System

Abstract

A system is provided.SOLUTION: A system comprising: means for obtaining ambient visual information using a high-resolution camera; means for obtaining ambient audio information using a microphone; means for analyzing the obtained visual information and extracting textual information; means for translating the obtained textual information into a desired foreign language using speech recognition technology; means for displaying the translated textual information using augmented reality technology; and speech synthesis means for reproducing the translated audio information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In today's world, studying abroad is considered the most effective way to learn a foreign language. However, various barriers exist, including financial reasons, family circumstances, the safety of the destination, and food issues, making studying abroad not easy for everyone. In particular, the practical learning experience gained by actually immersing oneself in a foreign language environment is difficult to achieve through traditional classroom or online learning. Furthermore, there are limited means of efficiently learning a foreign language while remaining in Japan. There is a need to solve these issues and provide a method that allows anyone to easily experience a foreign language environment. [Means for solving the problem]

[0005] The present invention provides a "language conversion mask" that allows users to experience a foreign language environment while in Japan. The mask uses a high-resolution camera and microphone to capture surrounding visual and audio information and transmits it to a server in real time. At the server, text information is extracted from the visual information using OCR technology, and audio information is converted into text using speech recognition technology. The extracted and converted text information is then translated into any foreign language. The translated text information is displayed in the user's field of view using augmented reality technology, and the translated audio information is played back to the user using speech synthesis technology. Users can also change the target language and adjust settings through the interface. This allows users to immerse themselves in a foreign language environment in their daily lives without having to study abroad, enabling them to efficiently learn a foreign language.

[0006] A "high-resolution camera" is a camera that has the ability to capture high-definition images, and is a device that enables detailed analysis of visual information.

[0007] A "microphone" is a device that converts sound into an electrical signal and is a means for acquiring surrounding audio information.

[0008] "Visual information" refers to image data and video data acquired by a camera, including textual information present in the surrounding environment.

[0009] "Audio information" refers to audio data acquired by a microphone, including surrounding conversations and sounds.

[0010] "OCR (Optical Character Recognition) technology" is a technology that recognizes character information in an image and converts it into text data.

[0011] "Voice recognition technology" is a technology that analyzes voice information and converts it into text data.

[0012] "Text information" refers to character data, and is information extracted or converted using OCR or voice recognition technology.

[0013] "Foreign language" refers to a language that is not the user's native language and is used in another country or region.

[0014] "Translation" is the process of converting textual information from one language into another.

[0015] "Augmented reality (AR) technology" is a technology that displays digital information overlaid on real-world images.

[0016] "TTS (Text-to-Speech) technology" is a technology that converts text data into speech.

[0017] A "server" is a computer system that receives data sent from a terminal and performs analysis and translation processing.

[0018] A "terminal" is a part of the mask worn by the user, and is a device that includes hardware such as a camera, microphone, display, and headphones.

[0019] "User" refers to a person who wears and uses the "language conversion mask."

[0020] An "interface" is something that provides a user with an operating means for changing system settings.

[0021] "Real-time" refers to a state in which processing is carried out almost simultaneously and information is updated without delay. [Brief explanation of the drawings]

[0022] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0023] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0024] First, the terms used in the following description will be explained.

[0025] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0026] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0027] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0028] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0029] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0030] [First embodiment]

[0031] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0032] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0033] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0034] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0035] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0036] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0037] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0038] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0039] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0040] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0041] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0042] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0043] This invention is a system that allows users to experience a foreign language environment while in Japan using a "language conversion mask." The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, and a user interface.

[0044] 1. Hardware Configuration

[0045] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, and headphones. The device transmits the acquired information to a server in real time.

[0046] Server: An advanced computer system that analyzes and translates the visual and audio information sent from the device. The server processes the information using OCR and speech recognition technology and sends the translation results back to the device.

[0047] Interface: A user interface allows for easy configuration changes, such as changing the target language, adjusting the volume, or turning certain features on or off.

[0048] 2. Program processing explanation

[0049] Device: After putting on the mask, the user activates the device, which immediately activates the high-resolution camera and microphone and begins collecting visual and audio information from the surrounding area.

[0050] Server: Receives the video and audio data sent from the device. The server first uses OCR technology to recognize the characters in the video image and extract the text information. Next, it uses voice recognition technology to convert the audio data into text.

[0051] Server: The server receives the text information and translates it into a pre-defined foreign language. The translation process uses machine translation technology, and in some cases may also involve the assistance of bilingual experts.

[0052] Server: The translated text data is divided into visual data and audio data. The visual data is formatted using AR technology to be displayed in the user's field of vision, and the audio data is converted into audio using speech synthesis technology.

[0053] Device: Visual data sent from the server is displayed on the AR display and superimposed on the user's field of view. Audio data is played back so that the user can hear it through headphones.

[0054] 3. Example of a system

[0055] Example 1: Sign translation

[0056] User: Walking around town.

[0057] Terminal: The camera takes a picture of the sign and sends the video data to the server.

[0058] Server: Uses OCR technology to recognize and translate the characters on the sign, then sends the translation results back to the device.

[0059] On your device: The translated text will be overlaid on the AR display.

[0060] Example 2: Conversation translation

[0061] User: Places an order at a restaurant.

[0062] Terminal: Records conversation with the waiter using a microphone and sends the audio data to the server.

[0063] Server: Converts conversations into text using speech recognition technology and translates them. The translation results are then converted back into text data and used for speech synthesis.

[0064] Device: Play the translated audio through headphones.

[0065] This system allows users to efficiently learn a foreign language while experiencing a foreign language environment in real time, without having to study abroad. This system supports practical foreign language learning while minimizing financial constraints and safety concerns.

[0066] The processing flow will be explained below.

[0067] Step 1:

[0068] User: Put on the mask and turn it on. The device will automatically connect to the server.

[0069] Step 2:

[0070] Device: Activate the mask's high-resolution camera and microphone and begin collecting visual and audio information from the surrounding area.

[0071] Step 3:

[0072] Terminal: Transmits the acquired visual and audio information to the server in real time.

[0073] Step 4:

[0074] Server: Analyzes the received video data using OCR technology and extracts text information from the image.

[0075] Step 5:

[0076] Server: At the same time, the received voice data is converted into text using voice recognition technology.

[0077] Step 6:

[0078] Server: Translates the extracted character information and speech-to-text information into the specified foreign language.

[0079] Step 7:

[0080] Server: The translated text information is divided into visual data and audio data. The visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[0081] Step 8:

[0082] Server: Sends the translation results to the device.

[0083] Step 9:

[0084] Device: The translated visual data is applied to the AR display and overlaid on the real-world image.

[0085] Step 10:

[0086] Device: Play the translated audio data through headphones.

[0087] Step 11:

[0088] Terminal: New visual and audio information is continuously acquired and sent to the server for real-time updates.

[0089] Step 12:

[0090] Server: Always analyzes and translates the latest data and sends it to the device.

[0091] Step 13:

[0092] User: Uses the interface to change the target language, adjust the volume, and turn certain features on or off.

[0093] Example 1

[0094] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0095] Currently, learning a foreign language requires studying abroad or using specialized learning tools, which is time-consuming and expensive. Furthermore, there are limited ways to experience a foreign language environment in real time, making practical learning difficult. Furthermore, fear of the foreign language can also be an obstacle to learning. Because traditional foreign language learning methods cannot effectively solve these problems, new learning methods are needed.

[0096] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0097] In this invention, the server includes a means for analyzing video data and audio data and applying OCR and speech recognition technologies, a means for translating text information into a foreign language using machine translation technology, and a means for displaying visual data in the user's field of view using AR technology. This allows users to experience a foreign language environment in real time, enabling efficient and practical foreign language learning. This also allows learning to be done while minimizing financial constraints and safety concerns.

[0098] A "high-resolution camera" is an optical device that can capture detailed images.

[0099] "Surrounding visual information" refers to all images and videos of the environment captured by the camera.

[0100] A "microphone" is an audio device used to pick up surrounding sounds.

[0101] "Ambient audio information" refers to all sounds in the environment picked up by the microphone.

[0102] "OCR technology" stands for optical character recognition technology, which extracts character information from an image as text data.

[0103] "Voice recognition technology" is a technology that analyzes voice data and converts it into text data.

[0104] "Text information" refers to all character data extracted or converted using OCR or voice recognition technology.

[0105] "Machine translation technology" is technology that automatically translates text from one language to another.

[0106] "Augmented reality technology" is a technology that overlays computer-generated information on real-world information.

[0107] "Speech synthesis technology" is a technology that converts text data into voice data.

[0108] A "server" is a high-performance computer system used for analyzing, processing, and storing data.

[0109] "Terminal" refers to any device or equipment operated by a user.

[0110] This invention is a system that allows users to experience a foreign language environment while in Japan using a "language conversion mask." The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, and a user interface.

[0111] Hardware Configuration

[0112] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, and headphones. The device transmits the acquired information to a server in real time.

[0113] Server: A high-performance computer system that analyzes and translates the visual and audio information sent from the device. The server processes the information using OCR and voice recognition technology and sends the translation results back to the device.

[0114] Interface: A user interface allows for easy configuration changes, such as changing the target language, adjusting the volume, or turning certain features on or off.

[0115] Software Configuration

[0116] OCR technology: Used to extract text information from video data. For example, Tesseract can be used as a common OCR library.

[0117] Speech recognition technology: Used to convert voice data collected by a microphone into text. For example, Google® Cloud Speech-to-Text API can be used.

[0118] Machine translation technology: Used to translate text information into a foreign language. For example, the DeepL translation API and other machine translation services are available.

[0119] AR technology: Used to display translated text information as visual data in the user's field of view. For example, AR display can be achieved using the Unity engine.

[0120] Speech synthesis technology: Used to convert the translated text information into speech. For example, Amazon Polly can be used.

[0121] Specific examples

[0122] 1. Sign translation

[0123] User: Walking around town.

[0124] Terminal: The camera takes a picture of the sign and sends the video data to the server.

[0125] Server: Extract the text from the sign using Tesseract OCR, translate it from Japanese to English using the DeepL translation API, and convert the translation results into AR display data using Unity.

[0126] Device: The translation results are displayed overlaid on the AR display.

[0127] 2. Conversation Translation

[0128] User: Places an order at a restaurant.

[0129] Terminal: Records conversation with the waiter using a microphone and sends the audio data to the server.

[0130] Server: Use Google Cloud Speech-to-Text to convert speech to text, then use the DeepL translation API to translate from Japanese to English, then use Amazon Polly to convert the translation back to speech.

[0131] Device: Play the translated audio through headphones.

[0132] Examples of prompt statements

[0133] "I found a sign in the city. Please translate the Japanese text into English."

[0134] "I want to order at a restaurant. Please translate what the waiter is saying into English."

[0135] This system allows users to efficiently learn a foreign language while experiencing a foreign language environment in real time. The system supports practical foreign language learning while minimizing financial constraints and safety concerns.

[0136] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0137] Step 1:

[0138] User: Starts the system. Puts on the language conversion mask and presses the "Start" button using the built-in interface. At this point, the target language and volume settings are also loaded.

[0139] Step 2:

[0140] Device: The mask's built-in high-resolution camera and microphone begin working. The camera captures the surrounding video and the microphone collects the surrounding audio. Specifically, the camera captures video data at 1080p resolution, and the noise-canceling microphone captures audio data.

[0141] Step 3:

[0142] Terminal: The acquired visual and audio information is sent to the server in real time. The data is compressed; for example, video data is compressed using H.264, and audio data is compressed using AAC.

[0143] Step 4:

[0144] Server: Analyzes video data received from the device using OCR technology. Specifically, it uses Tesseract OCR to detect characters in the image and extract them as text data. The input is video data, and the output is text data containing character information.

[0145] Step 5:

[0146] Server: Analyzes the received voice data using speech recognition technology. Specifically, it converts the voice data into text data using the Google Cloud Speech-to-Text API. The input is voice data, and the output is text data containing the voice content.

[0147] Step 6:

[0148] Server: The extracted and converted text data is translated using machine translation technology. Specifically, the DeepL translation API is used to translate Japanese text into any foreign language. The input is Japanese text data, and the output is text data in the foreign language.

[0149] Step 7:

[0150] Server: Converts the translated text data into visual data and audio data. The visual data is formatted to be displayed in the user's field of view using AR technology, and the audio data is converted into audio data using speech synthesis technology. Specifically, AR display data is generated using Unity, and audio data is generated using Amazon Polly. The input is text data in a foreign language, and the output is visual data and audio data.

[0151] Step 8:

[0152] Device: The visual data sent from the server is displayed on the AR display. Specifically, a high-resolution see-through display is used to overlay the translated text onto the real world. The audio data is also played back through headphones. Specifically, high-quality Bluetooth headphones are used to play the audio. This allows the user to confirm the translated information both visually and audibly.

[0153] (Application example 1)

[0154] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0155] In modern society, the difficulty of communicating in a foreign language environment is a barrier to economic activity and daily life. In particular, foreign customers in brick-and-mortar stores face difficulties in understanding product information and communicating smoothly with store staff. Existing translation systems often lack real-time performance and accuracy, and require time-consuming configuration changes. Therefore, a more effective and intuitive system is needed.

[0156] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0157] In this invention, the server includes means for acquiring surrounding visual information using a high-resolution camera, means for acquiring surrounding audio information using a microphone, means for translating product labels, and means for translating conversations between users and store clerks, thereby providing an environment in the store where customers can smoothly understand product information in foreign languages ​​and communicate with store clerks.

[0158] A "high-resolution camera" is a photographing device that can acquire visual information at high resolution.

[0159] A "microphone" is a device for acquiring surrounding audio information.

[0160] "Visual information" refers to video data captured by a camera.

[0161] "Audio information" refers to sound data captured by a microphone.

[0162] "Text information" refers to text data contained in visual information.

[0163] "Voice recognition technology" is a technology that analyzes voice information and converts it into text data.

[0164] "Text information" refers to character data extracted using voice recognition technology or OCR (Optical Character Recognition) technology.

[0165] A "foreign language" is a language other than the one the user understands.

[0166] "Translating" is the act of converting meaning from one language to another.

[0167] "Augmented reality technology" is a technology that displays computer-generated information overlaid on visual information.

[0168] "Speech synthesis means" refers to a device or technology that converts text data into speech and plays it back.

[0169] A "product label" is a label attached to a product to display information.

[0170] A "conversation" is any oral communication between two or more people.

[0171] A "server" is a remote computer system that processes data sent from a terminal and returns the necessary information.

[0172] An "interface" is an operating means by which a user changes system settings.

[0173] "Target language" refers to the language in which the translated results will be displayed.

[0174] "Volume" refers to the volume of the sound, and can be adjusted by the user.

[0175] The "specific function on / off setting" refers to a setting that allows the user to enable or disable a function that the user wants to use.

[0176] The system for implementing this invention has a specific configuration for providing a foreign language environment in a brick-and-mortar store. The system is composed of the following hardware and software.

[0177] Hardware Configuration

[0178] 1. High-resolution camera: This captures visual information such as product labels and in-store signs.

[0179] 2. Microphone: Captures surrounding audio information, especially conversations with store staff.

[0180] 3. AR display: The acquired and translated text information is displayed using augmented reality technology.

[0181] 4. Headphones: A device that allows the user to hear the translated audio information.

[0182] 5. Server: A computer system for analyzing and translating visual and audio information sent from the terminal.

[0183] Software Configuration

[0184] 1. OCR technology (Pytesseract): A technology for extracting text information from visual information acquired by a high-resolution camera.

[0185] 2. Speech Recognition: Technology for converting voice information obtained through a microphone into text.

[0186] 3. Machine translation technology (Googletrans): Technology for translating extracted and converted text information into a foreign language.

[0187] 4. Speech synthesis technology (Pyttsx3): Technology for converting translated text information into speech and playing it back.

[0188] 5. User Interface: The means of operation that allows users to easily change settings, including switching target languages, adjusting volume, and turning certain features on or off.

[0189] Specific operation of the system

[0190] Product label translation: When a user takes a photo of a product label with their smartphone camera, the high-resolution camera captures visual information. The device sends this information to a server, where text information is extracted using OCR technology. The information is then translated into the selected foreign language using machine translation technology, and the translation results are displayed on an AR display using augmented reality technology.

[0191] Translation of conversations with store clerks: When a user records a conversation with a store clerk using a microphone, the audio information is sent to the server. It is converted into text using speech recognition technology and translated using machine translation technology. The translation result is then converted back into text and played back using speech synthesis technology.

[0192] Specific examples

[0193] For example, if a user wants to translate a product label in a physical store that says "Milk" into English:

[0194] Take a photo of the product label with your smartphone camera.

[0195] The server extracts the text information "Milk" from the visual information and translates it into English "Milk."

[0196] The translated result will be displayed as "Milk" on the AR display.

[0197] Or, if you want to translate a conversation in a physical store where a user says "hello" in Japanese into English:

[0198] The conversation is recorded and sent to a server.

[0199] The server uses speech recognition technology to convert the text "Hello" into the English "Hello."

[0200] Play the translated audio through headphones.

[0201] Prompt Sentence Examples

[0202] "Please translate the foreign language signs in the store into English."

[0203] "Please translate this recorded conversation into English and play it back."

[0204] As a result, this system is designed to enable users to smoothly understand product information and communicate with store clerks even in a foreign language environment.

[0205] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0206] Step 1:

[0207] The user takes a photo of the product label with their smartphone camera.

[0208] Input: Product label image.

[0209] Specific operation: The user uses the smartphone camera to take a picture of the product label.

[0210] Step 2:

[0211] The device uses a high-resolution camera to capture visual information about the surroundings.

[0212] Input: A product label image taken by a camera.

[0213] Output: Retrieved visual information (product label image).

[0214] Specific operation: The device uses the camera to take an image of the product label and collect visual information.

[0215] Step 3:

[0216] The visual information acquired by the terminal is sent to the server.

[0217] Input: Product label image.

[0218] Output: Sending visual information (product label image) to the server.

[0219] Specific operation: The product label image acquired by the terminal is sent to the server via the network.

[0220] Step 4:

[0221] The server uses OCR technology to extract text information from the visual information.

[0222] Input: Product label image sent to the server.

[0223] Output: Extracted character information (text data).

[0224] Specific operation: The server uses Pytesseract to analyze the characters in the product label image and extract them as text data.

[0225] Step 5:

[0226] The server translates the extracted text information into a foreign language using machine translation technology.

[0227] Input: Extracted character information (text data).

[0228] Output: Translated text information (translated text data).

[0229] Specific operation: The server uses Google Translate to translate the text data into the set target language.

