system

Abstract

We provide the system. [Solution] Means for acquiring acoustic data, A means of analyzing acquired acoustic data to identify the type of sound, A means for generating text information based on the identified type of sound, A means of visually displaying the generated text information, A system that includes this.

Description

Technical Field

[0004] , , , ,

[0005] , , , , , ,

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot performed by at least one processor, the method including receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance that responds to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] <00​​​​​​​This invention provides a system that acquires acoustic data, analyzes that data, and identifies the type of sound. The acquired sounds are classified into specific categories using an AI model, and user-friendly text information is generated. The generated information is displayed visually and further notified in a way that is easily noticeable to the user. In this way, it enables people with hearing impairments to accurately understand surrounding sound information, supporting a safe and secure life.

[0006] "Acoustic data" refers to information that digitally records the physical waves of sound generated in a space.

[0007] "Analysis" refers to the process of breaking down obtained acoustic data into its individual components using a computer program and evaluating the characteristics of each sound.

[0008] "Types of sound" refer to categories classified based on the physical characteristics and origins of specific sounds.

[0009] "Text information" refers to information expressed as a string of characters that a user can understand, based on the type of sound obtained through analysis.

[0010] "Visual display" refers to the act of presenting information on a screen or display using text, shapes, colors, etc., in a way that can be understood through human vision.

[0011] "Notification" refers to informing someone of information using actions or means to convey that information to the recipient.

[0012] "Vibration means" refers to a system that uses devices or functions that generate physical vibrations to transmit information to the user as a physical sensation. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2]It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

MODE FOR CARRYING OUT THE INVENTION

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0019] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention provides a system that allows users with hearing impairments to visually obtain information about sound. The system is realized by collecting acoustic data, analyzing the sound to recognize specific types of sound, and providing the user with information in text format.

[0035] First, the user terminal uses a microphone to detect ambient sounds and acquires acoustic data. This data is then transmitted to the server in real time. The terminal uses an internet connection to transfer the data, ensuring that the audio data reaches the server efficiently.

[0036] The server receives acoustic data transmitted from the user's terminal. An AI model for speech recognition and analysis is built on the server to analyze the characteristics of each sound and classify it. By mapping sounds to specific categories, the server identifies the specific type of sound (e.g., car engine sound, ambulance siren sound, fire alarm sound, etc.).

[0037] Based on the analysis, the server generates text describing the identified sound types. This text is in a concise and easy-to-understand format, and the information is displayed visually through the user interface.

[0038] Next, the generated text information is sent back to the user's terminal and notified to the user. The notification is displayed as text on the screen and, in important cases, is also provided as feedback via vibration. For example, if the terminal detects a sound that is the siren of an emergency vehicle, the terminal will display "Emergency vehicle approaching" and warn the user with vibration.

[0039] For example, when a device detects the sound of a car engine, the server analyzes the sound and generates the text "Engine started." This allows the user to instantly receive auditory information about the engine sound as visual information.

[0040] This system is designed to enable users with hearing impairments to live safely and to quickly obtain important auditory information, especially in their daily lives.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user terminal samples ambient sound using its built-in microphone and periodically saves the audio data to a buffer. The saved audio data is then prepared for processing in short timeframes.

[0044] Step 2:

[0045] The user terminal converts buffered voice data into packets at regular intervals (e.g., every 2 seconds) and sends them to the server over the internet. Data transfer is designed to minimize communication delays.

[0046] Step 3:

[0047] The server receives audio data packets from the user's terminal and inputs the data into the AI ​​speech recognition model. The speech recognition model analyzes the characteristics of the data and extracts the sound features.

[0048] Step 4:

[0049] The server classifies the data into specific categories (e.g., engine sounds, siren sounds) based on the characteristics of the analyzed sound. Based on this classification information, it generates text information corresponding to the type of sound recognized.

[0050] Step 5:

[0051] The server sends the generated text information to the user's terminal using a lightweight communication protocol (e.g., JSON). The information is transferred quickly and can be received by the user immediately.

[0052] Step 6:

[0053] The user terminal processes text information received from the server and displays it on the user interface. The information is organized and displayed on the screen in a visually easy-to-understand manner.

