System

Abstract

A system is provided.SOLUTION: A system including: a display unit worn by a user; a terminal connected to the display unit; a server connected to the terminal; a voice capture unit that transmits voice data to the terminal; a text conversion unit that converts the voice data into text in the server; a translation unit that translates the text data converted by the text conversion unit; and a display unit that displays data translated by the translation unit on the display unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Currently available translation services have the problem of being "device-conscious," which creates barriers to "dialogue" by preventing users from seeing the other person's facial expressions when translating, or by blocking their ears with earphones, etc. As a result, natural dialogue is hindered and the use of speech translation devices is inconvenient. [Means for solving the problem]

[0005] The present invention provides a system including a display means worn by a user, a terminal connected to the display means, a server connected to the terminal, an audio capture means for transmitting audio data to the terminal, a text conversion means in the server for converting the audio data into text, a translation means for translating the text data converted by the text conversion means, and a display means for displaying the data translated by the translation means on a display means, thereby enabling natural communication by allowing users to continue a conversation without covering their ears while seeing the other person's facial expressions.

[0006] "User" refers to an individual or organization that uses the system.

[0007] The term "display means" refers to a device that can be worn by a user to visually confirm information.

[0008] "Terminal" refers to an electronic device that connects a display means and a server and transmits and receives data.

[0009] The term "server" refers to a computer system that processes data sent from a terminal and provides the required services.

[0010] "Audio capture means" refers to a device that has the function of collecting the user's voice and transmitting it to the terminal as voice data.

[0011] "Text conversion means" refers to a system that has the function of converting voice data collected by the voice capture means into text data.

[0012] "Translation means" refers to a system that has the function of translating the text data generated by the text conversion means into another language.

[0013] "Audio output means" refers to a device that has the function of outputting text data or translation data to the user as audio.

[0014] "Microphone" refers to a device for collecting sound, used as an audio capture means. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] The present invention implements a system that incorporates a generative AI (translation service) in audio glasses to provide an environment in which users can converse in a natural way. A specific example of this system is described below.

[0037] Overall system flow

[0038] This system is composed mainly of audio glasses worn by the user, a terminal, and a server. When a user puts on the audio glasses and starts a conversation, the system translates and provides speech in real time through the following process.

[0039] Program processing

[0040] 1. Preparing and connecting the audio glasses

[0041] When a user puts on the audio glasses, they automatically connect to the device and begin communicating with the server.

[0042] The server verifies the Audio Glasses connection and links it with the user data.

[0043] 2. Voice input recognition

[0044] When the user starts speaking, a microphone in the audio glasses captures the sound.

[0045] The audio data captured by the audio glasses is sent to the device.

[0046] 3. Translation of audio data

[0047] The terminal transmits the received voice data to the server.

[0048] The server uses voice recognition technology to convert the voice data into text.

[0049] The server uses a generated AI (translation service) to translate the text into the specified language.

[0050] 4. Returning the translation results

[0051] The server returns the translated text data to the terminal.

[0052] The device receives the translation results and sends them to the audio glasses.

[0053] 5. Visual and auditory feedback

[0054] The audio glasses visually display the translation results, allowing users to continue the conversation while checking the other person's facial expressions.

[0055] If necessary, the device will synthesize the translation result into voice and play it through the Audio Glasses' speakers.

[0056] Specific use cases

[0057] Everyday conversation translation

[0058] 1. Preparation

[0059] User A puts on the audio glasses and the system is ready.

[0060] 2. Voice Input

[0061] User A says, "Hello, how are you?"

[0062] The audio glasses capture the sound and send it to your device.

[0063] 3. Translation of audio data

[0064] The terminal transmits the received voice data to the server.

[0065] The server translates "Hello, how are you?" to "Hello, how are you?"

[0066] 4. Returning the translation results

[0067] The server returns the translation results to the terminal.

[0068] The device sends the translation results to the audio glasses.

[0069] 5. Feedback

[0070] The audio glasses visually display "Hello, how are you?"

[0071] User A checks the translation results while looking at the other person's facial expressions and continues the conversation in a natural way.

[0072] Use in business meetings

[0073] 1. Preparation

[0074] User B puts on the audio glasses and the system is ready.

[0075] 2. Voice Input

[0076] User B says, "How is this project going?"

[0077] The audio glasses capture the sound and send it to your device.

[0078] 3. Translation of audio data

[0079] The terminal transmits the received voice data to the server.

[0080] The server translates "How is the progress of this project?" to "How is the progress of this project?"

[0081] 4. Returning the translation results

[0082] The server returns the translation results to the terminal.

[0083] The device sends the translation results to the audio glasses.

[0084] 5. Feedback

[0085] The audio glasses visually display "How is the progress of this project?"

[0086] User B can check the translation results while looking at the other person's facial expression, allowing the business conversation to proceed smoothly.

[0087] In this way, the system provides an environment in which users can communicate naturally, helping to overcome language barriers.

[0088] The processing flow will be explained below.

[0089] Step 1:

[0090] The user puts on the audio glasses and powers on the device.

[0091] Step 2:

[0092] The device receives the connection signal from the audio glasses and confirms pairing.

[0093] Step 3:

[0094] The terminal sends the connection information to the server and links it with the user data.

[0095] Step 4:

[0096] The user initiates the interaction and the audio glasses' microphone captures what is being said.

[0097] Step 5:

[0098] The audio data captured by the audio glasses is sent to the device in real time.

[0099] Step 6:

[0100] The terminal transmits the received voice data to the server.

[0101] Step 7:

[0102] The server receives the voice data and converts it into text using speech recognition technology.

[0103] Step 8:

[0104] The server calls the generation AI (translation service) to translate the generated text.

[0105] Step 9:

[0106] The generation AI translates the text into the specified language and sends the translation results to the server.

[0107] Step 10:

[0108] The server returns the translated text data to the terminal.

[0109] Step 11:

[0110] The device receives the translation results and sends them to the audio glasses for visual display.

[0111] Step 12:

[0112] The audio glasses provide feedback to the user by displaying the translation results on a screen.

[0113] Step 13:

[0114] If necessary, the device synthesizes the translation results into voice and plays them back to the user through the Audio Glasses' speakers.

[0115] Step 14:

[0116] The user can check the displayed translation results and the played audio, and continue the conversation naturally while observing the other person's facial expressions.

[0117] Example 1

[0118] 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."

[0119] Conventional translation systems have had difficulty translating speech data in real time and providing visual and auditory feedback. Furthermore, they often fail to adequately consider improvements in translation performance or data security. This can make it difficult for users to communicate smoothly. It is desirable to solve these issues and provide an environment in which users can communicate naturally.

[0120] 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.

[0121] In this invention, the server includes a speech recognition unit, a generation AI model utilization unit, and an information protection unit, which enables rapid conversion of speech data into text, high-precision translation using the generation AI, and security protection through data encryption.

[0122] A "display means" is a device worn by a user to display visual information.

[0123] A "terminal" is an electronic device connected to a display means and for communicating with a server.

[0124] A "server" is a central processing unit that is connected to a terminal and processes and translates voice data.

[0125] An "audio capture means" is a device that captures a user's voice and converts it into a digital signal.

[0126] "Speech recognition means" refers to a technique or device that converts voice data into text data.

[0127] The "translation means" is a technology or device that translates the text data converted by the speech recognition means into a specified language.

[0128] "Means for utilizing a generative AI model" refers to a device or technology that uses a generative AI model to translate text data.

[0129] "Information protection measures" are technologies or devices that encrypt voice data and translation data to ensure data security during transmission and reception.

[0130] "Visual display means" refers to a screen incorporated in a display or lens for visually displaying the translation results.

[0131] "Audio output means" refers to a speaker or voice synthesis technology for outputting text data as voice.

[0132] This invention provides a system that uses audio glasses equipped with a generative AI model to translate and provide speech in real time, allowing users to converse in a natural way. The system is primarily composed of a display device worn by the user, a terminal, and a server.

[0133] Hardware and software used

[0134] The display means takes the form of audio glasses worn by the user. These audio glasses have a built-in microphone and small display. The terminal is, for example, a smartphone or tablet, and communicates with the display means via a wireless connection such as Bluetooth or Wi-Fi. The server is installed as a cloud server or on-premise server and performs translation using speech recognition technology and generative AI models (e.g., OpenAI (registered trademark), GPT-4 (registered trademark), or DeepL).

[0135] System Operation

[0136] Hardware connectivity and communication

[0137] When a user puts on the audio glasses, they automatically connect to the device. Once this connection is established, the device starts communicating with the server over the network. The server obtains the audio glasses and the user's profile information and configures the entire system accordingly.

[0138] Voice input and translation process

[0139] When a user speaks, the microphone in the audio glasses captures the sound, which is then converted into a digital format and transmitted over wireless to the device, where it is then encrypted and sent to a server.

[0140] The server first converts the received voice data into text data using a speech recognition means (e.g., Google® Cloud Speech-to-Text API). Then, the server translates the text data along with a prompt sentence using a generative AI model utilization means. For example, the prompt sentence may be "Please translate the following text into English: 'Hello, how are you?'"

[0141] Returning and displaying translation results

[0142] The translated text data is then re-encrypted and sent back to the device, which then formats it appropriately and sends it to the audio glasses. The audio glasses then visually display the translation results on a small display. If necessary, the device can also output the translation results as audio using speech synthesis technology (e.g., Google Text-to-Speech API) and play it through the audio glasses' speakers.

[0143] Specific use cases

[0144] Use in everyday conversation

[0145] 1. Preparation: User A puts on the audio glasses and the system is ready.

[0146] 2. Voice input: User A says, "Hello, how are you?" The audio glasses capture the voice and send it to the device.

[0147] 3. Voice data translation: The device sends the received voice data to the server, which translates "Hello, how are you?" into "Hello, how are you?"

[0148] 4. Returning the translation result: The server returns the translation result to the device, which then sends it to the audio glasses.

[0149] 5. Feedback: The audio glasses visually display "Hello, how are you?" and optionally play it audibly through the speaker.

[0150] Use in business meetings

[0151] 1. Preparation: User B puts on the audio glasses and the system is ready.

[0152] 2. Voice input: User B says, "How is the progress on this project?" The audio glasses capture the voice and send it to the device.

[0153] 3. Voice data translation: The device sends the received voice data to the server, which translates "How is the progress of this project?" into "How is the progress of this project?"

[0154] 4. Returning the translation result: The server returns the translation result to the device, which then sends it to the audio glasses.

[0155] 5. Feedback: The audio glasses will visually display "How is the progress of this project?" and will play audible feedback through the speakers if necessary.

[0156] In this way, the present invention provides an environment in which users can communicate naturally, helping to overcome language barriers.

[0157] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0158] Program processing flow

[0159] Step 1:

[0160] Preparing and connecting audio glasses

[0161] Specific behavior:

[0162] The user puts on the audio glasses, which automatically connect to the terminal as a display device.

[0163] The device confirms the Bluetooth connection with the audio glasses and then starts communicating with the server over the Internet.

[0164] The server verifies the connection between the audio glasses and the device, obtains the user's profile information, and links them.

[0165] input:

[0166] Audio glasses connection start signal

[0167] output:

[0168] Establishing a connection between the audio glasses, the device, and the server

[0169] Loading a user's profile information

[0170] Step 2:

[0171] Voice input recognition

[0172] Specific behavior:

[0173] The user speaks a word, for example, "Hello, how are you?"

[0174] A microphone inside the audio glasses captures sound and converts the audio data into a digital format.

[0175] The audio glasses transmit digital audio data to the device via Bluetooth.

[0176] input:

[0177] User-generated speech

[0178] output:

[0179] Audio data converted into digital format

[0180] Step 3:

[0181] Sending audio data

[0182] Specific behavior:

[0183] The device encrypts the audio data received from the audio glasses.

[0184] The terminal transmits the encrypted voice data to the server via the network.

[0185] input:

[0186] Audio data sent from audio glasses

[0187] output:

[0188] Sending encrypted audio data to the server

[0189] Step 4:

[0190] Speech recognition of audio data

[0191] Specific behavior:

[0192] The server decrypts the received encrypted voice data and converts it into text data using a voice recognition method (e.g., Google Cloud Speech-to-Text API).

[0193] input:

[0194] Encrypted audio data

[0195] output:

[0196] Text data

[0197] Step 5:

[0198] Text data translation

[0199] Specific behavior:

[0200] The server translates the text data into the specified language using a generative AI model, using the prompt "Please translate the following text into English: 'Hello, how are you?'"

[0201] input:

[0202] Text data generated by speech recognition

[0203] output:

[0204] Translated text data

[0205] Step 6:

[0206] Sending translation results

[0207] Specific behavior:

[0208] The server re-encrypts the translated text data and sends it to the terminal.

[0209] input:

[0210] Translated text data

[0211] output:

[0212] Encrypted translation data

[0213] Step 7:

[0214] Receiving and displaying translation results

[0215] Specific behavior:

[0216] The terminal receives and decrypts the encrypted translation data.

[0217] The device sends the decoded translation data to the audio glasses.

[0218] The audio glasses display the translation results using a visual display means.

[0219] input:

[0220] Encrypted translation data

[0221] output:

[0222] Translation results displayed on the audio glasses display

[0223] Step 8:

[0224] Audio output (if needed)

[0225] Specific behavior:

[0226] The device uses speech synthesis technology (e.g., Google Text-to-Speech API) to convert the translated text into speech.

[0227] The audio glasses play the sound through the speakers.

[0228] input:

[0229] Translated text data

[0230] output:

[0231] Voice output of translation results

[0232] Through the above processing steps, this system provides an environment in which users can interact in a natural way.

[0233] (Application example 1)

[0234] 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."

[0235] In conventional multilingual environments in factories, the transmission of work instructions took time, resulting in poor communication efficiency. In particular, in workplaces with a mix of workers from various countries, language barriers often compromised the accuracy and timing of work. Therefore, there was a need for a system that would enable accurate multilingual translation in real time, allowing work instructions to be transmitted quickly and efficiently.

[0236] 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.

[0237] In this invention, the server includes a means for converting voice data into text, a means for translating text data, and a means for generating prompt sentences including a generative AI model. This allows workers to immediately receive multilingual translation results visually and audibly in real time, enabling smooth communication even in multinational workplaces.

[0238] The "display means" is a device that allows the user to visually confirm information.

[0239] A "terminal" is a device that communicates with a display means and processes and transmits data.

[0240] A "server" is a central device that processes data sent from terminals and returns data as needed.

[0241] The "voice capture means" is a device for inputting the user's voice.

[0242] "Text conversion means" refers to a device or function for converting voice data into text data.

[0243] The "translation means" is a device or function for translating text data into another specified language.

[0244] A "generative AI model" is an artificial intelligence model that generates prompt sentences based on specified input data and generates appropriate output accordingly.

[0245] A "prompt sentence generation means" is a device or function that uses a generative AI model to generate a prompt sentence based on input data.

[0246] This invention provides real-time multilingual translation using a system that includes a display device worn by the user (e.g., audio glasses), a terminal, and a server. Specifically, the system is configured using the following hardware and software:

[0247] Hardware

[0248] Display means: Device worn by the user, such as audio glasses.

[0249] Terminal: A device that communicates with a display means, such as a smartphone or tablet.

[0250] Server: A central device that processes data sent from terminals.

[0251] Audio capture method: Microphone built into the audio glasses.

[0252] Audio output means: Speaker built into the audio glasses.

[0253] software

[0254] Speech recognition library (speech_recognition): Converts voice data into text data.

[0255] Translation library (translate): Translates text data into other specified languages.

[0256] Speech synthesis library (pyttsx3): Converts text data into speech data.

[0257] Process Overview

[0258] 1. Capture audio input:

[0259] The user's voice is captured by a microphone built into the audio glasses, which is highly sensitive and accurately captures the user's voice while rejecting surrounding noise.

[0260] 2. Audio to text conversion:

[0261] The server uses speech recognition technology to convert the audio data into text data. The speech_recognition library is responsible for this process.

[0262] 3. Translation of text data:

[0263] The translation library, translate, translates the text data, while a generative AI model generates prompts to improve translation accuracy.

[0264] 4. Prompt generation:

[0265] The generative AI model generates appropriate prompt sentences based on user input, which are then referenced by the server for optimal translation.

[0266] For example, when translating "Please stop the machine," the following prompt sentence is generated: "Translate the following Japanese sentence to English: 'Please stop the machine'"

[0267] 5. Output of translation results:

[0268] The translated text is sent to the display means via the terminal, and the translation result is displayed on the display of the audio glasses.

[0269] In addition, the translated text is converted into audio data using a speech synthesis library (pyttsx3) and played through the audio glasses' speakers.

[0270] Specific examples

[0271] For example, if a factory leader issues the command "Stop the machine" in Japanese, this voice is captured by the microphone in the audio glasses, and the following prompt sentence is generated by the generative AI model:

[0272] Translate the following Japanese sentence into English: 'Please stop the machine.'

[0273] As a result, the translated text "Please stop the machine" appears on the audio glasses' display and is simultaneously output as audio.

[0274] This allows foreign workers in the factory to understand accurate instructions in real time and continue working smoothly. This system will greatly improve communication efficiency in workplaces with multilingual environments.

[0275] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0276] Step 1:

[0277] The user wears the audio glasses and inputs voice. The microphone built into the audio glasses captures the user's speech. This voice data is sent to the device. The input is the user's voice, and the output is voice data.

[0278] Step 2:

[0279] The device sends the captured audio data to the server. The input is audio data, and the output is sending audio data to the server. The device communicates with the server via a network.

[0280] Step 3:

[0281] The server converts the received voice data into text data using the speech_recognition library. The input is voice data and the output is text data. This process converts the voice data into meaningful strings of characters.

[0282] Step 4:

[0283] The server uses a translation library (translate) to translate the text data into another specified language. At this time, a generative AI model generates a prompt sentence to improve the accuracy of the translation. The input is the text data, and the output is the translated text data. An example of a generated prompt sentence is "Translate the following Japanese sentence to English: 'Please stop the machine'".

[0284] Step 5:

[0285] The server returns the translated text data to the terminal. The input is the translated text data, and the output is the transmission of the text data to the terminal. The data from the server is received by the terminal.

[0286] Step 6:

[0287] The terminal sends the received translation text data to the audio glasses. The input is the translated text data, and the output is the transmission of the text data to the audio glasses. The terminal works in conjunction with the audio glasses.