[0230] Step 6:

[0231] The server sends the translation results to the terminal.

[0232] Input: Translated text information (translated text data).

[0233] Output: Sending the translation results to your device.

[0234] Specific operation: The server sends the translated text information back to the terminal via the network.

[0235] Step 7:

[0236] The device retrieves the translated text information and displays it on the AR display.

[0237] Input: Translated text information (translated text data).

[0238] Output: Translation results displayed on the AR display.

[0239] Specific operation: The translation results received by the device are displayed on the screen using AR technology, superimposed on the user's field of view.

[0240] Step 8:

[0241] The user checks the displayed translation results.

[0242] Input: Translation result displayed on the AR display.

[0243] Output: Product information in a foreign language that the user can understand.

[0244] Specific operation: The user checks the translated product information through the AR display on their smartphone.

[0245] Through these steps, users can access foreign language translations of product labels in real time in physical stores, facilitating smooth shopping in a foreign language environment.

[0246] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0247] This invention is a system that uses a "language conversion mask" to allow users to experience a foreign language environment while in Japan, and also recognizes and reflects the user's emotional state. The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, an emotion engine, and a user interface.

[0248] 1. Hardware Configuration

[0249] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, headphones, and an emotion engine. The device transmits the acquired information to a server in real time.

[0250] Server: A computer system that analyzes and translates visual information, audio information, and emotional data sent from the device. The server processes the information using OCR, speech recognition, and emotion analysis technologies, and sends the translation results back to the device.

[0251] Interface: Provides controls that allow users to easily change settings, such as changing the target language, adjusting the volume, or turning certain features on or off.

[0252] 2. Program processing explanation

[0253] Device: After putting on the mask, the user activates the device. The device immediately activates its high-resolution camera and microphone to collect surrounding visual information, audio information, and the user's facial expression data. The emotion engine analyzes the user's emotional state from their facial expressions and tone of voice.

[0254] Server: Receives the video data and facial expression data sent from the device. The server first uses OCR technology to recognize the characters in the video image and extract text information. Next, it uses voice recognition technology to convert the audio data into text.

[0255] Server: Translates the extracted text and speech-to-text information into the specified foreign language. It can provide adaptive feedback to the translation results based on the user's emotional data recognized by the emotion engine. For example, if the user is confused, the server will provide a translation using simpler expressions.

[0256] Server: The translated text data is separated into visual data and audio data. The visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[0257] Device: Visual data sent from the server is displayed on the AR display and superimposed on the user's field of view. Audio data is played back so that the user can hear it through headphones.

[0258] 3. Example of a system

[0259] Example 1: Sign translation and emotional adaptation

[0260] User: Walking around town.

[0261] Terminal: The camera takes a picture of the sign and sends the video data to the server. The emotion engine analyzes the user's facial expressions to determine their emotions.

[0262] Server: Uses OCR technology to recognize and translate the characters on the sign. If it detects that the user is confused, it provides a simple translation. It then sends the translation results back to the device.

[0263] On your device: The translated text will be overlaid on the AR display.

[0264] Example 2: Dialogue translation and emotional adaptation

[0265] User: Places an order at a restaurant.

[0266] Device: The microphone records the conversation with the waiter and sends the audio data to the server. The emotion engine analyzes the emotion from the tone of the user's voice.

[0267] Server: Converts conversations into text using speech recognition technology and translates them. If the user feels unsure, provides a translation with words of encouragement. Synthesizes speech and sends it to the device.

[0268] Device: Play the translated audio through headphones.

[0269] Through these processes, users can learn a foreign language efficiently while experiencing a foreign language environment that adapts to their emotional state. This system reduces the user's mental burden and provides a more natural learning experience.

[0270] The processing flow will be explained below.

[0271] Step 1:

[0272] User: Put on the mask and turn it on. The device will automatically connect to the server.

[0273] Step 2:

[0274] Device: Activate the mask's high-resolution camera, microphone, and emotion engine to begin collecting surrounding visual and audio information and the user's facial expression data.

[0275] Step 3:

[0276] Terminal: Collected visual, audio, and facial expression data is sent to the server in real time.

[0277] Step 4:

[0278] Server: Analyzes the received video data using OCR technology and extracts text information from the image.

[0279] Step 5:

[0280] Server: Converts the received voice data into text using voice recognition technology.

[0281] Step 6:

[0282] Server: Uses the emotion engine to analyze the received facial expression data and recognize the user's emotional state.

[0283] Step 7:

[0284] Server: Translates the extracted text and speech into the specified foreign language. It adjusts the translation results based on the user's emotional state. For example, if the user is confused, it uses simpler expressions.

[0285] Step 8:

[0286] Server: The translated text data is divided into visual data and audio data. The visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[0287] Step 9:

[0288] Server: Sends the translation results to the device.

[0289] Step 10:

[0290] Device: The translated visual data is applied to the AR display and overlaid on the real-world image.

[0291] Step 11:

[0292] Device: Play the translated audio data through headphones.

[0293] Step 12:

[0294] Terminal: New visual, audio and facial expression data is continuously acquired and sent to the server for real-time updates.

[0295] Step 13:

[0296] Server: Always analyzes and translates the latest data and sends it to the device.

[0297] Step 14:

[0298] User: Uses the interface to change the target language, adjust the volume, and turn certain features on or off.

[0299] Example 2

[0300] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0301] Currently, many language translation systems do not consider the user's emotional state when experiencing a foreign language environment, which can lead to confusion and stress. Furthermore, conventional translation systems do not perform the process from collecting visual and audio information to displaying the translation results in real time, making them difficult to use in situations where immediate response is required. This makes it difficult to improve the user's learning efficiency and the quality of their foreign language experience.

[0302] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing the user's facial expression and tone of voice to recognize the emotional state, means for adding adaptive feedback to the translation result based on the recognized emotional state, and means for analyzing the acquired visual information and audio information and translating it into a foreign language. This enables real-time translation adapted to the user's emotional state.

[0303] A "high-resolution camera" refers to a high-resolution camera that can capture detailed visual information about the surroundings.

[0304] "Microphone" refers to an acoustic sensor for collecting surrounding sound information.

[0305] "Visual information" refers to image data of the surroundings acquired through a high-resolution camera.

[0306] "Audio information" refers to ambient audio data collected through a microphone.

[0307] "Text information" refers to text data extracted from acquired visual information.

[0308] "Speech recognition technology" refers to the technology that analyzes acquired voice information and converts it into text data.

[0309] "Foreign language" refers to any non-native language that is configured for the user to experience.

[0310] "Augmented reality technology" refers to technology that displays virtual information overlaid on real visual information.

[0311] "Speech synthesis means" refers to technology that converts text data into voice data and plays it back.

[0312] "Emotional state" refers to the psychological state of a user as perceived from their facial expression and tone of voice.

[0313] "Feedback" refers to a response that makes adaptive modifications to the translation result based on a perceived emotional state.

[0314] "User interface" refers to the operating means by which a user can change system settings.

[0315] The term "server" refers to a computer system that analyzes acquired data and performs translation and feedback processing.

[0316] "Device" refers to a device equipped with a high-resolution camera, microphone, AR display, headphones, and emotion engine.

[0317] This invention is a system that uses a "language conversion mask" to allow users to experience a foreign language environment while in Japan, and also recognizes and reflects the user's emotional state. The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, an emotion engine, and a user interface.

[0318] Hardware Configuration

[0319] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, headphones, and an emotion engine. The device transmits the acquired information to a server in real time.

[0320] Server: A computer system that analyzes and translates visual information, audio information, and emotional data sent from the device. The server processes the information using OCR, speech recognition, and emotion analysis technologies, and sends the translation results back to the device.

[0321] Interface: Provides controls that allow users to easily change settings, such as changing the target language, adjusting the volume, or turning certain features on or off.

[0322] Program processing explanation

[0323] Device: After putting on the mask, the user activates the device. The device immediately activates its high-resolution camera and microphone to collect surrounding visual information, audio information, and the user's facial expression data. The emotion engine analyzes the user's emotional state from their facial expressions and tone of voice.

[0324] Server: Receives the video data and facial expression data sent from the device. The server first uses OCR technology to recognize the characters in the video image and extract text information. Next, it uses voice recognition technology to convert the audio data into text.

[0325] The extracted text information and speech-to-text information are translated into the specified foreign language. Adaptive feedback can be added to the translation results based on the user's emotional data recognized by the emotion engine. For example, if the user is confused, the server will provide a translation using simpler expressions.

[0326] The translated text data is divided into visual data and audio data, the visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[0327] Device: Visual data sent from the server is displayed on the AR display and superimposed on the user's field of view. Audio data is played back so that the user can hear it through headphones.

[0328] Example of a system

[0329] Example 1: Sign translation and emotional adaptation

[0330] User: Walking around town.

[0331] Terminal: The camera takes a picture of the sign and sends the video data to the server. The emotion engine analyzes the user's facial expressions to determine their emotions.

[0332] Server: Uses OCR technology to recognize and translate the characters on the sign. If it detects that the user is confused, it provides a simple translation. It then sends the translation results back to the device.

[0333] On your device: The translated text will be overlaid on the AR display.

[0334] Example 2: Dialogue translation and emotional adaptation

[0335] User: Places an order at a restaurant.

[0336] Device: The microphone records the conversation with the waiter and sends the audio data to the server. The emotion engine analyzes the emotion from the tone of the user's voice.

[0337] Server: Converts conversations into text using speech recognition technology and translates them. If the user feels unsure, provides a translation with words of encouragement. Synthesizes speech and sends it to the device.

[0338] Device: Play the translated audio through headphones.

[0339] This allows the user to efficiently learn a foreign language while experiencing an adaptive foreign language environment that corresponds to the user's emotional state.

[0340] Example prompts to input to the generative AI model

[0341] "Generate examples of sign translations and emotional adaptations. Provide a simple translation if the user is confused."

[0342] "Generate translations and emotional adaptation examples for conversations at a restaurant. If the user feels unsure, provide a translation with encouraging words."

[0343] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0344] Step 1: User puts on mask and starts the system

[0345] User: Put on the mask-type device and turn on the system.

[0346] Device: High-resolution camera, microphone, AR display, headphones, and emotion engine activated.

[0347] Input: Mask activation signal.

[0348] Output: Initial startup completion signal for various sensors and start of operation.

[0349] Step 2: Collect visual, audio, and emotional data

[0350] Device: A high-resolution camera captures visual information of the surroundings, a microphone collects audio information, and an emotion engine analyzes the user's facial expressions and tone of voice in real time to generate emotional state data.

[0351] Input: User's visual, audio, and facial expressions.

[0352] Output: captured images, recorded audio, and analyzed emotion data.

[0353] Step 3: Sending visual, audio, and emotional data

[0354] Terminal: Collected visual, audio, and emotional data is sent to the server in real time.

[0355] Input: captured images, recorded audio, and analyzed emotion data.

[0356] Output: The data sent to the server.

[0357] Step 4: Data analysis by the server (OCR, speech recognition, emotion analysis)

[0358] Server: Analyzes received visual information using OCR technology, recognizes characters in images, and extracts text information. It also converts received audio information into text data using speech recognition technology, and analyzes emotional data.

[0359] Input: Transmitted visual, audio, and emotional data.

[0360] Output: Extracted text information, transcribed audio information, and analyzed emotion data.

[0361] Step 5: Translation process

[0362] Server: Translates the extracted text information and speech-to-text information into a preset foreign language.

[0363] Input: Extracted text and transcribed audio information.

[0364] Output: Translated text information and translated audio information.

[0365] Step 6: Adding adaptive feedback

[0366] Server: Adds adaptive feedback to translation results based on recognized emotion data. For example, if the user is confused, the server provides translation results with simple expressions.

[0367] Input: Translated text information and parsed sentiment data.

[0368] Output: The final translation result with added feedback.

[0369] Step 7: Format and distribute data

[0370] Server: The translated text data is separated into visual data and audio data. The visual data is formatted for the AR display, and the audio data is converted into audio data using speech synthesis technology and sent to the device.

[0371] Input: The final translation result.

[0372] Output: AR display data and audio data.

[0373] Step 8: View and play back translation results

[0374] Device: Visual data sent from the server is displayed on the AR display, and audio data is played through headphones.

[0375] Input: Visual and audio data sent from the server.

[0376] Output: The textual information displayed to the user's eyes and the audio information played.

[0377] (Application example 2)

[0378] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0379] Foreign tourists often have difficulty understanding Japanese when shopping in brick-and-mortar stores in Japan. This limited understanding of product labels and conversations with store clerks limits their shopping experience. This issue needs to be resolved to enable foreign tourists to enjoy shopping more comfortably and smoothly. It is also necessary to provide appropriate feedback based on the user's emotional state.

[0380] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0381] In this invention, the server includes means for acquiring visual information of the surroundings using a high-resolution camera, means for acquiring audio information of the surroundings using a microphone, means for analyzing the acquired visual information and extracting text information, means for converting the acquired audio information into text using speech recognition technology, means for translating the extracted and converted text information into any foreign language, means for displaying the translated text information using augmented reality technology, means for synthesizing the voice to play back the translated audio information, means for analyzing the user's facial expression and tone of voice to recognize their emotional state, and means for adaptively feeding back the translation result in accordance with the recognized emotional state. This not only enables foreign tourists to enjoy shopping in brick-and-mortar stores, but also allows them to receive more personalized service by providing feedback in accordance with the user's emotions.

[0382] A "high-resolution camera" is a camera that can capture very detailed visual information.

[0383] A "microphone" is a device that captures surrounding sounds.

[0384] "Visual information" refers to video data acquired through a visual device such as a camera.

[0385] "Audio information" is audio data acquired through an audio device such as a microphone.

[0386] "Means for extracting character information" refers to technology or equipment that recognizes and extracts characters from visual information.

[0387] "Speech recognition technology" is a technology that converts acquired voice information into text data.

[0388] "Means for translating into a foreign language" refers to a technique or device that converts extracted or converted text information into another language.

[0389] "Augmented reality technology" is a technology that displays virtual information overlaid on real images.

[0390] "Speech synthesis means" refers to a technology or device that converts translated text information into speech and plays it back.

[0391] A "means for recognizing an emotional state" is a technology or device that analyzes a user's facial expressions and tone of voice to determine their emotions.

[0392] An "adaptive feedback mechanism" is a technique or device that provides context-sensitive responses or information based on a perceived emotional state.

[0393] This system eliminates the barriers that foreign tourists face when shopping in brick-and-mortar stores in Japan, allowing them to enjoy shopping comfortably and smoothly. Specifically, the system includes a high-resolution camera, a microphone, a server, an augmented reality display, headphones, an emotion analysis engine, and a user interface.

[0394] First, the smart glasses worn by the user are equipped with a high-resolution camera, microphone, augmented reality display, headphones, and an emotion analysis engine, which allows them to acquire visual and audio information from the surroundings in real time and send it to a server.

[0395] The server analyzes the visual and audio information sent from the device and performs the necessary translation processing. Specifically, the following technologies are used:

[0396] OCR technology (such as Google Cloud Vision API): Extracts characters from visual information acquired by a high-resolution camera and converts them into text data.

[0397] Speech recognition technology (such as Google Cloud Speech-to-Text): Converts voice information captured by a microphone into text data.

[0398] Translation technology (such as Google Cloud Translate API): Translates acquired text data into the specified foreign language.

[0399] Speech synthesis technology (such as Google Cloud Text-to-Speech): Converts translated text data into audio data.

[0400] Emotion analysis engine (such as Microsoft® Azure® Emotion API): Analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[0401] Furthermore, the system provides adaptive feedback based on the user's emotional state. For example, if the user is confused, the system can provide simpler and more polite translations and add words of encouragement, allowing the user to enjoy shopping with peace of mind.

[0402] The following are some examples of specific usage scenarios:

[0403] Example 1: Product label translation

[0404] The user wears the smart glasses and takes a picture of a product label in the store with the camera. The server uses OCR technology to recognize the text on the label and translates it. The translation result is displayed on an augmented reality display, allowing the user to check the product information.

[0405] Example 2: Translation of a conversation with a store clerk

[0406] When a user asks a question at the cash register, a microphone records the conversation and sends the audio data to a server. The server then uses speech recognition technology to convert the conversation into text and translate it. An emotion analysis engine analyzes the user's facial expressions and provides translation results, including encouraging words, if the user appears nervous. The translation results are then played through headphones using speech synthesis technology.

[0407] Example prompts for generative AI models

[0408] "Create an application that uses smart glasses to enable foreign tourists to shop in brick-and-mortar stores without understanding Japanese. It should have real-time translation functions, conversation translation functions, and the ability to analyze the user's emotional state and provide feedback. For example, it should translate product labels and directions, and translate conversations with store clerks."

[0409] This system will enable foreign tourists to enjoy shopping in Japan without having to worry about language barriers, while also enabling stores to improve customer satisfaction.

[0410] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0411] Step 1:

[0412] A user puts on the smart glasses and starts the device. The device activates the camera and microphone to capture visual and audio information from the surroundings in real time.

[0413] Input: The user puts on the smart glasses and activates them.

[0414] Output: Visual information captured by a high-resolution camera and audio information recorded by a microphone.

[0415] Step 2:

[0416] The visual and audio information acquired by the device is sent to the server. The visual information is sent as image data, and the audio information is sent as audio data.

[0417] Input: Acquired visual and audio information.

[0418] Output: Image and audio data sent to the server.

[0419] Step 3:

[0420] The server extracts text information from the visual information using OCR technology (e.g., Google Cloud Vision API), analyzes the image data, and generates text data.

[0421] Input: Image data sent from the device.

[0422] Output: The extracted text data.

[0423] Step 4:

[0424] The server converts the voice information into text data using voice recognition technology (e.g., Google Cloud Speech-to-Text), analyzes the voice data, and generates text data.

[0425] Input: Audio data sent from the device.

[0426] Output: Text data converted from audio information.

[0427] Step 5:

[0428] The server translates the acquired and converted text data into any foreign language using translation technology (e.g., Google Cloud Translate API), and then converts the acquired text data into the target language.

[0429] Input: Text data obtained using OCR and speech recognition technologies.

[0430] Output: The translated text data.

[0431] Step 6:

[0432] The server recognizes the user's emotional state using an emotion analysis engine (e.g., Microsoft Azure Emotion API). It analyzes the user's facial expression data and tone of voice to identify the user's emotional state.

[0433] Input: User's facial expression data and tone of voice.

[0434] Output: Perceived emotional state.

[0435] Step 7:

[0436] The server adaptively provides feedback on the translation results based on the recognized emotional state, for example, generating feedback using simple translation expressions if the user is confused.

