System

Abstract

A system is provided.SOLUTION: A system comprising: audio input means for capturing ambient audio; transmission means for transmitting the captured audio data over a network; audio recognition means for converting the received audio data into text data; and display means for displaying the converted text data.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] People with hearing impairments have great difficulty communicating with others in their daily lives. In particular, they have difficulty understanding the content of conversations in real time, which limits their ability to obtain information and share emotions. Therefore, there is a need for a system that allows people with hearing impairments to converse smoothly with others and obtain information. The present invention aims to solve these problems and provide a means for people with hearing impairments to understand conversations in real time and improve the quality of their communication. [Means for solving the problem]

[0005] The present invention provides a system including a voice input means for capturing ambient sounds, a transmission means for transmitting the captured voice data via a network, a voice recognition means for converting the received voice data into text data, and a display means for displaying the converted text data. The system further includes a preprocessing means for preprocessing the voice data to perform noise reduction, the voice recognition means performs context analysis, the transmission means compresses and transmits the voice data, and the display means uses an augmented reality display. This system enables hearing-impaired people to visually understand the content of conversations with others in real time, improving the quality of information acquisition and communication.

[0006] An "audio input means" is a device or sensor for capturing ambient sounds.

[0007] The "transmission means" is a device or module for transmitting the captured audio data to another device or server via a network.

[0008] A "voice recognition means" is a software or hardware component for converting received voice data into text data.

[0009] The "display means" is a device for visually displaying the converted text data.

[0010] The "preprocessing means" is a device or software module for performing preprocessing such as noise reduction on audio data.

[0011] "Context analysis" is the process of understanding the context within audio data and converting it into appropriate text.

[0012] The "compression means" is a device or software that compresses audio data to reduce its data size.

[0013] An "augmented reality display" is a display that displays digital information overlaid on the user's field of vision. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] The present invention is an AR glasses system for supporting the hearing impaired. A specific example of the system is described below.

[0036] System configuration

[0037] This system consists of three main components: the terminal (AR glasses), the server, and the user.

[0038] Terminal

[0039] Audio input method: The AR glasses worn by the user are equipped with a high-performance microphone that captures surrounding sounds.

[0040] Transmission means: A communication module is built in to transmit captured audio data to a server in real time.

[0041] Display means: An augmented reality display is installed to display the text data received from the server in the user's field of vision.

[0042] server

[0043] Speech recognition means: The server converts the received voice data into text data using a speech recognition engine. This engine is capable of highly accurate speech recognition and contextual analysis.

[0044] Pre-processing means: The server processes the received audio data and performs noise reduction and sound quality adjustment.

[0045] Text transmission means: Transmits the converted text data to the terminal in real time.

[0046] Specific examples

[0047] Scenario: Conversation in a cafe

[0048] 1. Voice Input

[0049] Consider a scenario where a user is having a conversation with a friend at a cafe, and the device's microphone captures what the friend says, for example, "Hi, how was your day?"

[0050] 2. Sending audio data

[0051] The audio data captured by the device is compressed, preprocessed using noise reduction and other techniques, and then sent to the server in real time.

[0052] 3. Converting Audio Data to Text

[0053] The server converts the received voice data into text data using a voice recognition engine. Specifically, the voice data "Hello, how was your day?" is converted directly into text data.

[0054] 4. Sending text data

[0055] The server formats the converted text data and sends it to the terminal.

[0056] 5. Text Display

[0057] The device displays the received text data on the AR glasses' display, and the text "Hello, how was your day?" appears in the user's field of vision.

[0058] User Experience

[0059] This system allows users to visually understand the sounds around them in real time. Users can obtain audio information by reading the text displayed on the AR glasses. This will enable the hearing impaired to communicate more smoothly in their daily lives.

[0060] As described above, the present invention is a very useful support tool for the hearing impaired, supporting real-time communication.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] The device activates the microphone in response to user operation and captures surrounding sounds. For example, if a user is talking to a friend at a cafe, the microphone will collect the friend's utterance of "hello."

[0064] Step 2:

[0065] The device performs preprocessing such as noise reduction on the captured voice data. The device eliminates environmental noise and improves the quality of the voice data, thereby improving the accuracy of voice recognition.

[0066] Step 3:

[0067] The terminal compresses the pre-processed voice data and converts it into a format for transmission. By reducing the data size, communication efficiency is improved.

[0068] Step 4:

[0069] The device transmits the compressed audio data to the server in real time over a network, for example, using Wi-Fi or mobile data communication.

[0070] Step 5:

[0071] The server receives the voice data sent from the device and prepares to analyze the received data.

[0072] Step 6:

[0073] The server runs the received voice data through a voice recognition engine and converts it into text data. For example, voice data saying "hello" is converted into the text "hello."

[0074] Step 7:

[0075] The server performs contextual analysis on the generated text data, which allows for a more accurate understanding of the meaning and intent of the speech.

[0076] Step 8:

[0077] The server sends the formatted text data to the terminal in real time. For example, the text "Hello" is sent to the terminal.

[0078] Step 9:

[0079] The terminal receives the text data sent from the server and prepares to display the received data.

[0080] Step 10:

[0081] The device formats and displays the received text on the AR glasses' display, and the word "Hello" appears in the user's field of vision.

[0082] This process allows users to visually understand what is being said around them as text in real time, which helps hearing-impaired users to communicate more smoothly with others.

[0083] Example 1

[0084] 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."

[0085] The purpose of this invention is to provide a support tool for the hearing impaired to facilitate smooth communication in daily life, in particular to enable them to efficiently understand auditory information by visualizing surrounding sounds as text in real time.

[0086] 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.

[0087] In this invention, the server includes a speech recognition unit that converts received speech data into text data using a highly accurate speech recognition engine, a preprocessing unit that preprocesses the speech data to perform noise reduction, and a context analysis unit that performs context analysis, thereby enabling accurate text conversion and display in real time.

[0088] "Audio input means" is a device for capturing ambient sounds.

[0089] The "transmission means" is a device or function for transmitting the captured audio data over a network.

[0090] The "voice recognition means" is a device or function for converting received voice data into text data using a highly accurate voice recognition engine.

[0091] A "display means" is a device or function including an augmented reality display for displaying the converted text data in real time in the user's field of view.

[0092] The "preprocessing means" is a device or function for preprocessing audio data to perform noise reduction.

[0093] "Context analysis" is an analytical process performed by a speech recognition means to understand the context of speech data and achieve more accurate text conversion.

[0094] This invention is an AR glasses system for supporting the hearing impaired. This system consists of three main components: AR glasses (terminals) worn by the user, a remote server, and the user.

[0095] Terminal

[0096] Voice input methods:

[0097] The AR glasses worn by users are equipped with high-performance microphones that capture the sounds of the surrounding environment. For example, when you are talking with a friend in a public place such as a cafe, the microphones pick up what your friend is saying.

[0098] Transmission method:

[0099] The captured audio data is transmitted in real time to a server using a communication module built into the device, which uses Wi-Fi or Bluetooth and undergoes noise reduction before transmission.

[0100] Display means:

[0101] The text data received from the server is displayed on the augmented reality display of the AR glasses. Specifically, the text pops up in the user's field of vision, allowing them to visually understand the audio information.

[0102] server

[0103] Voice recognition methods:

[0104] The server converts the received voice data into text data using a highly accurate voice recognition engine (e.g., a general-purpose voice recognition engine), which uses phonological algorithms to analyze the voice data and convert it into appropriate text.

[0105] Pretreatment methods:

[0106] The server preprocesses the audio data, reducing noise and adjusting the audio quality, allowing the speech recognition engine to convert speech to text more accurately.

[0107] Texting methods:

[0108] The converted text data is then formatted and sent immediately to the device. This involves removing extra spaces and adding necessary punctuation. Specifically, a Python script is used to convert the text data into JSON format and send it to the device via an HTTP request.

[0109] User Experience

[0110] This system allows users to visually understand the sounds around them in real time. For example, during a meeting, users can instantly read what their colleagues are saying as text using AR glasses. This will enable the hearing impaired to communicate more smoothly in their daily lives.

[0111] Specific examples

[0112] Scenario: Conversation in a cafe

[0113] 1. Voice Input

[0114] A user is talking to a friend at a cafe, and the device's microphone captures the friend saying, "Hello, how was your day?"

[0115] 2. Sending audio data

[0116] The device transmits the captured audio data to the server in real time, with noise reduction performed during transmission.

[0117] 3. Converting Audio Data to Text

[0118] The server receives the voice data and converts it into text data such as "Hello, how was your day?" using a general-purpose voice recognition engine.

[0119] 4. Sending text data

[0120] The server formats the converted text data using a Python script and sends it to the terminal.

[0121] 5. Text Display

[0122] The text data received by the device is displayed on the AR glasses' display, and the text "Hello, how was your day?" is displayed in the user's field of vision.

[0123] Prompt Sentence Examples

[0124] "Create a program that displays what your friend is saying in real time on your AR glasses."

[0125] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0126] Step 1:

[0127] Voice input

[0128] Device:

[0129] Input: A situation where a user wears AR glasses and recognizes surrounding sounds.

[0130] How it works: High-performance microphones built into the AR glasses capture surrounding sounds.

[0131] Output: Audio data captured by the microphone.

[0132] Data processing: Convert into digital format as an audio signal.

[0133] Step 2:

[0134] Sending audio data

[0135] Device:

[0136] Input: Audio data captured by a high-quality microphone.

[0137] How it works: The device's communication module transmits audio data to the server in real time, then performs noise reduction and compresses the data to an optimal format (e.g., MP3) before transmission.

[0138] Output: Filtered compressed audio data.

[0139] Data processing: Noise reduction and compression of audio data.

[0140] Step 3:

[0141] Converting audio data to text

[0142] server:

[0143] Input: Audio data sent from the device.

[0144] Specific operation: The server converts the received voice data into text data using a highly accurate voice recognition engine. A general-purpose voice recognition engine is used to analyze the data using a phonological algorithm.

[0145] Output: The converted text data.

[0146] Data processing: Converting voice data to text.

[0147] Step 4:

[0148] Preprocessing and sending text data

[0149] server:

[0150] Input: Text data converted by the speech recognition engine.

[0151] What it does: Formats the text data, removing extra spaces and adding necessary punctuation, converting it to JSON format using a Python script, and then sending it to the device via an HTTP request.

[0152] Output: Formatted and converted text data.

[0153] Data processing: Formatting text data and converting it to JSON format.

[0154] Step 5:

[0155] Text Display

[0156] Device:

[0157] Input: Formatted and converted text data sent from the server.

[0158] Specific operation: The device displays the received text data on the augmented reality display of the AR glasses. The text pops up in the user's field of view.

[0159] Output: The displayed text information.

[0160] Data processing: Converting text data into visual information.

[0161] (Application example 1)

[0162] 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."

[0163] Conventional communication support systems for the hearing impaired have limitations in their speech-to-text conversion capabilities, making it difficult to handle noise and complex speech contexts when used in physical store environments. Furthermore, the lack of real-time speech recognition and text display hinders smooth communication. Furthermore, there is a lack of technology that allows users to visually interpret information in a natural, unobtrusive way.

[0164] 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.

[0165] In this invention, the server includes an audio input means for capturing surrounding sounds, a communication means for transmitting the captured sound data via a network, a speech recognition means for converting the received sound data into text data, a preprocessing means for preprocessing the received sound data in real time and performing noise reduction, and a visual display means for displaying the converted text data on an augmented reality display. This allows hearing-impaired people to enjoy smooth and comfortable communication in physical stores, and enables real-time speech recognition and visual text display.

[0166] An "acoustic input means" is a device used to capture ambient sound.

[0167] "Communication means" refers to the device or technology used to transmit the captured audio data over a network.

[0168] "Speech recognition means" refers to a device or technology for converting received voice data into text data.

[0169] A "visual display means" is a device or technique for displaying the converted text data on an augmented reality display.

[0170] The "preprocessing means" refers to a device or technology for preprocessing received audio data in real time and performing noise reduction.

[0171] An "information processing system" is a comprehensive system that combines multiple means to process and display specific information.

[0172] A "brick and mortar store" is a commercial or service establishment that exists in a physical location.

[0173] "Context analysis" is a technology in which a speech recognition means understands the context of text data and performs appropriate text conversion.

[0174] "Augmented reality display" is a technology that displays digital information superimposed on the real world.

[0175] The system that realizes this application example consists of three main components: the terminal (AR glasses), the server, and the user.

[0176] Device (AR glasses)

[0177] The device includes the following elements:

[0178] Acoustic input means: This is a high-performance microphone that captures surrounding sounds. For example, when a store clerk explains a product, the microphone captures that sound.

[0179] Communication means: A communication module is built in to transmit captured audio data to a server in real time.

[0180] Visual display means: The system is equipped with an augmented reality display to display the text data received from the server in the user's field of vision. Through this display, the user can visually recognize the captured voice as text.

[0181] server

[0182] The server includes the following elements:

[0183] Speech recognition means: The received voice data is converted into text data by a speech recognition engine. This engine is capable of highly accurate speech recognition and contextual analysis.

[0184] Pre-processing means: Processes the received voice data and performs noise reduction and sound quality adjustment, which results in more accurate text conversion.

[0185] Communication method: Responsible for sending the converted text data to the terminal. This data is sent in real time, so the text is displayed without delay.

[0186] Example

[0187] Scenario: Ordering at a restaurant

[0188] 1. Audio capture via acoustic input means:

[0189] The device's microphone captures the voice of the waiter saying, "Today's recommendation is steak."

[0190] 2. Transmission of audio data by means of communication:

[0191] The captured audio data is transmitted to the server in real time via the terminal's communication module.

[0192] 3. Text conversion by speech recognition means:

[0193] The voice data is received on the server and converted into text data such as "Today's recommendation is steak" using a speech recognition engine. Contextual analysis is also performed, reducing the chance of misrecognition.

[0194] 4. Text data transmission and visual display:

[0195] The converted text data is sent to the terminal and displayed on the terminal's augmented reality display, allowing the user to understand the voice of the store clerk.

[0196] Hardware / Software used

[0197] Hardware:

[0198] High-performance microphone (for voice capture)

[0199] AR glasses (for displaying text)

[0200] software:

[0201] Python, socket, speech_recognition

[0202] Socket communication is used for communication between the server and the client

[0203] Prompt Sentence Examples

[0204] Below is an example of a prompt sentence to be input to the generative AI model.

[0205] I want to build an application that uses voice capture and text conversion to help hearing-impaired people understand when ordering at a restaurant. I want to create a system that converts the voice of a waiter saying, "Today's recommendation is steak," into text and displays it on the AR glasses.

[0206] As a result, this invention allows hearing-impaired people to visually understand audio information in real time in physical stores. Users can receive support by reading the text displayed on the AR glasses.

[0207] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0208] Step 1:

[0209] The device captures the surrounding sound using a high-performance microphone. Specifically, the microphone receives the sound as an analog signal and converts it into a digital signal. The input is the surrounding sound, and the output is digital sound data.

[0210] Step 2:

[0211] The terminal transmits the captured digital audio data to the server in real time via the communication module. The specific operations performed here are to generate data packets and transmit them over the network. The input is the digital audio data, and the output is the data packets transmitted to the server.

[0212] Step 3:

[0213] The server performs noise reduction on the received digital audio data using a pre-processing means. Specifically, it applies a noise filtering algorithm to remove unwanted noise from the audio data. The input is the received digital audio data, and the output is the clean audio data after noise reduction.

[0214] Step 4:

[0215] The server uses a speech recognition means to convert the noise-reduced speech data into text data. Specifically, a speech recognition engine analyzes the speech signal and generates corresponding text. The input is the clean speech data, and the output is the converted text data.

[0216] Step 5:

[0217] The server transmits the converted text data to the terminal via a communication means. Specific operations include packetizing the text data and transmitting it over a network. The input is the text data, and the output is the data transmitted to the terminal.

[0218] Step 6:

[0219] The terminal displays the received text data in the user's field of view using a visual display means. Specifically, the augmented reality display visualizes the text data and displays it to the user in real time. The input is the text data received from the server, and the output is the text displayed in the user's field of view.

[0220] 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.

[0221] The present invention is an AR glasses system for supporting the hearing impaired, and by adding the functionality of an emotion engine, it can recognize the user's emotions. A specific example of this is shown below.

[0222] System configuration

[0223] This system consists of four main components: the terminal (AR glasses), the server, the user, and the emotion engine.

[0224] Terminal

[0225] Audio input method: The AR glasses worn by the user are equipped with a high-performance microphone that captures surrounding sounds.

[0226] Transmission means: A communication module is built in to transmit captured audio data to a server in real time.

[0227] Display means: An augmented reality display is installed to display the text data received from the server and emotion recognition results in the user's field of vision.

[0228] server

[0229] Speech recognition means: The server converts the received voice data into text data using a speech recognition engine. This engine is capable of highly accurate speech recognition and contextual analysis.

[0230] Pre-processing means: The server processes the received audio data and performs noise reduction and sound quality adjustment.

[0231] Text transmission means: Transmits the converted text data to the terminal in real time.

