated information.

[0706] Step 7:

[0707] The server sends the generated information to the terminal, which then displays that information as an overlay on its visual display device. AR.js is used here. The input is the translated additional information, and the output is a visual overlay displayed in the user's field of view.

[0708] Step 8:

[0709] The device uses the Google Assistant API to analyze acquired voice information and execute instructions based on the user's voice commands. The input is digitized voice data, and the output is an action within the system (e.g., executing the command "add to cart").

[0710] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0711] This invention is implemented as a next-generation wearable device that combines the ability to recognize user emotions and optimize information delivery based on those emotions. Its distinguishing feature is that it not only acquires and displays information, but also understands the user's emotional state and provides personalized information and interaction.

[0712] Specifically, when a user wears a glasses-type device, the device not only simply acquires video and ambient audio from the user's field of vision, but also has the function of analyzing the user's facial expressions from the video data. This data is transmitted to a server in real time and scrutinized by an emotion engine.

[0713] The server uses an emotion engine to analyze facial expressions and tone of voice to estimate the user's emotional state. For example, if the server determines that the user is excited about something, it will provide more relevant details. Conversely, when the user is calm, the server will adjust to present a deeper analysis.

[0714] This information is transmitted from the server to the terminal, just like with regular information delivery. The terminal then overlays this information on one of its visual display units. This method allows the user to access the necessary information without their field of vision being obstructed.

[0715] Furthermore, the acquired audio data is translated in real time, and the translation results may be filtered according to the user's emotions. In situations where the user is feeling stressed, the system can present translation results that focus on important context.

[0716] In this way, by dynamically changing the method of information delivery according to the user's current emotions, a more intuitive and natural interaction is achieved. This invention allows users to easily obtain a more personalized experience and promotes the optimal use of information according to the situation.

[0717] The following describes the processing flow.

[0718] Step 1:

[0719] The device starts up and simultaneously acquires video data from the user's field of view and audio data from the surroundings. The camera captures the scenery in front of the user, and the microphone captures the audio environment.

[0720] Step 2:

[0721] The device sends the acquired video data to the server. This video data includes frame information for recognizing facial expressions.

[0722] Step 3:

[0723] The server receives video data and analyzes the user's facial expressions using a facial recognition algorithm. It extracts facial expression data such as smiles, surprise, and pessimism to determine the user's emotional state.

[0724] Step 4:

[0725] The audio data is sent to a server, which uses speech recognition technology to convert it into text. Furthermore, an emotion engine is used to supplement the user's emotional state based on the tone and speed of the speech.

[0726] Step 5:

[0727] The server generates information to provide to the user based on the emotional information it analyzes. For example, if the user is excited, it prioritizes generating relevant entertainment information.

[0728] Step 6:

[0729] The generated information is overlaid on one of the terminal's visual display units. The user can view this information without their entire field of vision being obstructed.

[0730] Step 7:

[0731] The device will read out voice information as needed. It provides voice guidance optimized for the user's emotional state, offering intuitive and easy-to-understand explanations.

[0732] Step 8:

[0733] When a user provides feedback on the information, the device collects that feedback and sends it to the server. The server then uses this data to improve the overall system.

[0734] (Example 2)

[0735] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0736] Conventional information delivery systems present only fixed information without considering the user's emotional state, resulting in a limited user experience. Furthermore, they often include a lot of unnecessary visual and auditory information, making it difficult to efficiently provide only the information relevant to the user. This hinders users from making optimal use of information in accordance with their situation and emotions.

[0737] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0738] In this invention, the server includes means for acquiring video information, means for acquiring audio information, means for analyzing the acquired video and audio information, means for estimating the emotional state based on the analysis results, means for generating information according to the estimated emotional state, means for presenting the generated information to the user, means for displaying the information overlaid on a visual device, and means for immediately translating the acquired audio information and presenting the translation result. This enables the provision of information optimized based on the user's emotions, thereby improving the user experience.

[0739] "Visual information" refers to visual data acquired using cameras or other recording devices, including data about the user's surrounding environment and the user's own facial expressions.