[0288] Step 7:

[0289] Audio Glasses visually displays translated text data using a display device. It also converts the text data into audio data using a speech synthesis library (pyttsx3) and plays it as audio through a built-in speaker. The input is the translated text data, and the output is a visual display and audio output. The user can check the translation results through the displayed text and played audio.

[0290] 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.

[0291] The present invention implements a system that incorporates a generative AI (translation service) and an emotion engine into audio glasses to provide an environment in which users can have natural conversations. This system allows users to overcome language barriers and understand the emotions of others. A specific example of this system is described below.

[0292] Overall system flow

[0293] This system is composed mainly of audio glasses worn by the user, a terminal, a server, and an emotion recognition engine. When a user puts on the audio glasses and starts a conversation, the system translates the speech and recognizes emotions in real time through the following process.

[0294] Program processing

[0295] 1. Preparing and connecting the audio glasses

[0296] When a user puts on the audio glasses, they automatically connect to the device and begin communicating with the server.

[0297] The server verifies the Audio Glasses connection and links it with the user data.

[0298] 2. Voice input recognition

[0299] When the user starts speaking, a microphone in the audio glasses captures the sound.

[0300] The audio data captured by the audio glasses is sent to the device in real time.

[0301] 3. Audio Data Processing

[0302] The terminal transmits the received voice data to the server.

[0303] The server receives the voice data and converts it into text using speech recognition technology.

[0304] 4. Emotional Recognition

[0305] The server analyzes the user's emotions using an emotion engine based on the voice data.

[0306] The emotion engine generates emotion data and returns it to the server.

[0307] 5. Text Translation

[0308] The server calls the generation AI (translation service) to translate the generated text.

[0309] The generative AI translates text into the specified language.

[0310] 6. Returning the translation results

[0311] The server returns the text data and emotion data of the translation result to the terminal.

[0312] The device receives the translation results and emotion data and sends them to the audio glasses.

[0313] 7. Visual and auditory feedback

[0314] The audio glasses provide feedback to the user by visually displaying translation results and emotional data.

[0315] If necessary, the device will synthesize the translation result into voice and play it through the Audio Glasses' speakers.

[0316] Specific use cases

[0317] Translation of everyday conversations and emotion recognition

[0318] 1. Preparation

[0319] User A puts on the audio glasses and the system is ready.

[0320] 2. Voice Input

[0321] User A says, "Hello, how are you?"

[0322] The audio glasses capture the sound and send it to your device.

[0323] 3. Audio Data Processing

[0324] The terminal transmits the received voice data to the server.

[0325] The server converts "Hello, how are you?" into text.

[0326] 4. Emotional Recognition

[0327] The server analyzes user A's emotions based on the voice data.

[0328] The emotion engine recognizes User A's emotion as "joy."

[0329] 5. Text Translation

[0330] The server passes this text to a generative AI translation service.

[0331] The generative AI translates this to "Hello, how are you?"

[0332] 6. Returning the translation results

[0333] The server returns the translation results and emotion data to the device.

[0334] The device sends the translation results to the audio glasses.

[0335] 7. Feedback

[0336] The audio glasses visually display "Hello, how are you?" and the emotion "Joy."

[0337] User A checks the displayed translation results and emotions, and continues the conversation naturally while observing the other person's facial expressions.

[0338] Use in business meetings

[0339] 1. Preparation

[0340] User B puts on the audio glasses and the system is ready.

[0341] 2. Voice Input

[0342] User B says, "How is this project going?"

[0343] The audio glasses capture the sound and send it to your device.

[0344] 3. Audio Data Processing

[0345] The terminal transmits the received voice data to the server.

[0346] The server converts "How is this project going?" into text.

[0347] 4. Emotional Recognition

[0348] The server analyzes User B's emotions based on the voice data.

[0349] The emotion engine recognizes User B's emotion as "interest."

[0350] 5. Text Translation

[0351] The server passes this text to a generative AI translation service.

[0352] The generative AI translates this to "How is the progress of this project?"

[0353] 6. Returning the translation results

[0354] The server returns the translation results and emotion data to the device.

[0355] The device sends the translation results to the audio glasses.

[0356] 7. Feedback

[0357] The audio glasses visually display "How is the progress of this project?" and the emotion "Interested."

[0358] User B checks the displayed translation results and sentiments, allowing the business conversation to proceed smoothly.

[0359] In this way, this system provides an environment in which users can communicate naturally, realizing dialogue that transcends language barriers.

[0360] The processing flow will be explained below.

[0361] Step 1:

[0362] The user puts on the audio glasses and turns on the device. The audio glasses connect to the device.

[0363] Step 2:

[0364] The device receives the connection signal from the audio glasses and confirms the pairing. The device sends the connection information to the server and links it with the user data.

[0365] Step 3:

[0366] When the user initiates a conversation, the audio glasses' microphone captures the spoken voice, which is then sent to the device in real time.

[0367] Step 4:

[0368] The terminal transmits the received voice data to the server, and the server receives the voice data.

[0369] Step 5:

[0370] The server uses speech recognition technology to convert the voice data into text, generating text data.

[0371] Step 6:

[0372] The server analyzes the user's emotions using an emotion engine based on the voice data, and the emotion engine generates emotion data and returns it to the server.

[0373] Step 7:

[0374] The server calls the generation AI (translation service) to translate the generated text. The generation AI translates the text into the specified language.

[0375] Step 8:

[0376] The server returns the text data and emotion data of the translation result to the terminal.

[0377] Step 9:

[0378] The device receives the translation results and emotion data and sends them to the audio glasses.

[0379] Step 10:

[0380] The audio glasses provide feedback to the user by visually displaying the translation results and emotional data, allowing the user to continue the dialogue based on the displayed information.

[0381] Step 11:

[0382] If necessary, the device will synthesize the translation result into voice and play it through the Audio Glasses' speakers.

[0383] Example 2

[0384] 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."

[0385] Conventional speech translation systems simply convert speech into text and translate that text, making it difficult to understand the emotions of the person they are speaking to. Another problem is that the use of multiple devices and applications makes the operation process complicated. The present invention aims to solve these problems and provide a system that allows users to have natural conversations.

[0386] 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 an analysis means for analyzing emotions based on voice information, a conversion means for converting the voice information into text information, and a translation means for translating the text information. This allows the user to understand not only the language of the person they are talking to, but also their emotions in real time.

[0387] A "display means" is a device worn by a user that displays information visually or audibly.

[0388] The "information processing terminal" is a device connected to a display means, and is a device that transmits and receives voice information and processes data.

[0389] A "data processing device" is a device connected to an information processing terminal, and is a system that converts and analyzes voice information.

[0390] The "audio capturing means" is a device that has the function of capturing audio and transmitting it to the information processing terminal.

[0391] The "conversion means" is a system in a data processing device that has the function of converting voice information into text information.

[0392] The "translation means" is a system having a function of translating the text information converted by the conversion means into another language.

[0393] The "analysis means" is a system that has the function of analyzing emotions based on voice information in a data processing device.

[0394] The "audio output means" is a device that has the function of outputting text information as audio.

[0395] An "audio input device" is a device that contains a microphone that functions as a means for capturing audio.

[0396] The present invention embodies a system that is mainly composed of a display device worn by a user, an information processing terminal, and a data processing device. This system enables users to overcome language barriers and even understand the emotions of others. Detailed embodiments of this system are described below.

[0397] System Configuration

[0398] This system includes a display means (audio glasses) worn by the user, an information processing terminal (smartphone or PC), a data processing device (server), a voice capture means (microphone in the audio glasses), a conversion means (voice recognition engine), a translation means (generative AI translation service), and an analysis means (emotion engine).

[0399] Hardware and Software

[0400] Display: A device worn by the user that displays information visually and audibly. For example, audio glasses.

[0401] Information processing terminal: A device connected to a display means that transmits and receives audio information and processes data. Specifically, this applies to smartphones and PCs.

[0402] Data Processing Device (Server): A system that converts and analyzes audio information. This includes suitable cloud servers.

[0403] Audio capture means: A device that has the function of capturing audio and transmitting it to an information processing terminal. The microphone built into the audio glasses is an example of this.

[0404] Conversion method: A system capable of converting voice information into text information. For example, Google's speech recognition API is used.

[0405] Translation tool: A system that can translate converted text into another language, such as OpenAI's generative AI translation model.

[0406] Analysis method: A system that has the function of analyzing emotions based on voice information. This corresponds to an emotion engine.

[0407] Usage example

[0408] Translation of everyday conversations and emotion recognition

[0409] 1. Preparation

[0410] The user puts on the audio glasses and the system is ready.

[0411] 2. Voice Input

[0412] The user says, "Hello, how are you?"

[0413] The audio glasses capture the sound and send it to your device.

[0414] 3. Audio Data Processing

[0415] The terminal transmits the received voice data to the server.

[0416] The server converts "Hello, how are you?" into text.

[0417] 4. Emotional Recognition

[0418] The server analyzes the user's emotions based on the voice data.

[0419] The emotion engine recognizes the user's emotion as "joy."

[0420] 5. Text Translation

[0421] The server passes this text to a generative AI translation service.

[0422] The generative AI translates this to "Hello, how are you?"

[0423] 6. Returning the translation results

[0424] The server returns the translation results and emotion data to the device.

[0425] The device sends the translation results to the audio glasses.

[0426] 7. Feedback

[0427] The audio glasses visually display "Hello, how are you?" and the emotion "Joy."

[0428] The user can check the displayed translation results and emotions, and continue a natural conversation while observing the other person's facial expressions.

[0429] Prompt Sentence Examples

[0430] The user says "Hello, how are you?" Translate this speech to "Hello, how are you?" and recognize the emotion.

[0431] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0432] Step 1:

[0433] Preparing and connecting audio glasses

[0434] When a user wears the audio glasses, the audio glasses are automatically connected to the information processing terminal via Bluetooth. The input is the user's operation of wearing the audio glasses, and the output is the state in which the audio glasses are connected to the information processing terminal.

[0435] The device confirms the Audio Glasses connection and starts communicating with the server. Specifically, the device detects the Audio Glasses Bluetooth connection and sends a connection request to the server via the Internet.

[0436] The server confirms the audioglass connection and links it with the user data. The input is a connection request from the terminal, and the output is the link information between the user data and the audioglass.

[0437] Step 2:

[0438] Voice input recognition

[0439] When the user starts speaking, the microphone in the audio glasses captures the sound. The input is the user's voice and the output is the captured voice data.

[0440] Audio glasses transmit captured audio data to the device in real time. The input is the captured audio data, and the output is the process of transmitting it to the device. Specifically, audio glasses store the audio data in an internal data buffer and transmit it to the device via Bluetooth.

[0441] Step 3:

[0442] Audio data processing

[0443] The terminal sends the received audio data to the server. The input is the audio data sent from the audio glasses, and the output is the process of sending it to the server. Specifically, the terminal transfers packets of audio data to the server via the network.

[0444] The server receives the voice data and converts it into text using voice recognition technology. The input is the voice data received from the terminal, and the output is the converted text data. Specifically, the server starts a voice recognition engine and converts the voice data into text.

[0445] Step 4:

[0446] Emotion recognition

[0447] The server analyzes the user's emotions based on the voice data using an emotion engine. The input is the voice data converted to text by the server, and the output is the analyzed emotion data. Specifically, the server supplies the text data to the emotion engine and performs emotion analysis.

[0448] The emotion engine generates emotion data and returns it to the server. The input is the text data supplied to the emotion engine, and the output is the generated emotion data. Specifically, the emotion engine analyzes the tone and content of the voice and generates emotion data such as "joy."

[0449] Step 5:

[0450] Text translation

[0451] The server calls the generation AI (translation service) to translate the generated text. The input is the converted text data and emotion data, and the output is the translated text data. Specifically, the server sends the text data to the generation AI and requests a translation.

[0452] The generative AI translates text into a specified language. The input is the transmitted text data, and the output is the translated text data. Specifically, the generative AI uses an internal translation model to translate "Hello, how are you?" into "Hello, how are you?"

[0453] Step 6:

[0454] Returning translation results

[0455] The server returns the translation result text data and emotion data to the terminal. The input is the translated text data and emotion data, and the output is the data sent to the terminal. In concrete terms, the server transfers the translation result and emotion data together to the terminal.

[0456] The device receives the translation results and emotion data and sends them to the audio glasses. The input is the translation data and emotion data received from the server, and the output is transmission to the audio glasses. Specifically, the device distributes the data it receives to the audio glasses via Bluetooth.

[0457] Step 7:

[0458] Visual and auditory feedback

[0459] The audio glasses provide feedback to the user by visually displaying the translation results and emotional data. The input is the translation data and emotional data received from the device, and the output is feedback to the user. Specifically, the audio glasses' HUD visually displays "Hello, how are you?" and the emotion "joy."

[0460] If necessary, the device will synthesize the translation result and play it through the Audio Glasses speaker. The input is the translation result text data, and the output is the synthesized voice data. Specifically, the device uses its internal voice synthesis engine to convert the text into voice and output it through the Audio Glasses speaker.

[0461] (Application example 2)

[0462] 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."

[0463] The problem that this invention aims to solve is to provide an environment in which users who speak different languages ​​can converse naturally. Furthermore, it aims to achieve deeper understanding and smoother communication by not only translating but also grasping emotions during the conversation in real time and providing feedback.

[0464] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes text conversion means for converting the voice data into text, translation means for translating the text data converted by the text conversion means, and emotion recognition means for recognizing emotions based on the voice data. This enables an environment in which users can converse in different languages ​​while also understanding the emotions of the other party.

[0465] "User" refers to a person who uses the system of the present invention.

[0466] "Display means" refers to a device worn by a user that visually displays information.

[0467] "Terminal" refers to a device that is connected to a display means and communicates with the Internet and a server.

[0468] "Server" refers to a computer system that processes data sent from a terminal and provides various services.

[0469] "Audio capture means" refers to a device that collects user voice data and transmits it to the terminal.

[0470] "Text conversion means" refers to technology that converts voice data into text data.

[0471] "Translation means" refers to a technology for translating text data into a different language.

[0472] "Emotion recognition means" refers to technology that analyzes and recognizes a user's emotions based on voice data.

[0473] "Audio output means" refers to a device that outputs text data and emotion data as audio.

[0474] The system of the present invention is composed mainly of audio glasses, a terminal, a server, and an emotion recognition engine to provide an environment for users to have natural conversations. This system enables smooth communication between users who speak different languages ​​and can grasp each other's emotions in real time.

[0475] System Configuration

[0476] Hardware:

[0477] Display means: A device worn by the user (audio glasses).

[0478] Device: A smartphone connected to the audio glasses that communicates with the server.

[0479] Audio capture method: Microphone built into the audio glasses.

[0480] software:

[0481] Speech recognition technology: Uses the SpeechRecognition library.

[0482] Translation technology: Google Cloud Translation API.

[0483] Emotion recognition technology: Uses the EmotionEngine library.

[0484] System Operation Overview

[0485] When a user wears the audio glasses and speaks to the system, the system processes the voice in the following steps.

[0486] 1. Audio capture:

[0487] What the user says is captured by the microphone in the audio glasses, and the captured voice data is sent to the server via the device.

[0488] 2. Speech to text transcription:

[0489] The server uses speech recognition technology to convert the voice data into text. This conversion process is performed using the SpeechRecognition library.

[0490] 3. Translation:

[0491] The converted text is then translated into the specified language using the Google Cloud Translation API.

[0492] 4. Emotion recognition:

[0493] At the same time, the server uses the EmotionEngine library to recognize the user's emotions from the voice data, which are then processed together with the translation data.

[0494] 5. Display and Feedback:

[0495] The translation results and recognized emotion data are finally displayed visually as feedback on the audio glasses, and if necessary, the translation results are output as audio.

[0496] Specific examples

[0497] Examples of use in tourist destinations

[0498] Consider a scenario in which a foreign tourist visits a tourist spot in Japan and asks a souvenir shop clerk, "What souvenir do you recommend?" In this case, the clerk is wearing audio glasses and can respond through the system as follows:

[0499] A tourist's question, "What souvenir would you recommend?" is captured by the audio glasses' microphone.

[0500] The voice data is sent to the server via the terminal and converted into text.

[0501] The text data is translated into "What is a recommended souvenir?"

[0502] At the same time, an emotion recognition engine analyzes tourists' emotions and generates emotional data such as curiosity and interest.

[0503] The translated text and emotion data are displayed on the audio glasses, providing visual feedback to the store associate.

[0504] If necessary, the device will output the translation result as speech, playing the English voice saying "What is a recommended souvenir?"

[0505] Prompt Sentence Examples

[0506] To clarify the problem that the invention is trying to solve, consider a specific example of a usage scenario.

[0507] Usage scenario: A foreign tourist asks a store clerk, "What souvenirs do you recommend?"

[0508] Example prompt: "Translate the customer's question into English and identify the emotion."

[0509] In this way, the system of the present invention can provide an environment in which users who speak different languages ​​can have natural conversations in real time and understand each other's emotions.

[0510] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0511] Step 1:

[0512] When the user starts speaking, the microphone in the audio glasses captures the sound. The input is the user's voice and the output is audio data.

[0513] Step 2:

[0514] The device receives audio data from the audio glasses. The received audio data is sent to the server via the device. The input is audio data, and the output is sending the audio data to the server.

[0515] Step 3:

[0516] The server receives the audio data and converts it into text using the SpeechRecognition library. The input is audio data and the output is text data.

[0517] Step 4:

[0518] The server receives the text data and translates it into the specified language using the Google Cloud Translation API. The input is the text data, and the output is the translated text data.

[0519] Step 5:

[0520] The server analyzes the user's emotions based on the voice data using the EmotionEngine library. The input is voice data and the output is emotional data.

[0521] Step 6:

[0522] The server returns the translated text data and emotion data to the terminal. The input is the translated text data and emotion data, and the output is transmission to the terminal.

[0523] Step 7:

[0524] The device receives the translation results and emotion data from the server and sends them to the audio glasses. The input is the translated text data and emotion data, and the output is sent to the audio glasses.

[0525] Step 8:

[0526] The audio glasses visually display the translation results and emotional data and provide feedback to the user. The input is the translated text data and emotional data, and the output is visual feedback. If necessary, the device can also synthesize the translation results into speech and play it through the audio glasses' speakers.

[0527] 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.

[0528] 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.

[0529] 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.

[0530] [Second embodiment]

[0531] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0532] 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.