[0232] Emotion Engine

[0233] Emotion recognition means: The emotion engine installed on the server recognizes the user's emotions based on voice data and facial expression data.

[0234] Emotion display means: Recognized emotion data is sent to the terminal and visually presented to the user via the display means.

[0235] Specific examples

[0236] Scenario: Conversation in a cafe

[0237] 1. Voice Input

[0238] Consider a scenario where a user is having a conversation with a friend at a cafe, and the device's microphone captures what the friend says, for example, "Hi, how was your day?"

[0239] 2. Sending audio data

[0240] The device preprocesses the captured audio data, removes noise, compresses it, and sends it to the server in real time.

[0241] 3. Converting Audio Data to Text

[0242] The server converts the received voice data into text data using a voice recognition engine. Specifically, the voice data "Hello, how was your day?" is converted directly into text data.

[0243] 4. Emotion recognition

[0244] The server's emotion engine analyzes the voice and facial expression data to recognize the emotion contained in the friend's speech. For example, if the friend speaks in a happy tone, the emotion "happy" is recognized.

[0245] 5. Sending text data and emotion data

[0246] The server formats the converted text data and the recognized emotion data and sends them to the device. The text "Hello, how was your day?" and the emotion data "I'm happy" are sent.

[0247] 6. Text and Emotion Display

[0248] The device displays the received text and emotion data on the AR glasses' display, providing it to the user's field of vision. The user's field of vision displays the message "Hello, how was your day?" along with the friend's emotion, "Happy."

[0249] User Experience

[0250] This system allows users to visually understand the surrounding voices in real time, while also recognizing the speaker's emotions. By reading the text and emotional information displayed in the AR glasses, users can grasp not only the voice but also the emotional nuances. This will enable hearing-impaired people to have richer communication in their daily lives.

[0251] As described above, the present invention is an extremely useful support tool for the hearing impaired, supporting real-time communication and enabling visual understanding of the emotions of the other party.

[0252] The processing flow will be explained below.

[0253] Step 1:

[0254] The device activates the microphone in response to user operation and captures surrounding sounds. For example, if a user is talking with a friend at a cafe, the microphone will collect the friend's words, "Hello, how was your day?"

[0255] Step 2:

[0256] The device performs preprocessing such as noise reduction on the captured voice data. The device eliminates environmental noise and improves the quality of the voice data, thereby improving the accuracy of voice recognition.

[0257] Step 3:

[0258] The terminal compresses the pre-processed voice data and converts it into a format for transmission. By reducing the data size, communication efficiency is improved.

[0259] Step 4:

[0260] The device transmits the compressed audio data to the server in real time over a network, for example, using Wi-Fi or mobile data communication.

[0261] Step 5:

[0262] The server receives the voice data sent from the device and prepares to analyze the received data.

[0263] Step 6:

[0264] The server runs the received voice data through a voice recognition engine and converts it into text data. For example, voice data such as "Hello, how was your day?" is converted into text such as "Hello, how was your day?"

[0265] Step 7:

[0266] The server performs contextual analysis on the text data, processing it to more accurately understand the meaning and intent of the utterance.

[0267] Step 8:

[0268] The server sends voice and facial expression data to the emotion engine for emotion recognition. For example, it analyzes a friend's tone of voice and facial expression to recognize emotions such as "happiness" or "fun."

[0269] Step 9:

[0270] The server formats the converted text data and the recognized emotion data and sends them to the device. The text "Hello, how was your day?" and the emotion data "I'm happy" are sent to the device.

[0271] Step 10:

[0272] The device receives the text data and emotion data sent from the server and prepares to display the received data.

[0273] Step 11:

[0274] The device then formats and displays the received text and emotion data on the AR glasses' display. The user's field of vision is displayed with the text "Hello, how was your day?" along with a pictogram or icon representing the emotion "happy."

[0275] These steps allow users to visually understand what is being said around them in real time as text, while also visually recognizing the speaker's emotions. This allows hearing-impaired people to grasp not only the nuances of speech but also the emotional nuances, enabling smoother communication.

[0276] Example 2

[0277] 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."

[0278] In everyday life, people with hearing impairments often find it difficult to understand the sounds around them and experience difficulties in communication. It is particularly important for them to understand not only the sound but also the speaker's emotions. However, previous technologies lacked the means to accurately recognize sounds and emotions in real time and to visually present them. The present invention aims to solve these problems and provide a system that enables people with hearing impairments to understand the sounds around them and the speaker's emotions in real time.

[0279] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0280] In this invention, the server includes an input means for capturing surrounding sounds, a transmission means for transmitting the captured sound data via a network, a conversion means for converting the received sound data into text data, and an emotion display means for displaying recognized emotion data, thereby enabling hearing-impaired people to visually understand surrounding sounds in real time and simultaneously recognize the emotions of the speaker.

[0281] "Input means" refers to devices and sensors for capturing ambient sound.

[0282] The "transmission means" refers to a communication module for transmitting the captured audio data to a server or the like via a network.

[0283] "Conversion means" refers to a voice recognition engine or software for converting received voice data into text data.

[0284] "Display means" refers to a display or projector for visually displaying the converted text data.

[0285] "Recognition means" refers to an algorithm or program for analyzing received voice data and facial expression data to recognize emotions.

[0286] "Emotion display means" refers to a module or display for visually presenting recognized emotion data.

[0287] "Preprocessing means" refers to filtering techniques and algorithms used to process audio data and perform noise reduction.

[0288] "Context analysis" refers to the process performed by a speech recognition means to understand the context of speech data and analyze it appropriately.

[0289] This invention proposes an AR glasses system to support the hearing impaired, which can visually present voice and the speaker's emotions in real time using an emotion engine. This system consists of four main entities: a terminal (AR glasses), a server, a user, and an emotion engine.

[0290] Terminal

[0291] The device is equipped with a high-performance microphone, a communication module, and an augmented reality display. Specifically, the following hardware and software are used:

[0292] Voice input: A high-performance microphone captures the surrounding sounds, for example, recording someone saying "Hello, how was your day?" in a cafe.

[0293] Transmission means: A Wi-Fi or mobile network communication module is built in to transmit captured audio data to a server in real time.

[0294] Display means: An augmented reality display is installed to display the text data and emotion data sent from the server in the user's field of vision.

[0295] server

[0296] The server is equipped with a speech recognition engine for processing voice data and converting it into text data, and an emotion engine for analyzing emotions. Specifically, the following processes are performed:

[0297] Speech recognition means: The server converts the received voice data into text data using a high-precision voice recognition engine (e.g., general voice recognition software).

[0298] Pre-processing method: Pre-process the audio data to reduce noise. Noise filtering techniques are used in this process.

[0299] Recognition means: The emotion engine analyzes voice data and, if necessary, facial expression data to recognize the user's emotions.

[0300] Text transmission method: The converted text data and emotion data are formatted and sent to the device.

[0301] Emotion Engine

[0302] The emotion engine analyzes the received voice and facial expression data to recognize the speaker's emotions. For example, it analyzes emotions such as "happy" or "sad" contained in a friend's speech.

[0303] User Experience

[0304] By wearing the AR glasses, users can visually understand the surrounding sounds in real time and simultaneously recognize the speaker's emotions, enabling hearing-impaired people to achieve richer communication in their daily lives.

[0305] Specific examples

[0306] Scenario: Conversation in a cafe

[0307] 1. Voice Input: Imagine a user is having a conversation with a friend at a cafe, and the device's microphone captures the friend saying, "Hello, how was your day?"

[0308] 2. Sending audio data: The device preprocesses the recorded audio data, removes noise, compresses it, and sends it to the server in real time.

[0309] 3. Converting voice data to text: The server analyzes the voice data received by the server using a voice recognition engine and converts it into text data. For example, the voice data "Hello, how was your day?" is converted into text.

[0310] 4. Emotion recognition: The server's emotion engine analyzes the voice and facial expression data to recognize the speaker's emotions. For example, if the speaker speaks in a happy tone, it will recognize the emotion as "happy."

[0311] 5. Sending text data and emotion data: The server sends the converted text data and the recognized emotion data to the device. The text "Hello, how was your day?" and the emotion data "I'm happy" are sent.

[0312] 6. Text and emotion display: The device displays the received text and emotion data on the AR glasses display and provides it to the user's field of view. The user's field of view will display the text "Hello, how was your day?" along with the friend's emotion "Happy."

[0313] Prompt Sentence Examples

[0314] Example prompts to input to a generative AI model:

[0315] "Please explain a system that uses an emotion engine to analyze a conversation with a friend, such as 'Hi, how was your day?', convert the speech to text, and recognize and display the emotion."

[0316] As described above, the system of the present invention is a very useful support tool for the hearing impaired, enabling them to visually understand speech and emotions in real time.

[0317] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0318] Step 1:

[0319] Audio input and preprocessing (terminal)

[0320] The device's high-performance microphone captures the surrounding audio. The input here is the surrounding audio, specifically a friend saying, "Hello, how was your day?" The captured audio data is passed through an internal noise reduction filter to remove noise and pre-process it into clear audio data. The output is high-quality audio data with noise removed.

[0321] Step 2:

[0322] Sending audio data (terminal)

[0323] The device sends the preprocessed audio data to the server in real time, where the input is the preprocessed audio data from step 1, sent to the server via Wi-Fi or mobile network, and the output is the audio data sent to the server.

[0324] Step 3:

[0325] Receiving and preprocessing audio data (server)

[0326] The server receives the audio data sent from the device. The input here is the audio data sent from the device, and the server performs additional noise reduction and sound quality adjustments. The output is the optimized audio data.

[0327] Step 4:

[0328] Speech recognition and text conversion (server)

[0329] The server analyzes the received voice data using a voice recognition engine and converts it into text data. The input here is the voice data optimized in step 3, specifically the voice data "Hello, how was your day?" that is converted into text. The output is text data.

[0330] Step 5:

[0331] Emotion recognition (server)

[0332] The server's emotion engine analyzes the voice data and facial expression data to recognize the speaker's emotions. The input here is the text data obtained in step 4 and information such as the tone, pace, and strength of the voice. For example, if the tone sounds happy, the emotion "happy" is recognized. The output is the recognized emotion data.

[0333] Step 6:

[0334] Sending text data and emotion data (server)

[0335] The server formats the converted text data and the recognized emotion data and sends them to the terminal. The input here is the text data obtained in step 4 and the emotion data recognized in step 5, which are appropriately formatted and sent to the terminal. The output is the text data and emotion data sent to the terminal.

[0336] Step 7:

[0337] Text display and emotion display (terminal)

[0338] The device displays the received text data and emotion data on the display of the AR glasses. The input here is the text and emotion data sent from the server in step 6, and the text "Hello, how was your day?" and the emotion "happy" are displayed in the user's field of view. The output is the visualized text and emotion data.

[0339] Step 8:

[0340] Information Awareness (User)

[0341] The user visually understands the displayed text and emotional information through the AR glasses. The input here is the text and emotional data displayed in step 7, and the user recognizes this information to understand the words and emotions of their friend. The output is the user's understanding and recognition.

[0342] (Application example 2)

[0343] 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."

[0344] Conventional speech recognition systems were able to convert voice data into text, but they were unable to recognize the speaker's emotions and display them visually. This made it difficult for hearing-impaired people to understand the conversations and emotions around them in real time. In brick-and-mortar stores in particular, it is important to simultaneously understand the language and emotional information of customer service staff, and this aspect needed to be improved.

[0345] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0346] In this invention, the server includes an audio input means for capturing surrounding sounds, a communication means for transmitting the captured sound data via a network, a voice recognition means for converting the received sound data into text data, and a visual display means for displaying the converted text data and the recognized emotion data in the user's field of view, thereby enabling hearing-impaired people to visually understand the linguistic information and emotion information of customer service staff simultaneously in real time in a brick-and-mortar store.

[0347] An "audio input means" is a device for capturing ambient sounds.

[0348] A "communication means" is a device for transmitting captured audio data over a network.

[0349] The "voice recognition means" is a device for converting received voice data into text data.

[0350] The "visual display means" is a device for displaying the converted text data and the recognized emotion data in the user's field of vision.

[0351] The "preprocessing means" is a device for preprocessing audio data to perform noise reduction.

[0352] The "emotion recognition means" is a device that analyzes voice and facial expression data to recognize emotions.

[0353] "Context analysis" is an analysis method that allows a speech recognition means to understand the meaning and intent of speech data.

[0354] This invention is a system for supporting hearing-impaired people, specifically implemented as a customer service support application in a brick-and-mortar store. The system includes a terminal, a server, and an emotion recognition engine. A specific example of the system is described below.

[0355] System configuration

[0356] Terminal

[0357] Acoustic input means: The device is equipped with a high-performance microphone to capture surrounding sounds. This microphone captures conversations in the physical store in real time.

[0358] Communication means: A communication module is built in to transmit captured audio data to a server via a network.

[0359] Visual display means: An augmented reality display is provided to display the converted text data and recognized emotion data in the user's field of vision.

[0360] server

[0361] Pre-processing means: The server performs pre-processing on the received audio data to reduce noise and adjust the sound quality.

[0362] Speech recognition means: The preprocessed speech data is converted into highly accurate text data using a speech recognition engine.

[0363] Emotion recognition means: Equipped with an emotion engine that analyzes received voice data and facial expression data to recognize the speaker's emotions.

[0364] User Experience

[0365] Using this system, hearing-impaired people can understand conversations with customer service staff in real time in a physical store. Specific examples include the following scenario:

[0366] Scenario: Conversation in a brick-and-mortar store

[0367] Voice input: A customer asks a staff member at a brick-and-mortar cafe, "What would you recommend about this cake?"

[0368] Audio data transmission: The device preprocesses the captured audio data to remove noise and transmits it to the server in real time.

[0369] Conversion of voice data to text: The voice data received by the server is converted into text data using a voice recognition engine, such as "What do you recommend about this cake?"

[0370] Emotion recognition: The server's emotion recognition engine analyzes the voice data and facial expression data to recognize the questioner's emotion of interest.

[0371] Sending text data and emotion data: The server sends the converted text data and emotion data to the terminal. The text "What do you recommend about this cake?" and the emotion data "I'm interested" are sent.

[0372] Text display and emotion display: The device displays the received text and emotion data on the AR glasses display, displaying "What do you recommend about this cake?" and "Interested" in the user's field of vision.

[0373] Hardware and software used

[0374] Hardware: Devices with high-performance microphones, communication modules, and augmented reality displays (e.g., AR glasses).

[0375] Software: High-precision speech recognition engines (e.g., Google Speech Recognition API), emotion recognition engines (e.g., the sentiment analysis pipeline in the transformers library), and communication libraries (e.g., requests).

[0376] Prompt Sentence Examples

[0377] Text: "Chocolate cake is recommended today!"

[0378] Emotion: "Fun"

[0379] This will make it easier for hearing-impaired people to understand customer service in physical stores and facilitate smooth communication.

[0380] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0381] Step 1:

[0382] When a user starts a conversation with a customer service staff member in a physical store, the device's audio input means captures the voice. The input is the conversational voice occurring in the physical store, and the output is the captured voice data. The device uses a high-performance microphone to detect surrounding sounds and record them as digital voice data.

[0383] Step 2:

[0384] The device sends the captured audio data to the server via a communication means. The input is the audio data obtained in step 1, and the output is the audio data sent via the network. The device uses a built-in communication module (such as Wi-Fi or Bluetooth) to send the data to the server in real time.

[0385] Step 3:

[0386] The server uses preprocessing means to reduce noise and adjust the sound quality of the received audio data. The input is the audio data sent from the terminal, and the output is the preprocessed audio data. The server uses DSP (Digital Signal Processing) technology to remove environmental noise from the audio data and create clear audio data.

[0387] Step 4:

[0388] The server converts the preprocessed voice data into text data using a speech recognition tool. The input is the preprocessed voice data, and the output is text data. The server converts the voice data into corresponding text using a high-precision speech recognition engine such as the Google Speech Recognition API.

[0389] Step 5:

[0390] The server analyzes the text data and voice data generated by the speech recognition means using the emotion recognition means to recognize the speaker's emotions. The input is the converted text data and voice data, and the output is the text data and emotion data. The server uses the emotion analysis pipeline of the transformers library to detect emotional elements in the text data.

[0391] Step 6:

[0392] The server transmits the converted text data and emotion data to the terminal via a communication means. The input is the text data and emotion data that are the results of the speech recognition and emotion recognition, and the output is data transmitted via a network. The server packages this data and transmits it to the terminal in real time.

[0393] Step 7:

[0394] The terminal displays the received text data and emotion data in the user's field of view using a visual display means. The input is the text data and emotion data sent from the server, and the output is the information displayed on the visual display of the AR glasses. Specifically, the terminal uses the augmented reality display to display the information "What do you recommend about this cake?" and "Interested" in the user's field of view.

[0395] Through these steps, hearing-impaired people can understand the content and emotions of conversations with store staff in real time, greatly improving the user's communication experience.

[0396] 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.

[0397] 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.

[0398] 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.