[0740] "Audio information" refers to auditory data collected via microphones or other recording devices, including ambient sounds and user speech.

[0741] "Means of analysis" refers to a method or apparatus for processing video and audio information to recognize and extract specific features or patterns from it.

[0742] "Means for estimating emotional state" refers to a technology or device for predicting a user's emotional state based on analyzed video and audio information.

[0743] "Means for generating information" refers to a method or apparatus for creating or selecting information to be provided to a user based on an estimated emotional state.

[0744] "Means of presentation" refers to a method or apparatus for visually or audibly displaying or reproducing generated information to a user.

[0745] "Means of displaying information overlaid on a visual device" refers to a technology for displaying digital information on the screen of a device worn by a user, along with images of the real world that are visible as a background.

[0746] "Means for instantly translating and presenting the translation result" refers to a method or apparatus for rapidly converting audio information into another language and providing the translated content to the user.

[0747] This invention is implemented as a next-generation wearable system that recognizes the user's emotional state in real time and provides personalized information. This system acquires video and audio information via a glasses-type device worn by the user (hereinafter referred to as the "terminal"). The terminal has a built-in high-resolution camera and microphone and collects visual and auditory data through the user's activities.

[0748] The terminal uses highly accurate facial recognition software to analyze video information. For example, a common face recognition framework (e.g., OpenCV or Dlib) may be used. This allows the system to capture the user's facial feature points and make an initial determination of their emotional state. The acquired video and audio information is transmitted to the server via wireless communication.

[0749] The server uses the incoming data to perform a detailed analysis of the user's emotional state using a generative AI model (e.g., an emotion analysis model based on TensorFlow or PyTorch). The server analyzes facial expressions and voice tone and generates corresponding emotion tags. Based on the analysis results, it also constructs optimized information using the generative means and sends it back to the terminal.

[0750] The terminal displays selected information as an overlay through hardware that overlays information sent from the server onto the user's field of view. This allows the user to view the necessary information without being visually obstructed by their surroundings.

[0751] As a concrete example, consider a scenario where a user visits a foreign tourist destination and obtains information. While the user views the tourist attraction through a glasses-type device, the device sends the image to a server, which performs emotion recognition. If the server determines that the user is showing an expression of admiration, it selects and provides detailed information about that tourist destination. Furthermore, if translation of surrounding audio information is necessary, the server instantly translates the audio information, filters the results on the device, and presents them to the user.

[0752] As an example of a prompt, if the user shows an excited expression towards a specific tourist destination, design an AI model that prioritizes and provides relevant information. By supplying this to the generating AI model, a more intuitive and personalized information delivery can be achieved.

[0753] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0754] Step 1:

[0755] When a user wears a glasses-type device, the terminal captures surrounding video and audio information. Its inputs include video data captured by a high-resolution camera and audio data recorded by a microphone. Specifically, the terminal collects this data in real time and immediately prepares to send it to a server.

[0756] Step 2:

[0757] The device analyzes collected video data using facial recognition software. The input is video data from the camera, and the output includes analyzed user facial features and preliminary emotion estimations. The operation involves using a general-purpose library like OpenCV to detect facial feature points and determine the initial emotional state (joy, anger, sadness, etc.).

[0758] Step 3:

[0759] The server receives analyzed video and audio data transmitted from the terminal. The input consists of feature point information and audio data, and the output is emotion tags that represent the user's detailed emotional state. The server uses a generative AI model to analyze subtle changes in facial expressions and voice tone, and the emotion engine precisely estimates the emotional state.

[0760] Step 4:

[0761] The server generates user-specific information based on estimated emotions. The input is emotion tags, and the output is customized informational content. Specifically, it selects the most relevant information from a set of emotion-based content and sends it to the device in a structured format.

[0762] Step 5:

[0763] The terminal displays information received from the server as an overlay on the user's field of view. The input is information content from the server, and the output is the information displayed on the user's field of view. Specifically, it overlays information onto the visual device through an application, allowing the user to obtain information while observing the actual environment.

[0764] Step 6:

[0765] The server translates audio data in real time and sends the results to the terminal. The input is audio data, and the output is translated text or audio. Specifically, it uses a language understanding library to convert the audio into another language, filters out important information, and provides it to the terminal in a format optimized for the user's situation.