[0437] Input: translated text data and recognized emotional state.

[0438] Output: Adaptive translation results.

[0439] Step 8:

[0440] The server separates the data into visual and audio data, formats the visual data so that it can be displayed using augmented reality technology, and converts the audio data into audio using voice synthesis technology (e.g., Google Cloud Text-to-Speech).

[0441] Input: Adaptive translation result data.

[0442] Output: Display and audio data for augmented reality.

[0443] Step 9:

[0444] The device displays the visual data sent from the server on an augmented reality display and plays the audio data through headphones, allowing the user to receive the translated information visually and audibly.

[0445] Input: Visual and audio data sent from the server.

[0446] Output: Translation information displayed on the augmented reality display and translated audio played through headphones.

[0447] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0448] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0449] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0450] [Second embodiment]

[0451] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0452] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0453] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0454] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0455] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0456] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0457] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0458] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0459] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0460] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0461] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0462] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0463] This invention is a system that allows users to experience a foreign language environment while in Japan using a "language conversion mask." The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, and a user interface.

[0464] 1. Hardware Configuration

[0465] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, and headphones. The device transmits the acquired information to a server in real time.

[0466] Server: An advanced computer system that analyzes and translates the visual and audio information sent from the device. The server processes the information using OCR and speech recognition technology and sends the translation results back to the device.

[0467] Interface: A user interface allows for easy configuration changes, such as changing the target language, adjusting the volume, or turning certain features on or off.

[0468] 2. Program processing explanation

[0469] Device: After putting on the mask, the user activates the device, which immediately activates the high-resolution camera and microphone and begins collecting visual and audio information from the surrounding area.

[0470] Server: Receives the video and audio data sent from the device. The server first uses OCR technology to recognize the characters in the video image and extract the text information. Next, it uses voice recognition technology to convert the audio data into text.

[0471] Server: The server receives the text information and translates it into a pre-defined foreign language. The translation process uses machine translation technology, and in some cases may also involve the assistance of bilingual experts.

[0472] Server: The translated text data is divided into visual data and audio data. The visual data is formatted using AR technology to be displayed in the user's field of vision, and the audio data is converted into audio using speech synthesis technology.

[0473] Device: Visual data sent from the server is displayed on the AR display and superimposed on the user's field of view. Audio data is played back so that the user can hear it through headphones.

[0474] 3. Example of a system

[0475] Example 1: Sign translation

[0476] User: Walking around town.

[0477] Terminal: The camera takes a picture of the sign and sends the video data to the server.

[0478] Server: Uses OCR technology to recognize and translate the characters on the sign, then sends the translation results back to the device.

[0479] On your device: The translated text will be overlaid on the AR display.

[0480] Example 2: Conversation translation

[0481] User: Places an order at a restaurant.

[0482] Terminal: Records conversation with the waiter using a microphone and sends the audio data to the server.

[0483] Server: Converts conversations into text using speech recognition technology and translates them. The translation results are then converted back into text data and used for speech synthesis.

[0484] Device: Play the translated audio through headphones.

[0485] This system allows users to efficiently learn a foreign language while experiencing a foreign language environment in real time, without having to study abroad. This system supports practical foreign language learning while minimizing financial constraints and safety concerns.

[0486] The processing flow will be explained below.

[0487] Step 1:

[0488] User: Put on the mask and turn it on. The device will automatically connect to the server.

[0489] Step 2:

[0490] Device: Activate the mask's high-resolution camera and microphone and begin collecting visual and audio information from the surrounding area.

[0491] Step 3:

[0492] Terminal: Transmits the acquired visual and audio information to the server in real time.

[0493] Step 4:

[0494] Server: Analyzes the received video data using OCR technology and extracts text information from the image.

[0495] Step 5:

[0496] Server: At the same time, the received voice data is converted into text using voice recognition technology.

[0497] Step 6:

[0498] Server: Translates the extracted character information and speech-to-text information into the specified foreign language.

[0499] Step 7:

[0500] Server: The translated text information is divided into visual data and audio data. The visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[0501] Step 8:

[0502] Server: Sends the translation results to the device.

[0503] Step 9:

[0504] Device: The translated visual data is applied to the AR display and overlaid on the real-world image.

[0505] Step 10:

[0506] Device: Play the translated audio data through headphones.

[0507] Step 11:

[0508] Terminal: New visual and audio information is continuously acquired and sent to the server for real-time updates.

[0509] Step 12:

[0510] Server: Always analyzes and translates the latest data and sends it to the device.

[0511] Step 13:

[0512] User: Uses the interface to change the target language, adjust the volume, and turn certain features on or off.

[0513] Example 1

[0514] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0515] Currently, learning a foreign language requires studying abroad or using specialized learning tools, which is time-consuming and expensive. Furthermore, there are limited ways to experience a foreign language environment in real time, making practical learning difficult. Furthermore, fear of the foreign language can also be an obstacle to learning. Because traditional foreign language learning methods cannot effectively solve these problems, new learning methods are needed.

[0516] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0517] In this invention, the server includes a means for analyzing video data and audio data and applying OCR and speech recognition technologies, a means for translating text information into a foreign language using machine translation technology, and a means for displaying visual data in the user's field of view using AR technology. This allows users to experience a foreign language environment in real time, enabling efficient and practical foreign language learning. This also allows learning to be done while minimizing financial constraints and safety concerns.

[0518] A "high-resolution camera" is an optical device that can capture detailed images.

[0519] "Surrounding visual information" refers to all images and videos of the environment captured by the camera.

[0520] A "microphone" is an audio device used to pick up surrounding sounds.

[0521] "Ambient audio information" refers to all sounds in the environment picked up by the microphone.

[0522] "OCR technology" stands for optical character recognition technology, which extracts character information from an image as text data.

[0523] "Voice recognition technology" is a technology that analyzes voice data and converts it into text data.

[0524] "Text information" refers to all character data extracted or converted using OCR or voice recognition technology.

[0525] "Machine translation technology" is technology that automatically translates text from one language to another.

[0526] "Augmented reality technology" is a technology that overlays computer-generated information on real-world information.

[0527] "Speech synthesis technology" is a technology that converts text data into voice data.

[0528] A "server" is a high-performance computer system used for analyzing, processing, and storing data.

[0529] "Terminal" refers to any device or equipment operated by a user.

[0530] This invention is a system that allows users to experience a foreign language environment while in Japan using a "language conversion mask." The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, and a user interface.

[0531] Hardware Configuration

[0532] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, and headphones. The device transmits the acquired information to a server in real time.

[0533] Server: A high-performance computer system that analyzes and translates the visual and audio information sent from the device. The server processes the information using OCR and voice recognition technology and sends the translation results back to the device.

[0534] Interface: A user interface allows for easy configuration changes, such as changing the target language, adjusting the volume, or turning certain features on or off.

[0535] Software Configuration

[0536] OCR technology: Used to extract text information from video data. For example, Tesseract can be used as a common OCR library.

[0537] Speech recognition technology: Used to convert voice data collected by a microphone into text. For example, Google Cloud Speech-to-Text API can be used.

[0538] Machine translation technology: Used to translate text information into a foreign language. For example, the DeepL translation API and other machine translation services are available.

[0539] AR technology: Used to display translated text information as visual data in the user's field of view. For example, AR display can be achieved using the Unity engine.

[0540] Speech synthesis technology: Used to convert the translated text information into speech. For example, Amazon Polly can be used.

[0541] Specific examples

[0542] 1. Sign translation

[0543] User: Walking around town.

[0544] Terminal: The camera takes a picture of the sign and sends the video data to the server.

[0545] Server: Extract the text from the sign using Tesseract OCR, translate it from Japanese to English using the DeepL translation API, and convert the translation results into AR display data using Unity.

[0546] Device: The translation results are displayed overlaid on the AR display.

[0547] 2. Conversation Translation

[0548] User: Places an order at a restaurant.

[0549] Terminal: Records conversation with the waiter using a microphone and sends the audio data to the server.

[0550] Server: Use Google Cloud Speech-to-Text to convert speech to text, then use the DeepL translation API to translate from Japanese to English, then use Amazon Polly to convert the translation back to speech.

[0551] Device: Play the translated audio through headphones.

[0552] Examples of prompt statements

[0553] "I found a sign in the city. Please translate the Japanese text into English."

[0554] "I want to order at a restaurant. Please translate what the waiter is saying into English."

[0555] This system allows users to efficiently learn a foreign language while experiencing a foreign language environment in real time. The system supports practical foreign language learning while minimizing financial constraints and safety concerns.

[0556] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0557] Step 1:

[0558] User: Starts the system. Puts on the language conversion mask and presses the "Start" button using the built-in interface. At this point, the target language and volume settings are also loaded.

[0559] Step 2:

[0560] Device: The mask's built-in high-resolution camera and microphone begin working. The camera captures the surrounding video and the microphone collects the surrounding audio. Specifically, the camera captures video data at 1080p resolution, and the noise-canceling microphone captures audio data.

[0561] Step 3:

[0562] Terminal: The acquired visual and audio information is sent to the server in real time. The data is compressed; for example, video data is compressed using H.264, and audio data is compressed using AAC.

[0563] Step 4:

[0564] Server: Analyzes video data received from the device using OCR technology. Specifically, it uses Tesseract OCR to detect characters in the image and extract them as text data. The input is video data, and the output is text data containing character information.

[0565] Step 5:

[0566] Server: Analyzes the received voice data using speech recognition technology. Specifically, it converts the voice data into text data using the Google Cloud Speech-to-Text API. The input is voice data, and the output is text data containing the voice content.

[0567] Step 6:

[0568] Server: The extracted and converted text data is translated using machine translation technology. Specifically, the DeepL translation API is used to translate Japanese text into any foreign language. The input is Japanese text data, and the output is text data in the foreign language.

[0569] Step 7:

[0570] Server: Converts the translated text data into visual data and audio data. The visual data is formatted to be displayed in the user's field of view using AR technology, and the audio data is converted into audio data using speech synthesis technology. Specifically, AR display data is generated using Unity, and audio data is generated using Amazon Polly. The input is text data in a foreign language, and the output is visual data and audio data.

[0571] Step 8:

[0572] Device: The visual data sent from the server is displayed on the AR display. Specifically, a high-resolution see-through display is used to overlay the translated text onto the real world. The audio data is also played back through headphones. Specifically, high-quality Bluetooth headphones are used to play the audio. This allows the user to confirm the translated information both visually and audibly.

[0573] (Application example 1)

[0574] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0575] In modern society, the difficulty of communicating in a foreign language environment is a barrier to economic activity and daily life. In particular, foreign customers in brick-and-mortar stores face difficulties in understanding product information and communicating smoothly with store staff. Existing translation systems often lack real-time performance and accuracy, and require time-consuming configuration changes. Therefore, a more effective and intuitive system is needed.

[0576] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0577] In this invention, the server includes means for acquiring surrounding visual information using a high-resolution camera, means for acquiring surrounding audio information using a microphone, means for translating product labels, and means for translating conversations between users and store clerks, thereby providing an environment in the store where customers can smoothly understand product information in foreign languages ​​and communicate with store clerks.

[0578] A "high-resolution camera" is a photographing device that can acquire visual information at high resolution.

[0579] A "microphone" is a device for acquiring surrounding audio information.

[0580] "Visual information" refers to video data captured by a camera.

[0581] "Audio information" refers to sound data captured by a microphone.

[0582] "Text information" refers to text data contained in visual information.

[0583] "Voice recognition technology" is a technology that analyzes voice information and converts it into text data.

[0584] "Text information" refers to character data extracted using voice recognition technology or OCR (Optical Character Recognition) technology.

[0585] A "foreign language" is a language other than the one the user understands.

[0586] "Translating" is the act of converting meaning from one language to another.

[0587] "Augmented reality technology" is a technology that displays computer-generated information overlaid on visual information.

[0588] "Speech synthesis means" refers to a device or technology that converts text data into speech and plays it back.

[0589] A "product label" is a label attached to a product to display information.

[0590] A "conversation" is any oral communication between two or more people.

[0591] A "server" is a remote computer system that processes data sent from a terminal and returns the necessary information.

[0592] An "interface" is an operating means by which a user changes system settings.

[0593] "Target language" refers to the language in which the translated results will be displayed.

[0594] "Volume" refers to the volume of the sound, and can be adjusted by the user.

[0595] The "specific function on / off setting" refers to a setting that allows the user to enable or disable a function that the user wants to use.

[0596] The system for implementing this invention has a specific configuration for providing a foreign language environment in a brick-and-mortar store. The system is composed of the following hardware and software.

[0597] Hardware Configuration

[0598] 1. High-resolution camera: This captures visual information such as product labels and in-store signs.

[0599] 2. Microphone: Captures surrounding audio information, especially conversations with store staff.

[0600] 3. AR display: The acquired and translated text information is displayed using augmented reality technology.

[0601] 4. Headphones: A device that allows the user to hear the translated audio information.

[0602] 5. Server: A computer system for analyzing and translating visual and audio information sent from the terminal.

[0603] Software Configuration

[0604] 1. OCR technology (Pytesseract): A technology for extracting text information from visual information acquired by a high-resolution camera.

[0605] 2. Speech Recognition: Technology for converting voice information obtained through a microphone into text.

[0606] 3. Machine translation technology (Googletrans): Technology for translating extracted and converted text information into a foreign language.

[0607] 4. Speech synthesis technology (Pyttsx3): Technology for converting translated text information into speech and playing it back.

[0608] 5. User Interface: The means of operation that allows users to easily change settings, including switching target languages, adjusting volume, and turning certain features on or off.

[0609] Specific operation of the system

[0610] Product label translation: When a user takes a photo of a product label with their smartphone camera, the high-resolution camera captures visual information. The device sends this information to a server, where text information is extracted using OCR technology. The information is then translated into the selected foreign language using machine translation technology, and the translation results are displayed on an AR display using augmented reality technology.

[0611] Translation of conversations with store clerks: When a user records a conversation with a store clerk using a microphone, the audio information is sent to the server. It is converted into text using speech recognition technology and translated using machine translation technology. The translation result is then converted back into text and played back using speech synthesis technology.

[0612] Specific examples

[0613] For example, if a user wants to translate a product label in a physical store that says "Milk" into English:

[0614] Take a photo of the product label with your smartphone camera.

[0615] The server extracts the text information "Milk" from the visual information and translates it into English "Milk."

[0616] The translated result will be displayed as "Milk" on the AR display.

[0617] Or, if you want to translate a conversation in a physical store where a user says "hello" in Japanese into English:

[0618] The conversation is recorded and sent to a server.

[0619] The server uses speech recognition technology to convert the text "Hello" into the English "Hello."

[0620] Play the translated audio through headphones.

[0621] Prompt Sentence Examples

[0622] "Please translate the foreign language signs in the store into English."

[0623] "Please translate this recorded conversation into English and play it back."

[0624] As a result, this system is designed to enable users to smoothly understand product information and communicate with store clerks even in a foreign language environment.

[0625] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0626] Step 1:

[0627] The user takes a photo of the product label with their smartphone camera.

[0628] Input: Product label image.

[0629] Specific operation: The user uses the smartphone camera to take a picture of the product label.

[0630] Step 2:

[0631] The device uses a high-resolution camera to capture visual information about the surroundings.

[0632] Input: A product label image taken by a camera.

[0633] Output: Retrieved visual information (product label image).

[0634] Specific operation: The device uses the camera to take an image of the product label and collect visual information.

[0635] Step 3:

[0636] The visual information acquired by the terminal is sent to the server.

[0637] Input: Product label image.

[0638] Output: Sending visual information (product label image) to the server.

[0639] Specific operation: The product label image acquired by the terminal is sent to the server via the network.

[0640] Step 4:

[0641] The server uses OCR technology to extract text information from the visual information.

[0642] Input: Product label image sent to the server.

[0643] Output: Extracted character information (text data).

[0644] Specific operation: The server uses Pytesseract to analyze the characters in the product label image and extract them as text data.

[0645] Step 5:

[0646] The server translates the extracted text information into a foreign language using machine translation technology.

[0647] Input: Extracted character information (text data).

[0648] Output: Translated text information (translated text data).

[0649] Specific operation: The server uses Google Translate to translate the text data into the set target language.

[0650] Step 6:

[0651] The server sends the translation results to the terminal.

[0652] Input: Translated text information (translated text data).

[0653] Output: Sending the translation results to your device.

[0654] Specific operation: The server sends the translated text information back to the terminal via the network.

[0655] Step 7:

[0656] The device retrieves the translated text information and displays it on the AR display.

[0657] Input: Translated text information (translated text data).

[0658] Output: Translation results displayed on the AR display.

[0659] Specific operation: The translation results received by the device are displayed on the screen using AR technology, superimposed on the user's field of view.

[0660] Step 8:

[0661] The user checks the displayed translation results.

[0662] Input: Translation result displayed on the AR display.

[0663] Output: Product information in a foreign language that the user can understand.

[0664] Specific operation: The user checks the translated product information through the AR display on their smartphone.

[0665] Through these steps, users can access foreign language translations of product labels in real time in physical stores, facilitating smooth shopping in a foreign language environment.

[0666] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0667] This invention is a system that uses a "language conversion mask" to allow users to experience a foreign language environment while in Japan, and also recognizes and reflects the user's emotional state. The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, an emotion engine, and a user interface.

[0668] 1. Hardware Configuration

[0669] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, headphones, and an emotion engine. The device transmits the acquired information to a server in real time.

[0670] Server: A computer system that analyzes and translates visual information, audio information, and emotional data sent from the device. The server processes the information using OCR, speech recognition, and emotion analysis technologies, and sends the translation results back to the device.

[0671] Interface: Provides controls that allow users to easily change settings, such as changing the target language, adjusting the volume, or turning certain features on or off.

[0672] 2. Program processing explanation

[0673] Device: After putting on the mask, the user activates the device. The device immediately activates its high-resolution camera and microphone to collect surrounding visual information, audio information, and the user's facial expression data. The emotion engine analyzes the user's emotional state from their facial expressions and tone of voice.

[0674] Server: Receives the video data and facial expression data sent from the device. The server first uses OCR technology to recognize the characters in the video image and extract text information. Next, it uses voice recognition technology to convert the audio data into text.

[0675] Server: Translates the extracted text and speech-to-text information into the specified foreign language. It can provide adaptive feedback to the translation results based on the user's emotional data recognized by the emotion engine. For example, if the user is confused, the server will provide a translation using simpler expressions.

[0676] Server: The translated text data is separated into visual data and audio data. The visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[0677] Device: Visual data sent from the server is displayed on the AR display and superimposed on the user's field of view. Audio data is played back so that the user can hear it through headphones.