[0533] 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).

[0534] 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.

[0535] 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.

[0536] 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).

[0537] 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.

[0538] 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.

[0539] 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.

[0540] 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.

[0541] 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.

[0542] 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."

[0543] The present invention implements a system that incorporates a generative AI (translation service) in audio glasses to provide an environment in which users can converse in a natural way. A specific example of this system is described below.

[0544] Overall system flow

[0545] This system is composed mainly of audio glasses worn by the user, a terminal, and a server. When a user puts on the audio glasses and starts a conversation, the system translates and provides speech in real time through the following process.

[0546] Program processing

[0547] 1. Preparing and connecting the audio glasses

[0548] When a user puts on the audio glasses, they automatically connect to the device and begin communicating with the server.

[0549] The server verifies the Audio Glasses connection and links it with the user data.

[0550] 2. Voice input recognition

[0551] When the user starts speaking, a microphone in the audio glasses captures the sound.

[0552] The audio data captured by the audio glasses is sent to the device.

[0553] 3. Translation of audio data

[0554] The terminal transmits the received voice data to the server.

[0555] The server uses voice recognition technology to convert the voice data into text.

[0556] The server uses a generated AI (translation service) to translate the text into the specified language.

[0557] 4. Returning the translation results

[0558] The server returns the translated text data to the terminal.

[0559] The device receives the translation results and sends them to the audio glasses.

[0560] 5. Visual and auditory feedback

[0561] The audio glasses visually display the translation results, allowing users to continue the conversation while checking the other person's facial expressions.

[0562] If necessary, the device will synthesize the translation result into voice and play it through the Audio Glasses' speakers.

[0563] Specific use cases

[0564] Everyday conversation translation

[0565] 1. Preparation

[0566] User A puts on the audio glasses and the system is ready.

[0567] 2. Voice Input

[0568] User A says, "Hello, how are you?"

[0569] The audio glasses capture the sound and send it to your device.

[0570] 3. Translation of audio data

[0571] The terminal transmits the received voice data to the server.

[0572] The server translates "Hello, how are you?" to "Hello, how are you?"

[0573] 4. Returning the translation results

[0574] The server returns the translation results to the terminal.

[0575] The device sends the translation results to the audio glasses.

[0576] 5. Feedback

[0577] The audio glasses visually display "Hello, how are you?"

[0578] User A checks the translation results while looking at the other person's facial expressions and continues the conversation in a natural way.

[0579] Use in business meetings

[0580] 1. Preparation

[0581] User B puts on the audio glasses and the system is ready.

[0582] 2. Voice Input

[0583] User B says, "How is this project going?"

[0584] The audio glasses capture the sound and send it to your device.

[0585] 3. Translation of audio data

[0586] The terminal transmits the received voice data to the server.

[0587] The server translates "How is the progress of this project?" to "How is the progress of this project?"

[0588] 4. Returning the translation results

[0589] The server returns the translation results to the terminal.

[0590] The device sends the translation results to the audio glasses.

[0591] 5. Feedback

[0592] The audio glasses visually display "How is the progress of this project?"

[0593] User B can check the translation results while looking at the other person's facial expression, allowing the business conversation to proceed smoothly.

[0594] In this way, the system provides an environment in which users can communicate naturally, helping to overcome language barriers.

[0595] The processing flow will be explained below.

[0596] Step 1:

[0597] The user puts on the audio glasses and powers on the device.

[0598] Step 2:

[0599] The device receives the connection signal from the audio glasses and confirms pairing.

[0600] Step 3:

[0601] The terminal sends the connection information to the server and links it with the user data.

[0602] Step 4:

[0603] The user initiates the interaction and the audio glasses' microphone captures what is being said.

[0604] Step 5:

[0605] The audio data captured by the audio glasses is sent to the device in real time.

[0606] Step 6:

[0607] The terminal transmits the received voice data to the server.

[0608] Step 7:

[0609] The server receives the voice data and converts it into text using speech recognition technology.

[0610] Step 8:

[0611] The server calls the generation AI (translation service) to translate the generated text.

[0612] Step 9:

[0613] The generation AI translates the text into the specified language and sends the translation results to the server.

[0614] Step 10:

[0615] The server returns the translated text data to the terminal.

[0616] Step 11:

[0617] The device receives the translation results and sends them to the audio glasses for visual display.

[0618] Step 12:

[0619] The audio glasses provide feedback to the user by displaying the translation results on a screen.

[0620] Step 13:

[0621] If necessary, the device synthesizes the translation results into voice and plays them back to the user through the Audio Glasses' speakers.

[0622] Step 14:

[0623] The user can check the displayed translation results and the played audio, and continue the conversation naturally while observing the other person's facial expressions.

[0624] Example 1

[0625] 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."

[0626] Conventional translation systems have had difficulty translating speech data in real time and providing visual and auditory feedback. Furthermore, they often fail to adequately consider improvements in translation performance or data security. This can make it difficult for users to communicate smoothly. It is desirable to solve these issues and provide an environment in which users can communicate naturally.

[0627] 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.

[0628] In this invention, the server includes a speech recognition unit, a generation AI model utilization unit, and an information protection unit, which enables rapid conversion of speech data into text, high-precision translation using the generation AI, and security protection through data encryption.

[0629] A "display means" is a device worn by a user to display visual information.

[0630] A "terminal" is an electronic device connected to a display means and for communicating with a server.

[0631] A "server" is a central processing unit that is connected to a terminal and processes and translates voice data.

[0632] An "audio capture means" is a device that captures a user's voice and converts it into a digital signal.

[0633] "Speech recognition means" refers to a technique or device that converts voice data into text data.

[0634] The "translation means" is a technology or device that translates the text data converted by the speech recognition means into a specified language.

[0635] "Means for utilizing a generative AI model" refers to a device or technology that uses a generative AI model to translate text data.

[0636] "Information protection measures" are technologies or devices that encrypt voice data and translation data to ensure data security during transmission and reception.

[0637] "Visual display means" refers to a screen incorporated in a display or lens for visually displaying the translation results.

[0638] "Audio output means" refers to a speaker or voice synthesis technology for outputting text data as voice.

[0639] This invention provides a system that uses audio glasses equipped with a generative AI model to translate and provide speech in real time, allowing users to converse in a natural way. The system is primarily composed of a display device worn by the user, a terminal, and a server.

[0640] Hardware and software used

[0641] The display means takes the form of audio glasses worn by the user. These audio glasses have a built-in microphone and small display. The device is, for example, a smartphone or tablet, and communicates with the display means via a wireless connection such as Bluetooth or Wi-Fi. The server is installed as a cloud server or on-premise server and performs translation using speech recognition technology and generative AI models (e.g., OpenAI GPT-4 or DeepL).

[0642] System Operation

[0643] Hardware connectivity and communication

[0644] When a user puts on the audio glasses, they automatically connect to the device. Once this connection is established, the device starts communicating with the server over the network. The server obtains the audio glasses and the user's profile information and configures the entire system accordingly.

[0645] Voice input and translation process

[0646] When a user speaks, the microphone in the audio glasses captures the sound, which is then converted into a digital format and transmitted over wireless to the device, where it is then encrypted and sent to a server.

[0647] The server first converts the received voice data into text data using a speech recognition means (e.g., Google Cloud Speech-to-Text API). Then, it translates the text data along with a prompt sentence using a generative AI model. For example, the prompt sentence could be "Please translate the following text into English: 'Hello, how are you?'"

[0648] Returning and displaying translation results

[0649] The translated text data is then re-encrypted and sent back to the device, which then formats it appropriately and sends it to the audio glasses. The audio glasses then visually display the translation results on a small display. If necessary, the device can also output the translation results as audio using speech synthesis technology (e.g., Google Text-to-Speech API) and play it through the audio glasses' speakers.

[0650] Specific use cases

[0651] Use in everyday conversation

[0652] 1. Preparation: User A puts on the audio glasses and the system is ready.

[0653] 2. Voice input: User A says, "Hello, how are you?" The audio glasses capture the voice and send it to the device.

[0654] 3. Voice data translation: The device sends the received voice data to the server, which translates "Hello, how are you?" into "Hello, how are you?"

[0655] 4. Returning the translation result: The server returns the translation result to the device, which then sends it to the audio glasses.

[0656] 5. Feedback: The audio glasses visually display "Hello, how are you?" and optionally play it audibly through the speaker.

[0657] Use in business meetings

[0658] 1. Preparation: User B puts on the audio glasses and the system is ready.

[0659] 2. Voice input: User B says, "How is the progress on this project?" The audio glasses capture the voice and send it to the device.

[0660] 3. Voice data translation: The device sends the received voice data to the server, which translates "How is the progress of this project?" into "How is the progress of this project?"

[0661] 4. Returning the translation result: The server returns the translation result to the device, which then sends it to the audio glasses.

[0662] 5. Feedback: The audio glasses will visually display "How is the progress of this project?" and will play audible feedback through the speakers if necessary.

[0663] In this way, the present invention provides an environment in which users can communicate naturally, helping to overcome language barriers.

[0664] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0665] Program processing flow

[0666] Step 1:

[0667] Preparing and connecting audio glasses

[0668] Specific behavior:

[0669] The user puts on the audio glasses, which automatically connect to the terminal as a display device.

[0670] The device confirms the Bluetooth connection with the audio glasses and then starts communicating with the server over the Internet.

[0671] The server verifies the connection between the audio glasses and the device, obtains the user's profile information, and links them.

[0672] input:

[0673] Audio glasses connection start signal

[0674] output:

[0675] Establishing a connection between the audio glasses, the device, and the server

[0676] Loading a user's profile information

[0677] Step 2:

[0678] Voice input recognition

[0679] Specific behavior:

[0680] The user speaks a word, for example, "Hello, how are you?"

[0681] A microphone inside the audio glasses captures sound and converts the audio data into a digital format.

[0682] The audio glasses transmit digital audio data to the device via Bluetooth.

[0683] input:

[0684] User-generated speech

[0685] output:

[0686] Audio data converted into digital format

[0687] Step 3:

[0688] Sending audio data

[0689] Specific behavior:

[0690] The device encrypts the audio data received from the audio glasses.

[0691] The terminal transmits the encrypted voice data to the server via the network.

[0692] input:

[0693] Audio data sent from audio glasses

[0694] output:

[0695] Sending encrypted audio data to the server

[0696] Step 4:

[0697] Speech recognition of audio data

[0698] Specific behavior:

[0699] The server decrypts the received encrypted voice data and converts it into text data using a voice recognition method (e.g., Google Cloud Speech-to-Text API).

[0700] input:

[0701] Encrypted audio data

[0702] output:

[0703] Text data

[0704] Step 5:

[0705] Text data translation

[0706] Specific behavior:

[0707] The server translates the text data into the specified language using a generative AI model, using the prompt "Please translate the following text into English: 'Hello, how are you?'"

[0708] input:

[0709] Text data generated by speech recognition

[0710] output:

[0711] Translated text data

[0712] Step 6:

[0713] Sending translation results

[0714] Specific behavior:

[0715] The server re-encrypts the translated text data and sends it to the terminal.

[0716] input:

[0717] Translated text data

[0718] output:

[0719] Encrypted translation data

[0720] Step 7:

[0721] Receiving and displaying translation results

[0722] Specific behavior:

[0723] The terminal receives and decrypts the encrypted translation data.

[0724] The device sends the decoded translation data to the audio glasses.

[0725] The audio glasses display the translation results using a visual display means.

[0726] input:

[0727] Encrypted translation data

[0728] output:

[0729] Translation results displayed on the audio glasses display

[0730] Step 8:

[0731] Audio output (if needed)

[0732] Specific behavior:

[0733] The device uses speech synthesis technology (e.g., Google Text-to-Speech API) to convert the translated text into speech.

[0734] The audio glasses play the sound through the speakers.

[0735] input:

[0736] Translated text data

[0737] output:

[0738] Voice output of translation results

[0739] Through the above processing steps, this system provides an environment in which users can interact in a natural way.

[0740] (Application example 1)

[0741] 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."

[0742] In conventional multilingual environments in factories, the transmission of work instructions took time, resulting in poor communication efficiency. In particular, in workplaces with a mix of workers from various countries, language barriers often compromised the accuracy and timing of work. Therefore, there was a need for a system that would enable accurate multilingual translation in real time, allowing work instructions to be transmitted quickly and efficiently.

[0743] 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.

[0744] In this invention, the server includes a means for converting voice data into text, a means for translating text data, and a means for generating prompt sentences including a generative AI model. This allows workers to immediately receive multilingual translation results visually and audibly in real time, enabling smooth communication even in multinational workplaces.

[0745] The "display means" is a device that allows the user to visually confirm information.

[0746] A "terminal" is a device that communicates with a display means and processes and transmits data.

[0747] A "server" is a central device that processes data sent from terminals and returns data as needed.

[0748] The "voice capture means" is a device for inputting the user's voice.

[0749] "Text conversion means" refers to a device or function for converting voice data into text data.

[0750] The "translation means" is a device or function for translating text data into another specified language.

[0751] A "generative AI model" is an artificial intelligence model that generates prompt sentences based on specified input data and generates appropriate output accordingly.

[0752] A "prompt sentence generation means" is a device or function that uses a generative AI model to generate a prompt sentence based on input data.

[0753] This invention provides real-time multilingual translation using a system that includes a display device worn by the user (e.g., audio glasses), a terminal, and a server. Specifically, the system is configured using the following hardware and software:

[0754] Hardware

[0755] Display means: Device worn by the user, such as audio glasses.

[0756] Terminal: A device that communicates with a display means, such as a smartphone or tablet.

[0757] Server: A central device that processes data sent from terminals.

[0758] Audio capture method: Microphone built into the audio glasses.

[0759] Audio output means: Speaker built into the audio glasses.

[0760] software

[0761] Speech recognition library (speech_recognition): Converts voice data into text data.

[0762] Translation library (translate): Translates text data into other specified languages.

[0763] Speech synthesis library (pyttsx3): Converts text data into speech data.

[0764] Process Overview

[0765] 1. Capture audio input:

[0766] The user's voice is captured by a microphone built into the audio glasses, which is highly sensitive and accurately captures the user's voice while rejecting surrounding noise.

[0767] 2. Audio to text conversion:

[0768] The server uses speech recognition technology to convert the audio data into text data. The speech_recognition library is responsible for this process.

[0769] 3. Translation of text data:

[0770] The translation library, translate, translates the text data, while a generative AI model generates prompts to improve translation accuracy.

[0771] 4. Prompt generation:

[0772] The generative AI model generates appropriate prompt sentences based on user input, which are then referenced by the server for optimal translation.

[0773] For example, when translating "Please stop the machine," the following prompt sentence is generated: "Translate the following Japanese sentence to English: 'Please stop the machine'"

[0774] 5. Output of translation results:

[0775] The translated text is sent to the display means via the terminal, and the translation result is displayed on the display of the audio glasses.

[0776] In addition, the translated text is converted into audio data using a speech synthesis library (pyttsx3) and played through the audio glasses' speakers.

[0777] Specific examples

[0778] For example, if a factory leader issues the command "Stop the machine" in Japanese, this voice is captured by the microphone in the audio glasses, and the following prompt sentence is generated by the generative AI model:

[0779] Translate the following Japanese sentence into English: 'Please stop the machine.'

[0780] As a result, the translated text "Please stop the machine" appears on the audio glasses' display and is simultaneously output as audio.

[0781] This allows foreign workers in the factory to understand accurate instructions in real time and continue working smoothly. This system will greatly improve communication efficiency in workplaces with multilingual environments.

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

[0783] Step 1:

[0784] The user wears the audio glasses and inputs voice. The microphone built into the audio glasses captures the user's speech. This voice data is sent to the device. The input is the user's voice, and the output is voice data.

[0785] Step 2:

[0786] The device sends the captured audio data to the server. The input is audio data, and the output is sending audio data to the server. The device communicates with the server via a network.

[0787] Step 3:

[0788] The server converts the received voice data into text data using the speech_recognition library. The input is voice data and the output is text data. This process converts the voice data into meaningful strings of characters.

[0789] Step 4:

[0790] The server uses a translation library (translate) to translate the text data into another specified language. At this time, a generative AI model generates a prompt sentence to improve the accuracy of the translation. The input is the text data, and the output is the translated text data. An example of a generated prompt sentence is "Translate the following Japanese sentence to English: 'Please stop the machine'".

[0791] Step 5:

[0792] The server returns the translated text data to the terminal. The input is the translated text data, and the output is the transmission of the text data to the terminal. The data from the server is received by the terminal.

[0793] Step 6:

[0794] The terminal sends the received translation text data to the audio glasses. The input is the translated text data, and the output is the transmission of the text data to the audio glasses. The terminal works in conjunction with the audio glasses.

[0795] Step 7:

[0796] Audio Glasses visually displays translated text data using a display device. It also converts the text data into audio data using a speech synthesis library (pyttsx3) and plays it as audio through a built-in speaker. The input is the translated text data, and the output is a visual display and audio output. The user can check the translation results through the displayed text and played audio.

[0797] 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.

[0798] The present invention implements a system that incorporates a generative AI (translation service) and an emotion engine into audio glasses to provide an environment in which users can have natural conversations. This system allows users to overcome language barriers and understand the emotions of others. A specific example of this system is described below.

[0799] Overall system flow

[0800] This system is composed mainly of audio glasses worn by the user, a terminal, a server, and an emotion recognition engine. When a user puts on the audio glasses and starts a conversation, the system translates the speech and recognizes emotions in real time through the following process.

[0801] Program processing

[0802] 1. Preparing and connecting the audio glasses

[0803] When a user puts on the audio glasses, they automatically connect to the device and begin communicating with the server.

[0804] The server verifies the Audio Glasses connection and links it with the user data.

[0805] 2. Voice input recognition

[0806] When the user starts speaking, a microphone in the audio glasses captures the sound.

[0807] The audio data captured by the audio glasses is sent to the device in real time.

[0808] 3. Audio Data Processing

[0809] The terminal transmits the received voice data to the server.

[0810] The server receives the voice data and converts it into text using speech recognition technology.

[0811] 4. Emotional Recognition

[0812] The server analyzes the user's emotions using an emotion engine based on the voice data.

[0813] The emotion engine generates emotion data and returns it to the server.

[0814] 5. Text Translation

[0815] The server calls the generation AI (translation service) to translate the generated text.

[0816] The generative AI translates text into the specified language.