[0766] (Application Example 2)

[0767] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0768] Current information delivery systems provide information uniformly without considering the user's emotional state, making it difficult to present information optimized for individual user situations and moods. Furthermore, in online shopping, it's difficult to adjust and optimize product information according to the user's interests and emotions, thus hindering customer satisfaction. In this context, there is a need for technology that can recognize user emotions in real time and efficiently provide personalized information based on those emotions.

[0769] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0770] In this invention, the server includes a device for acquiring video data, a device for acquiring audio data, and a device for generating information based on the analysis results. This makes it possible to provide information based on the user's emotional state.

[0771] "Video data" refers to visually captured data used to obtain the user's facial expressions and movements.

[0772] "Voice data" refers to acoustic data collected to record the user's voice and surrounding sounds.

[0773] "Device" refers to hardware or software used to perform a specific function or process.

[0774] "Analysis" is the process of processing acquired data to estimate the emotional state of the user.

[0775] "Emotional state" refers to the user's current emotional and mood state.

[0776] An "information generating device" is a processing device that creates personalized information for users based on analyzed data.

[0777] "User" refers to an individual who uses the system to obtain information.

[0778] A "virtual commerce space" is an online marketplace where users can browse and purchase goods in a digital environment.

[0779] "Product information" refers to information that includes details and specifications related to a product or service.

[0780] A "visual display device" is a display device used to present visual information to a user.

[0781] To realize this invention, a glasses-type device worn by the user, a server, and a terminal that manages the virtual trading space must work together in coordination. First, the user uses the glasses-type device to acquire visual and audio data in real time. This data is transferred to the server via the internet. The server analyzes the user's facial expressions by using image recognition software, such as "Google Cloud AutoML Vision API" or "Amazon Rekognition," to process the visual data. It also applies speech recognition technology to the audio data to analyze the user's voice tone and keywords.

[0782] The server uses these analysis results to generate appropriate product or promotional information, employing a generative AI model that estimates the user's emotional state. This information is transmitted to a terminal managing the virtual commerce space and displayed on the user's glasses-type device in a form adjusted based on the user's emotions. At this time, relevant product information is overlaid on the visual display device, allowing the user to view the information without obstructing their vision.

[0783] For example, if the server determines that a user is excited by a particular product while exploring a virtual shopping space, that product will be highlighted, and promotional prices and detailed information about related products will be displayed in vivid colors. This allows users to enjoy a shopping experience that matches their emotions.

[0784] An example of a prompt message is: "Create a prompt message that analyzes the user's emotions from their facial expressions and voice, and generates product information that matches those emotions."

[0785] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0786] Step 1:

[0787] The system collects video and audio data from a device that captures the user's visual and audio data in real time while the user wears glasses. This provides basic data for recording the user's facial expressions and voice.

[0788] Step 2:

[0789] The user's glasses-type device transfers the collected video and audio data to the server. The server receives this data and prepares it for processing. It receives video and audio data as input and stores it in an analyzable format.

[0790] Step 3:

[0791] The server performs facial recognition on the video data using image recognition software. Specifically, it extracts emotional features from the user's facial expressions using tools such as the "Google Cloud AutoML Vision API." As a result of the data processing, an emotion index, such as smiles or surprise, is generated. The output is the emotion index.

[0792] Step 4:

[0793] The server processes audio data using speech recognition technology, analyzing voice tone and keywords. The user's voice tone and specific phrases are associated with their emotional state. Audio data is used as input, and the audio analysis results are obtained as output.

[0794] Step 5:

[0795] The server integrates the emotion index obtained in steps 3 and 4 with the voice analysis results and uses a generative AI model to estimate the user's emotional state. This performs data calculations to accurately identify the user's current emotions. The output is the emotional state.

[0796] Step 6:

[0797] The server generates appropriate product information within the virtual trading space based on the estimated emotional state of the user. Since the product information is customized according to the emotion, the input is the emotional state, and the output is customized product information.