[0399] [Second embodiment]

[0400] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0401] 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.

[0402] 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).

[0403] 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.

[0404] 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.

[0405] 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).

[0406] 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.

[0407] 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.

[0408] 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.

[0409] 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.

[0410] 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.

[0411] 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."

[0412] The present invention is an AR glasses system for supporting the hearing impaired. A specific example of the system is described below.

[0413] System configuration

[0414] This system consists of three main components: the terminal (AR glasses), the server, and the user.

[0415] Terminal

[0416] Audio input method: The AR glasses worn by the user are equipped with a high-performance microphone that captures surrounding sounds.

[0417] Transmission means: A communication module is built in to transmit captured audio data to a server in real time.

[0418] Display means: An augmented reality display is installed to display the text data received from the server in the user's field of vision.

[0419] server

[0420] Speech recognition means: The server converts the received voice data into text data using a speech recognition engine. This engine is capable of highly accurate speech recognition and contextual analysis.

[0421] Pre-processing means: The server processes the received audio data and performs noise reduction and sound quality adjustment.

[0422] Text transmission means: Transmits the converted text data to the terminal in real time.

[0423] Specific examples

[0424] Scenario: Conversation in a cafe

[0425] 1. Voice Input

[0426] Consider a scenario where a user is having a conversation with a friend at a cafe, and the device's microphone captures what the friend says, for example, "Hi, how was your day?"

[0427] 2. Sending audio data

[0428] The audio data captured by the device is compressed, preprocessed using noise reduction and other techniques, and then sent to the server in real time.

[0429] 3. Converting Audio Data to Text

[0430] The server converts the received voice data into text data using a voice recognition engine. Specifically, the voice data "Hello, how was your day?" is converted directly into text data.

[0431] 4. Sending text data

[0432] The server formats the converted text data and sends it to the terminal.

[0433] 5. Text Display

[0434] The device displays the received text data on the AR glasses' display, and the text "Hello, how was your day?" appears in the user's field of vision.

[0435] User Experience

[0436] This system allows users to visually understand the sounds around them in real time. Users can obtain audio information by reading the text displayed on the AR glasses. This will enable the hearing impaired to communicate more smoothly in their daily lives.

[0437] As described above, the present invention is a very useful support tool for the hearing impaired, supporting real-time communication.

[0438] The processing flow will be explained below.

[0439] Step 1:

[0440] The device activates the microphone in response to user operation and captures surrounding sounds. For example, if a user is talking to a friend at a cafe, the microphone will collect the friend's utterance of "hello."

[0441] Step 2:

[0442] The device performs preprocessing such as noise reduction on the captured voice data. The device eliminates environmental noise and improves the quality of the voice data, thereby improving the accuracy of voice recognition.

[0443] Step 3:

[0444] The terminal compresses the pre-processed voice data and converts it into a format for transmission. By reducing the data size, communication efficiency is improved.

[0445] Step 4:

[0446] The device transmits the compressed audio data to the server in real time over a network, for example, using Wi-Fi or mobile data communication.

[0447] Step 5:

[0448] The server receives the voice data sent from the device and prepares to analyze the received data.

[0449] Step 6:

[0450] The server runs the received voice data through a voice recognition engine and converts it into text data. For example, voice data saying "hello" is converted into the text "hello."

[0451] Step 7:

[0452] The server performs contextual analysis on the generated text data, which allows for a more accurate understanding of the meaning and intent of the speech.

[0453] Step 8:

[0454] The server sends the formatted text data to the terminal in real time. For example, the text "Hello" is sent to the terminal.

[0455] Step 9:

[0456] The terminal receives the text data sent from the server and prepares to display the received data.

[0457] Step 10:

[0458] The device formats and displays the received text on the AR glasses' display, and the word "Hello" appears in the user's field of vision.

[0459] This process allows users to visually understand what is being said around them as text in real time, which helps hearing-impaired users to communicate more smoothly with others.

[0460] Example 1

[0461] 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."

[0462] The purpose of this invention is to provide a support tool for the hearing impaired to facilitate smooth communication in daily life, in particular to enable them to efficiently understand auditory information by visualizing surrounding sounds as text in real time.

[0463] 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.

[0464] In this invention, the server includes a speech recognition unit that converts received speech data into text data using a highly accurate speech recognition engine, a preprocessing unit that preprocesses the speech data to perform noise reduction, and a context analysis unit that performs context analysis, thereby enabling accurate text conversion and display in real time.

[0465] "Audio input means" is a device for capturing ambient sounds.

[0466] The "transmission means" is a device or function for transmitting the captured audio data over a network.

[0467] The "voice recognition means" is a device or function for converting received voice data into text data using a highly accurate voice recognition engine.

[0468] A "display means" is a device or function including an augmented reality display for displaying the converted text data in real time in the user's field of view.

[0469] The "preprocessing means" is a device or function for preprocessing audio data to perform noise reduction.

[0470] "Context analysis" is an analytical process performed by a speech recognition means to understand the context of speech data and achieve more accurate text conversion.

[0471] This invention is an AR glasses system for supporting the hearing impaired. This system consists of three main components: AR glasses (terminals) worn by the user, a remote server, and the user.

[0472] Terminal

[0473] Voice input methods:

[0474] The AR glasses worn by users are equipped with high-performance microphones that capture the sounds of the surrounding environment. For example, when you are talking with a friend in a public place such as a cafe, the microphones pick up what your friend is saying.

[0475] Transmission method:

[0476] The captured audio data is transmitted in real time to a server using a communication module built into the device, which uses Wi-Fi or Bluetooth and undergoes noise reduction before transmission.

[0477] Display means:

[0478] The text data received from the server is displayed on the augmented reality display of the AR glasses. Specifically, the text pops up in the user's field of vision, allowing them to visually understand the audio information.

[0479] server

[0480] Voice recognition methods:

[0481] The server converts the received voice data into text data using a highly accurate voice recognition engine (e.g., a general-purpose voice recognition engine), which uses phonological algorithms to analyze the voice data and convert it into appropriate text.

[0482] Pretreatment methods:

[0483] The server preprocesses the audio data, reducing noise and adjusting the audio quality, allowing the speech recognition engine to convert speech to text more accurately.

[0484] Texting methods:

[0485] The converted text data is then formatted and sent immediately to the device. This involves removing extra spaces and adding necessary punctuation. Specifically, a Python script is used to convert the text data into JSON format and send it to the device via an HTTP request.

[0486] User Experience

[0487] This system allows users to visually understand the sounds around them in real time. For example, during a meeting, users can instantly read what their colleagues are saying as text using AR glasses. This will enable the hearing impaired to communicate more smoothly in their daily lives.

[0488] Specific examples

[0489] Scenario: Conversation in a cafe

[0490] 1. Voice Input

[0491] A user is talking to a friend at a cafe, and the device's microphone captures the friend saying, "Hello, how was your day?"

[0492] 2. Sending audio data

[0493] The device transmits the captured audio data to the server in real time, with noise reduction performed during transmission.

[0494] 3. Converting Audio Data to Text

[0495] The server receives the voice data and converts it into text data such as "Hello, how was your day?" using a general-purpose voice recognition engine.

[0496] 4. Sending text data

[0497] The server formats the converted text data using a Python script and sends it to the terminal.

[0498] 5. Text Display

[0499] The text data received by the device is displayed on the AR glasses' display, and the text "Hello, how was your day?" is displayed in the user's field of vision.

[0500] Prompt Sentence Examples

[0501] "Create a program that displays what your friend is saying in real time on your AR glasses."

[0502] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0503] Step 1:

[0504] Voice input

[0505] Device:

[0506] Input: A situation where a user wears AR glasses and recognizes surrounding sounds.

[0507] How it works: High-performance microphones built into the AR glasses capture surrounding sounds.

[0508] Output: Audio data captured by the microphone.

[0509] Data processing: Convert into digital format as an audio signal.

[0510] Step 2:

[0511] Sending audio data

[0512] Device:

[0513] Input: Audio data captured by a high-quality microphone.

[0514] How it works: The device's communication module transmits audio data to the server in real time, then performs noise reduction and compresses the data to an optimal format (e.g., MP3) before transmission.

[0515] Output: Filtered compressed audio data.

[0516] Data processing: Noise reduction and compression of audio data.

[0517] Step 3:

[0518] Converting audio data to text

[0519] server:

[0520] Input: Audio data sent from the device.

[0521] Specific operation: The server converts the received voice data into text data using a highly accurate voice recognition engine. A general-purpose voice recognition engine is used to analyze the data using a phonological algorithm.

[0522] Output: The converted text data.

[0523] Data processing: Converting voice data to text.

[0524] Step 4:

[0525] Preprocessing and sending text data

[0526] server:

[0527] Input: Text data converted by the speech recognition engine.

[0528] What it does: Formats the text data, removing extra spaces and adding necessary punctuation, converting it to JSON format using a Python script, and then sending it to the device via an HTTP request.

[0529] Output: Formatted and converted text data.

[0530] Data processing: Formatting text data and converting it to JSON format.

[0531] Step 5:

[0532] Text Display

[0533] Device:

[0534] Input: Formatted and converted text data sent from the server.

[0535] Specific operation: The device displays the received text data on the augmented reality display of the AR glasses. The text pops up in the user's field of view.

[0536] Output: The displayed text information.

[0537] Data processing: Converting text data into visual information.

[0538] (Application example 1)

[0539] 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."

[0540] Conventional communication support systems for the hearing impaired have limitations in their speech-to-text conversion capabilities, making it difficult to handle noise and complex speech contexts when used in physical store environments. Furthermore, the lack of real-time speech recognition and text display hinders smooth communication. Furthermore, there is a lack of technology that allows users to visually interpret information in a natural, unobtrusive way.

[0541] 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.

[0542] In this invention, the server includes an audio input means for capturing surrounding sounds, a communication means for transmitting the captured sound data via a network, a speech recognition means for converting the received sound data into text data, a preprocessing means for preprocessing the received sound data in real time and performing noise reduction, and a visual display means for displaying the converted text data on an augmented reality display. This allows hearing-impaired people to enjoy smooth and comfortable communication in physical stores, and enables real-time speech recognition and visual text display.

[0543] An "acoustic input means" is a device used to capture ambient sound.

[0544] "Communication means" refers to the device or technology used to transmit the captured audio data over a network.

[0545] "Speech recognition means" refers to a device or technology for converting received voice data into text data.

[0546] A "visual display means" is a device or technique for displaying the converted text data on an augmented reality display.

[0547] The "preprocessing means" refers to a device or technology for preprocessing received audio data in real time and performing noise reduction.

[0548] An "information processing system" is a comprehensive system that combines multiple means to process and display specific information.

[0549] A "brick and mortar store" is a commercial or service establishment that exists in a physical location.

[0550] "Context analysis" is a technology in which a speech recognition means understands the context of text data and performs appropriate text conversion.

[0551] "Augmented reality display" is a technology that displays digital information superimposed on the real world.

[0552] The system that realizes this application example consists of three main components: the terminal (AR glasses), the server, and the user.

[0553] Device (AR glasses)

[0554] The device includes the following elements:

[0555] Acoustic input means: This is a high-performance microphone that captures surrounding sounds. For example, when a store clerk explains a product, the microphone captures that sound.

[0556] Communication means: A communication module is built in to transmit captured audio data to a server in real time.

[0557] Visual display means: The system is equipped with an augmented reality display to display the text data received from the server in the user's field of vision. Through this display, the user can visually recognize the captured voice as text.

[0558] server

[0559] The server includes the following elements:

[0560] Speech recognition means: The received voice data is converted into text data by a speech recognition engine. This engine is capable of highly accurate speech recognition and contextual analysis.

[0561] Pre-processing means: Processes the received voice data and performs noise reduction and sound quality adjustment, which results in more accurate text conversion.

[0562] Communication method: Responsible for sending the converted text data to the terminal. This data is sent in real time, so the text is displayed without delay.

[0563] Example

[0564] Scenario: Ordering at a restaurant

[0565] 1. Audio capture via acoustic input means:

[0566] The device's microphone captures the voice of the waiter saying, "Today's recommendation is steak."

[0567] 2. Transmission of audio data by means of communication:

[0568] The captured audio data is transmitted to the server in real time via the terminal's communication module.

[0569] 3. Text conversion by speech recognition means:

[0570] The voice data is received on the server and converted into text data such as "Today's recommendation is steak" using a speech recognition engine. Contextual analysis is also performed, reducing the chance of misrecognition.

[0571] 4. Text data transmission and visual display:

[0572] The converted text data is sent to the terminal and displayed on the terminal's augmented reality display, allowing the user to understand the voice of the store clerk.

[0573] Hardware / Software used

[0574] Hardware:

[0575] High-performance microphone (for voice capture)

[0576] AR glasses (for displaying text)

[0577] software:

[0578] Python, socket, speech_recognition

[0579] Socket communication is used for communication between the server and the client

[0580] Prompt Sentence Examples

[0581] Below is an example of a prompt sentence to be input to the generative AI model.

[0582] I want to build an application that uses voice capture and text conversion to help hearing-impaired people understand when ordering at a restaurant. I want to create a system that converts the voice of a waiter saying, "Today's recommendation is steak," into text and displays it on the AR glasses.

[0583] As a result, this invention allows hearing-impaired people to visually understand audio information in real time in physical stores. Users can receive support by reading the text displayed on the AR glasses.

[0584] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0585] Step 1:

[0586] The device captures the surrounding sound using a high-performance microphone. Specifically, the microphone receives the sound as an analog signal and converts it into a digital signal. The input is the surrounding sound, and the output is digital sound data.

[0587] Step 2:

[0588] The terminal transmits the captured digital audio data to the server in real time via the communication module. The specific operations performed here are to generate data packets and transmit them over the network. The input is the digital audio data, and the output is the data packets transmitted to the server.

[0589] Step 3:

[0590] The server performs noise reduction on the received digital audio data using a pre-processing means. Specifically, it applies a noise filtering algorithm to remove unwanted noise from the audio data. The input is the received digital audio data, and the output is the clean audio data after noise reduction.

[0591] Step 4:

[0592] The server uses a speech recognition means to convert the noise-reduced speech data into text data. Specifically, a speech recognition engine analyzes the speech signal and generates corresponding text. The input is the clean speech data, and the output is the converted text data.

[0593] Step 5:

[0594] The server transmits the converted text data to the terminal via a communication means. Specific operations include packetizing the text data and transmitting it over a network. The input is the text data, and the output is the data transmitted to the terminal.

[0595] Step 6:

[0596] The terminal displays the received text data in the user's field of view using a visual display means. Specifically, the augmented reality display visualizes the text data and displays it to the user in real time. The input is the text data received from the server, and the output is the text displayed in the user's field of view.

[0597] 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.

[0598] The present invention is an AR glasses system for supporting the hearing impaired, and by adding the functionality of an emotion engine, it can recognize the user's emotions. A specific example of this is shown below.

[0599] System configuration

[0600] This system consists of four main components: the terminal (AR glasses), the server, the user, and the emotion engine.

[0601] Terminal

[0602] Audio input method: The AR glasses worn by the user are equipped with a high-performance microphone that captures surrounding sounds.

[0603] Transmission means: A communication module is built in to transmit captured audio data to a server in real time.

[0604] Display means: An augmented reality display is installed to display the text data received from the server and emotion recognition results in the user's field of vision.

[0605] server

[0606] Speech recognition means: The server converts the received voice data into text data using a speech recognition engine. This engine is capable of highly accurate speech recognition and contextual analysis.

[0607] Pre-processing means: The server processes the received audio data and performs noise reduction and sound quality adjustment.

[0608] Text transmission means: Transmits the converted text data to the terminal in real time.

[0609] Emotion Engine

[0610] Emotion recognition means: The emotion engine installed on the server recognizes the user's emotions based on voice data and facial expression data.

[0611] Emotion display means: Recognized emotion data is sent to the terminal and visually presented to the user via the display means.

[0612] Specific examples

[0613] Scenario: Conversation in a cafe

[0614] 1. Voice Input

[0615] Consider a scenario where a user is having a conversation with a friend at a cafe, and the device's microphone captures what the friend says, for example, "Hi, how was your day?"

[0616] 2. Sending audio data

[0617] The device preprocesses the captured audio data, removes noise, compresses it, and sends it to the server in real time.

[0618] 3. Converting Audio Data to Text

[0619] The server converts the received voice data into text data using a voice recognition engine. Specifically, the voice data "Hello, how was your day?" is converted directly into text data.

[0620] 4. Emotion recognition

[0621] The server's emotion engine analyzes the voice and facial expression data to recognize the emotion contained in the friend's speech. For example, if the friend speaks in a happy tone, the emotion "happy" is recognized.

[0622] 5. Sending text data and emotion data

[0623] The server formats the converted text data and the recognized emotion data and sends them to the device. The text "Hello, how was your day?" and the emotion data "I'm happy" are sent.

[0624] 6. Text and Emotion Display

[0625] The device displays the received text and emotion data on the AR glasses' display, providing it to the user's field of vision. The user's field of vision displays the message "Hello, how was your day?" along with the friend's emotion, "Happy."