[0817] 6. Returning the translation results

[0818] The server returns the text data and emotion data of the translation result to the terminal.

[0819] The device receives the translation results and emotion data and sends them to the audio glasses.

[0820] 7. Visual and auditory feedback

[0821] The audio glasses provide feedback to the user by visually displaying translation results and emotional data.

[0822] If necessary, the device will synthesize the translation result into voice and play it through the Audio Glasses' speakers.

[0823] Specific use cases

[0824] Translation of everyday conversations and emotion recognition

[0825] 1. Preparation

[0826] User A puts on the audio glasses and the system is ready.

[0827] 2. Voice Input

[0828] User A says, "Hello, how are you?"

[0829] The audio glasses capture the sound and send it to your device.

[0830] 3. Audio Data Processing

[0831] The terminal transmits the received voice data to the server.

[0832] The server converts "Hello, how are you?" into text.

[0833] 4. Emotional Recognition

[0834] The server analyzes user A's emotions based on the voice data.

[0835] The emotion engine recognizes User A's emotion as "joy."

[0836] 5. Text Translation

[0837] The server passes this text to a generative AI translation service.

[0838] The generative AI translates this to "Hello, how are you?"

[0839] 6. Returning the translation results

[0840] The server returns the translation results and emotion data to the device.

[0841] The device sends the translation results to the audio glasses.

[0842] 7. Feedback

[0843] The audio glasses visually display "Hello, how are you?" and the emotion "Joy."

[0844] User A checks the displayed translation results and emotions, and continues the conversation naturally while observing the other person's facial expressions.

[0845] Use in business meetings

[0846] 1. Preparation

[0847] User B puts on the audio glasses and the system is ready.

[0848] 2. Voice Input

[0849] User B says, "How is this project going?"

[0850] The audio glasses capture the sound and send it to your device.

[0851] 3. Audio Data Processing

[0852] The terminal transmits the received voice data to the server.

[0853] The server converts "How is this project going?" into text.

[0854] 4. Emotional Recognition

[0855] The server analyzes User B's emotions based on the voice data.

[0856] The emotion engine recognizes User B's emotion as "interest."

[0857] 5. Text Translation

[0858] The server passes this text to a generative AI translation service.

[0859] The generative AI translates this to "How is the progress of this project?"

[0860] 6. Returning the translation results

[0861] The server returns the translation results and emotion data to the device.

[0862] The device sends the translation results to the audio glasses.

[0863] 7. Feedback

[0864] The audio glasses visually display "How is the progress of this project?" and the emotion "Interested."

[0865] User B checks the displayed translation results and sentiments, allowing the business conversation to proceed smoothly.

[0866] In this way, this system provides an environment in which users can communicate naturally, realizing dialogue that transcends language barriers.

[0867] The processing flow will be explained below.

[0868] Step 1:

[0869] The user puts on the audio glasses and turns on the device. The audio glasses connect to the device.

[0870] Step 2:

[0871] The device receives the connection signal from the audio glasses and confirms the pairing. The device sends the connection information to the server and links it with the user data.

[0872] Step 3:

[0873] When the user initiates a conversation, the audio glasses' microphone captures the spoken voice, which is then sent to the device in real time.

[0874] Step 4:

[0875] The terminal transmits the received voice data to the server, and the server receives the voice data.

[0876] Step 5:

[0877] The server uses speech recognition technology to convert the voice data into text, generating text data.

[0878] Step 6:

[0879] The server analyzes the user's emotions using an emotion engine based on the voice data, and the emotion engine generates emotion data and returns it to the server.

[0880] Step 7:

[0881] The server calls the generation AI (translation service) to translate the generated text. The generation AI translates the text into the specified language.

[0882] Step 8:

[0883] The server returns the text data and emotion data of the translation result to the terminal.

[0884] Step 9:

[0885] The device receives the translation results and emotion data and sends them to the audio glasses.

[0886] Step 10:

[0887] The audio glasses provide feedback to the user by visually displaying the translation results and emotional data, allowing the user to continue the dialogue based on the displayed information.

[0888] Step 11:

[0889] If necessary, the device will synthesize the translation result into voice and play it through the Audio Glasses' speakers.

[0890] Example 2

[0891] 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."

[0892] Conventional speech translation systems simply convert speech into text and translate that text, making it difficult to understand the emotions of the person they are speaking to. Another problem is that the use of multiple devices and applications makes the operation process complicated. The present invention aims to solve these problems and provide a system that allows users to have natural conversations.

[0893] 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 an analysis means for analyzing emotions based on voice information, a conversion means for converting the voice information into text information, and a translation means for translating the text information. This allows the user to understand not only the language of the person they are talking to, but also their emotions in real time.

[0894] A "display means" is a device worn by a user that displays information visually or audibly.

[0895] The "information processing terminal" is a device connected to a display means, and is a device that transmits and receives voice information and processes data.

[0896] A "data processing device" is a device connected to an information processing terminal, and is a system that converts and analyzes voice information.

[0897] The "audio capturing means" is a device that has the function of capturing audio and transmitting it to the information processing terminal.

[0898] The "conversion means" is a system in a data processing device that has the function of converting voice information into text information.

[0899] The "translation means" is a system having a function of translating the text information converted by the conversion means into another language.

[0900] The "analysis means" is a system that has the function of analyzing emotions based on voice information in a data processing device.

[0901] The "audio output means" is a device that has the function of outputting text information as audio.

[0902] An "audio input device" is a device that contains a microphone that functions as a means for capturing audio.

[0903] The present invention embodies a system that is mainly composed of a display device worn by a user, an information processing terminal, and a data processing device. This system enables users to overcome language barriers and even understand the emotions of others. Detailed embodiments of this system are described below.

[0904] System Configuration

[0905] This system includes a display means (audio glasses) worn by the user, an information processing terminal (smartphone or PC), a data processing device (server), a voice capture means (microphone in the audio glasses), a conversion means (voice recognition engine), a translation means (generative AI translation service), and an analysis means (emotion engine).

[0906] Hardware and Software

[0907] Display: A device worn by the user that displays information visually and audibly. For example, audio glasses.

[0908] Information processing terminal: A device connected to a display means that transmits and receives audio information and processes data. Specifically, this applies to smartphones and PCs.

[0909] Data Processing Device (Server): A system that converts and analyzes audio information. This includes suitable cloud servers.

[0910] Audio capture means: A device that has the function of capturing audio and transmitting it to an information processing terminal. The microphone built into the audio glasses is an example of this.

[0911] Conversion method: A system capable of converting voice information into text information. For example, Google's speech recognition API is used.

[0912] Translation tool: A system that can translate converted text into another language, such as OpenAI's generative AI translation model.

[0913] Analysis method: A system that has the function of analyzing emotions based on voice information. This corresponds to an emotion engine.

[0914] Usage example

[0915] Translation of everyday conversations and emotion recognition

[0916] 1. Preparation

[0917] The user puts on the audio glasses and the system is ready.

[0918] 2. Voice Input

[0919] The user says, "Hello, how are you?"

[0920] The audio glasses capture the sound and send it to your device.

[0921] 3. Audio Data Processing

[0922] The terminal transmits the received voice data to the server.

[0923] The server converts "Hello, how are you?" into text.

[0924] 4. Emotional Recognition

[0925] The server analyzes the user's emotions based on the voice data.

[0926] The emotion engine recognizes the user's emotion as "joy."

[0927] 5. Text Translation

[0928] The server passes this text to a generative AI translation service.

[0929] The generative AI translates this to "Hello, how are you?"

[0930] 6. Returning the translation results

[0931] The server returns the translation results and emotion data to the device.

[0932] The device sends the translation results to the audio glasses.

[0933] 7. Feedback

[0934] The audio glasses visually display "Hello, how are you?" and the emotion "Joy."

[0935] The user can check the displayed translation results and emotions, and continue a natural conversation while observing the other person's facial expressions.

[0936] Prompt Sentence Examples

[0937] The user says "Hello, how are you?" Translate this speech to "Hello, how are you?" and recognize the emotion.

[0938] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0939] Step 1:

[0940] Preparing and connecting audio glasses

[0941] When a user wears the audio glasses, the audio glasses are automatically connected to the information processing terminal via Bluetooth. The input is the user's operation of wearing the audio glasses, and the output is the state in which the audio glasses are connected to the information processing terminal.

[0942] The device confirms the Audio Glasses connection and starts communicating with the server. Specifically, the device detects the Audio Glasses Bluetooth connection and sends a connection request to the server via the Internet.

[0943] The server confirms the audioglass connection and links it with the user data. The input is a connection request from the terminal, and the output is the link information between the user data and the audioglass.

[0944] Step 2:

[0945] Voice input recognition

[0946] When the user starts speaking, the microphone in the audio glasses captures the sound. The input is the user's voice and the output is the captured voice data.

[0947] Audio glasses transmit captured audio data to the device in real time. The input is the captured audio data, and the output is the process of transmitting it to the device. Specifically, audio glasses store the audio data in an internal data buffer and transmit it to the device via Bluetooth.

[0948] Step 3:

[0949] Audio data processing

[0950] The terminal sends the received audio data to the server. The input is the audio data sent from the audio glasses, and the output is the process of sending it to the server. Specifically, the terminal transfers packets of audio data to the server via the network.

[0951] The server receives the voice data and converts it into text using voice recognition technology. The input is the voice data received from the terminal, and the output is the converted text data. Specifically, the server starts a voice recognition engine and converts the voice data into text.

[0952] Step 4:

[0953] Emotion recognition

[0954] The server analyzes the user's emotions based on the voice data using an emotion engine. The input is the voice data converted to text by the server, and the output is the analyzed emotion data. Specifically, the server supplies the text data to the emotion engine and performs emotion analysis.

[0955] The emotion engine generates emotion data and returns it to the server. The input is the text data supplied to the emotion engine, and the output is the generated emotion data. Specifically, the emotion engine analyzes the tone and content of the voice and generates emotion data such as "joy."

[0956] Step 5:

[0957] Text translation

[0958] The server calls the generation AI (translation service) to translate the generated text. The input is the converted text data and emotion data, and the output is the translated text data. Specifically, the server sends the text data to the generation AI and requests a translation.

[0959] The generative AI translates text into a specified language. The input is the transmitted text data, and the output is the translated text data. Specifically, the generative AI uses an internal translation model to translate "Hello, how are you?" into "Hello, how are you?"

[0960] Step 6:

[0961] Returning translation results

[0962] The server returns the translation result text data and emotion data to the terminal. The input is the translated text data and emotion data, and the output is the data sent to the terminal. In concrete terms, the server transfers the translation result and emotion data together to the terminal.

[0963] The device receives the translation results and emotion data and sends them to the audio glasses. The input is the translation data and emotion data received from the server, and the output is transmission to the audio glasses. Specifically, the device distributes the data it receives to the audio glasses via Bluetooth.

[0964] Step 7:

[0965] Visual and auditory feedback

[0966] The audio glasses provide feedback to the user by visually displaying the translation results and emotional data. The input is the translation data and emotional data received from the device, and the output is feedback to the user. Specifically, the audio glasses' HUD visually displays "Hello, how are you?" and the emotion "joy."

[0967] If necessary, the device will synthesize the translation result and play it through the Audio Glasses speaker. The input is the translation result text data, and the output is the synthesized voice data. Specifically, the device uses its internal voice synthesis engine to convert the text into voice and output it through the Audio Glasses speaker.

[0968] (Application example 2)

[0969] 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."

[0970] The problem that this invention aims to solve is to provide an environment in which users who speak different languages ​​can converse naturally. Furthermore, it aims to achieve deeper understanding and smoother communication by not only translating but also grasping emotions during the conversation in real time and providing feedback.

[0971] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes text conversion means for converting the voice data into text, translation means for translating the text data converted by the text conversion means, and emotion recognition means for recognizing emotions based on the voice data. This enables an environment in which users can converse in different languages ​​while also understanding the emotions of the other party.

[0972] "User" refers to a person who uses the system of the present invention.

[0973] "Display means" refers to a device worn by a user that visually displays information.

[0974] "Terminal" refers to a device that is connected to a display means and communicates with the Internet and a server.

[0975] "Server" refers to a computer system that processes data sent from a terminal and provides various services.

[0976] "Audio capture means" refers to a device that collects user voice data and transmits it to the terminal.

[0977] "Text conversion means" refers to technology that converts voice data into text data.

[0978] "Translation means" refers to a technology for translating text data into a different language.

[0979] "Emotion recognition means" refers to technology that analyzes and recognizes a user's emotions based on voice data.

[0980] "Audio output means" refers to a device that outputs text data and emotion data as audio.

[0981] The system of the present invention is composed mainly of audio glasses, a terminal, a server, and an emotion recognition engine to provide an environment for users to have natural conversations. This system enables smooth communication between users who speak different languages ​​and can grasp each other's emotions in real time.

[0982] System Configuration

[0983] Hardware:

[0984] Display means: A device worn by the user (audio glasses).

[0985] Device: A smartphone connected to the audio glasses that communicates with the server.

[0986] Audio capture method: Microphone built into the audio glasses.

[0987] software:

[0988] Speech recognition technology: Uses the SpeechRecognition library.

[0989] Translation technology: Google Cloud Translation API.

[0990] Emotion recognition technology: Uses the EmotionEngine library.

[0991] System Operation Overview

[0992] When a user wears the audio glasses and speaks to the system, the system processes the voice in the following steps.

[0993] 1. Audio capture:

[0994] What the user says is captured by the microphone in the audio glasses, and the captured voice data is sent to the server via the device.

[0995] 2. Speech to text transcription:

[0996] The server uses speech recognition technology to convert the voice data into text. This conversion process is performed using the SpeechRecognition library.

[0997] 3. Translation:

[0998] The converted text is then translated into the specified language using the Google Cloud Translation API.

[0999] 4. Emotion recognition:

[1000] At the same time, the server uses the EmotionEngine library to recognize the user's emotions from the voice data, which are then processed together with the translation data.

[1001] 5. Display and Feedback:

[1002] The translation results and recognized emotion data are finally displayed visually as feedback on the audio glasses, and if necessary, the translation results are output as audio.

[1003] Specific examples

[1004] Examples of use in tourist destinations

[1005] Consider a scenario in which a foreign tourist visits a tourist spot in Japan and asks a souvenir shop clerk, "What souvenir do you recommend?" In this case, the clerk is wearing audio glasses and can respond through the system as follows:

[1006] A tourist's question, "What souvenir would you recommend?" is captured by the audio glasses' microphone.

[1007] The voice data is sent to the server via the terminal and converted into text.

[1008] The text data is translated into "What is a recommended souvenir?"

[1009] At the same time, an emotion recognition engine analyzes tourists' emotions and generates emotional data such as curiosity and interest.

[1010] The translated text and emotion data are displayed on the audio glasses, providing visual feedback to the store associate.

[1011] If necessary, the device will output the translation result as speech, playing the English voice saying "What is a recommended souvenir?"

[1012] Prompt Sentence Examples

[1013] To clarify the problem that the invention is trying to solve, consider a specific example of a usage scenario.

[1014] Usage scenario: A foreign tourist asks a store clerk, "What souvenirs do you recommend?"

[1015] Example prompt: "Translate the customer's question into English and identify the emotion."

[1016] In this way, the system of the present invention can provide an environment in which users who speak different languages ​​can have natural conversations in real time and understand each other's emotions.

[1017] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1018] Step 1:

[1019] When the user starts speaking, the microphone in the audio glasses captures the sound. The input is the user's voice and the output is audio data.

[1020] Step 2:

[1021] The device receives audio data from the audio glasses. The received audio data is sent to the server via the device. The input is audio data, and the output is sending the audio data to the server.

[1022] Step 3:

[1023] The server receives the audio data and converts it into text using the SpeechRecognition library. The input is audio data and the output is text data.

[1024] Step 4:

[1025] The server receives the text data and translates it into the specified language using the Google Cloud Translation API. The input is the text data, and the output is the translated text data.

[1026] Step 5:

[1027] The server analyzes the user's emotions based on the voice data using the EmotionEngine library. The input is voice data and the output is emotional data.

[1028] Step 6:

[1029] The server returns the translated text data and emotion data to the terminal. The input is the translated text data and emotion data, and the output is transmission to the terminal.

[1030] Step 7:

[1031] The device receives the translation results and emotion data from the server and sends them to the audio glasses. The input is the translated text data and emotion data, and the output is sent to the audio glasses.

[1032] Step 8:

[1033] The audio glasses visually display the translation results and emotional data and provide feedback to the user. The input is the translated text data and emotional data, and the output is visual feedback. If necessary, the device can also synthesize the translation results into speech and play it through the audio glasses' speakers.

[1034] 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.

[1035] 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.

[1036] 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.

[1037] [Third embodiment]

[1038] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1039] 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.

[1040] 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).

[1041] 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.

[1042] 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.

[1043] 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).

[1044] 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.

[1045] 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.

[1046] 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.

[1047] 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.

[1048] 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.

[1049] 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."

[1050] The present invention implements a system that incorporates a generative AI (translation service) in audio glasses to provide an environment in which users can converse in a natural way. A specific example of this system is described below.

[1051] Overall system flow

[1052] This system is composed mainly of audio glasses worn by the user, a terminal, and a server. When a user puts on the audio glasses and starts a conversation, the system translates and provides speech in real time through the following process.

[1053] Program processing

[1054] 1. Preparing and connecting the audio glasses

[1055] When a user puts on the audio glasses, they automatically connect to the device and begin communicating with the server.

[1056] The server verifies the Audio Glasses connection and links it with the user data.

[1057] 2. Voice input recognition

[1058] When the user starts speaking, a microphone in the audio glasses captures the sound.

[1059] The audio data captured by the audio glasses is sent to the device.

[1060] 3. Translation of audio data

[1061] The terminal transmits the received voice data to the server.

[1062] The server uses voice recognition technology to convert the voice data into text.

[1063] The server uses a generated AI (translation service) to translate the text into the specified language.

[1064] 4. Returning the translation results

[1065] The server returns the translated text data to the terminal.

[1066] The device receives the translation results and sends them to the audio glasses.

[1067] 5. Visual and auditory feedback

[1068] The audio glasses visually display the translation results, allowing users to continue the conversation while checking the other person's facial expressions.

[1069] If necessary, the device will synthesize the translation result into voice and play it through the Audio Glasses' speakers.

[1070] Specific use cases

[1071] Everyday conversation translation

[1072] 1. Preparation

[1073] User A puts on the audio glasses and the system is ready.