[0798] Step 7:

[0799] The terminal overlays customized product information received from the server onto the user's glasses-type device. Specifically, it superimposes the necessary visual information onto one of the visual display devices. This allows the user to view product information that is relevant to their emotional state.

[0800] Step 8:

[0801] Users enjoy a shopping experience in a virtual commerce space based on the displayed product information. This enables interactions that are tailored to the user's emotions.

[0802] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0803] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0804] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0805] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0806] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0807] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0808] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0809] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0810] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0811] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0812] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0813] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0814] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0815] 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.

[0816] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0817] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0818] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0819] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0820] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0821] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0822] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0823] The following is further disclosed regarding the embodiments described above.

[0824] (Claim 1)

[0825] A means of acquiring video data,

[0826] A means of acquiring audio data,

[0827] An analysis means for analyzing acquired video and audio data,

[0828] A generation means for generating information based on the analysis results,

[0829] A system that includes a means of presenting generated information to the user.

[0830] (Claim 2)

[0831] The system according to claim 1, comprising presentation means for overlaying information onto one of the visual display units.

[0832] (Claim 3)

[0833] The system according to claim 1, comprising translation means for translating acquired audio data in real time and presenting the translation result.

[0834] "Example 1"

[0835] (Claim 1)

[0836] Means of acquiring video data,

[0837] Means for acquiring audio data,

[0838] Means for transmitting acquired video data and audio data to a remote information processing device,

[0839] An information processing device provides a means for analyzing video data and audio data using a large-scale learning model,

[0840] Means for generating relevant information based on analyzed data,

[0841] A system that includes means for presenting generated information to users.

[0842] (Claim 2)

[0843] The system according to claim 1, comprising means for overlaying information onto a visual display device.

[0844] (Claim 3)

[0845] The system according to claim 1, comprising means for translating acquired text data in real time and presenting the translation result.

[0846] "Application Example 1"

[0847] (Claim 1)

[0848] Means for acquiring video information,

[0849] Means for acquiring audio information,

[0850] A means for analyzing acquired video and audio information,

[0851] A means of generating data based on the analysis results,

[0852] A means of presenting the generated data to the user,

[0853] A system that includes means for recognizing voice commands and performing interactions.

[0854] (Claim 2)

[0855] The system according to claim 1, wherein information is superimposed and displayed on one side of a visual display device.

[0856] (Claim 3)

[0857] The system according to claim 1, which immediately translates acquired audio information and presents the translation result.

[0858] "Example 2 of combining an emotion engine"

[0859] (Claim 1)

[0860] Means for acquiring video information,

[0861] Means for acquiring audio information,

[0862] A means for analyzing acquired video and audio information,

[0863] A means of estimating emotional states based on the results of the analysis,

[0864] A means for generating information according to an estimated emotional state,

[0865] A system that includes means for presenting generated information to users.

[0866] (Claim 2)

[0867] The system according to claim 1, comprising means for displaying information superimposed on a visual device.

[0868] (Claim 3)

[0869] The system according to claim 1, comprising means for immediately translating acquired audio information and presenting the translation result.

[0870] "Application example 2 when combining with an emotional engine"

[0871] (Claim 1)

[0872] A device for acquiring video data,

[0873] A device for acquiring audio data,

[0874] A device for analyzing acquired video and audio data,

[0875] A device that generates information based on analysis results,

[0876] A device that presents generated information to the user,

[0877] A device that personalizes information based on the user's emotional state,

[0878] A system including a device that presents emotionally-adjusted product information in a virtual commercial space.

[0879] (Claim 2)

[0880] The system according to claim 1, wherein information is overlaid on one of the visual display devices.

[0881] (Claim 3)

[0882] The system according to claim 1, comprising a device that translates acquired audio data in real time and presents the translation result. [Explanation of symbols]

[0883] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of acquiring video data, A means of acquiring audio data, An analysis means for analyzing acquired video and audio data, A generation means for generating information based on the analysis results, A system that includes a means of presenting generated information to the user.

2. The system according to claim 1, comprising presentation means for overlaying information onto one of the visual display units.

3. The system according to claim 1, comprising translation means for translating acquired audio data in real time and presenting the translation result.

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