[0054] Step 7:

[0055] The user's device uses additional notification methods (vibration or alarm) depending on the importance of the information to alert the user. In urgent situations, vibration and other functions are used to complement visual notifications.

[0056] In this way, users can obtain important information about sound visually and tactilely, enabling them to make appropriate judgments and take appropriate actions.

[0057] (Example 1)

[0058] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0059] There is a need for a system that allows users with hearing impairments to safely and quickly obtain auditory information and support important decision-making in daily life. However, conventional technologies are insufficient in identifying sounds and providing information, and a more accurate means of information transmission is required.

[0060] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0061] In this invention, the server includes a device for collecting sound wave data, a device for analyzing the collected sound wave data and identifying sound attributes, and a device for generating textual information based on the identified sound attributes. This enables users with hearing impairments to instantly understand the characteristics of various sounds and quickly obtain visual information.

[0062] "Sound wave data" refers to information obtained by acquiring and recording ambient sounds as digital signals.

[0063] "Device" refers to a configuration that includes hardware or software for performing a specific function.

[0064] "Analysis" refers to the process of extracting features from data and converting them into information that is appropriate for a specific purpose.

[0065] "Sound attributes" refer to identifiable features used to identify and classify the type and characteristics of a sound.

[0066] "Identification" refers to distinguishing items from analyzed data that meet specific criteria.

[0067] "Textual information" refers to a string of characters that is understandable to humans and generated based on the analysis results.

[0068] "To output information visually" means to display information visually and provide it in a way that users can see and understand.

[0069] A "computer system" refers to a collection of hardware and software that allows various devices to work together to perform a specific task.

[0070] "Classification" refers to the process of assigning analyzed data to predefined categories.

[0071] "To inform" refers to notifying the target person of information and urging them to pay attention.

[0072] A "vibration device" refers to a device that has the function of transmitting information to the user by utilizing physical vibrations.

[0073] This invention is a system that allows users with hearing impairments to visually acquire information about their surrounding sounds. Specifically, it consists of a user terminal, a server, and software corresponding to each of these functions.

[0074] The user terminal acquires sound wave data using a built-in or external microphone. The acquired data is transmitted to the server via wireless communication technology (e.g., Wi-Fi or Bluetooth). The data is transferred in real time, and data compression techniques are used to minimize latency.

[0075] The server is equipped with a generative AI model for analyzing received sound wave data. This AI model uses data analysis algorithms to identify sound attributes and categorize sounds into specific groups. Sound attributes include frequency components, volume, tone, etc. Based on the analysis results, the server generates textual information that describes the identified sound attributes. The generated textual information is then formatted using natural language processing techniques to create a concise and user-friendly format.

[0076] The generated text information is sent back to the user's terminal and displayed visually on the screen. Simultaneously, the terminal's vibration device is used to notify the user of important information. This vibration device attracts the user's attention, especially when there is highly urgent information.

[0077] As a concrete example, consider a scenario where a user's device detects the sound of a car engine. This sound is sent to a server, where a generative AI model generates the text message "Engine started." This allows the user to visually obtain this information immediately.

[0078] Examples of prompts to input into a generative AI model include "Analyze this sound data and tell me what kind of sound it is" and "Classify the following sounds and generate text to provide to the user."

[0079] This system transmits auditory information to the user through sight and touch, enabling users with hearing impairments to live their daily lives safely and comfortably.

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] The device acquires ambient sound wave data through its built-in microphone. This sound wave data is input as an analog signal and converted into digital data through digital signal processing. Specifically, the sound waves are sampled, quantized, and output as binary data.

[0083] Step 2:

[0084] The terminal transmits the acquired digital sound wave data to the server via the internet. By applying a data compression algorithm before transmission, unnecessary data is removed, resulting in efficient data transfer. This step is completed when the compressed digital data reaches the server.

[0085] Step 3:

[0086] The server decompresses the received compressed digital data and performs audio analysis. The sound wave data is input to an AI model, which analyzes the characteristics of the sound. Specifically, it extracts features such as frequency components, volume, and tone, identifies the data based on these, and outputs the attributes of a specific sound.

[0087] Step 4:

[0088] The server inputs data into a classification algorithm based on the sound's attributes, classifying the sound into a specific category (e.g., car engine sound, siren sound, etc.). After the classification process, qualitative data output regarding the sound category is obtained.