[0626] User Experience

[0627] This system allows users to visually understand the surrounding voices in real time, while also recognizing the speaker's emotions. By reading the text and emotional information displayed in the AR glasses, users can grasp not only the voice but also the emotional nuances. This will enable hearing-impaired people to have richer communication in their daily lives.

[0628] As described above, the present invention is an extremely useful support tool for the hearing impaired, supporting real-time communication and enabling visual understanding of the emotions of the other party.

[0629] The processing flow will be explained below.

[0630] Step 1:

[0631] The device activates the microphone in response to user operation and captures surrounding sounds. For example, if a user is talking with a friend at a cafe, the microphone will collect the friend's words, "Hello, how was your day?"

[0632] Step 2:

[0633] The device performs preprocessing such as noise reduction on the captured voice data. The device eliminates environmental noise and improves the quality of the voice data, thereby improving the accuracy of voice recognition.

[0634] Step 3:

[0635] The terminal compresses the pre-processed voice data and converts it into a format for transmission. By reducing the data size, communication efficiency is improved.

[0636] Step 4:

[0637] The device transmits the compressed audio data to the server in real time over a network, for example, using Wi-Fi or mobile data communication.

[0638] Step 5:

[0639] The server receives the voice data sent from the device and prepares to analyze the received data.

[0640] Step 6:

[0641] The server runs the received voice data through a voice recognition engine and converts it into text data. For example, voice data such as "Hello, how was your day?" is converted into text such as "Hello, how was your day?"

[0642] Step 7:

[0643] The server performs contextual analysis on the text data, processing it to more accurately understand the meaning and intent of the utterance.

[0644] Step 8:

[0645] The server sends voice and facial expression data to the emotion engine for emotion recognition. For example, it analyzes a friend's tone of voice and facial expression to recognize emotions such as "happiness" or "fun."

[0646] Step 9:

[0647] The server formats the converted text data and the recognized emotion data and sends them to the device. The text "Hello, how was your day?" and the emotion data "I'm happy" are sent to the device.

[0648] Step 10:

[0649] The device receives the text data and emotion data sent from the server and prepares to display the received data.

[0650] Step 11:

[0651] The device then formats and displays the received text and emotion data on the AR glasses' display. The user's field of vision is displayed with the text "Hello, how was your day?" along with a pictogram or icon representing the emotion "happy."

[0652] These steps allow users to visually understand what is being said around them in real time as text, while also visually recognizing the speaker's emotions. This allows hearing-impaired people to grasp not only the nuances of speech but also the emotional nuances, enabling smoother communication.

[0653] Example 2

[0654] 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."

[0655] In everyday life, people with hearing impairments often find it difficult to understand the sounds around them and experience difficulties in communication. It is particularly important for them to understand not only the sound but also the speaker's emotions. However, previous technologies lacked the means to accurately recognize sounds and emotions in real time and to visually present them. The present invention aims to solve these problems and provide a system that enables people with hearing impairments to understand the sounds around them and the speaker's emotions in real time.

[0656] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0657] In this invention, the server includes an input means for capturing surrounding sounds, a transmission means for transmitting the captured sound data via a network, a conversion means for converting the received sound data into text data, and an emotion display means for displaying recognized emotion data, thereby enabling hearing-impaired people to visually understand surrounding sounds in real time and simultaneously recognize the emotions of the speaker.

[0658] "Input means" refers to devices and sensors for capturing ambient sound.

[0659] The "transmission means" refers to a communication module for transmitting the captured audio data to a server or the like via a network.

[0660] "Conversion means" refers to a voice recognition engine or software for converting received voice data into text data.

[0661] "Display means" refers to a display or projector for visually displaying the converted text data.

[0662] "Recognition means" refers to an algorithm or program for analyzing received voice data and facial expression data to recognize emotions.

[0663] "Emotion display means" refers to a module or display for visually presenting recognized emotion data.

[0664] "Preprocessing means" refers to filtering techniques and algorithms used to process audio data and perform noise reduction.

[0665] "Context analysis" refers to the process performed by a speech recognition means to understand the context of speech data and analyze it appropriately.

[0666] This invention proposes an AR glasses system to support the hearing impaired, which can visually present voice and the speaker's emotions in real time using an emotion engine. This system consists of four main entities: a terminal (AR glasses), a server, a user, and an emotion engine.

[0667] Terminal

[0668] The device is equipped with a high-performance microphone, a communication module, and an augmented reality display. Specifically, the following hardware and software are used:

[0669] Voice input: A high-performance microphone captures the surrounding sounds, for example, recording someone saying "Hello, how was your day?" in a cafe.

[0670] Transmission means: A Wi-Fi or mobile network communication module is built in to transmit captured audio data to a server in real time.

[0671] Display means: An augmented reality display is installed to display the text data and emotion data sent from the server in the user's field of vision.

[0672] server

[0673] The server is equipped with a speech recognition engine for processing voice data and converting it into text data, and an emotion engine for analyzing emotions. Specifically, the following processes are performed:

[0674] Speech recognition means: The server converts the received voice data into text data using a high-precision voice recognition engine (e.g., general voice recognition software).

[0675] Pre-processing method: Pre-process the audio data to reduce noise. Noise filtering techniques are used in this process.

[0676] Recognition means: The emotion engine analyzes voice data and, if necessary, facial expression data to recognize the user's emotions.

[0677] Text transmission method: The converted text data and emotion data are formatted and sent to the device.

[0678] Emotion Engine

[0679] The emotion engine analyzes the received voice and facial expression data to recognize the speaker's emotions. For example, it analyzes emotions such as "happy" or "sad" contained in a friend's speech.

[0680] User Experience

[0681] By wearing the AR glasses, users can visually understand the surrounding sounds in real time and simultaneously recognize the speaker's emotions, enabling hearing-impaired people to achieve richer communication in their daily lives.

[0682] Specific examples

[0683] Scenario: Conversation in a cafe

[0684] 1. Voice Input: Imagine a user is having a conversation with a friend at a cafe, and the device's microphone captures the friend saying, "Hello, how was your day?"

[0685] 2. Sending audio data: The device preprocesses the recorded audio data, removes noise, compresses it, and sends it to the server in real time.

[0686] 3. Converting voice data to text: The server analyzes the voice data received by the server using a voice recognition engine and converts it into text data. For example, the voice data "Hello, how was your day?" is converted into text.

[0687] 4. Emotion recognition: The server's emotion engine analyzes the voice and facial expression data to recognize the speaker's emotions. For example, if the speaker speaks in a happy tone, it will recognize the emotion as "happy."

[0688] 5. Sending text data and emotion data: The server sends the converted text data and the recognized emotion data to the device. The text "Hello, how was your day?" and the emotion data "I'm happy" are sent.

[0689] 6. Text and emotion display: The device displays the received text and emotion data on the AR glasses display and provides it to the user's field of view. The user's field of view will display the text "Hello, how was your day?" along with the friend's emotion "Happy."

[0690] Prompt Sentence Examples

[0691] Example prompts to input to a generative AI model:

[0692] "Please explain a system that uses an emotion engine to analyze a conversation with a friend, such as 'Hi, how was your day?', convert the speech to text, and recognize and display the emotion."

[0693] As described above, the system of the present invention is a very useful support tool for the hearing impaired, enabling them to visually understand speech and emotions in real time.

[0694] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0695] Step 1:

[0696] Audio input and preprocessing (terminal)

[0697] The device's high-performance microphone captures the surrounding audio. The input here is the surrounding audio, specifically a friend saying, "Hello, how was your day?" The captured audio data is passed through an internal noise reduction filter to remove noise and pre-process it into clear audio data. The output is high-quality audio data with noise removed.

[0698] Step 2:

[0699] Sending audio data (terminal)

[0700] The device sends the preprocessed audio data to the server in real time, where the input is the preprocessed audio data from step 1, sent to the server via Wi-Fi or mobile network, and the output is the audio data sent to the server.

[0701] Step 3:

[0702] Receiving and preprocessing audio data (server)

[0703] The server receives the audio data sent from the device. The input here is the audio data sent from the device, and the server performs additional noise reduction and sound quality adjustments. The output is the optimized audio data.

[0704] Step 4:

[0705] Speech recognition and text conversion (server)

[0706] The server analyzes the received voice data using a voice recognition engine and converts it into text data. The input here is the voice data optimized in step 3, specifically the voice data "Hello, how was your day?" that is converted into text. The output is text data.

[0707] Step 5:

[0708] Emotion recognition (server)

[0709] The server's emotion engine analyzes the voice data and facial expression data to recognize the speaker's emotions. The input here is the text data obtained in step 4 and information such as the tone, pace, and strength of the voice. For example, if the tone sounds happy, the emotion "happy" is recognized. The output is the recognized emotion data.

[0710] Step 6:

[0711] Sending text data and emotion data (server)

[0712] The server formats the converted text data and the recognized emotion data and sends them to the terminal. The input here is the text data obtained in step 4 and the emotion data recognized in step 5, which are appropriately formatted and sent to the terminal. The output is the text data and emotion data sent to the terminal.

[0713] Step 7:

[0714] Text display and emotion display (terminal)

[0715] The device displays the received text data and emotion data on the display of the AR glasses. The input here is the text and emotion data sent from the server in step 6, and the text "Hello, how was your day?" and the emotion "happy" are displayed in the user's field of view. The output is the visualized text and emotion data.

[0716] Step 8:

[0717] Information Awareness (User)

[0718] The user visually understands the displayed text and emotional information through the AR glasses. The input here is the text and emotional data displayed in step 7, and the user recognizes this information to understand the words and emotions of their friend. The output is the user's understanding and recognition.

[0719] (Application example 2)

[0720] 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."

[0721] Conventional speech recognition systems were able to convert voice data into text, but they were unable to recognize the speaker's emotions and display them visually. This made it difficult for hearing-impaired people to understand the conversations and emotions around them in real time. In brick-and-mortar stores in particular, it is important to simultaneously understand the language and emotional information of customer service staff, and this aspect needed to be improved.

[0722] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0723] In this invention, the server includes an audio input means for capturing surrounding sounds, a communication means for transmitting the captured sound data via a network, a voice recognition means for converting the received sound data into text data, and a visual display means for displaying the converted text data and the recognized emotion data in the user's field of view, thereby enabling hearing-impaired people to visually understand the linguistic information and emotion information of customer service staff simultaneously in real time in a brick-and-mortar store.

[0724] An "audio input means" is a device for capturing ambient sounds.

[0725] A "communication means" is a device for transmitting captured audio data over a network.

[0726] The "voice recognition means" is a device for converting received voice data into text data.

[0727] The "visual display means" is a device for displaying the converted text data and the recognized emotion data in the user's field of vision.

[0728] The "preprocessing means" is a device for preprocessing audio data to perform noise reduction.

[0729] The "emotion recognition means" is a device that analyzes voice and facial expression data to recognize emotions.

[0730] "Context analysis" is an analysis method that allows a speech recognition means to understand the meaning and intent of speech data.

[0731] This invention is a system for supporting hearing-impaired people, specifically implemented as a customer service support application in a brick-and-mortar store. The system includes a terminal, a server, and an emotion recognition engine. A specific example of the system is described below.

[0732] System configuration

[0733] Terminal

[0734] Acoustic input means: The device is equipped with a high-performance microphone to capture surrounding sounds. This microphone captures conversations in the physical store in real time.

[0735] Communication means: A communication module is built in to transmit captured audio data to a server via a network.

[0736] Visual display means: An augmented reality display is provided to display the converted text data and recognized emotion data in the user's field of vision.

[0737] server

[0738] Pre-processing means: The server performs pre-processing on the received audio data to reduce noise and adjust the sound quality.

[0739] Speech recognition means: The preprocessed speech data is converted into highly accurate text data using a speech recognition engine.

[0740] Emotion recognition means: Equipped with an emotion engine that analyzes received voice data and facial expression data to recognize the speaker's emotions.

[0741] User Experience

[0742] Using this system, hearing-impaired people can understand conversations with customer service staff in real time in a physical store. Specific examples include the following scenario:

[0743] Scenario: Conversation in a brick-and-mortar store

[0744] Voice input: A customer asks a staff member at a brick-and-mortar cafe, "What would you recommend about this cake?"

[0745] Audio data transmission: The device preprocesses the captured audio data to remove noise and transmits it to the server in real time.

[0746] Conversion of voice data to text: The voice data received by the server is converted into text data using a voice recognition engine, such as "What do you recommend about this cake?"

[0747] Emotion recognition: The server's emotion recognition engine analyzes the voice data and facial expression data to recognize the questioner's emotion of interest.

[0748] Sending text data and emotion data: The server sends the converted text data and emotion data to the terminal. The text "What do you recommend about this cake?" and the emotion data "I'm interested" are sent.

[0749] Text display and emotion display: The device displays the received text and emotion data on the AR glasses display, displaying "What do you recommend about this cake?" and "Interested" in the user's field of vision.

[0750] Hardware and software used

[0751] Hardware: Devices with high-performance microphones, communication modules, and augmented reality displays (e.g., AR glasses).

[0752] Software: High-precision speech recognition engines (e.g., Google Speech Recognition API), emotion recognition engines (e.g., the sentiment analysis pipeline in the transformers library), and communication libraries (e.g., requests).

[0753] Prompt Sentence Examples

[0754] Text: "Chocolate cake is recommended today!"

[0755] Emotion: "Fun"

[0756] This will make it easier for hearing-impaired people to understand customer service in physical stores and facilitate smooth communication.

[0757] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0758] Step 1:

[0759] When a user starts a conversation with a customer service staff member in a physical store, the device's audio input means captures the voice. The input is the conversational voice occurring in the physical store, and the output is the captured voice data. The device uses a high-performance microphone to detect surrounding sounds and record them as digital voice data.

[0760] Step 2:

[0761] The device sends the captured audio data to the server via a communication means. The input is the audio data obtained in step 1, and the output is the audio data sent via the network. The device uses a built-in communication module (such as Wi-Fi or Bluetooth) to send the data to the server in real time.

[0762] Step 3:

[0763] The server uses preprocessing means to reduce noise and adjust the sound quality of the received audio data. The input is the audio data sent from the terminal, and the output is the preprocessed audio data. The server uses DSP (Digital Signal Processing) technology to remove environmental noise from the audio data and create clear audio data.

[0764] Step 4:

[0765] The server converts the preprocessed voice data into text data using a speech recognition tool. The input is the preprocessed voice data, and the output is text data. The server converts the voice data into corresponding text using a high-precision speech recognition engine such as the Google Speech Recognition API.

[0766] Step 5:

[0767] The server analyzes the text data and voice data generated by the speech recognition means using the emotion recognition means to recognize the speaker's emotions. The input is the converted text data and voice data, and the output is the text data and emotion data. The server uses the emotion analysis pipeline of the transformers library to detect emotional elements in the text data.

[0768] Step 6:

[0769] The server transmits the converted text data and emotion data to the terminal via a communication means. The input is the text data and emotion data that are the results of the speech recognition and emotion recognition, and the output is data transmitted via a network. The server packages this data and transmits it to the terminal in real time.

[0770] Step 7:

[0771] The terminal displays the received text data and emotion data in the user's field of view using a visual display means. The input is the text data and emotion data sent from the server, and the output is the information displayed on the visual display of the AR glasses. Specifically, the terminal uses the augmented reality display to display the information "What do you recommend about this cake?" and "Interested" in the user's field of view.

[0772] Through these steps, hearing-impaired people can understand the content and emotions of conversations with store staff in real time, greatly improving the user's communication experience.

[0773] 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.

[0774] 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.

[0775] 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.

[0776] [Third embodiment]

[0777] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0778] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0779] 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).

[0780] 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.

[0781] 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.

[0782] 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).

[0783] 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.

[0784] 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.

[0785] 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.

[0786] 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.

[0787] 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.

[0788] 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."

[0789] The present invention is an AR glasses system for supporting the hearing impaired. A specific example of the system is described below.

[0790] System configuration

[0791] This system consists of three main components: the terminal (AR glasses), the server, and the user.

[0792] Terminal

[0793] Audio input method: The AR glasses worn by the user are equipped with a high-performance microphone that captures surrounding sounds.

[0794] Transmission means: A communication module is built in to transmit captured audio data to a server in real time.

[0795] Display means: An augmented reality display is installed to display the text data received from the server in the user's field of vision.

[0796] server

[0797] Speech recognition means: The server converts the received voice data into text data using a speech recognition engine. This engine is capable of highly accurate speech recognition and contextual analysis.

[0798] Pre-processing means: The server processes the received audio data and performs noise reduction and sound quality adjustment.

[0799] Text transmission means: Transmits the converted text data to the terminal in real time.

[0800] Specific examples

[0801] Scenario: Conversation in a cafe

[0802] 1. Voice Input

[0803] Consider a scenario where a user is having a conversation with a friend at a cafe, and the device's microphone captures what the friend says, for example, "Hi, how was your day?"

[0804] 2. Sending audio data

[0805] The audio data captured by the device is compressed, preprocessed using noise reduction and other techniques, and then sent to the server in real time.