[0678] 3. Example of a system

[0679] Example 1: Sign translation and emotional adaptation

[0680] User: Walking around town.

[0681] Terminal: The camera takes a picture of the sign and sends the video data to the server. The emotion engine analyzes the user's facial expressions to determine their emotions.

[0682] Server: Uses OCR technology to recognize and translate the characters on the sign. If it detects that the user is confused, it provides a simple translation. It then sends the translation results back to the device.

[0683] On your device: The translated text will be overlaid on the AR display.

[0684] Example 2: Dialogue translation and emotional adaptation

[0685] User: Places an order at a restaurant.

[0686] Device: The microphone records the conversation with the waiter and sends the audio data to the server. The emotion engine analyzes the emotion from the tone of the user's voice.

[0687] Server: Converts conversations into text using speech recognition technology and translates them. If the user feels unsure, provides a translation with words of encouragement. Synthesizes speech and sends it to the device.

[0688] Device: Play the translated audio through headphones.

[0689] Through these processes, users can learn a foreign language efficiently while experiencing a foreign language environment that adapts to their emotional state. This system reduces the user's mental burden and provides a more natural learning experience.

[0690] The processing flow will be explained below.

[0691] Step 1:

[0692] User: Put on the mask and turn it on. The device will automatically connect to the server.

[0693] Step 2:

[0694] Device: Activate the mask's high-resolution camera, microphone, and emotion engine to begin collecting surrounding visual and audio information and the user's facial expression data.

[0695] Step 3:

[0696] Terminal: Collected visual, audio, and facial expression data is sent to the server in real time.

[0697] Step 4:

[0698] Server: Analyzes the received video data using OCR technology and extracts text information from the image.

[0699] Step 5:

[0700] Server: Converts the received voice data into text using voice recognition technology.

[0701] Step 6:

[0702] Server: Uses the emotion engine to analyze the received facial expression data and recognize the user's emotional state.

[0703] Step 7:

[0704] Server: Translates the extracted text and speech into the specified foreign language. It adjusts the translation results based on the user's emotional state. For example, if the user is confused, it uses simpler expressions.

[0705] Step 8:

[0706] Server: The translated text data is divided into visual data and audio data. The visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[0707] Step 9:

[0708] Server: Sends the translation results to the device.

[0709] Step 10:

[0710] Device: The translated visual data is applied to the AR display and overlaid on the real-world image.

[0711] Step 11:

[0712] Device: Play the translated audio data through headphones.

[0713] Step 12:

[0714] Terminal: New visual, audio and facial expression data is continuously acquired and sent to the server for real-time updates.

[0715] Step 13:

[0716] Server: Always analyzes and translates the latest data and sends it to the device.

[0717] Step 14:

[0718] User: Uses the interface to change the target language, adjust the volume, and turn certain features on or off.

[0719] Example 2

[0720] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0721] Currently, many language translation systems do not consider the user's emotional state when experiencing a foreign language environment, which can lead to confusion and stress. Furthermore, conventional translation systems do not perform the process from collecting visual and audio information to displaying the translation results in real time, making them difficult to use in situations where immediate response is required. This makes it difficult to improve the user's learning efficiency and the quality of their foreign language experience.

[0722] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing the user's facial expression and tone of voice to recognize the emotional state, means for adding adaptive feedback to the translation result based on the recognized emotional state, and means for analyzing the acquired visual information and audio information and translating it into a foreign language. This enables real-time translation adapted to the user's emotional state.

[0723] A "high-resolution camera" refers to a high-resolution camera that can capture detailed visual information about the surroundings.

[0724] "Microphone" refers to an acoustic sensor for collecting surrounding sound information.

[0725] "Visual information" refers to image data of the surroundings acquired through a high-resolution camera.

[0726] "Audio information" refers to ambient audio data collected through a microphone.

[0727] "Text information" refers to text data extracted from acquired visual information.

[0728] "Speech recognition technology" refers to the technology that analyzes acquired voice information and converts it into text data.

[0729] "Foreign language" refers to any non-native language that is configured for the user to experience.

[0730] "Augmented reality technology" refers to technology that displays virtual information overlaid on real visual information.

[0731] "Speech synthesis means" refers to technology that converts text data into voice data and plays it back.

[0732] "Emotional state" refers to the psychological state of a user as perceived from their facial expression and tone of voice.

[0733] "Feedback" refers to a response that makes adaptive modifications to the translation result based on a perceived emotional state.

[0734] "User interface" refers to the operating means by which a user can change system settings.

[0735] The term "server" refers to a computer system that analyzes acquired data and performs translation and feedback processing.

[0736] "Device" refers to a device equipped with a high-resolution camera, microphone, AR display, headphones, and emotion engine.

[0737] This invention is a system that uses a "language conversion mask" to allow users to experience a foreign language environment while in Japan, and also recognizes and reflects the user's emotional state. The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, an emotion engine, and a user interface.

[0738] Hardware Configuration

[0739] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, headphones, and an emotion engine. The device transmits the acquired information to a server in real time.

[0740] Server: A computer system that analyzes and translates visual information, audio information, and emotional data sent from the device. The server processes the information using OCR, speech recognition, and emotion analysis technologies, and sends the translation results back to the device.

[0741] Interface: Provides controls that allow users to easily change settings, such as changing the target language, adjusting the volume, or turning certain features on or off.

[0742] Program processing explanation

[0743] Device: After putting on the mask, the user activates the device. The device immediately activates its high-resolution camera and microphone to collect surrounding visual information, audio information, and the user's facial expression data. The emotion engine analyzes the user's emotional state from their facial expressions and tone of voice.

[0744] Server: Receives the video data and facial expression data sent from the device. The server first uses OCR technology to recognize the characters in the video image and extract text information. Next, it uses voice recognition technology to convert the audio data into text.

[0745] The extracted text information and speech-to-text information are translated into the specified foreign language. Adaptive feedback can be added to the translation results based on the user's emotional data recognized by the emotion engine. For example, if the user is confused, the server will provide a translation using simpler expressions.

[0746] The translated text data is divided into visual data and audio data, the visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[0747] Device: Visual data sent from the server is displayed on the AR display and superimposed on the user's field of view. Audio data is played back so that the user can hear it through headphones.

[0748] Example of a system

[0749] Example 1: Sign translation and emotional adaptation

[0750] User: Walking around town.

[0751] Terminal: The camera takes a picture of the sign and sends the video data to the server. The emotion engine analyzes the user's facial expressions to determine their emotions.

[0752] Server: Uses OCR technology to recognize and translate the characters on the sign. If it detects that the user is confused, it provides a simple translation. It then sends the translation results back to the device.

[0753] On your device: The translated text will be overlaid on the AR display.

[0754] Example 2: Dialogue translation and emotional adaptation

[0755] User: Places an order at a restaurant.

[0756] Device: The microphone records the conversation with the waiter and sends the audio data to the server. The emotion engine analyzes the emotion from the tone of the user's voice.

[0757] Server: Converts conversations into text using speech recognition technology and translates them. If the user feels unsure, provides a translation with words of encouragement. Synthesizes speech and sends it to the device.

[0758] Device: Play the translated audio through headphones.

[0759] This allows the user to efficiently learn a foreign language while experiencing an adaptive foreign language environment that corresponds to the user's emotional state.

[0760] Example prompts to input to the generative AI model

[0761] "Generate examples of sign translations and emotional adaptations. Provide a simple translation if the user is confused."

[0762] "Generate translations and emotional adaptation examples for conversations at a restaurant. If the user feels unsure, provide a translation with encouraging words."

[0763] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0764] Step 1: User puts on mask and starts the system

[0765] User: Put on the mask-type device and turn on the system.

[0766] Device: High-resolution camera, microphone, AR display, headphones, and emotion engine activated.

[0767] Input: Mask activation signal.

[0768] Output: Initial startup completion signal for various sensors and start of operation.

[0769] Step 2: Collect visual, audio, and emotional data

[0770] Device: A high-resolution camera captures visual information of the surroundings, a microphone collects audio information, and an emotion engine analyzes the user's facial expressions and tone of voice in real time to generate emotional state data.

[0771] Input: User's visual, audio, and facial expressions.

[0772] Output: captured images, recorded audio, and analyzed emotion data.

[0773] Step 3: Sending visual, audio, and emotional data

[0774] Terminal: Collected visual, audio, and emotional data is sent to the server in real time.

[0775] Input: captured images, recorded audio, and analyzed emotion data.

[0776] Output: The data sent to the server.

[0777] Step 4: Data analysis by the server (OCR, speech recognition, emotion analysis)

[0778] Server: Analyzes received visual information using OCR technology, recognizes characters in images, and extracts text information. It also converts received audio information into text data using speech recognition technology, and analyzes emotional data.

[0779] Input: Transmitted visual, audio, and emotional data.

[0780] Output: Extracted text information, transcribed audio information, and analyzed emotion data.

[0781] Step 5: Translation process

[0782] Server: Translates the extracted text information and speech-to-text information into a preset foreign language.

[0783] Input: Extracted text and transcribed audio information.

[0784] Output: Translated text information and translated audio information.

[0785] Step 6: Adding adaptive feedback

[0786] Server: Adds adaptive feedback to translation results based on recognized emotion data. For example, if the user is confused, the server provides translation results with simple expressions.

[0787] Input: Translated text information and parsed sentiment data.

[0788] Output: The final translation result with added feedback.

[0789] Step 7: Format and distribute data

[0790] Server: The translated text data is separated into visual data and audio data. The visual data is formatted for the AR display, and the audio data is converted into audio data using speech synthesis technology and sent to the device.

[0791] Input: The final translation result.

[0792] Output: AR display data and audio data.

[0793] Step 8: View and play back translation results

[0794] Device: Visual data sent from the server is displayed on the AR display, and audio data is played through headphones.

[0795] Input: Visual and audio data sent from the server.

[0796] Output: The textual information displayed to the user's eyes and the audio information played.

[0797] (Application example 2)

[0798] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0799] Foreign tourists often have difficulty understanding Japanese when shopping in brick-and-mortar stores in Japan. This limited understanding of product labels and conversations with store clerks limits their shopping experience. This issue needs to be resolved to enable foreign tourists to enjoy shopping more comfortably and smoothly. It is also necessary to provide appropriate feedback based on the user's emotional state.

[0800] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0801] In this invention, the server includes means for acquiring visual information of the surroundings using a high-resolution camera, means for acquiring audio information of the surroundings using a microphone, means for analyzing the acquired visual information and extracting text information, means for converting the acquired audio information into text using speech recognition technology, means for translating the extracted and converted text information into any foreign language, means for displaying the translated text information using augmented reality technology, means for synthesizing the voice to play back the translated audio information, means for analyzing the user's facial expression and tone of voice to recognize their emotional state, and means for adaptively feeding back the translation result in accordance with the recognized emotional state. This not only enables foreign tourists to enjoy shopping in brick-and-mortar stores, but also allows them to receive more personalized service by providing feedback in accordance with the user's emotions.

[0802] A "high-resolution camera" is a camera that can capture very detailed visual information.

[0803] A "microphone" is a device that captures surrounding sounds.

[0804] "Visual information" refers to video data acquired through a visual device such as a camera.

[0805] "Audio information" is audio data acquired through an audio device such as a microphone.

[0806] "Means for extracting character information" refers to technology or equipment that recognizes and extracts characters from visual information.

[0807] "Speech recognition technology" is a technology that converts acquired voice information into text data.

[0808] "Means for translating into a foreign language" refers to a technique or device that converts extracted or converted text information into another language.

[0809] "Augmented reality technology" is a technology that displays virtual information overlaid on real images.

[0810] "Speech synthesis means" refers to a technology or device that converts translated text information into speech and plays it back.

[0811] A "means for recognizing an emotional state" is a technology or device that analyzes a user's facial expressions and tone of voice to determine their emotions.

[0812] An "adaptive feedback mechanism" is a technique or device that provides context-sensitive responses or information based on a perceived emotional state.

[0813] This system eliminates the barriers that foreign tourists face when shopping in brick-and-mortar stores in Japan, allowing them to enjoy shopping comfortably and smoothly. Specifically, the system includes a high-resolution camera, a microphone, a server, an augmented reality display, headphones, an emotion analysis engine, and a user interface.

[0814] First, the smart glasses worn by the user are equipped with a high-resolution camera, microphone, augmented reality display, headphones, and an emotion analysis engine, which allows them to acquire visual and audio information from the surroundings in real time and send it to a server.

[0815] The server analyzes the visual and audio information sent from the device and performs the necessary translation processing. Specifically, the following technologies are used:

[0816] OCR technology (such as Google Cloud Vision API): Extracts characters from visual information acquired by a high-resolution camera and converts them into text data.

[0817] Speech recognition technology (such as Google Cloud Speech-to-Text): Converts voice information captured by a microphone into text data.

[0818] Translation technology (such as Google Cloud Translate API): Translates acquired text data into the specified foreign language.

[0819] Speech synthesis technology (such as Google Cloud Text-to-Speech): Converts translated text data into audio data.

[0820] Emotion analysis engine (such as Microsoft Azure Emotion API): Analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[0821] Furthermore, the system provides adaptive feedback based on the user's emotional state. For example, if the user is confused, the system can provide simpler and more polite translations and add words of encouragement, allowing the user to enjoy shopping with peace of mind.

[0822] The following are some examples of specific usage scenarios:

[0823] Example 1: Product label translation

[0824] The user wears the smart glasses and takes a picture of a product label in the store with the camera. The server uses OCR technology to recognize the text on the label and translates it. The translation result is displayed on an augmented reality display, allowing the user to check the product information.

[0825] Example 2: Translation of a conversation with a store clerk

[0826] When a user asks a question at the cash register, a microphone records the conversation and sends the audio data to a server. The server then uses speech recognition technology to convert the conversation into text and translate it. An emotion analysis engine analyzes the user's facial expressions and provides translation results, including encouraging words, if the user appears nervous. The translation results are then played through headphones using speech synthesis technology.

[0827] Example prompts for generative AI models

[0828] "Create an application that uses smart glasses to enable foreign tourists to shop in brick-and-mortar stores without understanding Japanese. It should have real-time translation functions, conversation translation functions, and the ability to analyze the user's emotional state and provide feedback. For example, it should translate product labels and directions, and translate conversations with store clerks."

[0829] This system will enable foreign tourists to enjoy shopping in Japan without having to worry about language barriers, while also enabling stores to improve customer satisfaction.

[0830] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0831] Step 1:

[0832] A user puts on the smart glasses and starts the device. The device activates the camera and microphone to capture visual and audio information from the surroundings in real time.

[0833] Input: The user puts on the smart glasses and activates them.

[0834] Output: Visual information captured by a high-resolution camera and audio information recorded by a microphone.

[0835] Step 2:

[0836] The visual and audio information acquired by the device is sent to the server. The visual information is sent as image data, and the audio information is sent as audio data.

[0837] Input: Acquired visual and audio information.

[0838] Output: Image and audio data sent to the server.

[0839] Step 3:

[0840] The server extracts text information from the visual information using OCR technology (e.g., Google Cloud Vision API), analyzes the image data, and generates text data.

[0841] Input: Image data sent from the device.

[0842] Output: The extracted text data.

[0843] Step 4:

[0844] The server converts the voice information into text data using voice recognition technology (e.g., Google Cloud Speech-to-Text), analyzes the voice data, and generates text data.

[0845] Input: Audio data sent from the device.

[0846] Output: Text data converted from audio information.

[0847] Step 5:

[0848] The server translates the acquired and converted text data into any foreign language using translation technology (e.g., Google Cloud Translate API), and then converts the acquired text data into the target language.

[0849] Input: Text data obtained using OCR and speech recognition technologies.

[0850] Output: The translated text data.

[0851] Step 6:

[0852] The server recognizes the user's emotional state using an emotion analysis engine (e.g., Microsoft Azure Emotion API). It analyzes the user's facial expression data and tone of voice to identify the user's emotional state.

[0853] Input: User's facial expression data and tone of voice.

[0854] Output: Perceived emotional state.

[0855] Step 7:

[0856] The server adaptively provides feedback on the translation results based on the recognized emotional state, for example, generating feedback using simple translation expressions if the user is confused.

[0857] Input: translated text data and recognized emotional state.

[0858] Output: Adaptive translation results.

[0859] Step 8:

[0860] The server separates the data into visual and audio data, formats the visual data so that it can be displayed using augmented reality technology, and converts the audio data into audio using voice synthesis technology (e.g., Google Cloud Text-to-Speech).

[0861] Input: Adaptive translation result data.

[0862] Output: Display and audio data for augmented reality.

[0863] Step 9:

[0864] The device displays the visual data sent from the server on an augmented reality display and plays the audio data through headphones, allowing the user to receive the translated information visually and audibly.

[0865] Input: Visual and audio data sent from the server.

[0866] Output: Translation information displayed on the augmented reality display and translated audio played through headphones.

[0867] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0868] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0869] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0870] [Third embodiment]

[0871] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0872] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0873] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0874] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0875] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0876] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0877] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0878] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0879] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0880] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0881] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0882] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0883] This invention is a system that allows users to experience a foreign language environment while in Japan using a "language conversion mask." The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, and a user interface.

[0884] 1. Hardware Configuration

[0885] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, and headphones. The device transmits the acquired information to a server in real time.

[0886] Server: An advanced computer system that analyzes and translates the visual and audio information sent from the device. The server processes the information using OCR and speech recognition technology and sends the translation results back to the device.

[0887] Interface: A user interface allows for easy configuration changes, such as changing the target language, adjusting the volume, or turning certain features on or off.

[0888] 2. Program processing explanation

[0889] Device: After putting on the mask, the user activates the device, which immediately activates the high-resolution camera and microphone and begins collecting visual and audio information from the surrounding area.

[0890] Server: Receives the video and audio data sent from the device. The server first uses OCR technology to recognize the characters in the video image and extract the text information. Next, it uses voice recognition technology to convert the audio data into text.

[0891] Server: The server receives the text information and translates it into a pre-defined foreign language. The translation process uses machine translation technology, and in some cases may also involve the assistance of bilingual experts.

[0892] Server: The translated text data is divided into visual data and audio data. The visual data is formatted using AR technology to be displayed in the user's field of vision, and the audio data is converted into audio using speech synthesis technology.

[0893] Device: Visual data sent from the server is displayed on the AR display and superimposed on the user's field of view. Audio data is played back so that the user can hear it through headphones.

[0894] 3. Example of a system

[0895] Example 1: Sign translation

[0896] User: Walking around town.

[0897] Terminal: The camera takes a picture of the sign and sends the video data to the server.