[1074] 2. Voice Input

[1075] User A says, "Hello, how are you?"

[1076] The audio glasses capture the sound and send it to your device.

[1077] 3. Translation of audio data

[1078] The terminal transmits the received voice data to the server.

[1079] The server translates "Hello, how are you?" to "Hello, how are you?"

[1080] 4. Returning the translation results

[1081] The server returns the translation results to the terminal.

[1082] The device sends the translation results to the audio glasses.

[1083] 5. Feedback

[1084] The audio glasses visually display "Hello, how are you?"

[1085] User A checks the translation results while looking at the other person's facial expressions and continues the conversation in a natural way.

[1086] Use in business meetings

[1087] 1. Preparation

[1088] User B puts on the audio glasses and the system is ready.

[1089] 2. Voice Input

[1090] User B says, "How is this project going?"

[1091] The audio glasses capture the sound and send it to your device.

[1092] 3. Translation of audio data

[1093] The terminal transmits the received voice data to the server.

[1094] The server translates "How is the progress of this project?" to "How is the progress of this project?"

[1095] 4. Returning the translation results

[1096] The server returns the translation results to the terminal.

[1097] The device sends the translation results to the audio glasses.

[1098] 5. Feedback

[1099] The audio glasses visually display "How is the progress of this project?"

[1100] User B can check the translation results while looking at the other person's facial expression, allowing the business conversation to proceed smoothly.

[1101] In this way, the system provides an environment in which users can communicate naturally, helping to overcome language barriers.

[1102] The processing flow will be explained below.

[1103] Step 1:

[1104] The user puts on the audio glasses and powers on the device.

[1105] Step 2:

[1106] The device receives the connection signal from the audio glasses and confirms pairing.

[1107] Step 3:

[1108] The terminal sends the connection information to the server and links it with the user data.

[1109] Step 4:

[1110] The user initiates the interaction and the audio glasses' microphone captures what is being said.

[1111] Step 5:

[1112] The audio data captured by the audio glasses is sent to the device in real time.

[1113] Step 6:

[1114] The terminal transmits the received voice data to the server.

[1115] Step 7:

[1116] The server receives the voice data and converts it into text using speech recognition technology.

[1117] Step 8:

[1118] The server calls the generation AI (translation service) to translate the generated text.

[1119] Step 9:

[1120] The generation AI translates the text into the specified language and sends the translation results to the server.

[1121] Step 10:

[1122] The server returns the translated text data to the terminal.

[1123] Step 11:

[1124] The device receives the translation results and sends them to the audio glasses for visual display.

[1125] Step 12:

[1126] The audio glasses provide feedback to the user by displaying the translation results on a screen.

[1127] Step 13:

[1128] If necessary, the device synthesizes the translation results into voice and plays them back to the user through the Audio Glasses' speakers.

[1129] Step 14:

[1130] The user can check the displayed translation results and the played audio, and continue the conversation naturally while observing the other person's facial expressions.

[1131] Example 1

[1132] 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."

[1133] Conventional translation systems have had difficulty translating speech data in real time and providing visual and auditory feedback. Furthermore, they often fail to adequately consider improvements in translation performance or data security. This can make it difficult for users to communicate smoothly. It is desirable to solve these issues and provide an environment in which users can communicate naturally.

[1134] 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.

[1135] In this invention, the server includes a speech recognition unit, a generation AI model utilization unit, and an information protection unit, which enables rapid conversion of speech data into text, high-precision translation using the generation AI, and security protection through data encryption.

[1136] A "display means" is a device worn by a user to display visual information.

[1137] A "terminal" is an electronic device connected to a display means and for communicating with a server.

[1138] A "server" is a central processing unit that is connected to a terminal and processes and translates voice data.

[1139] An "audio capture means" is a device that captures a user's voice and converts it into a digital signal.

[1140] "Speech recognition means" refers to a technique or device that converts voice data into text data.

[1141] The "translation means" is a technology or device that translates the text data converted by the speech recognition means into a specified language.

[1142] "Means for utilizing a generative AI model" refers to a device or technology that uses a generative AI model to translate text data.

[1143] "Information protection measures" are technologies or devices that encrypt voice data and translation data to ensure data security during transmission and reception.

[1144] "Visual display means" refers to a screen incorporated in a display or lens for visually displaying the translation results.

[1145] "Audio output means" refers to a speaker or voice synthesis technology for outputting text data as voice.

[1146] This invention provides a system that uses audio glasses equipped with a generative AI model to translate and provide speech in real time, allowing users to converse in a natural way. The system is primarily composed of a display device worn by the user, a terminal, and a server.

[1147] Hardware and software used

[1148] The display means takes the form of audio glasses worn by the user. These audio glasses have a built-in microphone and small display. The device is, for example, a smartphone or tablet, and communicates with the display means via a wireless connection such as Bluetooth or Wi-Fi. The server is installed as a cloud server or on-premise server and performs translation using speech recognition technology and generative AI models (e.g., OpenAI GPT-4 or DeepL).

[1149] System Operation

[1150] Hardware connectivity and communication

[1151] When a user puts on the audio glasses, they automatically connect to the device. Once this connection is established, the device starts communicating with the server over the network. The server obtains the audio glasses and the user's profile information and configures the entire system accordingly.

[1152] Voice input and translation process

[1153] When a user speaks, the microphone in the audio glasses captures the sound, which is then converted into a digital format and transmitted over wireless to the device, where it is then encrypted and sent to a server.

[1154] The server first converts the received voice data into text data using a speech recognition means (e.g., Google Cloud Speech-to-Text API). Then, it translates the text data along with a prompt sentence using a generative AI model. For example, the prompt sentence could be "Please translate the following text into English: 'Hello, how are you?'"

[1155] Returning and displaying translation results

[1156] The translated text data is then re-encrypted and sent back to the device, which then formats it appropriately and sends it to the audio glasses. The audio glasses then visually display the translation results on a small display. If necessary, the device can also output the translation results as audio using speech synthesis technology (e.g., Google Text-to-Speech API) and play it through the audio glasses' speakers.

[1157] Specific use cases

[1158] Use in everyday conversation

[1159] 1. Preparation: User A puts on the audio glasses and the system is ready.

[1160] 2. Voice input: User A says, "Hello, how are you?" The audio glasses capture the voice and send it to the device.

[1161] 3. Voice data translation: The device sends the received voice data to the server, which translates "Hello, how are you?" into "Hello, how are you?"

[1162] 4. Returning the translation result: The server returns the translation result to the device, which then sends it to the audio glasses.

[1163] 5. Feedback: The audio glasses visually display "Hello, how are you?" and optionally play it audibly through the speaker.

[1164] Use in business meetings

[1165] 1. Preparation: User B puts on the audio glasses and the system is ready.

[1166] 2. Voice input: User B says, "How is the progress on this project?" The audio glasses capture the voice and send it to the device.

[1167] 3. Voice data translation: The device sends the received voice data to the server, which translates "How is the progress of this project?" into "How is the progress of this project?"

[1168] 4. Returning the translation result: The server returns the translation result to the device, which then sends it to the audio glasses.

[1169] 5. Feedback: The audio glasses will visually display "How is the progress of this project?" and will play audible feedback through the speakers if necessary.

[1170] In this way, the present invention provides an environment in which users can communicate naturally, helping to overcome language barriers.

[1171] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1172] Program processing flow

[1173] Step 1:

[1174] Preparing and connecting audio glasses

[1175] Specific behavior:

[1176] The user puts on the audio glasses, which automatically connect to the terminal as a display device.

[1177] The device confirms the Bluetooth connection with the audio glasses and then starts communicating with the server over the Internet.

[1178] The server verifies the connection between the audio glasses and the device, obtains the user's profile information, and links them.

[1179] input:

[1180] Audio glasses connection start signal

[1181] output:

[1182] Establishing a connection between the audio glasses, the device, and the server

[1183] Loading a user's profile information

[1184] Step 2:

[1185] Voice input recognition

[1186] Specific behavior:

[1187] The user speaks a word, for example, "Hello, how are you?"

[1188] A microphone inside the audio glasses captures sound and converts the audio data into a digital format.

[1189] The audio glasses transmit digital audio data to the device via Bluetooth.

[1190] input:

[1191] User-generated speech

[1192] output:

[1193] Audio data converted into digital format

[1194] Step 3:

[1195] Sending audio data

[1196] Specific behavior:

[1197] The device encrypts the audio data received from the audio glasses.

[1198] The terminal transmits the encrypted voice data to the server via the network.

[1199] input:

[1200] Audio data sent from audio glasses

[1201] output:

[1202] Sending encrypted audio data to the server

[1203] Step 4:

[1204] Speech recognition of audio data

[1205] Specific behavior:

[1206] The server decrypts the received encrypted voice data and converts it into text data using a voice recognition method (e.g., Google Cloud Speech-to-Text API).

[1207] input:

[1208] Encrypted audio data

[1209] output:

[1210] Text data

[1211] Step 5:

[1212] Text data translation

[1213] Specific behavior:

[1214] The server translates the text data into the specified language using a generative AI model, using the prompt "Please translate the following text into English: 'Hello, how are you?'"

[1215] input:

[1216] Text data generated by speech recognition

[1217] output:

[1218] Translated text data

[1219] Step 6:

[1220] Sending translation results

[1221] Specific behavior:

[1222] The server re-encrypts the translated text data and sends it to the terminal.

[1223] input:

[1224] Translated text data

[1225] output:

[1226] Encrypted translation data

[1227] Step 7:

[1228] Receiving and displaying translation results

[1229] Specific behavior:

[1230] The terminal receives and decrypts the encrypted translation data.

[1231] The device sends the decoded translation data to the audio glasses.

[1232] The audio glasses display the translation results using a visual display means.

[1233] input:

[1234] Encrypted translation data

[1235] output:

[1236] Translation results displayed on the audio glasses display

[1237] Step 8:

[1238] Audio output (if needed)

[1239] Specific behavior:

[1240] The device uses speech synthesis technology (e.g., Google Text-to-Speech API) to convert the translated text into speech.

[1241] The audio glasses play the sound through the speakers.

[1242] input:

[1243] Translated text data

[1244] output:

[1245] Voice output of translation results

[1246] Through the above processing steps, this system provides an environment in which users can interact in a natural way.

[1247] (Application example 1)

[1248] 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."

[1249] In conventional multilingual environments in factories, the transmission of work instructions took time, resulting in poor communication efficiency. In particular, in workplaces with a mix of workers from various countries, language barriers often compromised the accuracy and timing of work. Therefore, there was a need for a system that would enable accurate multilingual translation in real time, allowing work instructions to be transmitted quickly and efficiently.

[1250] 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.

[1251] In this invention, the server includes a means for converting voice data into text, a means for translating text data, and a means for generating prompt sentences including a generative AI model. This allows workers to immediately receive multilingual translation results visually and audibly in real time, enabling smooth communication even in multinational workplaces.

[1252] The "display means" is a device that allows the user to visually confirm information.

[1253] A "terminal" is a device that communicates with a display means and processes and transmits data.

[1254] A "server" is a central device that processes data sent from terminals and returns data as needed.

[1255] The "voice capture means" is a device for inputting the user's voice.

[1256] "Text conversion means" refers to a device or function for converting voice data into text data.

[1257] The "translation means" is a device or function for translating text data into another specified language.

[1258] A "generative AI model" is an artificial intelligence model that generates prompt sentences based on specified input data and generates appropriate output accordingly.

[1259] A "prompt sentence generation means" is a device or function that uses a generative AI model to generate a prompt sentence based on input data.

[1260] This invention provides real-time multilingual translation using a system that includes a display device worn by the user (e.g., audio glasses), a terminal, and a server. Specifically, the system is configured using the following hardware and software:

[1261] Hardware

[1262] Display means: Device worn by the user, such as audio glasses.

[1263] Terminal: A device that communicates with a display means, such as a smartphone or tablet.

[1264] Server: A central device that processes data sent from terminals.

[1265] Audio capture method: Microphone built into the audio glasses.

[1266] Audio output means: Speaker built into the audio glasses.

[1267] software

[1268] Speech recognition library (speech_recognition): Converts voice data into text data.

[1269] Translation library (translate): Translates text data into other specified languages.

[1270] Speech synthesis library (pyttsx3): Converts text data into speech data.

[1271] Process Overview

[1272] 1. Capture audio input:

[1273] The user's voice is captured by a microphone built into the audio glasses, which is highly sensitive and accurately captures the user's voice while rejecting surrounding noise.

[1274] 2. Audio to text conversion:

[1275] The server uses speech recognition technology to convert the audio data into text data. The speech_recognition library is responsible for this process.

[1276] 3. Translation of text data:

[1277] The translation library, translate, translates the text data, while a generative AI model generates prompts to improve translation accuracy.

[1278] 4. Prompt generation:

[1279] The generative AI model generates appropriate prompt sentences based on user input, which are then referenced by the server for optimal translation.

[1280] For example, when translating "Please stop the machine," the following prompt sentence is generated: "Translate the following Japanese sentence to English: 'Please stop the machine'"

[1281] 5. Output of translation results:

[1282] The translated text is sent to the display means via the terminal, and the translation result is displayed on the display of the audio glasses.

[1283] In addition, the translated text is converted into audio data using a speech synthesis library (pyttsx3) and played through the audio glasses' speakers.

[1284] Specific examples

[1285] For example, if a factory leader issues the command "Stop the machine" in Japanese, this voice is captured by the microphone in the audio glasses, and the following prompt sentence is generated by the generative AI model:

[1286] Translate the following Japanese sentence into English: 'Please stop the machine.'

[1287] As a result, the translated text "Please stop the machine" appears on the audio glasses' display and is simultaneously output as audio.

[1288] This allows foreign workers in the factory to understand accurate instructions in real time and continue working smoothly. This system will greatly improve communication efficiency in workplaces with multilingual environments.

[1289] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1290] Step 1:

[1291] The user wears the audio glasses and inputs voice. The microphone built into the audio glasses captures the user's speech. This voice data is sent to the device. The input is the user's voice, and the output is voice data.

[1292] Step 2:

[1293] The device sends the captured audio data to the server. The input is audio data, and the output is sending audio data to the server. The device communicates with the server via a network.

[1294] Step 3:

[1295] The server converts the received voice data into text data using the speech_recognition library. The input is voice data and the output is text data. This process converts the voice data into meaningful strings of characters.

[1296] Step 4:

[1297] The server uses a translation library (translate) to translate the text data into another specified language. At this time, a generative AI model generates a prompt sentence to improve the accuracy of the translation. The input is the text data, and the output is the translated text data. An example of a generated prompt sentence is "Translate the following Japanese sentence to English: 'Please stop the machine'".

[1298] Step 5:

[1299] The server returns the translated text data to the terminal. The input is the translated text data, and the output is the transmission of the text data to the terminal. The data from the server is received by the terminal.

[1300] Step 6:

[1301] The terminal sends the received translation text data to the audio glasses. The input is the translated text data, and the output is the transmission of the text data to the audio glasses. The terminal works in conjunction with the audio glasses.

[1302] Step 7:

[1303] Audio Glasses visually displays translated text data using a display device. It also converts the text data into audio data using a speech synthesis library (pyttsx3) and plays it as audio through a built-in speaker. The input is the translated text data, and the output is a visual display and audio output. The user can check the translation results through the displayed text and played audio.

[1304] 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.

[1305] The present invention implements a system that incorporates a generative AI (translation service) and an emotion engine into audio glasses to provide an environment in which users can have natural conversations. This system allows users to overcome language barriers and understand the emotions of others. A specific example of this system is described below.

[1306] Overall system flow

[1307] This system is composed mainly of audio glasses worn by the user, a terminal, a server, and an emotion recognition engine. When a user puts on the audio glasses and starts a conversation, the system translates the speech and recognizes emotions in real time through the following process.

[1308] Program processing

[1309] 1. Preparing and connecting the audio glasses

[1310] When a user puts on the audio glasses, they automatically connect to the device and begin communicating with the server.

[1311] The server verifies the Audio Glasses connection and links it with the user data.

[1312] 2. Voice input recognition

[1313] When the user starts speaking, a microphone in the audio glasses captures the sound.

[1314] The audio data captured by the audio glasses is sent to the device in real time.

[1315] 3. Audio Data Processing

[1316] The terminal transmits the received voice data to the server.

[1317] The server receives the voice data and converts it into text using speech recognition technology.

[1318] 4. Emotional Recognition

[1319] The server analyzes the user's emotions using an emotion engine based on the voice data.

[1320] The emotion engine generates emotion data and returns it to the server.

[1321] 5. Text Translation

[1322] The server calls the generation AI (translation service) to translate the generated text.

[1323] The generative AI translates text into the specified language.

[1324] 6. Returning the translation results

[1325] The server returns the text data and emotion data of the translation result to the terminal.

[1326] The device receives the translation results and emotion data and sends them to the audio glasses.

[1327] 7. Visual and auditory feedback

[1328] The audio glasses provide feedback to the user by visually displaying translation results and emotional data.

[1329] If necessary, the device will synthesize the translation result into voice and play it through the Audio Glasses' speakers.

[1330] Specific use cases

[1331] Translation of everyday conversations and emotion recognition

[1332] 1. Preparation

[1333] User A puts on the audio glasses and the system is ready.

[1334] 2. Voice Input

[1335] User A says, "Hello, how are you?"

[1336] The audio glasses capture the sound and send it to your device.

[1337] 3. Audio Data Processing

[1338] The terminal transmits the received voice data to the server.

[1339] The server converts "Hello, how are you?" into text.

[1340] 4. Emotional Recognition

[1341] The server analyzes user A's emotions based on the voice data.

[1342] The emotion engine recognizes User A's emotion as "joy."

[1343] 5. Text Translation

[1344] The server passes this text to a generative AI translation service.

[1345] The generative AI translates this to "Hello, how are you?"

[1346] 6. Returning the translation results

[1347] The server returns the translation results and emotion data to the device.

[1348] The device sends the translation results to the audio glasses.

[1349] 7. Feedback

[1350] The audio glasses visually display "Hello, how are you?" and the emotion "Joy."

[1351] User A checks the displayed translation results and emotions, and continues the conversation naturally while observing the other person's facial expressions.

[1352] Use in business meetings

[1353] 1. Preparation

[1354] User B puts on the audio glasses and the system is ready.

[1355] 2. Voice Input

[1356] User B says, "How is this project going?"