[0806] 3. Converting Audio Data to Text

[0807] The server converts the received voice data into text data using a voice recognition engine. Specifically, the voice data "Hello, how was your day?" is converted directly into text data.

[0808] 4. Sending text data

[0809] The server formats the converted text data and sends it to the terminal.

[0810] 5. Text Display

[0811] The device displays the received text data on the AR glasses' display, and the text "Hello, how was your day?" appears in the user's field of vision.

[0812] User Experience

[0813] This system allows users to visually understand the sounds around them in real time. Users can obtain audio information by reading the text displayed on the AR glasses. This will enable the hearing impaired to communicate more smoothly in their daily lives.

[0814] As described above, the present invention is a very useful support tool for the hearing impaired, supporting real-time communication.

[0815] The processing flow will be explained below.

[0816] Step 1:

[0817] The device activates the microphone in response to user operation and captures surrounding sounds. For example, if a user is talking to a friend at a cafe, the microphone will collect the friend's utterance of "hello."

[0818] Step 2:

[0819] The device performs preprocessing such as noise reduction on the captured voice data. The device eliminates environmental noise and improves the quality of the voice data, thereby improving the accuracy of voice recognition.

[0820] Step 3:

[0821] The terminal compresses the pre-processed voice data and converts it into a format for transmission. By reducing the data size, communication efficiency is improved.

[0822] Step 4:

[0823] The device transmits the compressed audio data to the server in real time over a network, for example, using Wi-Fi or mobile data communication.

[0824] Step 5:

[0825] The server receives the voice data sent from the device and prepares to analyze the received data.

[0826] Step 6:

[0827] The server runs the received voice data through a voice recognition engine and converts it into text data. For example, voice data saying "hello" is converted into the text "hello."

[0828] Step 7:

[0829] The server performs contextual analysis on the generated text data, which allows for a more accurate understanding of the meaning and intent of the speech.

[0830] Step 8:

[0831] The server sends the formatted text data to the terminal in real time. For example, the text "Hello" is sent to the terminal.

[0832] Step 9:

[0833] The terminal receives the text data sent from the server and prepares to display the received data.

[0834] Step 10:

[0835] The device formats and displays the received text on the AR glasses' display, and the word "Hello" appears in the user's field of vision.

[0836] This process allows users to visually understand what is being said around them as text in real time, which helps hearing-impaired users to communicate more smoothly with others.

[0837] Example 1

[0838] 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."

[0839] The purpose of this invention is to provide a support tool for the hearing impaired to facilitate smooth communication in daily life, in particular to enable them to efficiently understand auditory information by visualizing surrounding sounds as text in real time.

[0840] 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.

[0841] In this invention, the server includes a speech recognition unit that converts received speech data into text data using a highly accurate speech recognition engine, a preprocessing unit that preprocesses the speech data to perform noise reduction, and a context analysis unit that performs context analysis, thereby enabling accurate text conversion and display in real time.

[0842] "Audio input means" is a device for capturing ambient sounds.

[0843] The "transmission means" is a device or function for transmitting the captured audio data over a network.

[0844] The "voice recognition means" is a device or function for converting received voice data into text data using a highly accurate voice recognition engine.

[0845] A "display means" is a device or function including an augmented reality display for displaying the converted text data in real time in the user's field of view.

[0846] The "preprocessing means" is a device or function for preprocessing audio data to perform noise reduction.

[0847] "Context analysis" is an analytical process performed by a speech recognition means to understand the context of speech data and achieve more accurate text conversion.

[0848] This invention is an AR glasses system for supporting the hearing impaired. This system consists of three main components: AR glasses (terminals) worn by the user, a remote server, and the user.

[0849] Terminal

[0850] Voice input methods:

[0851] The AR glasses worn by users are equipped with high-performance microphones that capture the sounds of the surrounding environment. For example, when you are talking with a friend in a public place such as a cafe, the microphones pick up what your friend is saying.

[0852] Transmission method:

[0853] The captured audio data is transmitted in real time to a server using a communication module built into the device, which uses Wi-Fi or Bluetooth and undergoes noise reduction before transmission.

[0854] Display means:

[0855] The text data received from the server is displayed on the augmented reality display of the AR glasses. Specifically, the text pops up in the user's field of vision, allowing them to visually understand the audio information.

[0856] server

[0857] Voice recognition methods:

[0858] The server converts the received voice data into text data using a highly accurate voice recognition engine (e.g., a general-purpose voice recognition engine), which uses phonological algorithms to analyze the voice data and convert it into appropriate text.

[0859] Pretreatment methods:

[0860] The server preprocesses the audio data, reducing noise and adjusting the audio quality, allowing the speech recognition engine to convert speech to text more accurately.

[0861] Texting methods:

[0862] The converted text data is then formatted and sent immediately to the device. This involves removing extra spaces and adding necessary punctuation. Specifically, a Python script is used to convert the text data into JSON format and send it to the device via an HTTP request.

[0863] User Experience

[0864] This system allows users to visually understand the sounds around them in real time. For example, during a meeting, users can instantly read what their colleagues are saying as text using AR glasses. This will enable the hearing impaired to communicate more smoothly in their daily lives.

[0865] Specific examples

[0866] Scenario: Conversation in a cafe

[0867] 1. Voice Input

[0868] A user is talking to a friend at a cafe, and the device's microphone captures the friend saying, "Hello, how was your day?"

[0869] 2. Sending audio data

[0870] The device transmits the captured audio data to the server in real time, with noise reduction performed during transmission.

[0871] 3. Converting Audio Data to Text

[0872] The server receives the voice data and converts it into text data such as "Hello, how was your day?" using a general-purpose voice recognition engine.

[0873] 4. Sending text data

[0874] The server formats the converted text data using a Python script and sends it to the terminal.

[0875] 5. Text Display

[0876] The text data received by the device is displayed on the AR glasses' display, and the text "Hello, how was your day?" is displayed in the user's field of vision.

[0877] Prompt Sentence Examples

[0878] "Create a program that displays what your friend is saying in real time on your AR glasses."

[0879] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0880] Step 1:

[0881] Voice input

[0882] Device:

[0883] Input: A situation where a user wears AR glasses and recognizes surrounding sounds.

[0884] How it works: High-performance microphones built into the AR glasses capture surrounding sounds.

[0885] Output: Audio data captured by the microphone.

[0886] Data processing: Convert into digital format as an audio signal.

[0887] Step 2:

[0888] Sending audio data

[0889] Device:

[0890] Input: Audio data captured by a high-quality microphone.

[0891] How it works: The device's communication module transmits audio data to the server in real time, then performs noise reduction and compresses the data to an optimal format (e.g., MP3) before transmission.

[0892] Output: Filtered compressed audio data.

[0893] Data processing: Noise reduction and compression of audio data.

[0894] Step 3:

[0895] Converting audio data to text

[0896] server:

[0897] Input: Audio data sent from the device.

[0898] Specific operation: The server converts the received voice data into text data using a highly accurate voice recognition engine. A general-purpose voice recognition engine is used to analyze the data using a phonological algorithm.

[0899] Output: The converted text data.

[0900] Data processing: Converting voice data to text.

[0901] Step 4:

[0902] Preprocessing and sending text data

[0903] server:

[0904] Input: Text data converted by the speech recognition engine.

[0905] What it does: Formats the text data, removing extra spaces and adding necessary punctuation, converting it to JSON format using a Python script, and then sending it to the device via an HTTP request.

[0906] Output: Formatted and converted text data.

[0907] Data processing: Formatting text data and converting it to JSON format.

[0908] Step 5:

[0909] Text Display

[0910] Device:

[0911] Input: Formatted and converted text data sent from the server.

[0912] Specific operation: The device displays the received text data on the augmented reality display of the AR glasses. The text pops up in the user's field of view.

[0913] Output: The displayed text information.

[0914] Data processing: Converting text data into visual information.

[0915] (Application example 1)

[0916] 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."

[0917] Conventional communication support systems for the hearing impaired have limitations in their speech-to-text conversion capabilities, making it difficult to handle noise and complex speech contexts when used in physical store environments. Furthermore, the lack of real-time speech recognition and text display hinders smooth communication. Furthermore, there is a lack of technology that allows users to visually interpret information in a natural, unobtrusive way.

[0918] 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.

[0919] In this invention, the server includes an audio input means for capturing surrounding sounds, a communication means for transmitting the captured sound data via a network, a speech recognition means for converting the received sound data into text data, a preprocessing means for preprocessing the received sound data in real time and performing noise reduction, and a visual display means for displaying the converted text data on an augmented reality display. This allows hearing-impaired people to enjoy smooth and comfortable communication in physical stores, and enables real-time speech recognition and visual text display.

[0920] An "acoustic input means" is a device used to capture ambient sound.

[0921] "Communication means" refers to the device or technology used to transmit the captured audio data over a network.

[0922] "Speech recognition means" refers to a device or technology for converting received voice data into text data.

[0923] A "visual display means" is a device or technique for displaying the converted text data on an augmented reality display.

[0924] The "preprocessing means" refers to a device or technology for preprocessing received audio data in real time and performing noise reduction.

[0925] An "information processing system" is a comprehensive system that combines multiple means to process and display specific information.

[0926] A "brick and mortar store" is a commercial or service establishment that exists in a physical location.

[0927] "Context analysis" is a technology in which a speech recognition means understands the context of text data and performs appropriate text conversion.

[0928] "Augmented reality display" is a technology that displays digital information superimposed on the real world.

[0929] The system that realizes this application example consists of three main components: the terminal (AR glasses), the server, and the user.

[0930] Device (AR glasses)

[0931] The device includes the following elements:

[0932] Acoustic input means: This is a high-performance microphone that captures surrounding sounds. For example, when a store clerk explains a product, the microphone captures that sound.

[0933] Communication means: A communication module is built in to transmit captured audio data to a server in real time.

[0934] Visual display means: The system is equipped with an augmented reality display to display the text data received from the server in the user's field of vision. Through this display, the user can visually recognize the captured voice as text.

[0935] server

[0936] The server includes the following elements:

[0937] Speech recognition means: The received voice data is converted into text data by a speech recognition engine. This engine is capable of highly accurate speech recognition and contextual analysis.

[0938] Pre-processing means: Processes the received voice data and performs noise reduction and sound quality adjustment, which results in more accurate text conversion.

[0939] Communication method: Responsible for sending the converted text data to the terminal. This data is sent in real time, so the text is displayed without delay.

[0940] Example

[0941] Scenario: Ordering at a restaurant

[0942] 1. Audio capture via acoustic input means:

[0943] The device's microphone captures the voice of the waiter saying, "Today's recommendation is steak."

[0944] 2. Transmission of audio data by means of communication:

[0945] The captured audio data is transmitted to the server in real time via the terminal's communication module.

[0946] 3. Text conversion by speech recognition means:

[0947] The voice data is received on the server and converted into text data such as "Today's recommendation is steak" using a speech recognition engine. Contextual analysis is also performed, reducing the chance of misrecognition.

[0948] 4. Text data transmission and visual display:

[0949] The converted text data is sent to the terminal and displayed on the terminal's augmented reality display, allowing the user to understand the voice of the store clerk.

[0950] Hardware / Software used

[0951] Hardware:

[0952] High-performance microphone (for voice capture)

[0953] AR glasses (for displaying text)

[0954] software:

[0955] Python, socket, speech_recognition

[0956] Socket communication is used for communication between the server and the client

[0957] Prompt Sentence Examples

[0958] Below is an example of a prompt sentence to be input to the generative AI model.

[0959] I want to build an application that uses voice capture and text conversion to help hearing-impaired people understand when ordering at a restaurant. I want to create a system that converts the voice of a waiter saying, "Today's recommendation is steak," into text and displays it on the AR glasses.

[0960] As a result, this invention allows hearing-impaired people to visually understand audio information in real time in physical stores. Users can receive support by reading the text displayed on the AR glasses.

[0961] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0962] Step 1:

[0963] The device captures the surrounding sound using a high-performance microphone. Specifically, the microphone receives the sound as an analog signal and converts it into a digital signal. The input is the surrounding sound, and the output is digital sound data.

[0964] Step 2:

[0965] The terminal transmits the captured digital audio data to the server in real time via the communication module. The specific operations performed here are to generate data packets and transmit them over the network. The input is the digital audio data, and the output is the data packets transmitted to the server.

[0966] Step 3:

[0967] The server performs noise reduction on the received digital audio data using a pre-processing means. Specifically, it applies a noise filtering algorithm to remove unwanted noise from the audio data. The input is the received digital audio data, and the output is the clean audio data after noise reduction.

[0968] Step 4:

[0969] The server uses a speech recognition means to convert the noise-reduced speech data into text data. Specifically, a speech recognition engine analyzes the speech signal and generates corresponding text. The input is the clean speech data, and the output is the converted text data.

[0970] Step 5:

[0971] The server transmits the converted text data to the terminal via a communication means. Specific operations include packetizing the text data and transmitting it over a network. The input is the text data, and the output is the data transmitted to the terminal.

[0972] Step 6:

[0973] The terminal displays the received text data in the user's field of view using a visual display means. Specifically, the augmented reality display visualizes the text data and displays it to the user in real time. The input is the text data received from the server, and the output is the text displayed in the user's field of view.

[0974] 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.

[0975] The present invention is an AR glasses system for supporting the hearing impaired, and by adding the functionality of an emotion engine, it can recognize the user's emotions. A specific example of this is shown below.

[0976] System configuration

[0977] This system consists of four main components: the terminal (AR glasses), the server, the user, and the emotion engine.

[0978] Terminal

[0979] Audio input method: The AR glasses worn by the user are equipped with a high-performance microphone that captures surrounding sounds.

[0980] Transmission means: A communication module is built in to transmit captured audio data to a server in real time.

[0981] Display means: An augmented reality display is installed to display the text data received from the server and emotion recognition results in the user's field of vision.

[0982] server

[0983] Speech recognition means: The server converts the received voice data into text data using a speech recognition engine. This engine is capable of highly accurate speech recognition and contextual analysis.

[0984] Pre-processing means: The server processes the received audio data and performs noise reduction and sound quality adjustment.

[0985] Text transmission means: Transmits the converted text data to the terminal in real time.

[0986] Emotion Engine

[0987] Emotion recognition means: The emotion engine installed on the server recognizes the user's emotions based on voice data and facial expression data.

[0988] Emotion display means: Recognized emotion data is sent to the terminal and visually presented to the user via the display means.

[0989] Specific examples

[0990] Scenario: Conversation in a cafe

[0991] 1. Voice Input

[0992] Consider a scenario where a user is having a conversation with a friend at a cafe, and the device's microphone captures what the friend says, for example, "Hi, how was your day?"

[0993] 2. Sending audio data

[0994] The device preprocesses the captured audio data, removes noise, compresses it, and sends it to the server in real time.

[0995] 3. Converting Audio Data to Text

[0996] The server converts the received voice data into text data using a voice recognition engine. Specifically, the voice data "Hello, how was your day?" is converted directly into text data.

[0997] 4. Emotion recognition

[0998] The server's emotion engine analyzes the voice and facial expression data to recognize the emotion contained in the friend's speech. For example, if the friend speaks in a happy tone, the emotion "happy" is recognized.

[0999] 5. Sending text data and emotion data

[1000] The server formats the converted text data and the recognized emotion data and sends them to the device. The text "Hello, how was your day?" and the emotion data "I'm happy" are sent.

[1001] 6. Text and Emotion Display

[1002] The device displays the received text and emotion data on the AR glasses' display, providing it to the user's field of vision. The user's field of vision displays the message "Hello, how was your day?" along with the friend's emotion, "Happy."

[1003] User Experience

[1004] This system allows users to visually understand the surrounding voices in real time, while also recognizing the speaker's emotions. By reading the text and emotional information displayed in the AR glasses, users can grasp not only the voice but also the emotional nuances. This will enable hearing-impaired people to have richer communication in their daily lives.

[1005] As described above, the present invention is an extremely useful support tool for the hearing impaired, supporting real-time communication and enabling visual understanding of the emotions of the other party.

[1006] The processing flow will be explained below.

[1007] Step 1:

[1008] The device activates the microphone in response to user operation and captures surrounding sounds. For example, if a user is talking with a friend at a cafe, the microphone will collect the friend's words, "Hello, how was your day?"

[1009] Step 2:

[1010] The device performs preprocessing such as noise reduction on the captured voice data. The device eliminates environmental noise and improves the quality of the voice data, thereby improving the accuracy of voice recognition.

[1011] Step 3:

[1012] The terminal compresses the pre-processed voice data and converts it into a format for transmission. By reducing the data size, communication efficiency is improved.

[1013] Step 4:

[1014] The device transmits the compressed audio data to the server in real time over a network, for example, using Wi-Fi or mobile data communication.

[1015] Step 5:

[1016] The server receives the voice data sent from the device and prepares to analyze the received data.

[1017] Step 6:

[1018] The server runs the received voice data through a voice recognition engine and converts it into text data. For example, voice data such as "Hello, how was your day?" is converted into text such as "Hello, how was your day?"