[0898] Server: Uses OCR technology to recognize and translate the characters on the sign, then sends the translation results back to the device.

[0899] On your device: The translated text will be overlaid on the AR display.

[0900] Example 2: Conversation translation

[0901] User: Places an order at a restaurant.

[0902] Terminal: Records conversation with the waiter using a microphone and sends the audio data to the server.

[0903] Server: Converts conversations into text using speech recognition technology and translates them. The translation results are then converted back into text data and used for speech synthesis.

[0904] Device: Play the translated audio through headphones.

[0905] This system allows users to efficiently learn a foreign language while experiencing a foreign language environment in real time, without having to study abroad. This system supports practical foreign language learning while minimizing financial constraints and safety concerns.

[0906] The processing flow will be explained below.

[0907] Step 1:

[0908] User: Put on the mask and turn it on. The device will automatically connect to the server.

[0909] Step 2:

[0910] Device: Activate the mask's high-resolution camera and microphone and begin collecting visual and audio information from the surrounding area.

[0911] Step 3:

[0912] Terminal: Transmits the acquired visual and audio information to the server in real time.

[0913] Step 4:

[0914] Server: Analyzes the received video data using OCR technology and extracts text information from the image.

[0915] Step 5:

[0916] Server: At the same time, the received voice data is converted into text using voice recognition technology.

[0917] Step 6:

[0918] Server: Translates the extracted character information and speech-to-text information into the specified foreign language.

[0919] Step 7:

[0920] Server: The translated text information is divided into visual data and audio data. The visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[0921] Step 8:

[0922] Server: Sends the translation results to the device.

[0923] Step 9:

[0924] Device: The translated visual data is applied to the AR display and overlaid on the real-world image.

[0925] Step 10:

[0926] Device: Play the translated audio data through headphones.

[0927] Step 11:

[0928] Terminal: New visual and audio information is continuously acquired and sent to the server for real-time updates.

[0929] Step 12:

[0930] Server: Always analyzes and translates the latest data and sends it to the device.

[0931] Step 13:

[0932] User: Uses the interface to change the target language, adjust the volume, and turn certain features on or off.

[0933] Example 1

[0934] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0935] Currently, learning a foreign language requires studying abroad or using specialized learning tools, which is time-consuming and expensive. Furthermore, there are limited ways to experience a foreign language environment in real time, making practical learning difficult. Furthermore, fear of the foreign language can also be an obstacle to learning. Because traditional foreign language learning methods cannot effectively solve these problems, new learning methods are needed.

[0936] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0937] In this invention, the server includes a means for analyzing video data and audio data and applying OCR and speech recognition technologies, a means for translating text information into a foreign language using machine translation technology, and a means for displaying visual data in the user's field of view using AR technology. This allows users to experience a foreign language environment in real time, enabling efficient and practical foreign language learning. This also allows learning to be done while minimizing financial constraints and safety concerns.

[0938] A "high-resolution camera" is an optical device that can capture detailed images.

[0939] "Surrounding visual information" refers to all images and videos of the environment captured by the camera.

[0940] A "microphone" is an audio device used to pick up surrounding sounds.

[0941] "Ambient audio information" refers to all sounds in the environment picked up by the microphone.

[0942] "OCR technology" stands for optical character recognition technology, which extracts character information from an image as text data.

[0943] "Voice recognition technology" is a technology that analyzes voice data and converts it into text data.

[0944] "Text information" refers to all character data extracted or converted using OCR or voice recognition technology.

[0945] "Machine translation technology" is technology that automatically translates text from one language to another.

[0946] "Augmented reality technology" is a technology that overlays computer-generated information on real-world information.

[0947] "Speech synthesis technology" is a technology that converts text data into voice data.

[0948] A "server" is a high-performance computer system used for analyzing, processing, and storing data.

[0949] "Terminal" refers to any device or equipment operated by a user.

[0950] This invention is a system that allows users to experience a foreign language environment while in Japan using a "language conversion mask." The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, and a user interface.

[0951] Hardware Configuration

[0952] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, and headphones. The device transmits the acquired information to a server in real time.

[0953] Server: A high-performance computer system that analyzes and translates the visual and audio information sent from the device. The server processes the information using OCR and voice recognition technology and sends the translation results back to the device.

[0954] Interface: A user interface allows for easy configuration changes, such as changing the target language, adjusting the volume, or turning certain features on or off.

[0955] Software Configuration

[0956] OCR technology: Used to extract text information from video data. For example, Tesseract can be used as a common OCR library.

[0957] Speech recognition technology: Used to convert voice data collected by a microphone into text. For example, Google Cloud Speech-to-Text API can be used.

[0958] Machine translation technology: Used to translate text information into a foreign language. For example, the DeepL translation API and other machine translation services are available.

[0959] AR technology: Used to display translated text information as visual data in the user's field of view. For example, AR display can be achieved using the Unity engine.

[0960] Speech synthesis technology: Used to convert the translated text information into speech. For example, Amazon Polly can be used.

[0961] Specific examples

[0962] 1. Sign translation

[0963] User: Walking around town.

[0964] Terminal: The camera takes a picture of the sign and sends the video data to the server.

[0965] Server: Extract the text from the sign using Tesseract OCR, translate it from Japanese to English using the DeepL translation API, and convert the translation results into AR display data using Unity.

[0966] Device: The translation results are displayed overlaid on the AR display.

[0967] 2. Conversation Translation

[0968] User: Places an order at a restaurant.

[0969] Terminal: Records conversation with the waiter using a microphone and sends the audio data to the server.

[0970] Server: Use Google Cloud Speech-to-Text to convert speech to text, then use the DeepL translation API to translate from Japanese to English, then use Amazon Polly to convert the translation back to speech.

[0971] Device: Play the translated audio through headphones.

[0972] Examples of prompt statements

[0973] "I found a sign in the city. Please translate the Japanese text into English."

[0974] "I want to order at a restaurant. Please translate what the waiter is saying into English."

[0975] This system allows users to efficiently learn a foreign language while experiencing a foreign language environment in real time. The system supports practical foreign language learning while minimizing financial constraints and safety concerns.

[0976] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0977] Step 1:

[0978] User: Starts the system. Puts on the language conversion mask and presses the "Start" button using the built-in interface. At this point, the target language and volume settings are also loaded.

[0979] Step 2:

[0980] Device: The mask's built-in high-resolution camera and microphone begin working. The camera captures the surrounding video and the microphone collects the surrounding audio. Specifically, the camera captures video data at 1080p resolution, and the noise-canceling microphone captures audio data.

[0981] Step 3:

[0982] Terminal: The acquired visual and audio information is sent to the server in real time. The data is compressed; for example, video data is compressed using H.264, and audio data is compressed using AAC.

[0983] Step 4:

[0984] Server: Analyzes video data received from the device using OCR technology. Specifically, it uses Tesseract OCR to detect characters in the image and extract them as text data. The input is video data, and the output is text data containing character information.

[0985] Step 5:

[0986] Server: Analyzes the received voice data using speech recognition technology. Specifically, it converts the voice data into text data using the Google Cloud Speech-to-Text API. The input is voice data, and the output is text data containing the voice content.

[0987] Step 6:

[0988] Server: The extracted and converted text data is translated using machine translation technology. Specifically, the DeepL translation API is used to translate Japanese text into any foreign language. The input is Japanese text data, and the output is text data in the foreign language.

[0989] Step 7:

[0990] Server: Converts the translated text data into visual data and audio data. The visual data is formatted to be displayed in the user's field of view using AR technology, and the audio data is converted into audio data using speech synthesis technology. Specifically, AR display data is generated using Unity, and audio data is generated using Amazon Polly. The input is text data in a foreign language, and the output is visual data and audio data.

[0991] Step 8:

[0992] Device: The visual data sent from the server is displayed on the AR display. Specifically, a high-resolution see-through display is used to overlay the translated text onto the real world. The audio data is also played back through headphones. Specifically, high-quality Bluetooth headphones are used to play the audio. This allows the user to confirm the translated information both visually and audibly.

[0993] (Application example 1)

[0994] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0995] In modern society, the difficulty of communicating in a foreign language environment is a barrier to economic activity and daily life. In particular, foreign customers in brick-and-mortar stores face difficulties in understanding product information and communicating smoothly with store staff. Existing translation systems often lack real-time performance and accuracy, and require time-consuming configuration changes. Therefore, a more effective and intuitive system is needed.

[0996] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0997] In this invention, the server includes means for acquiring surrounding visual information using a high-resolution camera, means for acquiring surrounding audio information using a microphone, means for translating product labels, and means for translating conversations between users and store clerks, thereby providing an environment in the store where customers can smoothly understand product information in foreign languages ​​and communicate with store clerks.

[0998] A "high-resolution camera" is a photographing device that can acquire visual information at high resolution.

[0999] A "microphone" is a device for acquiring surrounding audio information.

[1000] "Visual information" refers to video data captured by a camera.

[1001] "Audio information" refers to sound data captured by a microphone.

[1002] "Text information" refers to text data contained in visual information.

[1003] "Voice recognition technology" is a technology that analyzes voice information and converts it into text data.

[1004] "Text information" refers to character data extracted using voice recognition technology or OCR (Optical Character Recognition) technology.

[1005] A "foreign language" is a language other than the one the user understands.

[1006] "Translating" is the act of converting meaning from one language to another.

[1007] "Augmented reality technology" is a technology that displays computer-generated information overlaid on visual information.

[1008] "Speech synthesis means" refers to a device or technology that converts text data into speech and plays it back.

[1009] A "product label" is a label attached to a product to display information.

[1010] A "conversation" is any oral communication between two or more people.

[1011] A "server" is a remote computer system that processes data sent from a terminal and returns the necessary information.

[1012] An "interface" is an operating means by which a user changes system settings.

[1013] "Target language" refers to the language in which the translated results will be displayed.

[1014] "Volume" refers to the volume of the sound, and can be adjusted by the user.

[1015] The "specific function on / off setting" refers to a setting that allows the user to enable or disable a function that the user wants to use.

[1016] The system for implementing this invention has a specific configuration for providing a foreign language environment in a brick-and-mortar store. The system is composed of the following hardware and software.

[1017] Hardware Configuration

[1018] 1. High-resolution camera: This captures visual information such as product labels and in-store signs.

[1019] 2. Microphone: Captures surrounding audio information, especially conversations with store staff.

[1020] 3. AR display: The acquired and translated text information is displayed using augmented reality technology.

[1021] 4. Headphones: A device that allows the user to hear the translated audio information.

[1022] 5. Server: A computer system for analyzing and translating visual and audio information sent from the terminal.

[1023] Software Configuration

[1024] 1. OCR technology (Pytesseract): A technology for extracting text information from visual information acquired by a high-resolution camera.

[1025] 2. Speech Recognition: Technology for converting voice information obtained through a microphone into text.

[1026] 3. Machine translation technology (Googletrans): Technology for translating extracted and converted text information into a foreign language.

[1027] 4. Speech synthesis technology (Pyttsx3): Technology for converting translated text information into speech and playing it back.

[1028] 5. User Interface: The means of operation that allows users to easily change settings, including switching target languages, adjusting volume, and turning certain features on or off.

[1029] Specific operation of the system

[1030] Product label translation: When a user takes a photo of a product label with their smartphone camera, the high-resolution camera captures visual information. The device sends this information to a server, where text information is extracted using OCR technology. The information is then translated into the selected foreign language using machine translation technology, and the translation results are displayed on an AR display using augmented reality technology.

[1031] Translation of conversations with store clerks: When a user records a conversation with a store clerk using a microphone, the audio information is sent to the server. It is converted into text using speech recognition technology and translated using machine translation technology. The translation result is then converted back into text and played back using speech synthesis technology.

[1032] Specific examples

[1033] For example, if a user wants to translate a product label in a physical store that says "Milk" into English:

[1034] Take a photo of the product label with your smartphone camera.

[1035] The server extracts the text information "Milk" from the visual information and translates it into English "Milk."

[1036] The translated result will be displayed as "Milk" on the AR display.

[1037] Or, if you want to translate a conversation in a physical store where a user says "hello" in Japanese into English:

[1038] The conversation is recorded and sent to a server.

[1039] The server uses speech recognition technology to convert the text "Hello" into the English "Hello."

[1040] Play the translated audio through headphones.

[1041] Prompt Sentence Examples

[1042] "Please translate the foreign language signs in the store into English."

[1043] "Please translate this recorded conversation into English and play it back."

[1044] As a result, this system is designed to enable users to smoothly understand product information and communicate with store clerks even in a foreign language environment.

[1045] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1046] Step 1:

[1047] The user takes a photo of the product label with their smartphone camera.

[1048] Input: Product label image.

[1049] Specific operation: The user uses the smartphone camera to take a picture of the product label.

[1050] Step 2:

[1051] The device uses a high-resolution camera to capture visual information about the surroundings.

[1052] Input: A product label image taken by a camera.

[1053] Output: Retrieved visual information (product label image).

[1054] Specific operation: The device uses the camera to take an image of the product label and collect visual information.

[1055] Step 3:

[1056] The visual information acquired by the terminal is sent to the server.

[1057] Input: Product label image.

[1058] Output: Sending visual information (product label image) to the server.

[1059] Specific operation: The product label image acquired by the terminal is sent to the server via the network.

[1060] Step 4:

[1061] The server uses OCR technology to extract text information from the visual information.

[1062] Input: Product label image sent to the server.

[1063] Output: Extracted character information (text data).

[1064] Specific operation: The server uses Pytesseract to analyze the characters in the product label image and extract them as text data.

[1065] Step 5:

[1066] The server translates the extracted text information into a foreign language using machine translation technology.

[1067] Input: Extracted character information (text data).

[1068] Output: Translated text information (translated text data).

[1069] Specific operation: The server uses Google Translate to translate the text data into the set target language.

[1070] Step 6:

[1071] The server sends the translation results to the terminal.

[1072] Input: Translated text information (translated text data).

[1073] Output: Sending the translation results to your device.

[1074] Specific operation: The server sends the translated text information back to the terminal via the network.

[1075] Step 7:

[1076] The device retrieves the translated text information and displays it on the AR display.

[1077] Input: Translated text information (translated text data).

[1078] Output: Translation results displayed on the AR display.

[1079] Specific operation: The translation results received by the device are displayed on the screen using AR technology, superimposed on the user's field of view.

[1080] Step 8:

[1081] The user checks the displayed translation results.

[1082] Input: Translation result displayed on the AR display.

[1083] Output: Product information in a foreign language that the user can understand.

[1084] Specific operation: The user checks the translated product information through the AR display on their smartphone.

[1085] Through these steps, users can access foreign language translations of product labels in real time in physical stores, facilitating smooth shopping in a foreign language environment.

[1086] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1087] This invention is a system that uses a "language conversion mask" to allow users to experience a foreign language environment while in Japan, and also recognizes and reflects the user's emotional state. The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, an emotion engine, and a user interface.

[1088] 1. Hardware Configuration

[1089] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, headphones, and an emotion engine. The device transmits the acquired information to a server in real time.

[1090] Server: A computer system that analyzes and translates visual information, audio information, and emotional data sent from the device. The server processes the information using OCR, speech recognition, and emotion analysis technologies, and sends the translation results back to the device.

[1091] Interface: Provides controls that allow users to easily change settings, such as changing the target language, adjusting the volume, or turning certain features on or off.

[1092] 2. Program processing explanation

[1093] Device: After putting on the mask, the user activates the device. The device immediately activates its high-resolution camera and microphone to collect surrounding visual information, audio information, and the user's facial expression data. The emotion engine analyzes the user's emotional state from their facial expressions and tone of voice.

[1094] Server: Receives the video data and facial expression data sent from the device. The server first uses OCR technology to recognize the characters in the video image and extract text information. Next, it uses voice recognition technology to convert the audio data into text.

[1095] Server: Translates the extracted text and speech-to-text information into the specified foreign language. It can provide adaptive feedback to the translation results based on the user's emotional data recognized by the emotion engine. For example, if the user is confused, the server will provide a translation using simpler expressions.

[1096] Server: The translated text data is separated into visual data and audio data. The visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[1097] Device: Visual data sent from the server is displayed on the AR display and superimposed on the user's field of view. Audio data is played back so that the user can hear it through headphones.

[1098] 3. Example of a system

[1099] Example 1: Sign translation and emotional adaptation

[1100] User: Walking around town.

[1101] Terminal: The camera takes a picture of the sign and sends the video data to the server. The emotion engine analyzes the user's facial expressions to determine their emotions.

[1102] Server: Uses OCR technology to recognize and translate the characters on the sign. If it detects that the user is confused, it provides a simple translation. It then sends the translation results back to the device.

[1103] On your device: The translated text will be overlaid on the AR display.

[1104] Example 2: Dialogue translation and emotional adaptation

[1105] User: Places an order at a restaurant.

[1106] Device: The microphone records the conversation with the waiter and sends the audio data to the server. The emotion engine analyzes the emotion from the tone of the user's voice.

[1107] Server: Converts conversations into text using speech recognition technology and translates them. If the user feels unsure, provides a translation with words of encouragement. Synthesizes speech and sends it to the device.

[1108] Device: Play the translated audio through headphones.

[1109] Through these processes, users can learn a foreign language efficiently while experiencing a foreign language environment that adapts to their emotional state. This system reduces the user's mental burden and provides a more natural learning experience.

[1110] The processing flow will be explained below.

[1111] Step 1:

[1112] User: Put on the mask and turn it on. The device will automatically connect to the server.

[1113] Step 2:

[1114] Device: Activate the mask's high-resolution camera, microphone, and emotion engine to begin collecting surrounding visual and audio information and the user's facial expression data.

[1115] Step 3:

[1116] Terminal: Collected visual, audio, and facial expression data is sent to the server in real time.

[1117] Step 4:

[1118] Server: Analyzes the received video data using OCR technology and extracts text information from the image.

[1119] Step 5:

[1120] Server: Converts the received voice data into text using voice recognition technology.

[1121] Step 6:

[1122] Server: Uses the emotion engine to analyze the received facial expression data and recognize the user's emotional state.

[1123] Step 7:

[1124] Server: Translates the extracted text and speech into the specified foreign language. It adjusts the translation results based on the user's emotional state. For example, if the user is confused, it uses simpler expressions.

[1125] Step 8:

[1126] Server: The translated text data is divided into visual data and audio data. The visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[1127] Step 9:

[1128] Server: Sends the translation results to the device.

[1129] Step 10:

[1130] Device: The translated visual data is applied to the AR display and overlaid on the real-world image.

[1131] Step 11:

[1132] Device: Play the translated audio data through headphones.