[1357] The audio glasses capture the sound and send it to your device.

[1358] 3. Audio Data Processing

[1359] The terminal transmits the received voice data to the server.

[1360] The server converts "How is this project going?" into text.

[1361] 4. Emotional Recognition

[1362] The server analyzes User B's emotions based on the voice data.

[1363] The emotion engine recognizes User B's emotion as "interest."

[1364] 5. Text Translation

[1365] The server passes this text to a generative AI translation service.

[1366] The generative AI translates this to "How is the progress of this project?"

[1367] 6. Returning the translation results

[1368] The server returns the translation results and emotion data to the device.

[1369] The device sends the translation results to the audio glasses.

[1370] 7. Feedback

[1371] The audio glasses visually display "How is the progress of this project?" and the emotion "Interested."

[1372] User B checks the displayed translation results and sentiments, allowing the business conversation to proceed smoothly.

[1373] In this way, this system provides an environment in which users can communicate naturally, realizing dialogue that transcends language barriers.

[1374] The processing flow will be explained below.

[1375] Step 1:

[1376] The user puts on the audio glasses and turns on the device. The audio glasses connect to the device.

[1377] Step 2:

[1378] The device receives the connection signal from the audio glasses and confirms the pairing. The device sends the connection information to the server and links it with the user data.

[1379] Step 3:

[1380] When the user initiates a conversation, the audio glasses' microphone captures the spoken voice, which is then sent to the device in real time.

[1381] Step 4:

[1382] The terminal transmits the received voice data to the server, and the server receives the voice data.

[1383] Step 5:

[1384] The server uses speech recognition technology to convert the voice data into text, generating text data.

[1385] Step 6:

[1386] The server analyzes the user's emotions using an emotion engine based on the voice data, and the emotion engine generates emotion data and returns it to the server.

[1387] Step 7:

[1388] The server calls the generation AI (translation service) to translate the generated text. The generation AI translates the text into the specified language.

[1389] Step 8:

[1390] The server returns the text data and emotion data of the translation result to the terminal.

[1391] Step 9:

[1392] The device receives the translation results and emotion data and sends them to the audio glasses.

[1393] Step 10:

[1394] The audio glasses provide feedback to the user by visually displaying the translation results and emotional data, allowing the user to continue the dialogue based on the displayed information.

[1395] Step 11:

[1396] If necessary, the device will synthesize the translation result into voice and play it through the Audio Glasses' speakers.

[1397] Example 2

[1398] 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."

[1399] Conventional speech translation systems simply convert speech into text and translate that text, making it difficult to understand the emotions of the person they are speaking to. Another problem is that the use of multiple devices and applications makes the operation process complicated. The present invention aims to solve these problems and provide a system that allows users to have natural conversations.

[1400] 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 an analysis means for analyzing emotions based on voice information, a conversion means for converting the voice information into text information, and a translation means for translating the text information. This allows the user to understand not only the language of the person they are talking to, but also their emotions in real time.

[1401] A "display means" is a device worn by a user that displays information visually or audibly.

[1402] The "information processing terminal" is a device connected to a display means, and is a device that transmits and receives voice information and processes data.

[1403] A "data processing device" is a device connected to an information processing terminal, and is a system that converts and analyzes voice information.

[1404] The "audio capturing means" is a device that has the function of capturing audio and transmitting it to the information processing terminal.

[1405] The "conversion means" is a system in a data processing device that has the function of converting voice information into text information.

[1406] The "translation means" is a system having a function of translating the text information converted by the conversion means into another language.

[1407] The "analysis means" is a system that has the function of analyzing emotions based on voice information in a data processing device.

[1408] The "audio output means" is a device that has the function of outputting text information as audio.

[1409] An "audio input device" is a device that contains a microphone that functions as a means for capturing audio.

[1410] The present invention embodies a system that is mainly composed of a display device worn by a user, an information processing terminal, and a data processing device. This system enables users to overcome language barriers and even understand the emotions of others. Detailed embodiments of this system are described below.

[1411] System Configuration

[1412] This system includes a display means (audio glasses) worn by the user, an information processing terminal (smartphone or PC), a data processing device (server), a voice capture means (microphone in the audio glasses), a conversion means (voice recognition engine), a translation means (generative AI translation service), and an analysis means (emotion engine).

[1413] Hardware and Software

[1414] Display: A device worn by the user that displays information visually and audibly. For example, audio glasses.

[1415] Information processing terminal: A device connected to a display means that transmits and receives audio information and processes data. Specifically, this applies to smartphones and PCs.

[1416] Data Processing Device (Server): A system that converts and analyzes audio information. This includes suitable cloud servers.

[1417] Audio capture means: A device that has the function of capturing audio and transmitting it to an information processing terminal. The microphone built into the audio glasses is an example of this.

[1418] Conversion method: A system capable of converting voice information into text information. For example, Google's speech recognition API is used.

[1419] Translation tool: A system that can translate converted text into another language, such as OpenAI's generative AI translation model.

[1420] Analysis method: A system that has the function of analyzing emotions based on voice information. This corresponds to an emotion engine.

[1421] Usage example

[1422] Translation of everyday conversations and emotion recognition

[1423] 1. Preparation

[1424] The user puts on the audio glasses and the system is ready.

[1425] 2. Voice Input

[1426] The user says, "Hello, how are you?"

[1427] The audio glasses capture the sound and send it to your device.

[1428] 3. Audio Data Processing

[1429] The terminal transmits the received voice data to the server.

[1430] The server converts "Hello, how are you?" into text.

[1431] 4. Emotional Recognition

[1432] The server analyzes the user's emotions based on the voice data.

[1433] The emotion engine recognizes the user's emotion as "joy."

[1434] 5. Text Translation

[1435] The server passes this text to a generative AI translation service.

[1436] The generative AI translates this to "Hello, how are you?"

[1437] 6. Returning the translation results

[1438] The server returns the translation results and emotion data to the device.

[1439] The device sends the translation results to the audio glasses.

[1440] 7. Feedback

[1441] The audio glasses visually display "Hello, how are you?" and the emotion "Joy."

[1442] The user can check the displayed translation results and emotions, and continue a natural conversation while observing the other person's facial expressions.

[1443] Prompt Sentence Examples

[1444] The user says "Hello, how are you?" Translate this speech to "Hello, how are you?" and recognize the emotion.

[1445] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1446] Step 1:

[1447] Preparing and connecting audio glasses

[1448] When a user wears the audio glasses, the audio glasses are automatically connected to the information processing terminal via Bluetooth. The input is the user's operation of wearing the audio glasses, and the output is the state in which the audio glasses are connected to the information processing terminal.

[1449] The device confirms the Audio Glasses connection and starts communicating with the server. Specifically, the device detects the Audio Glasses Bluetooth connection and sends a connection request to the server via the Internet.

[1450] The server confirms the audioglass connection and links it with the user data. The input is a connection request from the terminal, and the output is the link information between the user data and the audioglass.

[1451] Step 2:

[1452] Voice input recognition

[1453] When the user starts speaking, the microphone in the audio glasses captures the sound. The input is the user's voice and the output is the captured voice data.

[1454] Audio glasses transmit captured audio data to the device in real time. The input is the captured audio data, and the output is the process of transmitting it to the device. Specifically, audio glasses store the audio data in an internal data buffer and transmit it to the device via Bluetooth.

[1455] Step 3:

[1456] Audio data processing

[1457] The terminal sends the received audio data to the server. The input is the audio data sent from the audio glasses, and the output is the process of sending it to the server. Specifically, the terminal transfers packets of audio data to the server via the network.

[1458] The server receives the voice data and converts it into text using voice recognition technology. The input is the voice data received from the terminal, and the output is the converted text data. Specifically, the server starts a voice recognition engine and converts the voice data into text.

[1459] Step 4:

[1460] Emotion recognition

[1461] The server analyzes the user's emotions based on the voice data using an emotion engine. The input is the voice data converted to text by the server, and the output is the analyzed emotion data. Specifically, the server supplies the text data to the emotion engine and performs emotion analysis.

[1462] The emotion engine generates emotion data and returns it to the server. The input is the text data supplied to the emotion engine, and the output is the generated emotion data. Specifically, the emotion engine analyzes the tone and content of the voice and generates emotion data such as "joy."

[1463] Step 5:

[1464] Text translation

[1465] The server calls the generation AI (translation service) to translate the generated text. The input is the converted text data and emotion data, and the output is the translated text data. Specifically, the server sends the text data to the generation AI and requests a translation.

[1466] The generative AI translates text into a specified language. The input is the transmitted text data, and the output is the translated text data. Specifically, the generative AI uses an internal translation model to translate "Hello, how are you?" into "Hello, how are you?"

[1467] Step 6:

[1468] Returning translation results

[1469] The server returns the translation result text data and emotion data to the terminal. The input is the translated text data and emotion data, and the output is the data sent to the terminal. In concrete terms, the server transfers the translation result and emotion data together to the terminal.

[1470] The device receives the translation results and emotion data and sends them to the audio glasses. The input is the translation data and emotion data received from the server, and the output is transmission to the audio glasses. Specifically, the device distributes the data it receives to the audio glasses via Bluetooth.

[1471] Step 7:

[1472] Visual and auditory feedback

[1473] The audio glasses provide feedback to the user by visually displaying the translation results and emotional data. The input is the translation data and emotional data received from the device, and the output is feedback to the user. Specifically, the audio glasses' HUD visually displays "Hello, how are you?" and the emotion "joy."

[1474] If necessary, the device will synthesize the translation result and play it through the Audio Glasses speaker. The input is the translation result text data, and the output is the synthesized voice data. Specifically, the device uses its internal voice synthesis engine to convert the text into voice and output it through the Audio Glasses speaker.

[1475] (Application example 2)

[1476] 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."

[1477] The problem that this invention aims to solve is to provide an environment in which users who speak different languages ​​can converse naturally. Furthermore, it aims to achieve deeper understanding and smoother communication by not only translating but also grasping emotions during the conversation in real time and providing feedback.

[1478] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes text conversion means for converting the voice data into text, translation means for translating the text data converted by the text conversion means, and emotion recognition means for recognizing emotions based on the voice data. This enables an environment in which users can converse in different languages ​​while also understanding the emotions of the other party.

[1479] "User" refers to a person who uses the system of the present invention.

[1480] "Display means" refers to a device worn by a user that visually displays information.

[1481] "Terminal" refers to a device that is connected to a display means and communicates with the Internet and a server.

[1482] "Server" refers to a computer system that processes data sent from a terminal and provides various services.

[1483] "Audio capture means" refers to a device that collects user voice data and transmits it to the terminal.

[1484] "Text conversion means" refers to technology that converts voice data into text data.

[1485] "Translation means" refers to a technology for translating text data into a different language.

[1486] "Emotion recognition means" refers to technology that analyzes and recognizes a user's emotions based on voice data.

[1487] "Audio output means" refers to a device that outputs text data and emotion data as audio.

[1488] The system of the present invention is composed mainly of audio glasses, a terminal, a server, and an emotion recognition engine to provide an environment for users to have natural conversations. This system enables smooth communication between users who speak different languages ​​and can grasp each other's emotions in real time.

[1489] System Configuration

[1490] Hardware:

[1491] Display means: A device worn by the user (audio glasses).

[1492] Device: A smartphone connected to the audio glasses that communicates with the server.

[1493] Audio capture method: Microphone built into the audio glasses.

[1494] software:

[1495] Speech recognition technology: Uses the SpeechRecognition library.

[1496] Translation technology: Google Cloud Translation API.

[1497] Emotion recognition technology: Uses the EmotionEngine library.

[1498] System Operation Overview

[1499] When a user wears the audio glasses and speaks to the system, the system processes the voice in the following steps.

[1500] 1. Audio capture:

[1501] What the user says is captured by the microphone in the audio glasses, and the captured voice data is sent to the server via the device.

[1502] 2. Speech to text transcription:

[1503] The server uses speech recognition technology to convert the voice data into text. This conversion process is performed using the SpeechRecognition library.

[1504] 3. Translation:

[1505] The converted text is then translated into the specified language using the Google Cloud Translation API.

[1506] 4. Emotion recognition:

[1507] At the same time, the server uses the EmotionEngine library to recognize the user's emotions from the voice data, which are then processed together with the translation data.

[1508] 5. Display and Feedback:

[1509] The translation results and recognized emotion data are finally displayed visually as feedback on the audio glasses, and if necessary, the translation results are output as audio.

[1510] Specific examples

[1511] Examples of use in tourist destinations

[1512] Consider a scenario in which a foreign tourist visits a tourist spot in Japan and asks a souvenir shop clerk, "What souvenir do you recommend?" In this case, the clerk is wearing audio glasses and can respond through the system as follows:

[1513] A tourist's question, "What souvenir would you recommend?" is captured by the audio glasses' microphone.

[1514] The voice data is sent to the server via the terminal and converted into text.

[1515] The text data is translated into "What is a recommended souvenir?"

[1516] At the same time, an emotion recognition engine analyzes tourists' emotions and generates emotional data such as curiosity and interest.

[1517] The translated text and emotion data are displayed on the audio glasses, providing visual feedback to the store associate.

[1518] If necessary, the device will output the translation result as speech, playing the English voice saying "What is a recommended souvenir?"

[1519] Prompt Sentence Examples

[1520] To clarify the problem that the invention is trying to solve, consider a specific example of a usage scenario.

[1521] Usage scenario: A foreign tourist asks a store clerk, "What souvenirs do you recommend?"

[1522] Example prompt: "Translate the customer's question into English and identify the emotion."

[1523] In this way, the system of the present invention can provide an environment in which users who speak different languages ​​can have natural conversations in real time and understand each other's emotions.

[1524] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1525] Step 1:

[1526] When the user starts speaking, the microphone in the audio glasses captures the sound. The input is the user's voice and the output is audio data.

[1527] Step 2:

[1528] The device receives audio data from the audio glasses. The received audio data is sent to the server via the device. The input is audio data, and the output is sending the audio data to the server.

[1529] Step 3:

[1530] The server receives the audio data and converts it into text using the SpeechRecognition library. The input is audio data and the output is text data.

[1531] Step 4:

[1532] The server receives the text data and translates it into the specified language using the Google Cloud Translation API. The input is the text data, and the output is the translated text data.

[1533] Step 5:

[1534] The server analyzes the user's emotions based on the voice data using the EmotionEngine library. The input is voice data and the output is emotional data.

[1535] Step 6:

[1536] The server returns the translated text data and emotion data to the terminal. The input is the translated text data and emotion data, and the output is transmission to the terminal.

[1537] Step 7:

[1538] The device receives the translation results and emotion data from the server and sends them to the audio glasses. The input is the translated text data and emotion data, and the output is sent to the audio glasses.

[1539] Step 8:

[1540] The audio glasses visually display the translation results and emotional data and provide feedback to the user. The input is the translated text data and emotional data, and the output is visual feedback. If necessary, the device can also synthesize the translation results into speech and play it through the audio glasses' speakers.

[1541] 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.

[1542] 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.

[1543] 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.

[1544] [Fourth embodiment]

[1545] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1546] 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.

[1547] 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).

[1548] 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.

[1549] 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.

[1550] 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).

[1551] 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.

[1552] 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.

[1553] 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.

[1554] 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.

[1555] 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.

[1556] 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.

[1557] 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."

[1558] The present invention implements a system that incorporates a generative AI (translation service) in audio glasses to provide an environment in which users can converse in a natural way. A specific example of this system is described below.

[1559] Overall system flow

[1560] This system is composed mainly of audio glasses worn by the user, a terminal, and a server. When a user puts on the audio glasses and starts a conversation, the system translates and provides speech in real time through the following process.

[1561] Program processing

[1562] 1. Preparing and connecting the audio glasses

[1563] When a user puts on the audio glasses, they automatically connect to the device and begin communicating with the server.

[1564] The server verifies the Audio Glasses connection and links it with the user data.

[1565] 2. Voice input recognition

[1566] When the user starts speaking, a microphone in the audio glasses captures the sound.

[1567] The audio data captured by the audio glasses is sent to the device.

[1568] 3. Translation of audio data

[1569] The terminal transmits the received voice data to the server.

[1570] The server uses voice recognition technology to convert the voice data into text.

[1571] The server uses a generated AI (translation service) to translate the text into the specified language.

[1572] 4. Returning the translation results

[1573] The server returns the translated text data to the terminal.

[1574] The device receives the translation results and sends them to the audio glasses.

[1575] 5. Visual and auditory feedback

[1576] The audio glasses visually display the translation results, allowing users to continue the conversation while checking the other person's facial expressions.

[1577] If necessary, the device will synthesize the translation result into voice and play it through the Audio Glasses' speakers.

[1578] Specific use cases

[1579] Everyday conversation translation

[1580] 1. Preparation

[1581] User A puts on the audio glasses and the system is ready.

[1582] 2. Voice Input

[1583] User A says, "Hello, how are you?"

[1584] The audio glasses capture the sound and send it to your device.

[1585] 3. Translation of audio data

[1586] The terminal transmits the received voice data to the server.

[1587] The server translates "Hello, how are you?" to "Hello, how are you?"

[1588] 4. Returning the translation results

[1589] The server returns the translation results to the terminal.

[1590] The device sends the translation results to the audio glasses.

[1591] 5. Feedback

[1592] The audio glasses visually display "Hello, how are you?"

[1593] User A checks the translation results while looking at the other person's facial expressions and continues the conversation in a natural way.

[1594] Use in business meetings

[1595] 1. Preparation

[1596] User B puts on the audio glasses and the system is ready.

[1597] 2. Voice Input

[1598] User B says, "How is this project going?"

[1599] The audio glasses capture the sound and send it to your device.

[1600] 3. Translation of audio data

[1601] The terminal transmits the received voice data to the server.

[1602] The server translates "How is the progress of this project?" to "How is the progress of this project?"

[1603] 4. Returning the translation results

[1604] The server returns the translation results to the terminal.

[1605] The device sends the translation results to the audio glasses.

[1606] 5. Feedback

[1607] The audio glasses visually display "How is the progress of this project?"

[1608] User B can check the translation results while looking at the other person's facial expression, allowing the business conversation to proceed smoothly.

[1609] In this way, the system provides an environment in which users can communicate naturally, helping to overcome language barriers.

[1610] The processing flow will be explained below.

[1611] Step 1:

[1612] The user puts on the audio glasses and powers on the device.