[1019] Step 7:

[1020] The server performs contextual analysis on the text data, processing it to more accurately understand the meaning and intent of the utterance.

[1021] Step 8:

[1022] The server sends voice and facial expression data to the emotion engine for emotion recognition. For example, it analyzes a friend's tone of voice and facial expression to recognize emotions such as "happiness" or "fun."

[1023] Step 9:

[1024] The server formats the converted text data and the recognized emotion data and sends them to the device. The text "Hello, how was your day?" and the emotion data "I'm happy" are sent to the device.

[1025] Step 10:

[1026] The device receives the text data and emotion data sent from the server and prepares to display the received data.

[1027] Step 11:

[1028] The device then formats and displays the received text and emotion data on the AR glasses' display. The user's field of vision is displayed with the text "Hello, how was your day?" along with a pictogram or icon representing the emotion "happy."

[1029] These steps allow users to visually understand what is being said around them in real time as text, while also visually recognizing the speaker's emotions. This allows hearing-impaired people to grasp not only the nuances of speech but also the emotional nuances, enabling smoother communication.

[1030] Example 2

[1031] 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."

[1032] In everyday life, people with hearing impairments often find it difficult to understand the sounds around them and experience difficulties in communication. It is particularly important for them to understand not only the sound but also the speaker's emotions. However, previous technologies lacked the means to accurately recognize sounds and emotions in real time and to visually present them. The present invention aims to solve these problems and provide a system that enables people with hearing impairments to understand the sounds around them and the speaker's emotions in real time.

[1033] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1034] In this invention, the server includes an input means for capturing surrounding sounds, a transmission means for transmitting the captured sound data via a network, a conversion means for converting the received sound data into text data, and an emotion display means for displaying recognized emotion data, thereby enabling hearing-impaired people to visually understand surrounding sounds in real time and simultaneously recognize the emotions of the speaker.

[1035] "Input means" refers to devices and sensors for capturing ambient sound.

[1036] The "transmission means" refers to a communication module for transmitting the captured audio data to a server or the like via a network.

[1037] "Conversion means" refers to a voice recognition engine or software for converting received voice data into text data.

[1038] "Display means" refers to a display or projector for visually displaying the converted text data.

[1039] "Recognition means" refers to an algorithm or program for analyzing received voice data and facial expression data to recognize emotions.

[1040] "Emotion display means" refers to a module or display for visually presenting recognized emotion data.

[1041] "Preprocessing means" refers to filtering techniques and algorithms used to process audio data and perform noise reduction.

[1042] "Context analysis" refers to the process performed by a speech recognition means to understand the context of speech data and analyze it appropriately.

[1043] This invention proposes an AR glasses system to support the hearing impaired, which can visually present voice and the speaker's emotions in real time using an emotion engine. This system consists of four main entities: a terminal (AR glasses), a server, a user, and an emotion engine.

[1044] Terminal

[1045] The device is equipped with a high-performance microphone, a communication module, and an augmented reality display. Specifically, the following hardware and software are used:

[1046] Voice input: A high-performance microphone captures the surrounding sounds, for example, recording someone saying "Hello, how was your day?" in a cafe.

[1047] Transmission means: A Wi-Fi or mobile network communication module is built in to transmit captured audio data to a server in real time.

[1048] Display means: An augmented reality display is installed to display the text data and emotion data sent from the server in the user's field of vision.

[1049] server

[1050] The server is equipped with a speech recognition engine for processing voice data and converting it into text data, and an emotion engine for analyzing emotions. Specifically, the following processes are performed:

[1051] Speech recognition means: The server converts the received voice data into text data using a high-precision voice recognition engine (e.g., general voice recognition software).

[1052] Pre-processing method: Pre-process the audio data to reduce noise. Noise filtering techniques are used in this process.

[1053] Recognition means: The emotion engine analyzes voice data and, if necessary, facial expression data to recognize the user's emotions.

[1054] Text transmission method: The converted text data and emotion data are formatted and sent to the device.

[1055] Emotion Engine

[1056] The emotion engine analyzes the received voice and facial expression data to recognize the speaker's emotions. For example, it analyzes emotions such as "happy" or "sad" contained in a friend's speech.

[1057] User Experience

[1058] By wearing the AR glasses, users can visually understand the surrounding sounds in real time and simultaneously recognize the speaker's emotions, enabling hearing-impaired people to achieve richer communication in their daily lives.

[1059] Specific examples

[1060] Scenario: Conversation in a cafe

[1061] 1. Voice Input: Imagine a user is having a conversation with a friend at a cafe, and the device's microphone captures the friend saying, "Hello, how was your day?"

[1062] 2. Sending audio data: The device preprocesses the recorded audio data, removes noise, compresses it, and sends it to the server in real time.

[1063] 3. Converting voice data to text: The server analyzes the voice data received by the server using a voice recognition engine and converts it into text data. For example, the voice data "Hello, how was your day?" is converted into text.

[1064] 4. Emotion recognition: The server's emotion engine analyzes the voice and facial expression data to recognize the speaker's emotions. For example, if the speaker speaks in a happy tone, it will recognize the emotion as "happy."

[1065] 5. Sending text data and emotion data: The server sends the converted text data and the recognized emotion data to the device. The text "Hello, how was your day?" and the emotion data "I'm happy" are sent.

[1066] 6. Text and emotion display: The device displays the received text and emotion data on the AR glasses display and provides it to the user's field of view. The user's field of view will display the text "Hello, how was your day?" along with the friend's emotion "Happy."

[1067] Prompt Sentence Examples

[1068] Example prompts to input to a generative AI model:

[1069] "Please explain a system that uses an emotion engine to analyze a conversation with a friend, such as 'Hi, how was your day?', convert the speech to text, and recognize and display the emotion."

[1070] As described above, the system of the present invention is a very useful support tool for the hearing impaired, enabling them to visually understand speech and emotions in real time.

[1071] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1072] Step 1:

[1073] Audio input and preprocessing (terminal)

[1074] The device's high-performance microphone captures the surrounding audio. The input here is the surrounding audio, specifically a friend saying, "Hello, how was your day?" The captured audio data is passed through an internal noise reduction filter to remove noise and pre-process it into clear audio data. The output is high-quality audio data with noise removed.

[1075] Step 2:

[1076] Sending audio data (terminal)

[1077] The device sends the preprocessed audio data to the server in real time, where the input is the preprocessed audio data from step 1, sent to the server via Wi-Fi or mobile network, and the output is the audio data sent to the server.

[1078] Step 3:

[1079] Receiving and preprocessing audio data (server)

[1080] The server receives the audio data sent from the device. The input here is the audio data sent from the device, and the server performs additional noise reduction and sound quality adjustments. The output is the optimized audio data.

[1081] Step 4:

[1082] Speech recognition and text conversion (server)

[1083] The server analyzes the received voice data using a voice recognition engine and converts it into text data. The input here is the voice data optimized in step 3, specifically the voice data "Hello, how was your day?" that is converted into text. The output is text data.

[1084] Step 5:

[1085] Emotion recognition (server)

[1086] The server's emotion engine analyzes the voice data and facial expression data to recognize the speaker's emotions. The input here is the text data obtained in step 4 and information such as the tone, pace, and strength of the voice. For example, if the tone sounds happy, the emotion "happy" is recognized. The output is the recognized emotion data.

[1087] Step 6:

[1088] Sending text data and emotion data (server)

[1089] The server formats the converted text data and the recognized emotion data and sends them to the terminal. The input here is the text data obtained in step 4 and the emotion data recognized in step 5, which are appropriately formatted and sent to the terminal. The output is the text data and emotion data sent to the terminal.

[1090] Step 7:

[1091] Text display and emotion display (terminal)

[1092] The device displays the received text data and emotion data on the display of the AR glasses. The input here is the text and emotion data sent from the server in step 6, and the text "Hello, how was your day?" and the emotion "happy" are displayed in the user's field of view. The output is the visualized text and emotion data.

[1093] Step 8:

[1094] Information Awareness (User)

[1095] The user visually understands the displayed text and emotional information through the AR glasses. The input here is the text and emotional data displayed in step 7, and the user recognizes this information to understand the words and emotions of their friend. The output is the user's understanding and recognition.

[1096] (Application example 2)

[1097] 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."

[1098] Conventional speech recognition systems were able to convert voice data into text, but they were unable to recognize the speaker's emotions and display them visually. This made it difficult for hearing-impaired people to understand the conversations and emotions around them in real time. In brick-and-mortar stores in particular, it is important to simultaneously understand the language and emotional information of customer service staff, and this aspect needed to be improved.

[1099] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1100] In this invention, the server includes an audio input means for capturing surrounding sounds, a communication means for transmitting the captured sound data via a network, a voice recognition means for converting the received sound data into text data, and a visual display means for displaying the converted text data and the recognized emotion data in the user's field of view, thereby enabling hearing-impaired people to visually understand the linguistic information and emotion information of customer service staff simultaneously in real time in a brick-and-mortar store.

[1101] An "audio input means" is a device for capturing ambient sounds.

[1102] A "communication means" is a device for transmitting captured audio data over a network.

[1103] The "voice recognition means" is a device for converting received voice data into text data.

[1104] The "visual display means" is a device for displaying the converted text data and the recognized emotion data in the user's field of vision.

[1105] The "preprocessing means" is a device for preprocessing audio data to perform noise reduction.

[1106] The "emotion recognition means" is a device that analyzes voice and facial expression data to recognize emotions.

[1107] "Context analysis" is an analysis method that allows a speech recognition means to understand the meaning and intent of speech data.

[1108] This invention is a system for supporting hearing-impaired people, specifically implemented as a customer service support application in a brick-and-mortar store. The system includes a terminal, a server, and an emotion recognition engine. A specific example of the system is described below.

[1109] System configuration

[1110] Terminal

[1111] Acoustic input means: The device is equipped with a high-performance microphone to capture surrounding sounds. This microphone captures conversations in the physical store in real time.

[1112] Communication means: A communication module is built in to transmit captured audio data to a server via a network.

[1113] Visual display means: An augmented reality display is provided to display the converted text data and recognized emotion data in the user's field of vision.

[1114] server

[1115] Pre-processing means: The server performs pre-processing on the received audio data to reduce noise and adjust the sound quality.

[1116] Speech recognition means: The preprocessed speech data is converted into highly accurate text data using a speech recognition engine.

[1117] Emotion recognition means: Equipped with an emotion engine that analyzes received voice data and facial expression data to recognize the speaker's emotions.

[1118] User Experience

[1119] Using this system, hearing-impaired people can understand conversations with customer service staff in real time in a physical store. Specific examples include the following scenario:

[1120] Scenario: Conversation in a brick-and-mortar store

[1121] Voice input: A customer asks a staff member at a brick-and-mortar cafe, "What would you recommend about this cake?"

[1122] Audio data transmission: The device preprocesses the captured audio data to remove noise and transmits it to the server in real time.

[1123] Conversion of voice data to text: The voice data received by the server is converted into text data using a voice recognition engine, such as "What do you recommend about this cake?"

[1124] Emotion recognition: The server's emotion recognition engine analyzes the voice data and facial expression data to recognize the questioner's emotion of interest.

[1125] Sending text data and emotion data: The server sends the converted text data and emotion data to the terminal. The text "What do you recommend about this cake?" and the emotion data "I'm interested" are sent.

[1126] Text display and emotion display: The device displays the received text and emotion data on the AR glasses display, displaying "What do you recommend about this cake?" and "Interested" in the user's field of vision.

[1127] Hardware and software used

[1128] Hardware: Devices with high-performance microphones, communication modules, and augmented reality displays (e.g., AR glasses).

[1129] Software: High-precision speech recognition engines (e.g., Google Speech Recognition API), emotion recognition engines (e.g., the sentiment analysis pipeline in the transformers library), and communication libraries (e.g., requests).

[1130] Prompt Sentence Examples

[1131] Text: "Chocolate cake is recommended today!"

[1132] Emotion: "Fun"

[1133] This will make it easier for hearing-impaired people to understand customer service in physical stores and facilitate smooth communication.

[1134] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1135] Step 1:

[1136] When a user starts a conversation with a customer service staff member in a physical store, the device's audio input means captures the voice. The input is the conversational voice occurring in the physical store, and the output is the captured voice data. The device uses a high-performance microphone to detect surrounding sounds and record them as digital voice data.

[1137] Step 2:

[1138] The device sends the captured audio data to the server via a communication means. The input is the audio data obtained in step 1, and the output is the audio data sent via the network. The device uses a built-in communication module (such as Wi-Fi or Bluetooth) to send the data to the server in real time.

[1139] Step 3:

[1140] The server uses preprocessing means to reduce noise and adjust the sound quality of the received audio data. The input is the audio data sent from the terminal, and the output is the preprocessed audio data. The server uses DSP (Digital Signal Processing) technology to remove environmental noise from the audio data and create clear audio data.

[1141] Step 4:

[1142] The server converts the preprocessed voice data into text data using a speech recognition tool. The input is the preprocessed voice data, and the output is text data. The server converts the voice data into corresponding text using a high-precision speech recognition engine such as the Google Speech Recognition API.

[1143] Step 5:

[1144] The server analyzes the text data and voice data generated by the speech recognition means using the emotion recognition means to recognize the speaker's emotions. The input is the converted text data and voice data, and the output is the text data and emotion data. The server uses the emotion analysis pipeline of the transformers library to detect emotional elements in the text data.

[1145] Step 6:

[1146] The server transmits the converted text data and emotion data to the terminal via a communication means. The input is the text data and emotion data that are the results of the speech recognition and emotion recognition, and the output is data transmitted via a network. The server packages this data and transmits it to the terminal in real time.

[1147] Step 7:

[1148] The terminal displays the received text data and emotion data in the user's field of view using a visual display means. The input is the text data and emotion data sent from the server, and the output is the information displayed on the visual display of the AR glasses. Specifically, the terminal uses the augmented reality display to display the information "What do you recommend about this cake?" and "Interested" in the user's field of view.

[1149] Through these steps, hearing-impaired people can understand the content and emotions of conversations with store staff in real time, greatly improving the user's communication experience.

[1150] 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.

[1151] 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.

[1152] 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.

[1153] [Fourth embodiment]

[1154] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1155] 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.

[1156] 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).

[1157] 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.

[1158] 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.

[1159] 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).

[1160] 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.

[1161] 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.

[1162] 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.

[1163] 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.

[1164] 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.

[1165] 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.

[1166] 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."

[1167] The present invention is an AR glasses system for supporting the hearing impaired. A specific example of the system is described below.

[1168] System configuration

[1169] This system consists of three main components: the terminal (AR glasses), the server, and the user.

[1170] Terminal

[1171] Audio input method: The AR glasses worn by the user are equipped with a high-performance microphone that captures surrounding sounds.

[1172] Transmission means: A communication module is built in to transmit captured audio data to a server in real time.

[1173] Display means: An augmented reality display is installed to display the text data received from the server in the user's field of vision.

[1174] server

[1175] Speech recognition means: The server converts the received voice data into text data using a speech recognition engine. This engine is capable of highly accurate speech recognition and contextual analysis.

[1176] Pre-processing means: The server processes the received audio data and performs noise reduction and sound quality adjustment.

[1177] Text transmission means: Transmits the converted text data to the terminal in real time.

[1178] Specific examples

[1179] Scenario: Conversation in a cafe

[1180] 1. Voice Input

[1181] Consider a scenario where a user is having a conversation with a friend at a cafe, and the device's microphone captures what the friend says, for example, "Hi, how was your day?"

[1182] 2. Sending audio data

[1183] The audio data captured by the device is compressed, preprocessed using noise reduction and other techniques, and then sent to the server in real time.

[1184] 3. Converting Audio Data to Text

[1185] The server converts the received voice data into text data using a voice recognition engine. Specifically, the voice data "Hello, how was your day?" is converted directly into text data.

[1186] 4. Sending text data

[1187] The server formats the converted text data and sends it to the terminal.

[1188] 5. Text Display

[1189] The device displays the received text data on the AR glasses' display, and the text "Hello, how was your day?" appears in the user's field of vision.

[1190] User Experience

[1191] This system allows users to visually understand the sounds around them in real time. Users can obtain audio information by reading the text displayed on the AR glasses. This will enable the hearing impaired to communicate more smoothly in their daily lives.

[1192] As described above, the present invention is a very useful support tool for the hearing impaired, supporting real-time communication.

[1193] The processing flow will be explained below.

[1194] Step 1:

[1195] The device activates the microphone in response to user operation and captures surrounding sounds. For example, if a user is talking to a friend at a cafe, the microphone will collect the friend's utterance of "hello."

[1196] Step 2:

[1197] The device performs preprocessing such as noise reduction on the captured voice data. The device eliminates environmental noise and improves the quality of the voice data, thereby improving the accuracy of voice recognition.

[1198] Step 3:

[1199] The terminal compresses the pre-processed voice data and converts it into a format for transmission. By reducing the data size, communication efficiency is improved.

[1200] Step 4:

[1201] The device transmits the compressed audio data to the server in real time over a network, for example, using Wi-Fi or mobile data communication.