[1133] Step 12:

[1134] Terminal: New visual, audio and facial expression data is continuously acquired and sent to the server for real-time updates.

[1135] Step 13:

[1136] Server: Always analyzes and translates the latest data and sends it to the device.

[1137] Step 14:

[1138] User: Uses the interface to change the target language, adjust the volume, and turn certain features on or off.

[1139] Example 2

[1140] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1141] Currently, many language translation systems do not consider the user's emotional state when experiencing a foreign language environment, which can lead to confusion and stress. Furthermore, conventional translation systems do not perform the process from collecting visual and audio information to displaying the translation results in real time, making them difficult to use in situations where immediate response is required. This makes it difficult to improve the user's learning efficiency and the quality of their foreign language experience.

[1142] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing the user's facial expression and tone of voice to recognize the emotional state, means for adding adaptive feedback to the translation result based on the recognized emotional state, and means for analyzing the acquired visual information and audio information and translating it into a foreign language. This enables real-time translation adapted to the user's emotional state.

[1143] A "high-resolution camera" refers to a high-resolution camera that can capture detailed visual information about the surroundings.

[1144] "Microphone" refers to an acoustic sensor for collecting surrounding sound information.

[1145] "Visual information" refers to image data of the surroundings acquired through a high-resolution camera.

[1146] "Audio information" refers to ambient audio data collected through a microphone.

[1147] "Text information" refers to text data extracted from acquired visual information.

[1148] "Speech recognition technology" refers to the technology that analyzes acquired voice information and converts it into text data.

[1149] "Foreign language" refers to any non-native language that is configured for the user to experience.

[1150] "Augmented reality technology" refers to technology that displays virtual information overlaid on real visual information.

[1151] "Speech synthesis means" refers to technology that converts text data into voice data and plays it back.

[1152] "Emotional state" refers to the psychological state of a user as perceived from their facial expression and tone of voice.

[1153] "Feedback" refers to a response that makes adaptive modifications to the translation result based on a perceived emotional state.

[1154] "User interface" refers to the operating means by which a user can change system settings.

[1155] The term "server" refers to a computer system that analyzes acquired data and performs translation and feedback processing.

[1156] "Device" refers to a device equipped with a high-resolution camera, microphone, AR display, headphones, and emotion engine.

[1157] This invention is a system that uses a "language conversion mask" to allow users to experience a foreign language environment while in Japan, and also recognizes and reflects the user's emotional state. The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, an emotion engine, and a user interface.

[1158] Hardware Configuration

[1159] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, headphones, and an emotion engine. The device transmits the acquired information to a server in real time.

[1160] Server: A computer system that analyzes and translates visual information, audio information, and emotional data sent from the device. The server processes the information using OCR, speech recognition, and emotion analysis technologies, and sends the translation results back to the device.

[1161] Interface: Provides controls that allow users to easily change settings, such as changing the target language, adjusting the volume, or turning certain features on or off.

[1162] Program processing explanation

[1163] Device: After putting on the mask, the user activates the device. The device immediately activates its high-resolution camera and microphone to collect surrounding visual information, audio information, and the user's facial expression data. The emotion engine analyzes the user's emotional state from their facial expressions and tone of voice.

[1164] Server: Receives the video data and facial expression data sent from the device. The server first uses OCR technology to recognize the characters in the video image and extract text information. Next, it uses voice recognition technology to convert the audio data into text.

[1165] The extracted text information and speech-to-text information are translated into the specified foreign language. Adaptive feedback can be added to the translation results based on the user's emotional data recognized by the emotion engine. For example, if the user is confused, the server will provide a translation using simpler expressions.

[1166] The translated text data is divided into visual data and audio data, the visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[1167] Device: Visual data sent from the server is displayed on the AR display and superimposed on the user's field of view. Audio data is played back so that the user can hear it through headphones.

[1168] Example of a system

[1169] Example 1: Sign translation and emotional adaptation

[1170] User: Walking around town.

[1171] Terminal: The camera takes a picture of the sign and sends the video data to the server. The emotion engine analyzes the user's facial expressions to determine their emotions.

[1172] Server: Uses OCR technology to recognize and translate the characters on the sign. If it detects that the user is confused, it provides a simple translation. It then sends the translation results back to the device.

[1173] On your device: The translated text will be overlaid on the AR display.

[1174] Example 2: Dialogue translation and emotional adaptation

[1175] User: Places an order at a restaurant.

[1176] Device: The microphone records the conversation with the waiter and sends the audio data to the server. The emotion engine analyzes the emotion from the tone of the user's voice.

[1177] Server: Converts conversations into text using speech recognition technology and translates them. If the user feels unsure, provides a translation with words of encouragement. Synthesizes speech and sends it to the device.

[1178] Device: Play the translated audio through headphones.

[1179] This allows the user to efficiently learn a foreign language while experiencing an adaptive foreign language environment that corresponds to the user's emotional state.

[1180] Example prompts to input to the generative AI model

[1181] "Generate examples of sign translations and emotional adaptations. Provide a simple translation if the user is confused."

[1182] "Generate translations and emotional adaptation examples for conversations at a restaurant. If the user feels unsure, provide a translation with encouraging words."

[1183] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1184] Step 1: User puts on mask and starts the system

[1185] User: Put on the mask-type device and turn on the system.

[1186] Device: High-resolution camera, microphone, AR display, headphones, and emotion engine activated.

[1187] Input: Mask activation signal.

[1188] Output: Initial startup completion signal for various sensors and start of operation.

[1189] Step 2: Collect visual, audio, and emotional data

[1190] Device: A high-resolution camera captures visual information of the surroundings, a microphone collects audio information, and an emotion engine analyzes the user's facial expressions and tone of voice in real time to generate emotional state data.

[1191] Input: User's visual, audio, and facial expressions.

[1192] Output: captured images, recorded audio, and analyzed emotion data.

[1193] Step 3: Sending visual, audio, and emotional data

[1194] Terminal: Collected visual, audio, and emotional data is sent to the server in real time.

[1195] Input: captured images, recorded audio, and analyzed emotion data.

[1196] Output: The data sent to the server.

[1197] Step 4: Data analysis by the server (OCR, speech recognition, emotion analysis)

[1198] Server: Analyzes received visual information using OCR technology, recognizes characters in images, and extracts text information. It also converts received audio information into text data using speech recognition technology, and analyzes emotional data.

[1199] Input: Transmitted visual, audio, and emotional data.

[1200] Output: Extracted text information, transcribed audio information, and analyzed emotion data.

[1201] Step 5: Translation process

[1202] Server: Translates the extracted text information and speech-to-text information into a preset foreign language.

[1203] Input: Extracted text and transcribed audio information.

[1204] Output: Translated text information and translated audio information.

[1205] Step 6: Adding adaptive feedback

[1206] Server: Adds adaptive feedback to translation results based on recognized emotion data. For example, if the user is confused, the server provides translation results with simple expressions.

[1207] Input: Translated text information and parsed sentiment data.

[1208] Output: The final translation result with added feedback.

[1209] Step 7: Format and distribute data

[1210] Server: The translated text data is separated into visual data and audio data. The visual data is formatted for the AR display, and the audio data is converted into audio data using speech synthesis technology and sent to the device.

[1211] Input: The final translation result.

[1212] Output: AR display data and audio data.

[1213] Step 8: View and play back translation results

[1214] Device: Visual data sent from the server is displayed on the AR display, and audio data is played through headphones.

[1215] Input: Visual and audio data sent from the server.

[1216] Output: The textual information displayed to the user's eyes and the audio information played.

[1217] (Application example 2)

[1218] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1219] Foreign tourists often have difficulty understanding Japanese when shopping in brick-and-mortar stores in Japan. This limited understanding of product labels and conversations with store clerks limits their shopping experience. This issue needs to be resolved to enable foreign tourists to enjoy shopping more comfortably and smoothly. It is also necessary to provide appropriate feedback based on the user's emotional state.

[1220] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1221] In this invention, the server includes means for acquiring visual information of the surroundings using a high-resolution camera, means for acquiring audio information of the surroundings using a microphone, means for analyzing the acquired visual information and extracting text information, means for converting the acquired audio information into text using speech recognition technology, means for translating the extracted and converted text information into any foreign language, means for displaying the translated text information using augmented reality technology, means for synthesizing the voice to play back the translated audio information, means for analyzing the user's facial expression and tone of voice to recognize their emotional state, and means for adaptively feeding back the translation result in accordance with the recognized emotional state. This not only enables foreign tourists to enjoy shopping in brick-and-mortar stores, but also allows them to receive more personalized service by providing feedback in accordance with the user's emotions.

[1222] A "high-resolution camera" is a camera that can capture very detailed visual information.

[1223] A "microphone" is a device that captures surrounding sounds.

[1224] "Visual information" refers to video data acquired through a visual device such as a camera.

[1225] "Audio information" is audio data acquired through an audio device such as a microphone.

[1226] "Means for extracting character information" refers to technology or equipment that recognizes and extracts characters from visual information.

[1227] "Speech recognition technology" is a technology that converts acquired voice information into text data.

[1228] "Means for translating into a foreign language" refers to a technique or device that converts extracted or converted text information into another language.

[1229] "Augmented reality technology" is a technology that displays virtual information overlaid on real images.

[1230] "Speech synthesis means" refers to a technology or device that converts translated text information into speech and plays it back.

[1231] A "means for recognizing an emotional state" is a technology or device that analyzes a user's facial expressions and tone of voice to determine their emotions.

[1232] An "adaptive feedback mechanism" is a technique or device that provides context-sensitive responses or information based on a perceived emotional state.

[1233] This system eliminates the barriers that foreign tourists face when shopping in brick-and-mortar stores in Japan, allowing them to enjoy shopping comfortably and smoothly. Specifically, the system includes a high-resolution camera, a microphone, a server, an augmented reality display, headphones, an emotion analysis engine, and a user interface.

[1234] First, the smart glasses worn by the user are equipped with a high-resolution camera, microphone, augmented reality display, headphones, and an emotion analysis engine, which allows them to acquire visual and audio information from the surroundings in real time and send it to a server.

[1235] The server analyzes the visual and audio information sent from the device and performs the necessary translation processing. Specifically, the following technologies are used:

[1236] OCR technology (such as Google Cloud Vision API): Extracts characters from visual information acquired by a high-resolution camera and converts them into text data.

[1237] Speech recognition technology (such as Google Cloud Speech-to-Text): Converts voice information captured by a microphone into text data.

[1238] Translation technology (such as Google Cloud Translate API): Translates acquired text data into the specified foreign language.

[1239] Speech synthesis technology (such as Google Cloud Text-to-Speech): Converts translated text data into audio data.

[1240] Emotion analysis engine (such as Microsoft Azure Emotion API): Analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[1241] Furthermore, the system provides adaptive feedback based on the user's emotional state. For example, if the user is confused, the system can provide simpler and more polite translations and add words of encouragement, allowing the user to enjoy shopping with peace of mind.

[1242] The following are some examples of specific usage scenarios:

[1243] Example 1: Product label translation

[1244] The user wears the smart glasses and takes a picture of a product label in the store with the camera. The server uses OCR technology to recognize the text on the label and translates it. The translation result is displayed on an augmented reality display, allowing the user to check the product information.

[1245] Example 2: Translation of a conversation with a store clerk

[1246] When a user asks a question at the cash register, a microphone records the conversation and sends the audio data to a server. The server then uses speech recognition technology to convert the conversation into text and translate it. An emotion analysis engine analyzes the user's facial expressions and provides translation results, including encouraging words, if the user appears nervous. The translation results are then played through headphones using speech synthesis technology.

[1247] Example prompts for generative AI models

[1248] "Create an application that uses smart glasses to enable foreign tourists to shop in brick-and-mortar stores without understanding Japanese. It should have real-time translation functions, conversation translation functions, and the ability to analyze the user's emotional state and provide feedback. For example, it should translate product labels and directions, and translate conversations with store clerks."

[1249] This system will enable foreign tourists to enjoy shopping in Japan without having to worry about language barriers, while also enabling stores to improve customer satisfaction.

[1250] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1251] Step 1:

[1252] A user puts on the smart glasses and starts the device. The device activates the camera and microphone to capture visual and audio information from the surroundings in real time.

[1253] Input: The user puts on the smart glasses and activates them.

[1254] Output: Visual information captured by a high-resolution camera and audio information recorded by a microphone.

[1255] Step 2:

[1256] The visual and audio information acquired by the device is sent to the server. The visual information is sent as image data, and the audio information is sent as audio data.

[1257] Input: Acquired visual and audio information.

[1258] Output: Image and audio data sent to the server.

[1259] Step 3:

[1260] The server extracts text information from the visual information using OCR technology (e.g., Google Cloud Vision API), analyzes the image data, and generates text data.

[1261] Input: Image data sent from the device.

[1262] Output: The extracted text data.

[1263] Step 4:

[1264] The server converts the voice information into text data using voice recognition technology (e.g., Google Cloud Speech-to-Text), analyzes the voice data, and generates text data.

[1265] Input: Audio data sent from the device.

[1266] Output: Text data converted from audio information.

[1267] Step 5:

[1268] The server translates the acquired and converted text data into any foreign language using translation technology (e.g., Google Cloud Translate API), and then converts the acquired text data into the target language.

[1269] Input: Text data obtained using OCR and speech recognition technologies.

[1270] Output: The translated text data.

[1271] Step 6:

[1272] The server recognizes the user's emotional state using an emotion analysis engine (e.g., Microsoft Azure Emotion API). It analyzes the user's facial expression data and tone of voice to identify the user's emotional state.

[1273] Input: User's facial expression data and tone of voice.

[1274] Output: Perceived emotional state.

[1275] Step 7:

[1276] The server adaptively provides feedback on the translation results based on the recognized emotional state, for example, generating feedback using simple translation expressions if the user is confused.

[1277] Input: translated text data and recognized emotional state.

[1278] Output: Adaptive translation results.

[1279] Step 8:

[1280] The server separates the data into visual and audio data, formats the visual data so that it can be displayed using augmented reality technology, and converts the audio data into audio using voice synthesis technology (e.g., Google Cloud Text-to-Speech).

[1281] Input: Adaptive translation result data.

[1282] Output: Display and audio data for augmented reality.

[1283] Step 9:

[1284] The device displays the visual data sent from the server on an augmented reality display and plays the audio data through headphones, allowing the user to receive the translated information visually and audibly.

[1285] Input: Visual and audio data sent from the server.

[1286] Output: Translation information displayed on the augmented reality display and translated audio played through headphones.

[1287] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1288] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1289] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1290] [Fourth embodiment]

[1291] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1292] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1293] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1294] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1295] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1296] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1297] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1298] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1299] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1300] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1301] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1302] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1303] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1304] This invention is a system that allows users to experience a foreign language environment while in Japan using a "language conversion mask." The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, and a user interface.

[1305] 1. Hardware Configuration

[1306] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, and headphones. The device transmits the acquired information to a server in real time.

[1307] Server: An advanced computer system that analyzes and translates the visual and audio information sent from the device. The server processes the information using OCR and speech recognition technology and sends the translation results back to the device.

[1308] Interface: A user interface allows for easy configuration changes, such as changing the target language, adjusting the volume, or turning certain features on or off.

[1309] 2. Program processing explanation

[1310] Device: After putting on the mask, the user activates the device, which immediately activates the high-resolution camera and microphone and begins collecting visual and audio information from the surrounding area.

[1311] Server: Receives the video and audio data sent from the device. The server first uses OCR technology to recognize the characters in the video image and extract the text information. Next, it uses voice recognition technology to convert the audio data into text.

[1312] Server: The server receives the text information and translates it into a pre-defined foreign language. The translation process uses machine translation technology, and in some cases may also involve the assistance of bilingual experts.

[1313] Server: The translated text data is divided into visual data and audio data. The visual data is formatted using AR technology to be displayed in the user's field of vision, and the audio data is converted into audio using speech synthesis technology.

[1314] Device: Visual data sent from the server is displayed on the AR display and superimposed on the user's field of view. Audio data is played back so that the user can hear it through headphones.

[1315] 3. Example of a system

[1316] Example 1: Sign translation

[1317] User: Walking around town.

[1318] Terminal: The camera takes a picture of the sign and sends the video data to the server.

[1319] Server: Uses OCR technology to recognize and translate the characters on the sign, then sends the translation results back to the device.

[1320] On your device: The translated text will be overlaid on the AR display.

[1321] Example 2: Conversation translation

[1322] User: Places an order at a restaurant.

[1323] Terminal: Records conversation with the waiter using a microphone and sends the audio data to the server.

[1324] Server: Converts conversations into text using speech recognition technology and translates them. The translation results are then converted back into text data and used for speech synthesis.

[1325] Device: Play the translated audio through headphones.

[1326] This system allows users to efficiently learn a foreign language while experiencing a foreign language environment in real time, without having to study abroad. This system supports practical foreign language learning while minimizing financial constraints and safety concerns.

[1327] The processing flow will be explained below.

[1328] Step 1:

[1329] User: Put on the mask and turn it on. The device will automatically connect to the server.

[1330] Step 2:

[1331] Device: Activate the mask's high-resolution camera and microphone and begin collecting visual and audio information from the surrounding area.

[1332] Step 3:

[1333] Terminal: Transmits the acquired visual and audio information to the server in real time.

[1334] Step 4:

[1335] Server: Analyzes the received video data using OCR technology and extracts text information from the image.

[1336] Step 5:

[1337] Server: At the same time, the received voice data is converted into text using voice recognition technology.

[1338] Step 6:

[1339] Server: Translates the extracted character information and speech-to-text information into the specified foreign language.

[1340] Step 7:

[1341] Server: The translated text information is divided into visual data and audio data. The visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[1342] Step 8:

[1343] Server: Sends the translation results to the device.

[1344] Step 9:

[1345] Device: The translated visual data is applied to the AR display and overlaid on the real-world image.

[1346] Step 10:

[1347] Device: Play the translated audio data through headphones.

[1348] Step 11:

[1349] Terminal: New visual and audio information is continuously acquired and sent to the server for real-time updates.

[1350] Step 12:

[1351] Server: Always analyzes and translates the latest data and sends it to the device.

[1352] Step 13:

[1353] User: Uses the interface to change the target language, adjust the volume, and turn certain features on or off.

[1354] Example 1

[1355] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1356] Currently, learning a foreign language requires studying abroad or using specialized learning tools, which is time-consuming and expensive. Furthermore, there are limited ways to experience a foreign language environment in real time, making practical learning difficult. Furthermore, fear of the foreign language can also be an obstacle to learning. Because traditional foreign language learning methods cannot effectively solve these problems, new learning methods are needed.