[0089] Step 5:

[0090] The server generates text information for the user based on the identified sound category information. A generative AI model uses natural language processing to create descriptive text. Specifically, text such as "Vehicle engine started" or "Emergency vehicle approaching" is generated and prepared to be sent from the server to the terminal.

[0091] Step 6:

[0092] The device receives text information sent from the server and displays it on the screen. The display format is optimized so that the user can visually confirm this information. Additionally, in the case of important notifications, the device's vibration function activates to provide tactile feedback to the user.

[0093] Step 7:

[0094] Users receive textual information and vibrations displayed on their devices, allowing them to instantly understand auditory information through both sight and touch. This process enables them to accurately perceive auditory information in their daily lives and take necessary actions quickly.

[0095] (Application Example 1)

[0096] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0097] In autonomous vehicles, passengers with hearing impairments may be unable to perceive important auditory information from their surroundings, compromising safety and a sense of security. Therefore, a system is needed that can visually and effectively communicate audible warnings tailored to the vehicle's situation.

[0098] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0099] In this invention, the server includes means for acquiring acoustic signals, means for analyzing the acquired acoustic signals and identifying the type of sound, and means for generating textual information based on the identified type of sound. This makes it possible for passengers with hearing impairments in an autonomous vehicle to visually obtain surrounding acoustic information and enhance their awareness of important situations.

[0100] An "acoustic signal" is a signal that converts ambient sound into an electrical signal and makes it into an analyzable format.

[0101] A "sound type" is a classification of sound based on analyzed acoustic signals.

[0102] "Character information" refers to visual string information generated based on a specific type of sound.

[0103] "Vibration means" refers to means of generating vibrations to attract the attention of passengers based on a specified audible warning.

[0104] "Means of visual display" refers to means of visually showing generated textual information through a display or similar device.

[0105] The system implementing this invention aims to provide safe travel for passengers with hearing impairments by acquiring and analyzing acoustic signals to generate textual information and presenting it visually to the user.

[0106] The terminal is equipped with a high-sensitivity microphone that captures ambient sounds as acoustic signals. These acoustic signals are transmitted to a server in real time. The server receives the acoustic signals and uses an AI model and a speech analysis engine (e.g., TENSORFLOW® or PyTorch) to analyze them and identify the type of sound. This allows for the identification of specific acoustic warnings (e.g., ambulance sirens, collision avoidance alarms).

[0107] Subsequently, the server generates text information based on the identified sound type and sends the generated text information to the terminal. The terminal visually displays the received text information on its screen and, if necessary, uses vibration to warn the user. This allows users to obtain important ambient sound information without relying on their hearing.

[0108] As a concrete example, if an autonomous vehicle detects an ambulance siren while passing through an intersection, the system will generate text information such as "An ambulance is approaching" and display it on the screen. The terminal will also vibrate slightly to alert the passenger. An example of a prompt message to be input to the generation AI model used in this case is: "Analyze the surrounding sounds as auditory data and generate the following warning message: An ambulance siren has been detected."

[0109] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0110] Step 1:

[0111] The device uses a microphone to pick up ambient sounds and converts them into digital data as acoustic signals. This digital data becomes the input. The device then sends this acoustic signal to the server.

[0112] Step 2:

[0113] The server receives acoustic signals transmitted from the terminal. Based on this input, the server analyzes the acoustic signals using an AI model (e.g., TensorFlow or PyTorch). Data calculations include spectral analysis of the sound to identify the type of sound and determine the category of the sound. The output is information about the identified type of sound.

[0114] Step 3:

[0115] The server generates text information based on the identified sound type. The input is the sound type identified in the previous step, and the output is text information to notify the user. A generative AI model is used to convert the data into text. A prompt sentence is used as input to the model; for example, "Analyze ambient sounds as auditory data and generate the following warning message: Ambulance siren sound detected."

[0116] Step 4:

[0117] The server sends the generated character information to the terminal. The input is the generated character information, and the output is a notification message sent to the terminal.

[0118] Step 5:

[0119] The terminal visually displays received text information on its screen. Furthermore, if the sound type indicates a warning is necessary, the terminal uses vibration to trigger the warning. Input is text information notification from the server, and output is display and vibration. For example, the screen might display "Ambulance approaching," and the terminal would vibrate slightly to alert the user.