[1202] Step 5:

[1203] The server receives the voice data sent from the device and prepares to analyze the received data.

[1204] Step 6:

[1205] The server runs the received voice data through a voice recognition engine and converts it into text data. For example, voice data saying "hello" is converted into the text "hello."

[1206] Step 7:

[1207] The server performs contextual analysis on the generated text data, which allows for a more accurate understanding of the meaning and intent of the speech.

[1208] Step 8:

[1209] The server sends the formatted text data to the terminal in real time. For example, the text "Hello" is sent to the terminal.

[1210] Step 9:

[1211] The terminal receives the text data sent from the server and prepares to display the received data.

[1212] Step 10:

[1213] The device formats and displays the received text on the AR glasses' display, and the word "Hello" appears in the user's field of vision.

[1214] This process allows users to visually understand what is being said around them as text in real time, which helps hearing-impaired users to communicate more smoothly with others.

[1215] Example 1

[1216] 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."

[1217] The purpose of this invention is to provide a support tool for the hearing impaired to facilitate smooth communication in daily life, in particular to enable them to efficiently understand auditory information by visualizing surrounding sounds as text in real time.

[1218] 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.

[1219] In this invention, the server includes a speech recognition unit that converts received speech data into text data using a highly accurate speech recognition engine, a preprocessing unit that preprocesses the speech data to perform noise reduction, and a context analysis unit that performs context analysis, thereby enabling accurate text conversion and display in real time.

[1220] "Audio input means" is a device for capturing ambient sounds.

[1221] The "transmission means" is a device or function for transmitting the captured audio data over a network.

[1222] The "voice recognition means" is a device or function for converting received voice data into text data using a highly accurate voice recognition engine.

[1223] A "display means" is a device or function including an augmented reality display for displaying the converted text data in real time in the user's field of view.

[1224] The "preprocessing means" is a device or function for preprocessing audio data to perform noise reduction.

[1225] "Context analysis" is an analytical process performed by a speech recognition means to understand the context of speech data and achieve more accurate text conversion.

[1226] This invention is an AR glasses system for supporting the hearing impaired. This system consists of three main components: AR glasses (terminals) worn by the user, a remote server, and the user.

[1227] Terminal

[1228] Voice input methods:

[1229] The AR glasses worn by users are equipped with high-performance microphones that capture the sounds of the surrounding environment. For example, when you are talking with a friend in a public place such as a cafe, the microphones pick up what your friend is saying.

[1230] Transmission method:

[1231] The captured audio data is transmitted in real time to a server using a communication module built into the device, which uses Wi-Fi or Bluetooth and undergoes noise reduction before transmission.

[1232] Display means:

[1233] The text data received from the server is displayed on the augmented reality display of the AR glasses. Specifically, the text pops up in the user's field of vision, allowing them to visually understand the audio information.

[1234] server

[1235] Voice recognition methods:

[1236] The server converts the received voice data into text data using a highly accurate voice recognition engine (e.g., a general-purpose voice recognition engine), which uses phonological algorithms to analyze the voice data and convert it into appropriate text.

[1237] Pretreatment methods:

[1238] The server preprocesses the audio data, reducing noise and adjusting the audio quality, allowing the speech recognition engine to convert speech to text more accurately.

[1239] Texting methods:

[1240] The converted text data is then formatted and sent immediately to the device. This involves removing extra spaces and adding necessary punctuation. Specifically, a Python script is used to convert the text data into JSON format and send it to the device via an HTTP request.

[1241] User Experience

[1242] This system allows users to visually understand the sounds around them in real time. For example, during a meeting, users can instantly read what their colleagues are saying as text using AR glasses. This will enable the hearing impaired to communicate more smoothly in their daily lives.

[1243] Specific examples

[1244] Scenario: Conversation in a cafe

[1245] 1. Voice Input

[1246] A user is talking to a friend at a cafe, and the device's microphone captures the friend saying, "Hello, how was your day?"

[1247] 2. Sending audio data

[1248] The device transmits the captured audio data to the server in real time, with noise reduction performed during transmission.

[1249] 3. Converting Audio Data to Text

[1250] The server receives the voice data and converts it into text data such as "Hello, how was your day?" using a general-purpose voice recognition engine.

[1251] 4. Sending text data

[1252] The server formats the converted text data using a Python script and sends it to the terminal.

[1253] 5. Text Display

[1254] The text data received by the device is displayed on the AR glasses' display, and the text "Hello, how was your day?" is displayed in the user's field of vision.

[1255] Prompt Sentence Examples

[1256] "Create a program that displays what your friend is saying in real time on your AR glasses."

[1257] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1258] Step 1:

[1259] Voice input

[1260] Device:

[1261] Input: A situation where a user wears AR glasses and recognizes surrounding sounds.

[1262] How it works: High-performance microphones built into the AR glasses capture surrounding sounds.

[1263] Output: Audio data captured by the microphone.

[1264] Data processing: Convert into digital format as an audio signal.

[1265] Step 2:

[1266] Sending audio data

[1267] Device:

[1268] Input: Audio data captured by a high-quality microphone.

[1269] How it works: The device's communication module transmits audio data to the server in real time, then performs noise reduction and compresses the data to an optimal format (e.g., MP3) before transmission.

[1270] Output: Filtered compressed audio data.

[1271] Data processing: Noise reduction and compression of audio data.

[1272] Step 3:

[1273] Converting audio data to text

[1274] server:

[1275] Input: Audio data sent from the device.

[1276] Specific operation: The server converts the received voice data into text data using a highly accurate voice recognition engine. A general-purpose voice recognition engine is used to analyze the data using a phonological algorithm.

[1277] Output: The converted text data.

[1278] Data processing: Converting voice data to text.

[1279] Step 4:

[1280] Preprocessing and sending text data

[1281] server:

[1282] Input: Text data converted by the speech recognition engine.

[1283] What it does: Formats the text data, removing extra spaces and adding necessary punctuation, converting it to JSON format using a Python script, and then sending it to the device via an HTTP request.

[1284] Output: Formatted and converted text data.

[1285] Data processing: Formatting text data and converting it to JSON format.

[1286] Step 5:

[1287] Text Display

[1288] Device:

[1289] Input: Formatted and converted text data sent from the server.

[1290] Specific operation: The device displays the received text data on the augmented reality display of the AR glasses. The text pops up in the user's field of view.

[1291] Output: The displayed text information.

[1292] Data processing: Converting text data into visual information.

[1293] (Application example 1)

[1294] 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."

[1295] Conventional communication support systems for the hearing impaired have limitations in their speech-to-text conversion capabilities, making it difficult to handle noise and complex speech contexts when used in physical store environments. Furthermore, the lack of real-time speech recognition and text display hinders smooth communication. Furthermore, there is a lack of technology that allows users to visually interpret information in a natural, unobtrusive way.

[1296] 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.

[1297] In this invention, the server includes an audio input means for capturing surrounding sounds, a communication means for transmitting the captured sound data via a network, a speech recognition means for converting the received sound data into text data, a preprocessing means for preprocessing the received sound data in real time and performing noise reduction, and a visual display means for displaying the converted text data on an augmented reality display. This allows hearing-impaired people to enjoy smooth and comfortable communication in physical stores, and enables real-time speech recognition and visual text display.

[1298] An "acoustic input means" is a device used to capture ambient sound.

[1299] "Communication means" refers to the device or technology used to transmit the captured audio data over a network.

[1300] "Speech recognition means" refers to a device or technology for converting received voice data into text data.

[1301] A "visual display means" is a device or technique for displaying the converted text data on an augmented reality display.

[1302] The "preprocessing means" refers to a device or technology for preprocessing received audio data in real time and performing noise reduction.

[1303] An "information processing system" is a comprehensive system that combines multiple means to process and display specific information.

[1304] A "brick and mortar store" is a commercial or service establishment that exists in a physical location.

[1305] "Context analysis" is a technology in which a speech recognition means understands the context of text data and performs appropriate text conversion.

[1306] "Augmented reality display" is a technology that displays digital information superimposed on the real world.

[1307] The system that realizes this application example consists of three main components: the terminal (AR glasses), the server, and the user.

[1308] Device (AR glasses)

[1309] The device includes the following elements:

[1310] Acoustic input means: This is a high-performance microphone that captures surrounding sounds. For example, when a store clerk explains a product, the microphone captures that sound.

[1311] Communication means: A communication module is built in to transmit captured audio data to a server in real time.

[1312] Visual display means: The system is equipped with an augmented reality display to display the text data received from the server in the user's field of vision. Through this display, the user can visually recognize the captured voice as text.

[1313] server

[1314] The server includes the following elements:

[1315] Speech recognition means: The received voice data is converted into text data by a speech recognition engine. This engine is capable of highly accurate speech recognition and contextual analysis.

[1316] Pre-processing means: Processes the received voice data and performs noise reduction and sound quality adjustment, which results in more accurate text conversion.

[1317] Communication method: Responsible for sending the converted text data to the terminal. This data is sent in real time, so the text is displayed without delay.

[1318] Example

[1319] Scenario: Ordering at a restaurant

[1320] 1. Audio capture via acoustic input means:

[1321] The device's microphone captures the voice of the waiter saying, "Today's recommendation is steak."

[1322] 2. Transmission of audio data by means of communication:

[1323] The captured audio data is transmitted to the server in real time via the terminal's communication module.

[1324] 3. Text conversion by speech recognition means:

[1325] The voice data is received on the server and converted into text data such as "Today's recommendation is steak" using a speech recognition engine. Contextual analysis is also performed, reducing the chance of misrecognition.

[1326] 4. Text data transmission and visual display:

[1327] The converted text data is sent to the terminal and displayed on the terminal's augmented reality display, allowing the user to understand the voice of the store clerk.

[1328] Hardware / Software used

[1329] Hardware:

[1330] High-performance microphone (for voice capture)

[1331] AR glasses (for displaying text)

[1332] software:

[1333] Python, socket, speech_recognition

[1334] Socket communication is used for communication between the server and the client

[1335] Prompt Sentence Examples

[1336] Below is an example of a prompt sentence to be input to the generative AI model.

[1337] I want to build an application that uses voice capture and text conversion to help hearing-impaired people understand when ordering at a restaurant. I want to create a system that converts the voice of a waiter saying, "Today's recommendation is steak," into text and displays it on the AR glasses.

[1338] As a result, this invention allows hearing-impaired people to visually understand audio information in real time in physical stores. Users can receive support by reading the text displayed on the AR glasses.

[1339] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1340] Step 1:

[1341] The device captures the surrounding sound using a high-performance microphone. Specifically, the microphone receives the sound as an analog signal and converts it into a digital signal. The input is the surrounding sound, and the output is digital sound data.

[1342] Step 2:

[1343] The terminal transmits the captured digital audio data to the server in real time via the communication module. The specific operations performed here are to generate data packets and transmit them over the network. The input is the digital audio data, and the output is the data packets transmitted to the server.

[1344] Step 3:

[1345] The server performs noise reduction on the received digital audio data using a pre-processing means. Specifically, it applies a noise filtering algorithm to remove unwanted noise from the audio data. The input is the received digital audio data, and the output is the clean audio data after noise reduction.

[1346] Step 4:

[1347] The server uses a speech recognition means to convert the noise-reduced speech data into text data. Specifically, a speech recognition engine analyzes the speech signal and generates corresponding text. The input is the clean speech data, and the output is the converted text data.

[1348] Step 5:

[1349] The server transmits the converted text data to the terminal via a communication means. Specific operations include packetizing the text data and transmitting it over a network. The input is the text data, and the output is the data transmitted to the terminal.

[1350] Step 6:

[1351] The terminal displays the received text data in the user's field of view using a visual display means. Specifically, the augmented reality display visualizes the text data and displays it to the user in real time. The input is the text data received from the server, and the output is the text displayed in the user's field of view.

[1352] 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.

[1353] The present invention is an AR glasses system for supporting the hearing impaired, and by adding the functionality of an emotion engine, it can recognize the user's emotions. A specific example of this is shown below.

[1354] System configuration

[1355] This system consists of four main components: the terminal (AR glasses), the server, the user, and the emotion engine.

[1356] Terminal

[1357] Audio input method: The AR glasses worn by the user are equipped with a high-performance microphone that captures surrounding sounds.

[1358] Transmission means: A communication module is built in to transmit captured audio data to a server in real time.

[1359] Display means: An augmented reality display is installed to display the text data received from the server and emotion recognition results in the user's field of vision.

[1360] server

[1361] Speech recognition means: The server converts the received voice data into text data using a speech recognition engine. This engine is capable of highly accurate speech recognition and contextual analysis.

[1362] Pre-processing means: The server processes the received audio data and performs noise reduction and sound quality adjustment.

[1363] Text transmission means: Transmits the converted text data to the terminal in real time.

[1364] Emotion Engine

[1365] Emotion recognition means: The emotion engine installed on the server recognizes the user's emotions based on voice data and facial expression data.

[1366] Emotion display means: Recognized emotion data is sent to the terminal and visually presented to the user via the display means.

[1367] Specific examples

[1368] Scenario: Conversation in a cafe

[1369] 1. Voice Input

[1370] Consider a scenario where a user is having a conversation with a friend at a cafe, and the device's microphone captures what the friend says, for example, "Hi, how was your day?"

[1371] 2. Sending audio data

[1372] The device preprocesses the captured audio data, removes noise, compresses it, and sends it to the server in real time.

[1373] 3. Converting Audio Data to Text

[1374] The server converts the received voice data into text data using a voice recognition engine. Specifically, the voice data "Hello, how was your day?" is converted directly into text data.

[1375] 4. Emotion recognition

[1376] The server's emotion engine analyzes the voice and facial expression data to recognize the emotion contained in the friend's speech. For example, if the friend speaks in a happy tone, the emotion "happy" is recognized.

[1377] 5. Sending text data and emotion data

[1378] The server formats the converted text data and the recognized emotion data and sends them to the device. The text "Hello, how was your day?" and the emotion data "I'm happy" are sent.

[1379] 6. Text and Emotion Display

[1380] The device displays the received text and emotion data on the AR glasses' display, providing it to the user's field of vision. The user's field of vision displays the message "Hello, how was your day?" along with the friend's emotion, "Happy."

[1381] User Experience

[1382] This system allows users to visually understand the surrounding voices in real time, while also recognizing the speaker's emotions. By reading the text and emotional information displayed in the AR glasses, users can grasp not only the voice but also the emotional nuances. This will enable hearing-impaired people to have richer communication in their daily lives.

[1383] As described above, the present invention is an extremely useful support tool for the hearing impaired, supporting real-time communication and enabling visual understanding of the emotions of the other party.

[1384] The processing flow will be explained below.

[1385] Step 1:

[1386] The device activates the microphone in response to user operation and captures surrounding sounds. For example, if a user is talking with a friend at a cafe, the microphone will collect the friend's words, "Hello, how was your day?"

[1387] Step 2:

[1388] The device performs preprocessing such as noise reduction on the captured voice data. The device eliminates environmental noise and improves the quality of the voice data, thereby improving the accuracy of voice recognition.

[1389] Step 3:

[1390] The terminal compresses the pre-processed voice data and converts it into a format for transmission. By reducing the data size, communication efficiency is improved.

[1391] Step 4:

[1392] The device transmits the compressed audio data to the server in real time over a network, for example, using Wi-Fi or mobile data communication.

[1393] Step 5:

[1394] The server receives the voice data sent from the device and prepares to analyze the received data.

[1395] Step 6:

[1396] The server runs the received voice data through a voice recognition engine and converts it into text data. For example, voice data such as "Hello, how was your day?" is converted into text such as "Hello, how was your day?"

[1397] Step 7:

[1398] The server performs contextual analysis on the text data, processing it to more accurately understand the meaning and intent of the utterance.

[1399] Step 8:

[1400] The server sends voice and facial expression data to the emotion engine for emotion recognition. For example, it analyzes a friend's tone of voice and facial expression to recognize emotions such as "happiness" or "fun."

[1401] Step 9:

[1402] The server formats the converted text data and the recognized emotion data and sends them to the device. The text "Hello, how was your day?" and the emotion data "I'm happy" are sent to the device.

[1403] Step 10:

[1404] The device receives the text data and emotion data sent from the server and prepares to display the received data.

[1405] Step 11:

[1406] The device then formats and displays the received text and emotion data on the AR glasses' display. The user's field of vision is displayed with the text "Hello, how was your day?" along with a pictogram or icon representing the emotion "happy."

[1407] These steps allow users to visually understand what is being said around them in real time as text, while also visually recognizing the speaker's emotions. This allows hearing-impaired people to grasp not only the nuances of speech but also the emotional nuances, enabling smoother communication.

[1408] Example 2

[1409] 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."

[1410] In everyday life, people with hearing impairments often find it difficult to understand the sounds around them and experience difficulties in communication. It is particularly important for them to understand not only the sound but also the speaker's emotions. However, previous technologies lacked the means to accurately recognize sounds and emotions in real time and to visually present them. The present invention aims to solve these problems and provide a system that enables people with hearing impairments to understand the sounds around them and the speaker's emotions in real time.