[1357] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1358] In this invention, the server includes a means for analyzing video data and audio data and applying OCR and speech recognition technologies, a means for translating text information into a foreign language using machine translation technology, and a means for displaying visual data in the user's field of view using AR technology. This allows users to experience a foreign language environment in real time, enabling efficient and practical foreign language learning. This also allows learning to be done while minimizing financial constraints and safety concerns.

[1359] A "high-resolution camera" is an optical device that can capture detailed images.

[1360] "Surrounding visual information" refers to all images and videos of the environment captured by the camera.

[1361] A "microphone" is an audio device used to pick up surrounding sounds.

[1362] "Ambient audio information" refers to all sounds in the environment picked up by the microphone.

[1363] "OCR technology" stands for optical character recognition technology, which extracts character information from an image as text data.

[1364] "Voice recognition technology" is a technology that analyzes voice data and converts it into text data.

[1365] "Text information" refers to all character data extracted or converted using OCR or voice recognition technology.

[1366] "Machine translation technology" is technology that automatically translates text from one language to another.

[1367] "Augmented reality technology" is a technology that overlays computer-generated information on real-world information.

[1368] "Speech synthesis technology" is a technology that converts text data into voice data.

[1369] A "server" is a high-performance computer system used for analyzing, processing, and storing data.

[1370] "Terminal" refers to any device or equipment operated by a user.

[1371] This invention is a system that allows users to experience a foreign language environment while in Japan using a "language conversion mask." The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, and a user interface.

[1372] Hardware Configuration

[1373] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, and headphones. The device transmits the acquired information to a server in real time.

[1374] Server: A high-performance computer system that analyzes and translates the visual and audio information sent from the device. The server processes the information using OCR and voice recognition technology and sends the translation results back to the device.

[1375] Interface: A user interface allows for easy configuration changes, such as changing the target language, adjusting the volume, or turning certain features on or off.

[1376] Software Configuration

[1377] OCR technology: Used to extract text information from video data. For example, Tesseract can be used as a common OCR library.

[1378] Speech recognition technology: Used to convert voice data collected by a microphone into text. For example, Google Cloud Speech-to-Text API can be used.

[1379] Machine translation technology: Used to translate text information into a foreign language. For example, the DeepL translation API and other machine translation services are available.

[1380] AR technology: Used to display translated text information as visual data in the user's field of view. For example, AR display can be achieved using the Unity engine.

[1381] Speech synthesis technology: Used to convert the translated text information into speech. For example, Amazon Polly can be used.

[1382] Specific examples

[1383] 1. Sign translation

[1384] User: Walking around town.

[1385] Terminal: The camera takes a picture of the sign and sends the video data to the server.

[1386] Server: Extract the text from the sign using Tesseract OCR, translate it from Japanese to English using the DeepL translation API, and convert the translation results into AR display data using Unity.

[1387] Device: The translation results are displayed overlaid on the AR display.

[1388] 2. Conversation Translation

[1389] User: Places an order at a restaurant.

[1390] Terminal: Records conversation with the waiter using a microphone and sends the audio data to the server.

[1391] Server: Use Google Cloud Speech-to-Text to convert speech to text, then use the DeepL translation API to translate from Japanese to English, then use Amazon Polly to convert the translation back to speech.

[1392] Device: Play the translated audio through headphones.

[1393] Examples of prompt statements

[1394] "I found a sign in the city. Please translate the Japanese text into English."

[1395] "I want to order at a restaurant. Please translate what the waiter is saying into English."

[1396] This system allows users to efficiently learn a foreign language while experiencing a foreign language environment in real time. The system supports practical foreign language learning while minimizing financial constraints and safety concerns.

[1397] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1398] Step 1:

[1399] User: Starts the system. Puts on the language conversion mask and presses the "Start" button using the built-in interface. At this point, the target language and volume settings are also loaded.

[1400] Step 2:

[1401] Device: The mask's built-in high-resolution camera and microphone begin working. The camera captures the surrounding video and the microphone collects the surrounding audio. Specifically, the camera captures video data at 1080p resolution, and the noise-canceling microphone captures audio data.

[1402] Step 3:

[1403] Terminal: The acquired visual and audio information is sent to the server in real time. The data is compressed; for example, video data is compressed using H.264, and audio data is compressed using AAC.

[1404] Step 4:

[1405] Server: Analyzes video data received from the device using OCR technology. Specifically, it uses Tesseract OCR to detect characters in the image and extract them as text data. The input is video data, and the output is text data containing character information.

[1406] Step 5:

[1407] Server: Analyzes the received voice data using speech recognition technology. Specifically, it converts the voice data into text data using the Google Cloud Speech-to-Text API. The input is voice data, and the output is text data containing the voice content.

[1408] Step 6:

[1409] Server: The extracted and converted text data is translated using machine translation technology. Specifically, the DeepL translation API is used to translate Japanese text into any foreign language. The input is Japanese text data, and the output is text data in the foreign language.

[1410] Step 7:

[1411] Server: Converts the translated text data into visual data and audio data. The visual data is formatted to be displayed in the user's field of view using AR technology, and the audio data is converted into audio data using speech synthesis technology. Specifically, AR display data is generated using Unity, and audio data is generated using Amazon Polly. The input is text data in a foreign language, and the output is visual data and audio data.

[1412] Step 8:

[1413] Device: The visual data sent from the server is displayed on the AR display. Specifically, a high-resolution see-through display is used to overlay the translated text onto the real world. The audio data is also played back through headphones. Specifically, high-quality Bluetooth headphones are used to play the audio. This allows the user to confirm the translated information both visually and audibly.

[1414] (Application example 1)

[1415] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1416] In modern society, the difficulty of communicating in a foreign language environment is a barrier to economic activity and daily life. In particular, foreign customers in brick-and-mortar stores face difficulties in understanding product information and communicating smoothly with store staff. Existing translation systems often lack real-time performance and accuracy, and require time-consuming configuration changes. Therefore, a more effective and intuitive system is needed.

[1417] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1418] In this invention, the server includes means for acquiring surrounding visual information using a high-resolution camera, means for acquiring surrounding audio information using a microphone, means for translating product labels, and means for translating conversations between users and store clerks, thereby providing an environment in the store where customers can smoothly understand product information in foreign languages ​​and communicate with store clerks.

[1419] A "high-resolution camera" is a photographing device that can acquire visual information at high resolution.

[1420] A "microphone" is a device for acquiring surrounding audio information.

[1421] "Visual information" refers to video data captured by a camera.

[1422] "Audio information" refers to sound data captured by a microphone.

[1423] "Text information" refers to text data contained in visual information.

[1424] "Voice recognition technology" is a technology that analyzes voice information and converts it into text data.

[1425] "Text information" refers to character data extracted using voice recognition technology or OCR (Optical Character Recognition) technology.

[1426] A "foreign language" is a language other than the one the user understands.

[1427] "Translating" is the act of converting meaning from one language to another.

[1428] "Augmented reality technology" is a technology that displays computer-generated information overlaid on visual information.

[1429] "Speech synthesis means" refers to a device or technology that converts text data into speech and plays it back.

[1430] A "product label" is a label attached to a product to display information.

[1431] A "conversation" is any oral communication between two or more people.

[1432] A "server" is a remote computer system that processes data sent from a terminal and returns the necessary information.

[1433] An "interface" is an operating means by which a user changes system settings.

[1434] "Target language" refers to the language in which the translated results will be displayed.

[1435] "Volume" refers to the volume of the sound, and can be adjusted by the user.

[1436] The "specific function on / off setting" refers to a setting that allows the user to enable or disable a function that the user wants to use.

[1437] The system for implementing this invention has a specific configuration for providing a foreign language environment in a brick-and-mortar store. The system is composed of the following hardware and software.

[1438] Hardware Configuration

[1439] 1. High-resolution camera: This captures visual information such as product labels and in-store signs.

[1440] 2. Microphone: Captures surrounding audio information, especially conversations with store staff.

[1441] 3. AR display: The acquired and translated text information is displayed using augmented reality technology.

[1442] 4. Headphones: A device that allows the user to hear the translated audio information.

[1443] 5. Server: A computer system for analyzing and translating visual and audio information sent from the terminal.

[1444] Software Configuration

[1445] 1. OCR technology (Pytesseract): A technology for extracting text information from visual information acquired by a high-resolution camera.

[1446] 2. Speech Recognition: Technology for converting voice information obtained through a microphone into text.

[1447] 3. Machine translation technology (Googletrans): Technology for translating extracted and converted text information into a foreign language.

[1448] 4. Speech synthesis technology (Pyttsx3): Technology for converting translated text information into speech and playing it back.

[1449] 5. User Interface: The means of operation that allows users to easily change settings, including switching target languages, adjusting volume, and turning certain features on or off.

[1450] Specific operation of the system

[1451] Product label translation: When a user takes a photo of a product label with their smartphone camera, the high-resolution camera captures visual information. The device sends this information to a server, where text information is extracted using OCR technology. The information is then translated into the selected foreign language using machine translation technology, and the translation results are displayed on an AR display using augmented reality technology.

[1452] Translation of conversations with store clerks: When a user records a conversation with a store clerk using a microphone, the audio information is sent to the server. It is converted into text using speech recognition technology and translated using machine translation technology. The translation result is then converted back into text and played back using speech synthesis technology.

[1453] Specific examples

[1454] For example, if a user wants to translate a product label in a physical store that says "Milk" into English:

[1455] Take a photo of the product label with your smartphone camera.

[1456] The server extracts the text information "Milk" from the visual information and translates it into English "Milk."

[1457] The translated result will be displayed as "Milk" on the AR display.

[1458] Or, if you want to translate a conversation in a physical store where a user says "hello" in Japanese into English:

[1459] The conversation is recorded and sent to a server.

[1460] The server uses speech recognition technology to convert the text "Hello" into the English "Hello."

[1461] Play the translated audio through headphones.

[1462] Prompt Sentence Examples

[1463] "Please translate the foreign language signs in the store into English."

[1464] "Please translate this recorded conversation into English and play it back."

[1465] As a result, this system is designed to enable users to smoothly understand product information and communicate with store clerks even in a foreign language environment.

[1466] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1467] Step 1:

[1468] The user takes a photo of the product label with their smartphone camera.

[1469] Input: Product label image.

[1470] Specific operation: The user uses the smartphone camera to take a picture of the product label.

[1471] Step 2:

[1472] The device uses a high-resolution camera to capture visual information about the surroundings.

[1473] Input: A product label image taken by a camera.

[1474] Output: Retrieved visual information (product label image).

[1475] Specific operation: The device uses the camera to take an image of the product label and collect visual information.

[1476] Step 3:

[1477] The visual information acquired by the terminal is sent to the server.

[1478] Input: Product label image.

[1479] Output: Sending visual information (product label image) to the server.

[1480] Specific operation: The product label image acquired by the terminal is sent to the server via the network.

[1481] Step 4:

[1482] The server uses OCR technology to extract text information from the visual information.

[1483] Input: Product label image sent to the server.

[1484] Output: Extracted character information (text data).

[1485] Specific operation: The server uses Pytesseract to analyze the characters in the product label image and extract them as text data.

[1486] Step 5:

[1487] The server translates the extracted text information into a foreign language using machine translation technology.

[1488] Input: Extracted character information (text data).

[1489] Output: Translated text information (translated text data).

[1490] Specific operation: The server uses Google Translate to translate the text data into the set target language.

[1491] Step 6:

[1492] The server sends the translation results to the terminal.

[1493] Input: Translated text information (translated text data).

[1494] Output: Sending the translation results to your device.

[1495] Specific operation: The server sends the translated text information back to the terminal via the network.

[1496] Step 7:

[1497] The device retrieves the translated text information and displays it on the AR display.

[1498] Input: Translated text information (translated text data).

[1499] Output: Translation results displayed on the AR display.

[1500] Specific operation: The translation results received by the device are displayed on the screen using AR technology, superimposed on the user's field of view.

[1501] Step 8:

[1502] The user checks the displayed translation results.

[1503] Input: Translation result displayed on the AR display.

[1504] Output: Product information in a foreign language that the user can understand.

[1505] Specific operation: The user checks the translated product information through the AR display on their smartphone.

[1506] Through these steps, users can access foreign language translations of product labels in real time in physical stores, facilitating smooth shopping in a foreign language environment.

[1507] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1508] This invention is a system that uses a "language conversion mask" to allow users to experience a foreign language environment while in Japan, and also recognizes and reflects the user's emotional state. The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, an emotion engine, and a user interface.

[1509] 1. Hardware Configuration

[1510] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, headphones, and an emotion engine. The device transmits the acquired information to a server in real time.

[1511] Server: A computer system that analyzes and translates visual information, audio information, and emotional data sent from the device. The server processes the information using OCR, speech recognition, and emotion analysis technologies, and sends the translation results back to the device.

[1512] Interface: Provides controls that allow users to easily change settings, such as changing the target language, adjusting the volume, or turning certain features on or off.

[1513] 2. Program processing explanation

[1514] Device: After putting on the mask, the user activates the device. The device immediately activates its high-resolution camera and microphone to collect surrounding visual information, audio information, and the user's facial expression data. The emotion engine analyzes the user's emotional state from their facial expressions and tone of voice.

[1515] Server: Receives the video data and facial expression data sent from the device. The server first uses OCR technology to recognize the characters in the video image and extract text information. Next, it uses voice recognition technology to convert the audio data into text.

[1516] Server: Translates the extracted text and speech-to-text information into the specified foreign language. It can provide adaptive feedback to the translation results based on the user's emotional data recognized by the emotion engine. For example, if the user is confused, the server will provide a translation using simpler expressions.

[1517] Server: The translated text data is separated into visual data and audio data. The visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[1518] Device: Visual data sent from the server is displayed on the AR display and superimposed on the user's field of view. Audio data is played back so that the user can hear it through headphones.

[1519] 3. Example of a system

[1520] Example 1: Sign translation and emotional adaptation

[1521] User: Walking around town.

[1522] Terminal: The camera takes a picture of the sign and sends the video data to the server. The emotion engine analyzes the user's facial expressions to determine their emotions.

[1523] Server: Uses OCR technology to recognize and translate the characters on the sign. If it detects that the user is confused, it provides a simple translation. It then sends the translation results back to the device.

[1524] On your device: The translated text will be overlaid on the AR display.

[1525] Example 2: Dialogue translation and emotional adaptation

[1526] User: Places an order at a restaurant.

[1527] Device: The microphone records the conversation with the waiter and sends the audio data to the server. The emotion engine analyzes the emotion from the tone of the user's voice.

[1528] Server: Converts conversations into text using speech recognition technology and translates them. If the user feels unsure, provides a translation with words of encouragement. Synthesizes speech and sends it to the device.

[1529] Device: Play the translated audio through headphones.

[1530] Through these processes, users can learn a foreign language efficiently while experiencing a foreign language environment that adapts to their emotional state. This system reduces the user's mental burden and provides a more natural learning experience.

[1531] The processing flow will be explained below.

[1532] Step 1:

[1533] User: Put on the mask and turn it on. The device will automatically connect to the server.

[1534] Step 2:

[1535] Device: Activate the mask's high-resolution camera, microphone, and emotion engine to begin collecting surrounding visual and audio information and the user's facial expression data.

[1536] Step 3:

[1537] Terminal: Collected visual, audio, and facial expression data is sent to the server in real time.

[1538] Step 4:

[1539] Server: Analyzes the received video data using OCR technology and extracts text information from the image.

[1540] Step 5:

[1541] Server: Converts the received voice data into text using voice recognition technology.

[1542] Step 6:

[1543] Server: Uses the emotion engine to analyze the received facial expression data and recognize the user's emotional state.

[1544] Step 7:

[1545] Server: Translates the extracted text and speech into the specified foreign language. It adjusts the translation results based on the user's emotional state. For example, if the user is confused, it uses simpler expressions.

[1546] Step 8:

[1547] Server: The translated text data is divided into visual data and audio data. The visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[1548] Step 9:

[1549] Server: Sends the translation results to the device.

[1550] Step 10:

[1551] Device: The translated visual data is applied to the AR display and overlaid on the real-world image.

[1552] Step 11:

[1553] Device: Play the translated audio data through headphones.

[1554] Step 12:

[1555] Terminal: New visual, audio and facial expression data is continuously acquired and sent to the server for real-time updates.

[1556] Step 13:

[1557] Server: Always analyzes and translates the latest data and sends it to the device.

[1558] Step 14:

[1559] User: Uses the interface to change the target language, adjust the volume, and turn certain features on or off.

[1560] Example 2

[1561] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1562] Currently, many language translation systems do not consider the user's emotional state when experiencing a foreign language environment, which can lead to confusion and stress. Furthermore, conventional translation systems do not perform the process from collecting visual and audio information to displaying the translation results in real time, making them difficult to use in situations where immediate response is required. This makes it difficult to improve the user's learning efficiency and the quality of their foreign language experience.

[1563] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing the user's facial expression and tone of voice to recognize the emotional state, means for adding adaptive feedback to the translation result based on the recognized emotional state, and means for analyzing the acquired visual information and audio information and translating it into a foreign language. This enables real-time translation adapted to the user's emotional state.

[1564] A "high-resolution camera" refers to a high-resolution camera that can capture detailed visual information about the surroundings.

[1565] "Microphone" refers to an acoustic sensor for collecting surrounding sound information.

[1566] "Visual information" refers to image data of the surroundings acquired through a high-resolution camera.

[1567] "Audio information" refers to ambient audio data collected through a microphone.

[1568] "Text information" refers to text data extracted from acquired visual information.

[1569] "Speech recognition technology" refers to the technology that analyzes acquired voice information and converts it into text data.

[1570] "Foreign language" refers to any non-native language that is configured for the user to experience.

[1571] "Augmented reality technology" refers to technology that displays virtual information overlaid on real visual information.

[1572] "Speech synthesis means" refers to technology that converts text data into voice data and plays it back.

[1573] "Emotional state" refers to the psychological state of a user as perceived from their facial expression and tone of voice.

[1574] "Feedback" refers to a response that makes adaptive modifications to the translation result based on a perceived emotional state.

[1575] "User interface" refers to the operating means by which a user can change system settings.

[1576] The term "server" refers to a computer system that analyzes acquired data and performs translation and feedback processing.

[1577] "Device" refers to a device equipped with a high-resolution camera, microphone, AR display, headphones, and emotion engine.

[1578] This invention is a system that uses a "language conversion mask" to allow users to experience a foreign language environment while in Japan, and also recognizes and reflects the user's emotional state. The system includes a high-resolution camera, a microphone, a server, an AR display, headphones, an emotion engine, and a user interface.