[0120] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0121] This invention combines a system for visually acquiring sound-related information for users with hearing impairments with an emotion engine to provide information tailored to the user's emotional state. The basic system configuration involves acquiring, analyzing, visualizing, and notifying the user of acoustic data, but it also enables sensing the user's emotions and optimizing the response.

[0122] First, the user's device collects ambient sounds using a microphone and acquires acoustic data. This data is transmitted to the server in real time. During this process, the device also collects data to recognize the user's emotions. For example, emotions are estimated from facial expressions and tone of voice via the camera and microphone.

[0123] The server analyzes the acoustic data transmitted from the terminal using an AI model. Here, the sounds are classified into specific categories and the type of sound is identified. Furthermore, the emotion engine analyzes the emotional data from the user and identifies the emotional state. The emotion engine recognizes basic emotions such as joy, sadness, and surprise, and determines what kind of feedback is optimal.

[0124] Based on the analysis results, the server adjusts the generated text information. For example, if a user is feeling anxious, reassuring information can be added. This text information is displayed visually through the user interface. In addition to providing regular information, the generated information is presented in a format that is most easily received by the user.

[0125] Ultimately, the user device receives the generated text information and provides optimal visual feedback based on the user's emotional state, and potentially supplementary information through vibration. For example, if an emergency warning sound is detected and the user is startled, the device might display a message such as "Please be careful, stay calm" and vibrate to further alert the user.

[0126] In this way, the present invention not only provides users with hearing impairments with information about the type of sound, but also has a form that enables flexible responses in accordance with their emotions. This can improve the user's safety and quality of life.

[0127] The following describes the processing flow.

[0128] Step 1:

[0129] The user terminal samples ambient sounds using its built-in microphone and stores the acoustic data in a buffer. It also captures the user's facial expressions and voice tone using a camera and voice input to acquire emotional data.

[0130] Step 2:

[0131] The user terminal packets the acquired acoustic and emotional data at specific time intervals and sends them to the server. This transmission process is performed in real time, ensuring that all data is transferred without fail.

[0132] Step 3:

[0133] The server inputs acoustic data into a speech recognition model and analyzes the characteristics of the sounds in the data. It extracts sound features from the analysis results and classifies the sounds into specific categories based on them.

[0134] Step 4:

[0135] The server inputs emotional data into the emotion engine to recognize the user's emotional state. The emotion engine analyzes multiple emotional components to identify major emotions such as joy, sadness, and surprise.

[0136] Step 5:

[0137] The server integrates the analyzed sound type with the user's emotional state to optimize the generated text information. For example, if a warning sound is analyzed and the server recognizes that the user is surprised, it will generate a message such as "Please stay calm and evacuate."

[0138] Step 6:

[0139] The server sends optimized text information to the user's terminal. This communication is rapid, minimizing information delays.

[0140] Step 7:

[0141] The user terminal processes text information received from the server and displays it on the user interface. The information is visually highlighted with colors and icons corresponding to the user's emotional state.

[0142] Step 8:

[0143] The user's device will notify them using vibration as needed. Effective feedback tailored to urgency and emotion is implemented to ensure the user's attention is captured.

[0144] Through this series of processes, the system makes it easier for the user to understand surrounding sound information and provides considerate responses that are tailored to their emotions.

[0145] (Example 2)

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

[0147] For users with hearing impairments to obtain real-time information about sound and take appropriate action based on that information, feedback is needed that takes into account not only the surrounding acoustic conditions but also their own emotional state. However, existing technologies only identify and visually display the type of sound, and are not sufficient to provide information that takes into account the user's emotional changes. Furthermore, there has been a challenge in adequately addressing situations where immediacy and ease of understanding are required in information provision.

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

[0149] In this invention, the server includes means for acquiring acoustic data, means for analyzing the acquired acoustic data and identifying the type of sound, means for analyzing the user's facial expressions and voice data and identifying their emotional state, means for generating text information based on the identified type of sound and emotional state, means for visually displaying the generated text information, and means for additionally providing the generated text information as vibrations. This enables a user with a hearing impairment to instantly grasp the type of sound and provide visual and tactile feedback that takes into account their emotional response to that sound.