[1613] Step 2:

[1614] The device receives the connection signal from the audio glasses and confirms pairing.

[1615] Step 3:

[1616] The terminal sends the connection information to the server and links it with the user data.

[1617] Step 4:

[1618] The user initiates the interaction and the audio glasses' microphone captures what is being said.

[1619] Step 5:

[1620] The audio data captured by the audio glasses is sent to the device in real time.

[1621] Step 6:

[1622] The terminal transmits the received voice data to the server.

[1623] Step 7:

[1624] The server receives the voice data and converts it into text using speech recognition technology.

[1625] Step 8:

[1626] The server calls the generation AI (translation service) to translate the generated text.

[1627] Step 9:

[1628] The generation AI translates the text into the specified language and sends the translation results to the server.

[1629] Step 10:

[1630] The server returns the translated text data to the terminal.

[1631] Step 11:

[1632] The device receives the translation results and sends them to the audio glasses for visual display.

[1633] Step 12:

[1634] The audio glasses provide feedback to the user by displaying the translation results on a screen.

[1635] Step 13:

[1636] If necessary, the device synthesizes the translation results into voice and plays them back to the user through the Audio Glasses' speakers.

[1637] Step 14:

[1638] The user can check the displayed translation results and the played audio, and continue the conversation naturally while observing the other person's facial expressions.

[1639] Example 1

[1640] 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."

[1641] Conventional translation systems have had difficulty translating speech data in real time and providing visual and auditory feedback. Furthermore, they often fail to adequately consider improvements in translation performance or data security. This can make it difficult for users to communicate smoothly. It is desirable to solve these issues and provide an environment in which users can communicate naturally.

[1642] 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.

[1643] In this invention, the server includes a speech recognition unit, a generation AI model utilization unit, and an information protection unit, which enables rapid conversion of speech data into text, high-precision translation using the generation AI, and security protection through data encryption.

[1644] A "display means" is a device worn by a user to display visual information.

[1645] A "terminal" is an electronic device connected to a display means and for communicating with a server.

[1646] A "server" is a central processing unit that is connected to a terminal and processes and translates voice data.

[1647] An "audio capture means" is a device that captures a user's voice and converts it into a digital signal.

[1648] "Speech recognition means" refers to a technique or device that converts voice data into text data.

[1649] The "translation means" is a technology or device that translates the text data converted by the speech recognition means into a specified language.

[1650] "Means for utilizing a generative AI model" refers to a device or technology that uses a generative AI model to translate text data.

[1651] "Information protection measures" are technologies or devices that encrypt voice data and translation data to ensure data security during transmission and reception.

[1652] "Visual display means" refers to a screen incorporated in a display or lens for visually displaying the translation results.

[1653] "Audio output means" refers to a speaker or voice synthesis technology for outputting text data as voice.

[1654] This invention provides a system that uses audio glasses equipped with a generative AI model to translate and provide speech in real time, allowing users to converse in a natural way. The system is primarily composed of a display device worn by the user, a terminal, and a server.

[1655] Hardware and software used

[1656] The display means takes the form of audio glasses worn by the user. These audio glasses have a built-in microphone and small display. The device is, for example, a smartphone or tablet, and communicates with the display means via a wireless connection such as Bluetooth or Wi-Fi. The server is installed as a cloud server or on-premise server and performs translation using speech recognition technology and generative AI models (e.g., OpenAI GPT-4 or DeepL).

[1657] System Operation

[1658] Hardware connectivity and communication

[1659] When a user puts on the audio glasses, they automatically connect to the device. Once this connection is established, the device starts communicating with the server over the network. The server obtains the audio glasses and the user's profile information and configures the entire system accordingly.

[1660] Voice input and translation process

[1661] When a user speaks, the microphone in the audio glasses captures the sound, which is then converted into a digital format and transmitted over wireless to the device, where it is then encrypted and sent to a server.

[1662] The server first converts the received voice data into text data using a speech recognition means (e.g., Google Cloud Speech-to-Text API). Then, it translates the text data along with a prompt sentence using a generative AI model. For example, the prompt sentence could be "Please translate the following text into English: 'Hello, how are you?'"

[1663] Returning and displaying translation results

[1664] The translated text data is then re-encrypted and sent back to the device, which then formats it appropriately and sends it to the audio glasses. The audio glasses then visually display the translation results on a small display. If necessary, the device can also output the translation results as audio using speech synthesis technology (e.g., Google Text-to-Speech API) and play it through the audio glasses' speakers.

[1665] Specific use cases

[1666] Use in everyday conversation

[1667] 1. Preparation: User A puts on the audio glasses and the system is ready.

[1668] 2. Voice input: User A says, "Hello, how are you?" The audio glasses capture the voice and send it to the device.

[1669] 3. Voice data translation: The device sends the received voice data to the server, which translates "Hello, how are you?" into "Hello, how are you?"

[1670] 4. Returning the translation result: The server returns the translation result to the device, which then sends it to the audio glasses.

[1671] 5. Feedback: The audio glasses visually display "Hello, how are you?" and optionally play it audibly through the speaker.

[1672] Use in business meetings

[1673] 1. Preparation: User B puts on the audio glasses and the system is ready.

[1674] 2. Voice input: User B says, "How is the progress on this project?" The audio glasses capture the voice and send it to the device.

[1675] 3. Voice data translation: The device sends the received voice data to the server, which translates "How is the progress of this project?" into "How is the progress of this project?"

[1676] 4. Returning the translation result: The server returns the translation result to the device, which then sends it to the audio glasses.

[1677] 5. Feedback: The audio glasses will visually display "How is the progress of this project?" and will play audible feedback through the speakers if necessary.

[1678] In this way, the present invention provides an environment in which users can communicate naturally, helping to overcome language barriers.

[1679] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1680] Program processing flow

[1681] Step 1:

[1682] Preparing and connecting audio glasses

[1683] Specific behavior:

[1684] The user puts on the audio glasses, which automatically connect to the terminal as a display device.

[1685] The device confirms the Bluetooth connection with the audio glasses and then starts communicating with the server over the Internet.

[1686] The server verifies the connection between the audio glasses and the device, obtains the user's profile information, and links them.

[1687] input:

[1688] Audio glasses connection start signal

[1689] output:

[1690] Establishing a connection between the audio glasses, the device, and the server

[1691] Loading a user's profile information

[1692] Step 2:

[1693] Voice input recognition

[1694] Specific behavior:

[1695] The user speaks a word, for example, "Hello, how are you?"

[1696] A microphone inside the audio glasses captures sound and converts the audio data into a digital format.

[1697] The audio glasses transmit digital audio data to the device via Bluetooth.

[1698] input:

[1699] User-generated speech

[1700] output:

[1701] Audio data converted into digital format

[1702] Step 3:

[1703] Sending audio data

[1704] Specific behavior:

[1705] The device encrypts the audio data received from the audio glasses.

[1706] The terminal transmits the encrypted voice data to the server via the network.

[1707] input:

[1708] Audio data sent from audio glasses

[1709] output:

[1710] Sending encrypted audio data to the server

[1711] Step 4:

[1712] Speech recognition of audio data

[1713] Specific behavior:

[1714] The server decrypts the received encrypted voice data and converts it into text data using a voice recognition method (e.g., Google Cloud Speech-to-Text API).

[1715] input:

[1716] Encrypted audio data

[1717] output:

[1718] Text data

[1719] Step 5:

[1720] Text data translation

[1721] Specific behavior:

[1722] The server translates the text data into the specified language using a generative AI model, using the prompt "Please translate the following text into English: 'Hello, how are you?'"

[1723] input:

[1724] Text data generated by speech recognition

[1725] output:

[1726] Translated text data

[1727] Step 6:

[1728] Sending translation results

[1729] Specific behavior:

[1730] The server re-encrypts the translated text data and sends it to the terminal.

[1731] input:

[1732] Translated text data

[1733] output:

[1734] Encrypted translation data

[1735] Step 7:

[1736] Receiving and displaying translation results

[1737] Specific behavior:

[1738] The terminal receives and decrypts the encrypted translation data.

[1739] The device sends the decoded translation data to the audio glasses.

[1740] The audio glasses display the translation results using a visual display means.

[1741] input:

[1742] Encrypted translation data

[1743] output:

[1744] Translation results displayed on the audio glasses display

[1745] Step 8:

[1746] Audio output (if needed)

[1747] Specific behavior:

[1748] The device uses speech synthesis technology (e.g., Google Text-to-Speech API) to convert the translated text into speech.

[1749] The audio glasses play the sound through the speakers.

[1750] input:

[1751] Translated text data

[1752] output:

[1753] Voice output of translation results

[1754] Through the above processing steps, this system provides an environment in which users can interact in a natural way.

[1755] (Application example 1)

[1756] 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."

[1757] In conventional multilingual environments in factories, the transmission of work instructions took time, resulting in poor communication efficiency. In particular, in workplaces with a mix of workers from various countries, language barriers often compromised the accuracy and timing of work. Therefore, there was a need for a system that would enable accurate multilingual translation in real time, allowing work instructions to be transmitted quickly and efficiently.

[1758] 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.

[1759] In this invention, the server includes a means for converting voice data into text, a means for translating text data, and a means for generating prompt sentences including a generative AI model. This allows workers to immediately receive multilingual translation results visually and audibly in real time, enabling smooth communication even in multinational workplaces.

[1760] The "display means" is a device that allows the user to visually confirm information.

[1761] A "terminal" is a device that communicates with a display means and processes and transmits data.

[1762] A "server" is a central device that processes data sent from terminals and returns data as needed.

[1763] The "voice capture means" is a device for inputting the user's voice.

[1764] "Text conversion means" refers to a device or function for converting voice data into text data.

[1765] The "translation means" is a device or function for translating text data into another specified language.

[1766] A "generative AI model" is an artificial intelligence model that generates prompt sentences based on specified input data and generates appropriate output accordingly.

[1767] A "prompt sentence generation means" is a device or function that uses a generative AI model to generate a prompt sentence based on input data.

[1768] This invention provides real-time multilingual translation using a system that includes a display device worn by the user (e.g., audio glasses), a terminal, and a server. Specifically, the system is configured using the following hardware and software:

[1769] Hardware

[1770] Display means: Device worn by the user, such as audio glasses.

[1771] Terminal: A device that communicates with a display means, such as a smartphone or tablet.

[1772] Server: A central device that processes data sent from terminals.

[1773] Audio capture method: Microphone built into the audio glasses.

[1774] Audio output means: Speaker built into the audio glasses.

[1775] software

[1776] Speech recognition library (speech_recognition): Converts voice data into text data.

[1777] Translation library (translate): Translates text data into other specified languages.

[1778] Speech synthesis library (pyttsx3): Converts text data into speech data.

[1779] Process Overview

[1780] 1. Capture audio input:

[1781] The user's voice is captured by a microphone built into the audio glasses, which is highly sensitive and accurately captures the user's voice while rejecting surrounding noise.

[1782] 2. Audio to text conversion:

[1783] The server uses speech recognition technology to convert the audio data into text data. The speech_recognition library is responsible for this process.

[1784] 3. Translation of text data:

[1785] The translation library, translate, translates the text data, while a generative AI model generates prompts to improve translation accuracy.

[1786] 4. Prompt generation:

[1787] The generative AI model generates appropriate prompt sentences based on user input, which are then referenced by the server for optimal translation.

[1788] For example, when translating "Please stop the machine," the following prompt sentence is generated: "Translate the following Japanese sentence to English: 'Please stop the machine'"

[1789] 5. Output of translation results:

[1790] The translated text is sent to the display means via the terminal, and the translation result is displayed on the display of the audio glasses.

[1791] In addition, the translated text is converted into audio data using a speech synthesis library (pyttsx3) and played through the audio glasses' speakers.

[1792] Specific examples

[1793] For example, if a factory leader issues the command "Stop the machine" in Japanese, this voice is captured by the microphone in the audio glasses, and the following prompt sentence is generated by the generative AI model:

[1794] Translate the following Japanese sentence into English: 'Please stop the machine.'

[1795] As a result, the translated text "Please stop the machine" appears on the audio glasses' display and is simultaneously output as audio.

[1796] This allows foreign workers in the factory to understand accurate instructions in real time and continue working smoothly. This system will greatly improve communication efficiency in workplaces with multilingual environments.

[1797] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1798] Step 1:

[1799] The user wears the audio glasses and inputs voice. The microphone built into the audio glasses captures the user's speech. This voice data is sent to the device. The input is the user's voice, and the output is voice data.

[1800] Step 2:

[1801] The device sends the captured audio data to the server. The input is audio data, and the output is sending audio data to the server. The device communicates with the server via a network.

[1802] Step 3:

[1803] The server converts the received voice data into text data using the speech_recognition library. The input is voice data and the output is text data. This process converts the voice data into meaningful strings of characters.

[1804] Step 4:

[1805] The server uses a translation library (translate) to translate the text data into another specified language. At this time, a generative AI model generates a prompt sentence to improve the accuracy of the translation. The input is the text data, and the output is the translated text data. An example of a generated prompt sentence is "Translate the following Japanese sentence to English: 'Please stop the machine'".

[1806] Step 5:

[1807] The server returns the translated text data to the terminal. The input is the translated text data, and the output is the transmission of the text data to the terminal. The data from the server is received by the terminal.

[1808] Step 6:

[1809] The terminal sends the received translation text data to the audio glasses. The input is the translated text data, and the output is the transmission of the text data to the audio glasses. The terminal works in conjunction with the audio glasses.

[1810] Step 7:

[1811] Audio Glasses visually displays translated text data using a display device. It also converts the text data into audio data using a speech synthesis library (pyttsx3) and plays it as audio through a built-in speaker. The input is the translated text data, and the output is a visual display and audio output. The user can check the translation results through the displayed text and played audio.

[1812] 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.

[1813] The present invention implements a system that incorporates a generative AI (translation service) and an emotion engine into audio glasses to provide an environment in which users can have natural conversations. This system allows users to overcome language barriers and understand the emotions of others. A specific example of this system is described below.

[1814] Overall system flow

[1815] This system is composed mainly of audio glasses worn by the user, a terminal, a server, and an emotion recognition engine. When a user puts on the audio glasses and starts a conversation, the system translates the speech and recognizes emotions in real time through the following process.

[1816] Program processing

[1817] 1. Preparing and connecting the audio glasses

[1818] When a user puts on the audio glasses, they automatically connect to the device and begin communicating with the server.

[1819] The server verifies the Audio Glasses connection and links it with the user data.

[1820] 2. Voice input recognition

[1821] When the user starts speaking, a microphone in the audio glasses captures the sound.

[1822] The audio data captured by the audio glasses is sent to the device in real time.

[1823] 3. Audio Data Processing

[1824] The terminal transmits the received voice data to the server.

[1825] The server receives the voice data and converts it into text using speech recognition technology.

[1826] 4. Emotional Recognition

[1827] The server analyzes the user's emotions using an emotion engine based on the voice data.

[1828] The emotion engine generates emotion data and returns it to the server.

[1829] 5. Text Translation

[1830] The server calls the generation AI (translation service) to translate the generated text.

[1831] The generative AI translates text into the specified language.

[1832] 6. Returning the translation results

[1833] The server returns the text data and emotion data of the translation result to the terminal.

[1834] The device receives the translation results and emotion data and sends them to the audio glasses.

[1835] 7. Visual and auditory feedback

[1836] The audio glasses provide feedback to the user by visually displaying translation results and emotional data.

[1837] If necessary, the device will synthesize the translation result into voice and play it through the Audio Glasses' speakers.

[1838] Specific use cases

[1839] Translation of everyday conversations and emotion recognition

[1840] 1. Preparation

[1841] User A puts on the audio glasses and the system is ready.

[1842] 2. Voice Input

[1843] User A says, "Hello, how are you?"

[1844] The audio glasses capture the sound and send it to your device.

[1845] 3. Audio Data Processing

[1846] The terminal transmits the received voice data to the server.

[1847] The server converts "Hello, how are you?" into text.

[1848] 4. Emotional Recognition

[1849] The server analyzes user A's emotions based on the voice data.

[1850] The emotion engine recognizes User A's emotion as "joy."

[1851] 5. Text Translation

[1852] The server passes this text to a generative AI translation service.

[1853] The generative AI translates this to "Hello, how are you?"

[1854] 6. Returning the translation results

[1855] The server returns the translation results and emotion data to the device.

[1856] The device sends the translation results to the audio glasses.

[1857] 7. Feedback

[1858] The audio glasses visually display "Hello, how are you?" and the emotion "Joy."

[1859] User A checks the displayed translation results and emotions, and continues the conversation naturally while observing the other person's facial expressions.

[1860] Use in business meetings

[1861] 1. Preparation

[1862] User B puts on the audio glasses and the system is ready.

[1863] 2. Voice Input

[1864] User B says, "How is this project going?"

[1865] The audio glasses capture the sound and send it to your device.

[1866] 3. Audio Data Processing

[1867] The terminal transmits the received voice data to the server.

[1868] The server converts "How is this project going?" into text.

[1869] 4. Emotional Recognition

[1870] The server analyzes User B's emotions based on the voice data.

[1871] The emotion engine recognizes User B's emotion as "interest."

[1872] 5. Text Translation

[1873] The server passes this text to a generative AI translation service.

[1874] The generative AI translates this to "How is the progress of this project?"

[1875] 6. Returning the translation results

[1876] The server returns the translation results and emotion data to the device.

[1877] The device sends the translation results to the audio glasses.

[1878] 7. Feedback

[1879] The audio glasses visually display "How is the progress of this project?" and the emotion "Interested."

[1880] User B checks the displayed translation results and sentiments, allowing the business conversation to proceed smoothly.

[1881] In this way, this system provides an environment in which users can communicate naturally, realizing dialogue that transcends language barriers.

[1882] The processing flow will be explained below.

[1883] Step 1:

[1884] The user puts on the audio glasses and turns on the device. The audio glasses connect to the device.

[1885] Step 2:

[1886] The device receives the connection signal from the audio glasses and confirms the pairing. The device sends the connection information to the server and links it with the user data.

[1887] Step 3:

[1888] When the user initiates a conversation, the audio glasses' microphone captures the spoken voice, which is then sent to the device in real time.

[1889] Step 4:

[1890] The terminal transmits the received voice data to the server, and the server receives the voice data.

[1891] Step 5:

[1892] The server uses speech recognition technology to convert the voice data into text, generating text data.