[1411] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1412] In this invention, the server includes an input means for capturing surrounding sounds, a transmission means for transmitting the captured sound data via a network, a conversion means for converting the received sound data into text data, and an emotion display means for displaying recognized emotion data, thereby enabling hearing-impaired people to visually understand surrounding sounds in real time and simultaneously recognize the emotions of the speaker.

[1413] "Input means" refers to devices and sensors for capturing ambient sound.

[1414] The "transmission means" refers to a communication module for transmitting the captured audio data to a server or the like via a network.

[1415] "Conversion means" refers to a voice recognition engine or software for converting received voice data into text data.

[1416] "Display means" refers to a display or projector for visually displaying the converted text data.

[1417] "Recognition means" refers to an algorithm or program for analyzing received voice data and facial expression data to recognize emotions.

[1418] "Emotion display means" refers to a module or display for visually presenting recognized emotion data.

[1419] "Preprocessing means" refers to filtering techniques and algorithms used to process audio data and perform noise reduction.

[1420] "Context analysis" refers to the process performed by a speech recognition means to understand the context of speech data and analyze it appropriately.

[1421] This invention proposes an AR glasses system to support the hearing impaired, which can visually present voice and the speaker's emotions in real time using an emotion engine. This system consists of four main entities: a terminal (AR glasses), a server, a user, and an emotion engine.

[1422] Terminal

[1423] The device is equipped with a high-performance microphone, a communication module, and an augmented reality display. Specifically, the following hardware and software are used:

[1424] Voice input: A high-performance microphone captures the surrounding sounds, for example, recording someone saying "Hello, how was your day?" in a cafe.

[1425] Transmission means: A Wi-Fi or mobile network communication module is built in to transmit captured audio data to a server in real time.

[1426] Display means: An augmented reality display is installed to display the text data and emotion data sent from the server in the user's field of vision.

[1427] server

[1428] The server is equipped with a speech recognition engine for processing voice data and converting it into text data, and an emotion engine for analyzing emotions. Specifically, the following processes are performed:

[1429] Speech recognition means: The server converts the received voice data into text data using a high-precision voice recognition engine (e.g., general voice recognition software).

[1430] Pre-processing method: Pre-process the audio data to reduce noise. Noise filtering techniques are used in this process.

[1431] Recognition means: The emotion engine analyzes voice data and, if necessary, facial expression data to recognize the user's emotions.

[1432] Text transmission method: The converted text data and emotion data are formatted and sent to the device.

[1433] Emotion Engine

[1434] The emotion engine analyzes the received voice and facial expression data to recognize the speaker's emotions. For example, it analyzes emotions such as "happy" or "sad" contained in a friend's speech.

[1435] User Experience

[1436] By wearing the AR glasses, users can visually understand the surrounding sounds in real time and simultaneously recognize the speaker's emotions, enabling hearing-impaired people to achieve richer communication in their daily lives.

[1437] Specific examples

[1438] Scenario: Conversation in a cafe

[1439] 1. Voice Input: Imagine a user is having a conversation with a friend at a cafe, and the device's microphone captures the friend saying, "Hello, how was your day?"

[1440] 2. Sending audio data: The device preprocesses the recorded audio data, removes noise, compresses it, and sends it to the server in real time.

[1441] 3. Converting voice data to text: The server analyzes the voice data received by the server using a voice recognition engine and converts it into text data. For example, the voice data "Hello, how was your day?" is converted into text.

[1442] 4. Emotion recognition: The server's emotion engine analyzes the voice and facial expression data to recognize the speaker's emotions. For example, if the speaker speaks in a happy tone, it will recognize the emotion as "happy."

[1443] 5. Sending text data and emotion data: The server sends the converted text data and the recognized emotion data to the device. The text "Hello, how was your day?" and the emotion data "I'm happy" are sent.

[1444] 6. Text and emotion display: The device displays the received text and emotion data on the AR glasses display and provides it to the user's field of view. The user's field of view will display the text "Hello, how was your day?" along with the friend's emotion "Happy."

[1445] Prompt Sentence Examples

[1446] Example prompts to input to a generative AI model:

[1447] "Please explain a system that uses an emotion engine to analyze a conversation with a friend, such as 'Hi, how was your day?', convert the speech to text, and recognize and display the emotion."

[1448] As described above, the system of the present invention is a very useful support tool for the hearing impaired, enabling them to visually understand speech and emotions in real time.

[1449] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1450] Step 1:

[1451] Audio input and preprocessing (terminal)

[1452] The device's high-performance microphone captures the surrounding audio. The input here is the surrounding audio, specifically a friend saying, "Hello, how was your day?" The captured audio data is passed through an internal noise reduction filter to remove noise and pre-process it into clear audio data. The output is high-quality audio data with noise removed.

[1453] Step 2:

[1454] Sending audio data (terminal)

[1455] The device sends the preprocessed audio data to the server in real time, where the input is the preprocessed audio data from step 1, sent to the server via Wi-Fi or mobile network, and the output is the audio data sent to the server.

[1456] Step 3:

[1457] Receiving and preprocessing audio data (server)

[1458] The server receives the audio data sent from the device. The input here is the audio data sent from the device, and the server performs additional noise reduction and sound quality adjustments. The output is the optimized audio data.

[1459] Step 4:

[1460] Speech recognition and text conversion (server)

[1461] The server analyzes the received voice data using a voice recognition engine and converts it into text data. The input here is the voice data optimized in step 3, specifically the voice data "Hello, how was your day?" that is converted into text. The output is text data.

[1462] Step 5:

[1463] Emotion recognition (server)

[1464] The server's emotion engine analyzes the voice data and facial expression data to recognize the speaker's emotions. The input here is the text data obtained in step 4 and information such as the tone, pace, and strength of the voice. For example, if the tone sounds happy, the emotion "happy" is recognized. The output is the recognized emotion data.

[1465] Step 6:

[1466] Sending text data and emotion data (server)

[1467] The server formats the converted text data and the recognized emotion data and sends them to the terminal. The input here is the text data obtained in step 4 and the emotion data recognized in step 5, which are appropriately formatted and sent to the terminal. The output is the text data and emotion data sent to the terminal.

[1468] Step 7:

[1469] Text display and emotion display (terminal)

[1470] The device displays the received text data and emotion data on the display of the AR glasses. The input here is the text and emotion data sent from the server in step 6, and the text "Hello, how was your day?" and the emotion "happy" are displayed in the user's field of view. The output is the visualized text and emotion data.

[1471] Step 8:

[1472] Information Awareness (User)

[1473] The user visually understands the displayed text and emotional information through the AR glasses. The input here is the text and emotional data displayed in step 7, and the user recognizes this information to understand the words and emotions of their friend. The output is the user's understanding and recognition.

[1474] (Application example 2)

[1475] 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."

[1476] Conventional speech recognition systems were able to convert voice data into text, but they were unable to recognize the speaker's emotions and display them visually. This made it difficult for hearing-impaired people to understand the conversations and emotions around them in real time. In brick-and-mortar stores in particular, it is important to simultaneously understand the language and emotional information of customer service staff, and this aspect needed to be improved.

[1477] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1478] In this invention, the server includes an audio input means for capturing surrounding sounds, a communication means for transmitting the captured sound data via a network, a voice recognition means for converting the received sound data into text data, and a visual display means for displaying the converted text data and the recognized emotion data in the user's field of view, thereby enabling hearing-impaired people to visually understand the linguistic information and emotion information of customer service staff simultaneously in real time in a brick-and-mortar store.

[1479] An "audio input means" is a device for capturing ambient sounds.

[1480] A "communication means" is a device for transmitting captured audio data over a network.

[1481] The "voice recognition means" is a device for converting received voice data into text data.

[1482] The "visual display means" is a device for displaying the converted text data and the recognized emotion data in the user's field of vision.

[1483] The "preprocessing means" is a device for preprocessing audio data to perform noise reduction.

[1484] The "emotion recognition means" is a device that analyzes voice and facial expression data to recognize emotions.

[1485] "Context analysis" is an analysis method that allows a speech recognition means to understand the meaning and intent of speech data.

[1486] This invention is a system for supporting hearing-impaired people, specifically implemented as a customer service support application in a brick-and-mortar store. The system includes a terminal, a server, and an emotion recognition engine. A specific example of the system is described below.

[1487] System configuration

[1488] Terminal

[1489] Acoustic input means: The device is equipped with a high-performance microphone to capture surrounding sounds. This microphone captures conversations in the physical store in real time.

[1490] Communication means: A communication module is built in to transmit captured audio data to a server via a network.

[1491] Visual display means: An augmented reality display is provided to display the converted text data and recognized emotion data in the user's field of vision.

[1492] server

[1493] Pre-processing means: The server performs pre-processing on the received audio data to reduce noise and adjust the sound quality.

[1494] Speech recognition means: The preprocessed speech data is converted into highly accurate text data using a speech recognition engine.

[1495] Emotion recognition means: Equipped with an emotion engine that analyzes received voice data and facial expression data to recognize the speaker's emotions.

[1496] User Experience

[1497] Using this system, hearing-impaired people can understand conversations with customer service staff in real time in a physical store. Specific examples include the following scenario:

[1498] Scenario: Conversation in a brick-and-mortar store

[1499] Voice input: A customer asks a staff member at a brick-and-mortar cafe, "What would you recommend about this cake?"

[1500] Audio data transmission: The device preprocesses the captured audio data to remove noise and transmits it to the server in real time.

[1501] Conversion of voice data to text: The voice data received by the server is converted into text data using a voice recognition engine, such as "What do you recommend about this cake?"

[1502] Emotion recognition: The server's emotion recognition engine analyzes the voice data and facial expression data to recognize the questioner's emotion of interest.

[1503] Sending text data and emotion data: The server sends the converted text data and emotion data to the terminal. The text "What do you recommend about this cake?" and the emotion data "I'm interested" are sent.

[1504] Text display and emotion display: The device displays the received text and emotion data on the AR glasses display, displaying "What do you recommend about this cake?" and "Interested" in the user's field of vision.

[1505] Hardware and software used

[1506] Hardware: Devices with high-performance microphones, communication modules, and augmented reality displays (e.g., AR glasses).

[1507] Software: High-precision speech recognition engines (e.g., Google Speech Recognition API), emotion recognition engines (e.g., the sentiment analysis pipeline in the transformers library), and communication libraries (e.g., requests).

[1508] Prompt Sentence Examples

[1509] Text: "Chocolate cake is recommended today!"

[1510] Emotion: "Fun"

[1511] This will make it easier for hearing-impaired people to understand customer service in physical stores and facilitate smooth communication.

[1512] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1513] Step 1:

[1514] When a user starts a conversation with a customer service staff member in a physical store, the device's audio input means captures the voice. The input is the conversational voice occurring in the physical store, and the output is the captured voice data. The device uses a high-performance microphone to detect surrounding sounds and record them as digital voice data.

[1515] Step 2:

[1516] The device sends the captured audio data to the server via a communication means. The input is the audio data obtained in step 1, and the output is the audio data sent via the network. The device uses a built-in communication module (such as Wi-Fi or Bluetooth) to send the data to the server in real time.

[1517] Step 3:

[1518] The server uses preprocessing means to reduce noise and adjust the sound quality of the received audio data. The input is the audio data sent from the terminal, and the output is the preprocessed audio data. The server uses DSP (Digital Signal Processing) technology to remove environmental noise from the audio data and create clear audio data.

[1519] Step 4:

[1520] The server converts the preprocessed voice data into text data using a speech recognition tool. The input is the preprocessed voice data, and the output is text data. The server converts the voice data into corresponding text using a high-precision speech recognition engine such as the Google Speech Recognition API.

[1521] Step 5:

[1522] The server analyzes the text data and voice data generated by the speech recognition means using the emotion recognition means to recognize the speaker's emotions. The input is the converted text data and voice data, and the output is the text data and emotion data. The server uses the emotion analysis pipeline of the transformers library to detect emotional elements in the text data.

[1523] Step 6:

[1524] The server transmits the converted text data and emotion data to the terminal via a communication means. The input is the text data and emotion data that are the results of the speech recognition and emotion recognition, and the output is data transmitted via a network. The server packages this data and transmits it to the terminal in real time.

[1525] Step 7:

[1526] The terminal displays the received text data and emotion data in the user's field of view using a visual display means. The input is the text data and emotion data sent from the server, and the output is the information displayed on the visual display of the AR glasses. Specifically, the terminal uses the augmented reality display to display the information "What do you recommend about this cake?" and "Interested" in the user's field of view.

[1527] Through these steps, hearing-impaired people can understand the content and emotions of conversations with store staff in real time, greatly improving the user's communication experience.

[1528] 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.

[1529] 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.

[1530] 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.

[1531] 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.

[1532] 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.

[1533] 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.

[1534] 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).

[1535] 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.

[1536] 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."

[1537] 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.

[1538] 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).

[1539] 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.

[1540] 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.

[1541] 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.

[1542] 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.

[1543] 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.

[1544] 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.

[1545] 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.

[1546] 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.

[1547] 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.

[1548] 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.

[1549] The following is further disclosed regarding the above embodiment.

[1550] (Claim 1)

[1551] an audio input means for capturing ambient audio;

[1552] a transmitting means for transmitting the captured audio data via a network;

[1553] a speech recognition means for converting received speech data into text data;

[1554] display means for displaying the converted text data;

[1555] A system including:

[1556] (Claim 2)

[1557] 10. The system of claim 1, further comprising preprocessing means for preprocessing the audio data to perform noise reduction.

[1558] (Claim 3)

[1559] 2. The system of claim 1, wherein the speech recognition means performs contextual analysis.

[1560] (Claim 4)

[1561] 2. The system according to claim 1, wherein the transmitting means compresses and transmits the audio data.

[1562] (Claim 5)

[1563] 10. The system of claim 1, wherein the display means uses an augmented reality display.

[1564] "Example 1"

[1565] (Claim 1)

[1566] an audio input means for capturing ambient audio;

[1567] a transmitting means for transmitting the captured audio data via a network;

[1568] A speech recognition means for converting received speech data into text data using a highly accurate speech recognition engine;

[1569] display means including an augmented reality display for displaying the converted text data in real time in the user's field of view;

[1570] A system including:

[1571] (Claim 2)

[1572] 10. The system of claim 1, further comprising preprocessing means for preprocessing the audio data to perform noise reduction.

[1573] (Claim 3)

[1574] 2. The system of claim 1, wherein the speech recognition means performs contextual analysis.

[1575] "Application Example 1"

[1576] (Claim 1)

[1577] an acoustic input means for capturing ambient sounds;

[1578] a communication means for transmitting the captured audio data via a network;

[1579] a speech recognition means for converting received speech data into text data;

[1580] visual display means for displaying the converted text data on an augmented reality display;

[1581] a pre-processing means for pre-processing the received audio data in real time and performing noise reduction;

[1582] An information processing system including:

[1583] (Claim 2)

[1584] 10. The information processing system of claim 1, which captures and displays audio in a physical store.

[1585] (Claim 3)

[1586] 2. The information processing system according to claim 1, wherein the speech recognition means performs context analysis.

[1587] "Example 2: Combining Emotion Engines"

[1588] (Claim 1)

[1589] an input means for capturing ambient audio;

[1590] a transmitting means for transmitting the captured audio data via a network;

[1591] A conversion means for converting the received voice data into text data;

[1592] display means for displaying the converted text data;

[1593] A recognition means for analyzing received voice data and facial expression data to recognize emotions;

[1594] emotion display means for displaying the recognized emotion data;

[1595] A system including:

[1596] (Claim 2)

[1597] 10. The system of claim 1, further comprising preprocessing means for preprocessing the audio data to perform noise reduction.

[1598] (Claim 3)

[1599] 2. The system of claim 1, wherein the conversion means performs a contextual analysis.

[1600] "Application example 2 when combining emotion engines"

[1601] (Claim 1)

[1602] an acoustic input means for capturing ambient sounds;

[1603] a communication means for transmitting the captured audio data via a network;

[1604] a speech recognition means for converting received speech data into text data;

[1605] visual display means for displaying the converted text data and the recognized emotion data in the user's field of view;

[1606] A system including:

[1607] (Claim 2)

[1608] 10. The system of claim 1, further comprising preprocessing means for preprocessing the audio data to perform noise reduction.

[1609] (Claim 3)

[1610] 2. The system according to claim 1, wherein the speech recognition means performs context analysis and the emotion recognition means analyzes speech and facial expression data to recognize emotions. [Explanation of symbols]

[1611] 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. an audio input means for capturing ambient audio; a transmitting means for transmitting the captured audio data via a network; a speech recognition means for converting received speech data into text data; display means for displaying the converted text data; A system including:

2. 10. The system of claim 1, further comprising preprocessing means for preprocessing the audio data to perform noise reduction.

3. 2. The system of claim 1, wherein the speech recognition means performs contextual analysis.

4. 2. The system according to claim 1, wherein the transmitting means compresses and transmits the audio data.

5. 10. The system of claim 1, wherein the display means uses an augmented reality display.

Images