[0150] "Acoustic data" refers to information about sound acquired from the surrounding environment, and is collected in a format that can be processed as an electronic signal.

[0151] "Analysis" refers to the process of processing collected acoustic and emotional data to extract specific information, and is carried out using generative AI models.

[0152] "Emotional state" refers to information that indicates the user's current psychological response, and is estimated from facial expressions and tone of voice.

[0153] "Text information" refers to visual textual information generated based on analyzed acoustic data and emotional states, and is provided in a format that is easy for the user to understand.

[0154] "Visual display" refers to the act of showing generated text information to the user via a display or screen.

[0155] "Provided as vibration" refers to a means of conveying generated information to the user through vibration, and is used as haptic feedback.

[0156] This invention is a system for users with hearing impairments to visually acquire information about their surroundings and receive emotionally responsive feedback. Users can receive information on a daily basis using a special terminal. This document describes the specific hardware and software used, as well as the data processing procedures.

[0157] The device uses a microphone to collect ambient sounds in real time. This data is temporarily stored in the device's internal memory as acoustic data. Simultaneously, it uses a camera and additional sensors to detect the user's facial expressions and voice tone, collecting this as emotion data. The device uses a wireless communication module to transmit this data to a server.

[0158] The server analyzes the received acoustic data using a generative AI model. This analysis classifies the sounds into specific types and, if necessary, into categories. Furthermore, an emotion engine analyzes the user's emotional data to identify emotional states such as joy, sadness, and surprise. Based on these analysis results, the server generates optimal text information according to the prompt.

[0159] For example, if the sound of a dog barking is detected while walking in a park, the user's surprise is estimated. When the sound is identified as "dog barking," the server generates a message saying, "It looks like you're playing with your dog. Please stay calm and enjoy yourself." This message is sent back to the user's device, where it is displayed visually and the device vibrates slightly to attract the user's attention.

[0160] An example of a prompt to input into the generation AI model would be something like, "Check which sounds are being analyzed in the surroundings and generate the most appropriate text based on the user's emotional state."

[0161] By implementing this system, users with hearing impairments can carry out their daily activities with peace of mind through feedback.

[0162] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0163] Step 1:

[0164] The device uses a microphone to collect ambient sounds and records them as acoustic data. This acoustic data is collected in real time and temporarily stored in the device's internal memory. The camera and sensors are activated to detect the user's facial expressions and voice tone, collecting emotional data. This emotional data is also temporarily stored within the device. Inputs include audio and images from the microphone and camera, while outputs are acoustic and emotional data for analysis.

[0165] Step 2:

[0166] The terminal transmits collected acoustic and emotional data to the server. A wireless communication module is used to transfer the data to the server in real time. The input consists of acoustic and emotional data within the terminal, and the output is the transfer of this data to the server.

[0167] Step 3:

[0168] The server inputs the received acoustic data into a generating AI model for analysis. This analysis process classifies the sounds into specific categories and identifies the types of sounds. Additionally, an emotion engine analyzes emotional data to identify the user's emotional state. The input consists of acoustic data and emotional data sent to the server, while the output is the identification of sound types and emotional states.

[0169] Step 4:

[0170] The server generates optimal text information using prompts based on the analysis results. For example, following a prompt such as "Check which sounds are being analyzed in the surroundings and generate optimal text based on the user's emotional state," the AI ​​model generates text corresponding to the sounds and emotions. The input is the type of sound and the emotional state, and the output is text information for the user.

[0171] Step 5:

[0172] The terminal receives text information sent from the server and displays it visually. It provides complementary feedback via vibration as needed. Input is text information from the server, and output is the presentation of visual and tactile information to the user. Specifically, the terminal displays messages on the screen and activates a vibration motor as needed.

[0173] (Application Example 2)

[0174] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0175] To make the virtual shopping experience more comfortable for users with hearing impairments, it is necessary not only to acquire and visualize ambient sound information but also to provide information tailored to the user's emotional state. However, current systems lack methods to appropriately recognize user emotions and optimize information, resulting in challenges in improving the ease of information reception and user satisfaction.

[0176] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0177] In this invention, the server includes means for analyzing acoustic information and identifying the type of sound, means for detecting the user's emotional state, and means for adjusting textual information based on the emotional state. This makes it possible to not only visualize acoustic information for users with hearing impairments, but also to provide optimal information tailored to the user's emotions.