[1579] Hardware Configuration

[1580] Device: The device includes a mask worn by the user, which is equipped with a high-resolution camera, microphone, AR display, headphones, and an emotion engine. The device transmits the acquired information to a server in real time.

[1581] Server: A computer system that analyzes and translates visual information, audio information, and emotional data sent from the device. The server processes the information using OCR, speech recognition, and emotion analysis technologies, and sends the translation results back to the device.

[1582] Interface: Provides controls that allow users to easily change settings, such as changing the target language, adjusting the volume, or turning certain features on or off.

[1583] Program processing explanation

[1584] Device: After putting on the mask, the user activates the device. The device immediately activates its high-resolution camera and microphone to collect surrounding visual information, audio information, and the user's facial expression data. The emotion engine analyzes the user's emotional state from their facial expressions and tone of voice.

[1585] Server: Receives the video data and facial expression data sent from the device. The server first uses OCR technology to recognize the characters in the video image and extract text information. Next, it uses voice recognition technology to convert the audio data into text.

[1586] The extracted text information and speech-to-text information are translated into the specified foreign language. Adaptive feedback can be added to the translation results based on the user's emotional data recognized by the emotion engine. For example, if the user is confused, the server will provide a translation using simpler expressions.

[1587] The translated text data is divided into visual data and audio data, the visual data is formatted for display using AR technology, and the audio data is converted into audio using speech synthesis technology.

[1588] Device: Visual data sent from the server is displayed on the AR display and superimposed on the user's field of view. Audio data is played back so that the user can hear it through headphones.

[1589] Example of a system

[1590] Example 1: Sign translation and emotional adaptation

[1591] User: Walking around town.

[1592] Terminal: The camera takes a picture of the sign and sends the video data to the server. The emotion engine analyzes the user's facial expressions to determine their emotions.

[1593] Server: Uses OCR technology to recognize and translate the characters on the sign. If it detects that the user is confused, it provides a simple translation. It then sends the translation results back to the device.

[1594] On your device: The translated text will be overlaid on the AR display.

[1595] Example 2: Dialogue translation and emotional adaptation

[1596] User: Places an order at a restaurant.

[1597] Device: The microphone records the conversation with the waiter and sends the audio data to the server. The emotion engine analyzes the emotion from the tone of the user's voice.

[1598] Server: Converts conversations into text using speech recognition technology and translates them. If the user feels unsure, provides a translation with words of encouragement. Synthesizes speech and sends it to the device.

[1599] Device: Play the translated audio through headphones.

[1600] This allows the user to efficiently learn a foreign language while experiencing an adaptive foreign language environment that corresponds to the user's emotional state.

[1601] Example prompts to input to the generative AI model

[1602] "Generate examples of sign translations and emotional adaptations. Provide a simple translation if the user is confused."

[1603] "Generate translations and emotional adaptation examples for conversations at a restaurant. If the user feels unsure, provide a translation with encouraging words."

[1604] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1605] Step 1: User puts on mask and starts the system

[1606] User: Put on the mask-type device and turn on the system.

[1607] Device: High-resolution camera, microphone, AR display, headphones, and emotion engine activated.

[1608] Input: Mask activation signal.

[1609] Output: Initial startup completion signal for various sensors and start of operation.

[1610] Step 2: Collect visual, audio, and emotional data

[1611] Device: A high-resolution camera captures visual information of the surroundings, a microphone collects audio information, and an emotion engine analyzes the user's facial expressions and tone of voice in real time to generate emotional state data.

[1612] Input: User's visual, audio, and facial expressions.

[1613] Output: captured images, recorded audio, and analyzed emotion data.

[1614] Step 3: Sending visual, audio, and emotional data

[1615] Terminal: Collected visual, audio, and emotional data is sent to the server in real time.

[1616] Input: captured images, recorded audio, and analyzed emotion data.

[1617] Output: The data sent to the server.

[1618] Step 4: Data analysis by the server (OCR, speech recognition, emotion analysis)

[1619] Server: Analyzes received visual information using OCR technology, recognizes characters in images, and extracts text information. It also converts received audio information into text data using speech recognition technology, and analyzes emotional data.

[1620] Input: Transmitted visual, audio, and emotional data.

[1621] Output: Extracted text information, transcribed audio information, and analyzed emotion data.

[1622] Step 5: Translation process

[1623] Server: Translates the extracted text information and speech-to-text information into a preset foreign language.

[1624] Input: Extracted text and transcribed audio information.

[1625] Output: Translated text information and translated audio information.

[1626] Step 6: Adding adaptive feedback

[1627] Server: Adds adaptive feedback to translation results based on recognized emotion data. For example, if the user is confused, the server provides translation results with simple expressions.

[1628] Input: Translated text information and parsed sentiment data.

[1629] Output: The final translation result with added feedback.

[1630] Step 7: Format and distribute data

[1631] Server: The translated text data is separated into visual data and audio data. The visual data is formatted for the AR display, and the audio data is converted into audio data using speech synthesis technology and sent to the device.

[1632] Input: The final translation result.

[1633] Output: AR display data and audio data.

[1634] Step 8: View and play back translation results

[1635] Device: Visual data sent from the server is displayed on the AR display, and audio data is played through headphones.

[1636] Input: Visual and audio data sent from the server.

[1637] Output: The textual information displayed to the user's eyes and the audio information played.

[1638] (Application example 2)

[1639] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1640] Foreign tourists often have difficulty understanding Japanese when shopping in brick-and-mortar stores in Japan. This limited understanding of product labels and conversations with store clerks limits their shopping experience. This issue needs to be resolved to enable foreign tourists to enjoy shopping more comfortably and smoothly. It is also necessary to provide appropriate feedback based on the user's emotional state.

[1641] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1642] In this invention, the server includes means for acquiring visual information of the surroundings using a high-resolution camera, means for acquiring audio information of the surroundings using a microphone, means for analyzing the acquired visual information and extracting text information, means for converting the acquired audio information into text using speech recognition technology, means for translating the extracted and converted text information into any foreign language, means for displaying the translated text information using augmented reality technology, means for synthesizing the voice to play back the translated audio information, means for analyzing the user's facial expression and tone of voice to recognize their emotional state, and means for adaptively feeding back the translation result in accordance with the recognized emotional state. This not only enables foreign tourists to enjoy shopping in brick-and-mortar stores, but also allows them to receive more personalized service by providing feedback in accordance with the user's emotions.

[1643] A "high-resolution camera" is a camera that can capture very detailed visual information.

[1644] A "microphone" is a device that captures surrounding sounds.

[1645] "Visual information" refers to video data acquired through a visual device such as a camera.

[1646] "Audio information" is audio data acquired through an audio device such as a microphone.

[1647] "Means for extracting character information" refers to technology or equipment that recognizes and extracts characters from visual information.

[1648] "Speech recognition technology" is a technology that converts acquired voice information into text data.

[1649] "Means for translating into a foreign language" refers to a technique or device that converts extracted or converted text information into another language.

[1650] "Augmented reality technology" is a technology that displays virtual information overlaid on real images.

[1651] "Speech synthesis means" refers to a technology or device that converts translated text information into speech and plays it back.

[1652] A "means for recognizing an emotional state" is a technology or device that analyzes a user's facial expressions and tone of voice to determine their emotions.

[1653] An "adaptive feedback mechanism" is a technique or device that provides context-sensitive responses or information based on a perceived emotional state.

[1654] This system eliminates the barriers that foreign tourists face when shopping in brick-and-mortar stores in Japan, allowing them to enjoy shopping comfortably and smoothly. Specifically, the system includes a high-resolution camera, a microphone, a server, an augmented reality display, headphones, an emotion analysis engine, and a user interface.

[1655] First, the smart glasses worn by the user are equipped with a high-resolution camera, microphone, augmented reality display, headphones, and an emotion analysis engine, which allows them to acquire visual and audio information from the surroundings in real time and send it to a server.

[1656] The server analyzes the visual and audio information sent from the device and performs the necessary translation processing. Specifically, the following technologies are used:

[1657] OCR technology (such as Google Cloud Vision API): Extracts characters from visual information acquired by a high-resolution camera and converts them into text data.

[1658] Speech recognition technology (such as Google Cloud Speech-to-Text): Converts voice information captured by a microphone into text data.

[1659] Translation technology (such as Google Cloud Translate API): Translates acquired text data into the specified foreign language.

[1660] Speech synthesis technology (such as Google Cloud Text-to-Speech): Converts translated text data into audio data.

[1661] Emotion analysis engine (such as Microsoft Azure Emotion API): Analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[1662] Furthermore, the system provides adaptive feedback based on the user's emotional state. For example, if the user is confused, the system can provide simpler and more polite translations and add words of encouragement, allowing the user to enjoy shopping with peace of mind.

[1663] The following are some examples of specific usage scenarios:

[1664] Example 1: Product label translation

[1665] The user wears the smart glasses and takes a picture of a product label in the store with the camera. The server uses OCR technology to recognize the text on the label and translates it. The translation result is displayed on an augmented reality display, allowing the user to check the product information.

[1666] Example 2: Translation of a conversation with a store clerk

[1667] When a user asks a question at the cash register, a microphone records the conversation and sends the audio data to a server. The server then uses speech recognition technology to convert the conversation into text and translate it. An emotion analysis engine analyzes the user's facial expressions and provides translation results, including encouraging words, if the user appears nervous. The translation results are then played through headphones using speech synthesis technology.

[1668] Example prompts for generative AI models

[1669] "Create an application that uses smart glasses to enable foreign tourists to shop in brick-and-mortar stores without understanding Japanese. It should have real-time translation functions, conversation translation functions, and the ability to analyze the user's emotional state and provide feedback. For example, it should translate product labels and directions, and translate conversations with store clerks."

[1670] This system will enable foreign tourists to enjoy shopping in Japan without having to worry about language barriers, while also enabling stores to improve customer satisfaction.

[1671] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1672] Step 1:

[1673] A user puts on the smart glasses and starts the device. The device activates the camera and microphone to capture visual and audio information from the surroundings in real time.

[1674] Input: The user puts on the smart glasses and activates them.

[1675] Output: Visual information captured by a high-resolution camera and audio information recorded by a microphone.

[1676] Step 2:

[1677] The visual and audio information acquired by the device is sent to the server. The visual information is sent as image data, and the audio information is sent as audio data.

[1678] Input: Acquired visual and audio information.

[1679] Output: Image and audio data sent to the server.

[1680] Step 3:

[1681] The server extracts text information from the visual information using OCR technology (e.g., Google Cloud Vision API), analyzes the image data, and generates text data.

[1682] Input: Image data sent from the device.

[1683] Output: The extracted text data.

[1684] Step 4:

[1685] The server converts the voice information into text data using voice recognition technology (e.g., Google Cloud Speech-to-Text), analyzes the voice data, and generates text data.

[1686] Input: Audio data sent from the device.

[1687] Output: Text data converted from audio information.

[1688] Step 5:

[1689] The server translates the acquired and converted text data into any foreign language using translation technology (e.g., Google Cloud Translate API), and then converts the acquired text data into the target language.

[1690] Input: Text data obtained using OCR and speech recognition technologies.

[1691] Output: The translated text data.

[1692] Step 6:

[1693] The server recognizes the user's emotional state using an emotion analysis engine (e.g., Microsoft Azure Emotion API). It analyzes the user's facial expression data and tone of voice to identify the user's emotional state.

[1694] Input: User's facial expression data and tone of voice.

[1695] Output: Perceived emotional state.

[1696] Step 7:

[1697] The server adaptively provides feedback on the translation results based on the recognized emotional state, for example, generating feedback using simple translation expressions if the user is confused.

[1698] Input: translated text data and recognized emotional state.

[1699] Output: Adaptive translation results.

[1700] Step 8:

[1701] The server separates the data into visual and audio data, formats the visual data so that it can be displayed using augmented reality technology, and converts the audio data into audio using voice synthesis technology (e.g., Google Cloud Text-to-Speech).

[1702] Input: Adaptive translation result data.

[1703] Output: Display and audio data for augmented reality.

[1704] Step 9:

[1705] The device displays the visual data sent from the server on an augmented reality display and plays the audio data through headphones, allowing the user to receive the translated information visually and audibly.

[1706] Input: Visual and audio data sent from the server.

[1707] Output: Translation information displayed on the augmented reality display and translated audio played through headphones.

[1708] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1709] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1710] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1711] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1712] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1713] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1714] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1715] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1716] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1717] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1718] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1719] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1720] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1721] 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.

[1722] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1723] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1724] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1725] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1726] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1727] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1728] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1729] The following is further disclosed regarding the above embodiment.

[1730] (Claim 1)

[1731] A means for acquiring visual information of the surroundings using a high-resolution camera;

[1732] A means for acquiring surrounding audio information using a microphone;

[1733] A means for analyzing the acquired visual information and extracting text information;

[1734] A means for converting the acquired voice information into text using voice recognition technology;

[1735] means for translating the extracted and converted text information into any foreign language;

[1736] a means for displaying the translated text information using augmented reality technology;

[1737] a speech synthesis means for reproducing the translated speech information;

[1738] A system including:

[1739] (Claim 2)

[1740] transmitting the acquired visual and audio information to a server;

[1741] Analysis and translation are performed on the server,

[1742] 2. The system according to claim 1, wherein the translation result is transmitted to the terminal.

[1743] (Claim 3)

[1744] an interface that allows a user to change settings;

[1745] Selected target language and volume,

[1746] 10. The system of claim 1, wherein the system adjusts the on / off settings of specific features.

[1747] "Example 1"

[1748] (Claim 1)

[1749] A means for acquiring visual information of the surroundings using a high-resolution camera;

[1750] A means for acquiring surrounding audio information using a microphone;

[1751] A means for analyzing the acquired visual information and extracting text information;

[1752] A means for converting the acquired voice information into text using voice recognition technology;

[1753] means for translating the extracted and converted text information into any foreign language;

[1754] a means for displaying the translated text information using augmented reality technology;

[1755] a speech synthesis means for reproducing the translated speech information;

[1756] A means for analyzing the video data and audio data using a server and applying OCR and speech recognition technologies;

[1757] a means for translating textual information into a foreign language using machine translation technology;

[1758] A means for displaying visual data in the user's field of view using AR technology;

[1759] A system including:

[1760] (Claim 2)

[1761] transmitting the acquired visual and audio information to a server;

[1762] Analysis and translation are performed on the server,

[1763] 2. The system according to claim 1, wherein the translation result is transmitted to the terminal.

[1764] (Claim 3)

[1765] an interface that allows a user to change settings;

[1766] Selected target language and volume,

[1767] 10. The system of claim 1, wherein the system adjusts the on / off settings of specific features.

[1768] "Application Example 1"

[1769] (Claim 1)

[1770] A means for acquiring visual information of the surroundings using a high-resolution camera;

[1771] A means for acquiring surrounding audio information using a microphone;

[1772] A means for analyzing the acquired visual information and extracting text information;

[1773] A means for converting the acquired voice information into text using voice recognition technology;

[1774] means for translating the extracted and converted text information into any foreign language;

[1775] a means for displaying the translated text information using augmented reality technology;

[1776] a speech synthesis means for reproducing the translated speech information;

[1777] A means to translate product labels;

[1778] A system that includes a means for translating conversations between customers and store clerks.

[1779] (Claim 2)

[1780] transmitting the acquired visual and audio information to a server;

[1781] Analysis and translation are performed on the server,

[1782] 2. The system according to claim 1, wherein the translation result is transmitted to the terminal.

[1783] (Claim 3)

[1784] an interface that allows a user to change settings;

[1785] Selected target language and volume,

[1786] 10. The system of claim 1, wherein the on / off settings of certain features can be adjusted.

[1787] "Example 2: Combining Emotion Engines"

[1788] (Claim 1)

[1789] A means for acquiring visual information of the surroundings using a high-resolution camera;

[1790] A means for acquiring surrounding audio information using a microphone;

[1791] A means for analyzing the acquired visual information and extracting text information;

[1792] A means for converting the acquired voice information into text using voice recognition technology;

[1793] means for translating the extracted and converted text information into any foreign language;

[1794] a means for displaying the translated text information using augmented reality technology;

[1795] a speech synthesis means for reproducing the translated speech information;

[1796] means for analyzing the user's facial expressions and tone of voice to recognize their emotional state;

[1797] means for applying adaptive feedback to the translation result based on the perceived emotional state;

[1798] A system including:

[1799] (Claim 2)

[1800] transmitting the acquired visual and audio information to a server;

[1801] Analysis and translation are performed on the server,

[1802] 2. The system according to claim 1, wherein the translation result is transmitted to the terminal.

[1803] (Claim 3)

[1804] an interface that allows a user to change settings;

[1805] Selected target language and volume,

[1806] 10. The system of claim 1, wherein the system adjusts the on / off settings of specific features.

[1807] "Application example 2 when combining emotion engines"

[1808] (Claim 1)

[1809] A means for acquiring visual information of the surroundings using a high-resolution camera;

[1810] A means for acquiring surrounding audio information using a microphone;

[1811] A means for analyzing the acquired visual information and extracting text information;

[1812] A means for converting the acquired voice information into text using voice recognition technology;

[1813] means for translating the extracted and converted text information into any foreign language;

[1814] a means for displaying the translated text information using augmented reality technology;

[1815] a speech synthesis means for reproducing the translated speech information;

[1816] means for recognizing an emotional state of a user by analyzing the user's facial expression and tone of voice;

[1817] means for adaptively feeding back the translation results according to the recognized emotional state;

[1818] A system including:

[1819] (Claim 2)

[1820] transmitting the acquired visual and audio information to a server;

[1821] Analysis and translation are performed on the server,

[1822] 2. The system according to claim 1, wherein the translation result is transmitted to the terminal.

[1823] (Claim 3)

[1824] an interface that allows a user to change settings;

[1825] Selected target language and volume,

[1826] 10. The system of claim 1, wherein the system adjusts the on / off settings of specific features. [Explanation of symbols]

[1827] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for acquiring visual information of the surroundings using a high-resolution camera; A means for acquiring surrounding audio information using a microphone; A means for analyzing the acquired visual information and extracting text information; A means for converting the acquired voice information into text using voice recognition technology; means for translating the extracted and converted text information into any foreign language; a means for displaying the translated text information using augmented reality technology; a speech synthesis means for reproducing the translated speech information; A system including:

2. transmitting the acquired visual and audio information to a server; Analysis and translation are performed on the server, 2. The system according to claim 1, wherein the translation result is transmitted to a terminal.

3. an interface that allows a user to change settings; Selected target language and volume, The system of claim 1, wherein the system adjusts the on / off settings of specific features.

Images