[1893] Step 6:

[1894] The server analyzes the user's emotions using an emotion engine based on the voice data, and the emotion engine generates emotion data and returns it to the server.

[1895] Step 7:

[1896] The server calls the generation AI (translation service) to translate the generated text. The generation AI translates the text into the specified language.

[1897] Step 8:

[1898] The server returns the text data and emotion data of the translation result to the terminal.

[1899] Step 9:

[1900] The device receives the translation results and emotion data and sends them to the audio glasses.

[1901] Step 10:

[1902] The audio glasses provide feedback to the user by visually displaying the translation results and emotional data, allowing the user to continue the dialogue based on the displayed information.

[1903] Step 11:

[1904] If necessary, the device will synthesize the translation result into voice and play it through the Audio Glasses' speakers.

[1905] Example 2

[1906] 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."

[1907] Conventional speech translation systems simply convert speech into text and translate that text, making it difficult to understand the emotions of the person they are speaking to. Another problem is that the use of multiple devices and applications makes the operation process complicated. The present invention aims to solve these problems and provide a system that allows users to have natural conversations.

[1908] 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 an analysis means for analyzing emotions based on voice information, a conversion means for converting the voice information into text information, and a translation means for translating the text information. This allows the user to understand not only the language of the person they are talking to, but also their emotions in real time.

[1909] A "display means" is a device worn by a user that displays information visually or audibly.

[1910] The "information processing terminal" is a device connected to a display means, and is a device that transmits and receives voice information and processes data.

[1911] A "data processing device" is a device connected to an information processing terminal, and is a system that converts and analyzes voice information.

[1912] The "audio capturing means" is a device that has the function of capturing audio and transmitting it to the information processing terminal.

[1913] The "conversion means" is a system in a data processing device that has the function of converting voice information into text information.

[1914] The "translation means" is a system having a function of translating the text information converted by the conversion means into another language.

[1915] The "analysis means" is a system that has the function of analyzing emotions based on voice information in a data processing device.

[1916] The "audio output means" is a device that has the function of outputting text information as audio.

[1917] An "audio input device" is a device that contains a microphone that functions as a means for capturing audio.

[1918] The present invention embodies a system that is mainly composed of a display device worn by a user, an information processing terminal, and a data processing device. This system enables users to overcome language barriers and even understand the emotions of others. Detailed embodiments of this system are described below.

[1919] System Configuration

[1920] This system includes a display means (audio glasses) worn by the user, an information processing terminal (smartphone or PC), a data processing device (server), a voice capture means (microphone in the audio glasses), a conversion means (voice recognition engine), a translation means (generative AI translation service), and an analysis means (emotion engine).

[1921] Hardware and Software

[1922] Display: A device worn by the user that displays information visually and audibly. For example, audio glasses.

[1923] Information processing terminal: A device connected to a display means that transmits and receives audio information and processes data. Specifically, this applies to smartphones and PCs.

[1924] Data Processing Device (Server): A system that converts and analyzes audio information. This includes suitable cloud servers.

[1925] Audio capture means: A device that has the function of capturing audio and transmitting it to an information processing terminal. The microphone built into the audio glasses is an example of this.

[1926] Conversion method: A system capable of converting voice information into text information. For example, Google's speech recognition API is used.

[1927] Translation tool: A system that can translate converted text into another language, such as OpenAI's generative AI translation model.

[1928] Analysis method: A system that has the function of analyzing emotions based on voice information. This corresponds to an emotion engine.

[1929] Usage example

[1930] Translation of everyday conversations and emotion recognition

[1931] 1. Preparation

[1932] The user puts on the audio glasses and the system is ready.

[1933] 2. Voice Input

[1934] The user says, "Hello, how are you?"

[1935] The audio glasses capture the sound and send it to your device.

[1936] 3. Audio Data Processing

[1937] The terminal transmits the received voice data to the server.

[1938] The server converts "Hello, how are you?" into text.

[1939] 4. Emotional Recognition

[1940] The server analyzes the user's emotions based on the voice data.

[1941] The emotion engine recognizes the user's emotion as "joy."

[1942] 5. Text Translation

[1943] The server passes this text to a generative AI translation service.

[1944] The generative AI translates this to "Hello, how are you?"

[1945] 6. Returning the translation results

[1946] The server returns the translation results and emotion data to the device.

[1947] The device sends the translation results to the audio glasses.

[1948] 7. Feedback

[1949] The audio glasses visually display "Hello, how are you?" and the emotion "Joy."

[1950] The user can check the displayed translation results and emotions, and continue a natural conversation while observing the other person's facial expressions.

[1951] Prompt Sentence Examples

[1952] The user says "Hello, how are you?" Translate this speech to "Hello, how are you?" and recognize the emotion.

[1953] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1954] Step 1:

[1955] Preparing and connecting audio glasses

[1956] When a user wears the audio glasses, the audio glasses are automatically connected to the information processing terminal via Bluetooth. The input is the user's operation of wearing the audio glasses, and the output is the state in which the audio glasses are connected to the information processing terminal.

[1957] The device confirms the Audio Glasses connection and starts communicating with the server. Specifically, the device detects the Audio Glasses Bluetooth connection and sends a connection request to the server via the Internet.

[1958] The server confirms the audioglass connection and links it with the user data. The input is a connection request from the terminal, and the output is the link information between the user data and the audioglass.

[1959] Step 2:

[1960] Voice input recognition

[1961] When the user starts speaking, the microphone in the audio glasses captures the sound. The input is the user's voice and the output is the captured voice data.

[1962] Audio glasses transmit captured audio data to the device in real time. The input is the captured audio data, and the output is the process of transmitting it to the device. Specifically, audio glasses store the audio data in an internal data buffer and transmit it to the device via Bluetooth.

[1963] Step 3:

[1964] Audio data processing

[1965] The terminal sends the received audio data to the server. The input is the audio data sent from the audio glasses, and the output is the process of sending it to the server. Specifically, the terminal transfers packets of audio data to the server via the network.

[1966] The server receives the voice data and converts it into text using voice recognition technology. The input is the voice data received from the terminal, and the output is the converted text data. Specifically, the server starts a voice recognition engine and converts the voice data into text.

[1967] Step 4:

[1968] Emotion recognition

[1969] The server analyzes the user's emotions based on the voice data using an emotion engine. The input is the voice data converted to text by the server, and the output is the analyzed emotion data. Specifically, the server supplies the text data to the emotion engine and performs emotion analysis.

[1970] The emotion engine generates emotion data and returns it to the server. The input is the text data supplied to the emotion engine, and the output is the generated emotion data. Specifically, the emotion engine analyzes the tone and content of the voice and generates emotion data such as "joy."

[1971] Step 5:

[1972] Text translation

[1973] The server calls the generation AI (translation service) to translate the generated text. The input is the converted text data and emotion data, and the output is the translated text data. Specifically, the server sends the text data to the generation AI and requests a translation.

[1974] The generative AI translates text into a specified language. The input is the transmitted text data, and the output is the translated text data. Specifically, the generative AI uses an internal translation model to translate "Hello, how are you?" into "Hello, how are you?"

[1975] Step 6:

[1976] Returning translation results

[1977] The server returns the translation result text data and emotion data to the terminal. The input is the translated text data and emotion data, and the output is the data sent to the terminal. In concrete terms, the server transfers the translation result and emotion data together to the terminal.

[1978] The device receives the translation results and emotion data and sends them to the audio glasses. The input is the translation data and emotion data received from the server, and the output is transmission to the audio glasses. Specifically, the device distributes the data it receives to the audio glasses via Bluetooth.

[1979] Step 7:

[1980] Visual and auditory feedback

[1981] The audio glasses provide feedback to the user by visually displaying the translation results and emotional data. The input is the translation data and emotional data received from the device, and the output is feedback to the user. Specifically, the audio glasses' HUD visually displays "Hello, how are you?" and the emotion "joy."

[1982] If necessary, the device will synthesize the translation result and play it through the Audio Glasses speaker. The input is the translation result text data, and the output is the synthesized voice data. Specifically, the device uses its internal voice synthesis engine to convert the text into voice and output it through the Audio Glasses speaker.

[1983] (Application example 2)

[1984] 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."

[1985] The problem that this invention aims to solve is to provide an environment in which users who speak different languages ​​can converse naturally. Furthermore, it aims to achieve deeper understanding and smoother communication by not only translating but also grasping emotions during the conversation in real time and providing feedback.

[1986] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes text conversion means for converting the voice data into text, translation means for translating the text data converted by the text conversion means, and emotion recognition means for recognizing emotions based on the voice data. This enables an environment in which users can converse in different languages ​​while also understanding the emotions of the other party.

[1987] "User" refers to a person who uses the system of the present invention.

[1988] "Display means" refers to a device worn by a user that visually displays information.

[1989] "Terminal" refers to a device that is connected to a display means and communicates with the Internet and a server.

[1990] "Server" refers to a computer system that processes data sent from a terminal and provides various services.

[1991] "Audio capture means" refers to a device that collects user voice data and transmits it to the terminal.

[1992] "Text conversion means" refers to technology that converts voice data into text data.

[1993] "Translation means" refers to a technology for translating text data into a different language.

[1994] "Emotion recognition means" refers to technology that analyzes and recognizes a user's emotions based on voice data.

[1995] "Audio output means" refers to a device that outputs text data and emotion data as audio.

[1996] The system of the present invention is composed mainly of audio glasses, a terminal, a server, and an emotion recognition engine to provide an environment for users to have natural conversations. This system enables smooth communication between users who speak different languages ​​and can grasp each other's emotions in real time.

[1997] System Configuration

[1998] Hardware:

[1999] Display means: A device worn by the user (audio glasses).

[2000] Device: A smartphone connected to the audio glasses that communicates with the server.

[2001] Audio capture method: Microphone built into the audio glasses.

[2002] software:

[2003] Speech recognition technology: Uses the SpeechRecognition library.

[2004] Translation technology: Google Cloud Translation API.

[2005] Emotion recognition technology: Uses the EmotionEngine library.

[2006] System Operation Overview

[2007] When a user wears the audio glasses and speaks to the system, the system processes the voice in the following steps.

[2008] 1. Audio capture:

[2009] What the user says is captured by the microphone in the audio glasses, and the captured voice data is sent to the server via the device.

[2010] 2. Speech to text transcription:

[2011] The server uses speech recognition technology to convert the voice data into text. This conversion process is performed using the SpeechRecognition library.

[2012] 3. Translation:

[2013] The converted text is then translated into the specified language using the Google Cloud Translation API.

[2014] 4. Emotion recognition:

[2015] At the same time, the server uses the EmotionEngine library to recognize the user's emotions from the voice data, which are then processed together with the translation data.

[2016] 5. Display and Feedback:

[2017] The translation results and recognized emotion data are finally displayed visually as feedback on the audio glasses, and if necessary, the translation results are output as audio.

[2018] Specific examples

[2019] Examples of use in tourist destinations

[2020] Consider a scenario in which a foreign tourist visits a tourist spot in Japan and asks a souvenir shop clerk, "What souvenir do you recommend?" In this case, the clerk is wearing audio glasses and can respond through the system as follows:

[2021] A tourist's question, "What souvenir would you recommend?" is captured by the audio glasses' microphone.

[2022] The voice data is sent to the server via the terminal and converted into text.

[2023] The text data is translated into "What is a recommended souvenir?"

[2024] At the same time, an emotion recognition engine analyzes tourists' emotions and generates emotional data such as curiosity and interest.

[2025] The translated text and emotion data are displayed on the audio glasses, providing visual feedback to the store associate.

[2026] If necessary, the device will output the translation result as speech, playing the English voice saying "What is a recommended souvenir?"

[2027] Prompt Sentence Examples

[2028] To clarify the problem that the invention is trying to solve, consider a specific example of a usage scenario.

[2029] Usage scenario: A foreign tourist asks a store clerk, "What souvenirs do you recommend?"

[2030] Example prompt: "Translate the customer's question into English and identify the emotion."

[2031] In this way, the system of the present invention can provide an environment in which users who speak different languages ​​can have natural conversations in real time and understand each other's emotions.

[2032] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2033] Step 1:

[2034] When the user starts speaking, the microphone in the audio glasses captures the sound. The input is the user's voice and the output is audio data.

[2035] Step 2:

[2036] The device receives audio data from the audio glasses. The received audio data is sent to the server via the device. The input is audio data, and the output is sending the audio data to the server.

[2037] Step 3:

[2038] The server receives the audio data and converts it into text using the SpeechRecognition library. The input is audio data and the output is text data.

[2039] Step 4:

[2040] The server receives the text data and translates it into the specified language using the Google Cloud Translation API. The input is the text data, and the output is the translated text data.

[2041] Step 5:

[2042] The server analyzes the user's emotions based on the voice data using the EmotionEngine library. The input is voice data and the output is emotional data.

[2043] Step 6:

[2044] The server returns the translated text data and emotion data to the terminal. The input is the translated text data and emotion data, and the output is transmission to the terminal.

[2045] Step 7:

[2046] The device receives the translation results and emotion data from the server and sends them to the audio glasses. The input is the translated text data and emotion data, and the output is sent to the audio glasses.

[2047] Step 8:

[2048] The audio glasses visually display the translation results and emotional data and provide feedback to the user. The input is the translated text data and emotional data, and the output is visual feedback. If necessary, the device can also synthesize the translation results into speech and play it through the audio glasses' speakers.

[2049] 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.

[2050] 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.

[2051] 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.

[2052] 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.

[2053] 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.

[2054] 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.

[2055] 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).

[2056] 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.

[2057] 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."

[2058] 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.

[2059] 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).

[2060] 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.

[2061] 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.

[2062] 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.

[2063] 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.

[2064] 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.

[2065] 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.

[2066] 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.

[2067] 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.

[2068] 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.

[2069] 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.

[2070] The following is further disclosed regarding the above embodiment.

[2071] (Claim 1)

[2072] a display means worn by a user;

[2073] a terminal connected to the display means;

[2074] a server connected to the terminal;

[2075] an audio capture means for transmitting audio data to the terminal;

[2076] a text conversion means in the server for converting the voice data into text;

[2077] a translation means for translating the text data converted by the text conversion means;

[2078] a display means for displaying the data translated by the translation means on a display means;

[2079] A system including:

[2080] (Claim 2)

[2081] 2. The system according to claim 1, wherein the display means further includes audio output means for outputting the text data as audio.

[2082] (Claim 3)

[2083] 10. The system of claim 1, wherein the display means includes a built-in microphone as a means for capturing audio.

[2084] "Example 1"

[2085] (Claim 1)

[2086] a display means worn by a user;

[2087] a terminal connected to the display means;

[2088] a server connected to the terminal;

[2089] an audio capture means for transmitting audio data to the terminal;

[2090] a speech recognition means for converting the speech data into text in the server;

[2091] a translation means for translating the text data converted by the speech recognition means into a specified language;

[2092] a display means for displaying the data translated by the translation means on a display means;

[2093] A generation AI model utilization means for the server to translate text data using the generation AI model;

[2094] an information protection means for encrypting and transmitting voice data and translation data by the terminal;

[2095] a visual display means for visually displaying the translation result;

[2096] A system including:

[2097] (Claim 2)

[2098] 2. The system according to claim 1, wherein the display means further includes audio output means for outputting the text data as audio.

[2099] (Claim 3)

[2100] 10. The system of claim 1, wherein the display means includes a built-in microphone as a means for capturing audio.

[2101] "Application Example 1"

[2102] (Claim 1)

[2103] a display means worn by a user;

[2104] a terminal connected to the display means;

[2105] a server connected to the terminal;

[2106] an audio capture means for transmitting audio data to the terminal;

[2107] a text conversion means in the server for converting the voice data into text;

[2108] a translation means for translating the text data converted by the text conversion means;

[2109] a display means for displaying the data translated by the translation means on a display means;

[2110] A prompt sentence generation means including a generative AI model that retranslates the translated text data into another language and outputs the retranslated text data as speech;

[2111] A system including:

[2112] (Claim 2)

[2113] 2. The system according to claim 1, wherein the display means further includes audio output means for outputting the text data and the retranslated data as audio.

[2114] (Claim 3)

[2115] 10. The system of claim 1, wherein the display means includes a built-in microphone as a means for capturing audio.

[2116] "Example 2: Combining Emotion Engines"

[2117] (Claim 1)

[2118] a display means worn by a user;

[2119] an information processing terminal connected to the display means;

[2120] a data processing device connected to the information processing terminal;

[2121] a voice capturing means for transmitting voice information to the information processing terminal;

[2122] a conversion means for converting the voice information into character information in the data processing device;

[2123] a translation means for translating the character information converted by the conversion means;

[2124] a display means for displaying the information translated by the translation means on a display means;

[2125] an analysis means for analyzing emotions based on voice information in the data processing device;

[2126] a display means for displaying the emotion on a display means;

[2127] A system including:

[2128] (Claim 2)

[2129] 2. The system according to claim 1, wherein the display means further includes audio output means for outputting the character information as audio.

[2130] (Claim 3)

[2131] 2. The system according to claim 1, wherein said display means incorporates an audio input device as an audio capturing means.

[2132] "Application example 2 when combining emotion engines"

[2133] (Claim 1)

[2134] a display means worn by a user;

[2135] a terminal connected to the display means;

[2136] a server connected to the terminal;

[2137] an audio capture means for transmitting audio data to the terminal;

[2138] a text conversion means in the server for converting the voice data into text;

[2139] a translation means for translating the text data converted by the text conversion means;

[2140] emotion recognition means for recognizing emotions based on the voice data;

[2141] a display means for displaying the data translated by the translation means and the emotion data recognized by the emotion recognition means;

[2142] A system including:

[2143] (Claim 2)

[2144] 2. The system according to claim 1, wherein the display means further includes audio output means for outputting the text data and emotion data as audio.

[2145] (Claim 3)

[2146] 10. The system of claim 1, wherein the display means includes a built-in microphone as a means for capturing audio. [Explanation of symbols]

[2147] 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 display means worn by a user; a terminal connected to the display means; a server connected to the terminal; an audio capture means for transmitting audio data to the terminal; a text conversion means in the server for converting the voice data into text; a translation means for translating the text data converted by the text conversion means; a display means for displaying the data translated by the translation means on a display means; A system including:

2. 2. The system according to claim 1, wherein said display means further includes voice output means for outputting said text data as voice.

3. 2. The system of claim 1, wherein said display means includes a built-in microphone as a means for capturing sound.

Images