[0178] "Acoustic information" refers to sound vibration data within a space, which is acquired through sensors such as microphones.

[0179] "Analysis" refers to the process of breaking down acquired acoustic information and emotional state data to clarify their characteristics and types.

[0180] "Sound type" refers to the distinction between ambient sounds, conversation sounds, alarm sounds, etc., identified from analyzed acoustic information, and classifies their properties.

[0181] "Textual information" refers to information in text format generated based on the type of sound analyzed, and is provided to the user as visual feedback.

[0182] "Emotional state" refers to the state of psychological emotions estimated from the user's facial expressions and voice, and includes emotions such as joy and anxiety.

[0183] "Adjustment" refers to modifying text information generated according to the user's emotional state, and displaying it in a way that is easiest for the user to understand and accept.

[0184] "Visually displaying" refers to providing generated text information in a way that users can see using a display device such as a screen.

[0185] "Vibration means" refers to a device or function that notifies the user through vibration as physical feedback based on generated text information.

[0186] This invention is a system aimed at enabling users with hearing impairments to comfortably enjoy shopping in virtual stores. The embodiments of this system will be described in detail below.

[0187] First, the user terminal is equipped with a microphone to acquire acoustic information and a camera to detect the user's emotional state. This terminal transmits the acoustic information and the user's emotional data to the server in real time.

[0188] The server performs a process of analyzing acoustic information and identifying the type of sound. This acoustic analysis utilizes cloud-based acoustic analysis AI (for example, a service that converts speech to text). Furthermore, the user's emotional state is analyzed using an emotion analysis engine (for example, a service that estimates emotions from facial expressions and voice). This analysis allows the server to identify the user's psychological state and generate emotionally appropriate feedback.

[0189] The generated text information is adjusted by the server based on the user's emotional state. For example, if the user is excited, the product recommendation list can be expanded and relaxing messages can be added. The adjusted text information is displayed visually on the user's terminal and, if necessary, physically notified by vibration. This allows the user to accurately perceive ambient sound information within the virtual store while receiving information tailored to their emotional state.

[0190] For example, even if a user has difficulty hearing announcements about special offers in the store, this system will display the offer information as text. Furthermore, if the user is emotionally unstable, a message such as "Please calm down and take a look" will be added to make the user experience more comfortable.

[0191] Furthermore, an example of a prompt to the generation AI model when building this system is, "Convert the surrounding audio into text and generate a message to display based on the user's emotional state." This ensures that the system functions properly and provides information that is relevant to the user's emotions.

[0192] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0193] Step 1:

[0194] The user terminal acquires ambient acoustic information using its built-in microphone. Simultaneously, it captures the user's facial expressions with a camera to acquire emotion data. This data is sent to the server as input. The output consists of the transmitted acoustic information and emotion data.

[0195] Step 2:

[0196] The server uses an acoustic analysis AI to analyze the received acoustic information. This analysis process classifies sounds based on their characteristics. The input is acoustic information, and the output is the identification of the type of sound. Specifically, it classifies common sounds such as ambient sounds and alarms.

[0197] Step 3:

[0198] Simultaneously, the server uses an emotion analysis engine to analyze the user's emotional data. The input data includes facial expressions and tone of voice. This process involves data processing to identify the user's emotional state as output. Emotional states are classified into categories such as excitement, anxiety, and joy.

[0199] Step 4:

[0200] The server generates and adjusts text information based on the identified sound type and the user's emotional state. In this step, the results of acoustic information analysis and emotion analysis are taken as input, and text information is created using a generative AI model. The output is the adjusted text information.

[0201] Step 5:

[0202] The adjusted text information is transmitted to the user's terminal. The terminal visually displays this text information on its screen. In addition, it provides physical notification to the user using vibration if necessary. This allows the user to receive information and announcements within the virtual store, improving the experience.

[0203] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0204] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0205] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0206] [Second Embodiment]

[0207] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0208] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0209] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0210] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0211] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0212] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0213] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0214] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0215] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0216] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0217] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0218] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0219] This invention provides a system that allows users with hearing impairments to visually obtain information about sound. The system is realized by collecting acoustic data, analyzing the sound to recognize specific types of sound, and providing the user with information in text format.

[0220] First, the user terminal uses a microphone to detect ambient sounds and acquires acoustic data. This data is then transmitted to the server in real time. The terminal uses an internet connection to transfer the data, ensuring that the audio data reaches the server efficiently.

[0221] The server receives acoustic data transmitted from the user's terminal. An AI model for speech recognition and analysis is built on the server to analyze the characteristics of each sound and classify it. By mapping sounds to specific categories, the server identifies the specific type of sound (e.g., car engine sound, ambulance siren sound, fire alarm sound, etc.).

[0222] Based on the analysis, the server generates text describing the identified sound types. This text is in a concise and easy-to-understand format, and the information is displayed visually through the user interface.

[0223] Next, the generated text information is sent back to the user's terminal and notified to the user. The notification is displayed as text on the screen and, in important cases, is also provided as feedback via vibration. For example, if the terminal detects a sound that is the siren of an emergency vehicle, the terminal will display "Emergency vehicle approaching" and warn the user with vibration.

[0224] For example, when a device detects the sound of a car engine, the server analyzes the sound and generates the text "Engine started." This allows the user to instantly receive auditory information about the engine sound as visual information.

[0225] This system is designed to enable users with hearing impairments to live safely and to quickly obtain important auditory information, especially in their daily lives.

[0226] The following describes the processing flow.

[0227] Step 1:

[0228] The user terminal samples ambient sound using its built-in microphone and periodically saves the audio data to a buffer. The saved audio data is then prepared for processing in short timeframes.

[0229] Step 2:

[0230] The user terminal converts buffered voice data into packets at regular intervals (e.g., every 2 seconds) and sends them to the server over the internet. Data transfer is designed to minimize communication delays.

[0231] Step 3:

[0232] The server receives audio data packets from the user's terminal and inputs the data into the AI ​​speech recognition model. The speech recognition model analyzes the characteristics of the data and extracts the sound features.

[0233] Step 4:

[0234] The server classifies the data into specific categories (e.g., engine sounds, siren sounds) based on the characteristics of the analyzed sound. Based on this classification information, it generates text information corresponding to the type of sound recognized.

[0235] Step 5:

[0236] The server sends the generated text information to the user's terminal using a lightweight communication protocol (e.g., JSON). The information is transferred quickly and can be received by the user immediately.

[0237] Step 6:

[0238] The user terminal processes text information received from the server and displays it on the user interface. The information is organized and displayed on the screen in a visually easy-to-understand manner.

[0239] Step 7:

[0240] The user's device uses additional notification methods (vibration or alarm) depending on the importance of the information to alert the user. In urgent situations, vibration and other functions are used to complement visual notifications.

[0241] In this way, users can obtain important information about sound visually and tactilely, enabling them to make appropriate judgments and take appropriate actions.

[0242] (Example 1)

[0243] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0244] There is a need for a system that allows users with hearing impairments to safely and quickly obtain auditory information and support important decision-making in daily life. However, conventional technologies are insufficient in identifying sounds and providing information, and a more accurate means of information transmission is required.

[0245] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0246] In this invention, the server includes a device for collecting sound wave data, a device for analyzing the collected sound wave data and identifying sound attributes, and a device for generating textual information based on the identified sound attributes. This enables users with hearing impairments to instantly understand the characteristics of various sounds and quickly obtain visual information.

[0247] "Sound wave data" refers to information obtained by acquiring and recording ambient sounds as digital signals.

[0248] "Device" refers to a configuration that includes hardware or software for performing a specific function.

[0249] "Analysis" refers to the process of extracting features from data and converting them into information that is appropriate for a specific purpose.

[0250] "Sound attributes" refer to identifiable features used to identify and classify the type and characteristics of a sound.

[0251] "Identification" refers to distinguishing items from analyzed data that meet specific criteria.

[0252] "Textual information" refers to a string of characters that is understandable to humans and generated based on the analysis results.

[0253] "To output information visually" means to display information visually and provide it in a way that users can see and understand.

[0254] A "computer system" refers to a collection of hardware and software that allows various devices to work together to perform a specific task.

[0255] "Classification" refers to the process of assigning analyzed data to predefined categories.

[0256] "To inform" refers to notifying the target person of information and urging them to pay attention.

[0257] A "vibration device" refers to a device that has the function of transmitting information to the user by utilizing physical vibrations.

[0258] This invention is a system that allows users with hearing impairments to visually acquire information about their surrounding sounds. Specifically, it consists of a user terminal, a server, and software corresponding to each of these functions.

[0259] The user terminal acquires sound wave data using a built-in or external microphone. The acquired data is transmitted to the server via wireless communication technology (e.g., Wi-Fi or Bluetooth). The data is transferred in real time, and data compression techniques are used to minimize latency.

[0260] The server is equipped with a generative AI model for analyzing received sound wave data. This AI model uses data analysis algorithms to identify sound attributes and categorize sounds into specific groups. Sound attributes include frequency components, volume, tone, etc. Based on the analysis results, the server generates textual information that describes the identified sound attributes. The generated textual information is then formatted using natural language processing techniques to create a concise and user-friendly format.

[0261] The generated text information is sent back to the user's terminal and displayed visually on the screen. Simultaneously, the terminal's vibration device is used to notify the user of important information. This vibration device attracts the user's attention, especially when there is highly urgent information.

[0262] As a concrete example, consider a scenario where a user's device detects the sound of a car engine. This sound is sent to a server, where a generative AI model generates the text message "Engine started." This allows the user to visually obtain this information immediately.

[0263] Examples of prompts to input into a generative AI model include "Analyze this sound data and tell me what kind of sound it is" and "Classify the following sounds and generate text to provide to the user."

[0264] This system transmits auditory information to the user through sight and touch, enabling users with hearing impairments to live their daily lives safely and comfortably.

[0265] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0266] Step 1:

[0267] The device acquires ambient sound wave data through its built-in microphone. This sound wave data is input as an analog signal and converted into digital data through digital signal processing. Specifically, the sound waves are sampled, quantized, and output as binary data.

[0268] Step 2:

[0269] The terminal transmits the acquired digital sound wave data to the server via the internet. By applying a data compression algorithm before transmission, unnecessary data is removed, resulting in efficient data transfer. This step is completed when the compressed digital data reaches the server.

[0270] Step 3:

[0271] The server decompresses the received compressed digital data and performs audio analysis. The sound wave data is input to an AI model, which analyzes the characteristics of the sound. Specifically, it extracts features such as frequency components, volume, and tone, identifies the data based on these, and outputs the attributes of a specific sound.

[0272] Step 4:

[0273] The server inputs data into a classification algorithm based on the sound's attributes, classifying the sound into a specific category (e.g., car engine sound, siren sound, etc.). After the classification process, qualitative data output regarding the sound category is obtained.

[0274] Step 5:

[0275] The server generates text information for the user based on the identified sound category information. A generative AI model uses natural language processing to create descriptive text. Specifically, text such as "Vehicle engine started" or "Emergency vehicle approaching" is generated and prepared to be sent from the server to the terminal.

[0276] Step 6:

[0277] The terminal receives the character information transmitted from the server and displays it on the display. The display format is optimized so that the user can visually confirm this information. Also, in the case of an important notification, the vibration function of the terminal activates to provide tactile feedback to the user.

[0278] Step 7:

[0279] The user receives the character information and vibration displayed on the terminal and can immediately understand the information related to sound through vision and touch. Through this process, it becomes possible to accurately capture sound information in daily life and quickly take necessary actions.

[0280] (Application Example 1)

[0281] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0282] In an autonomous vehicle, there is a problem that the safety and sense of security are impaired because passengers with hearing impairments cannot recognize important ambient acoustic information. Therefore, a system that can visually and effectively transmit acoustic warnings according to the vehicle's situation is required.

[0283] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0284] In this invention, the server includes means for acquiring an acoustic signal, means for analyzing the acquired acoustic signal to identify the type of sound, and means for generating character information based on the identified type of sound. Thereby, passengers with hearing impairments in an autonomous vehicle can visually obtain ambient acoustic information and enhance their recognition of important situations.

[0285] An "acoustic signal" is a signal for converting ambient sound into an electrical signal in an analyzable format.

[0286] "Sound type" refers to the type of sound classified based on the analyzed acoustic signal.

[0287] "Character information" refers to visual string information generated based on the identified sound type.

[0288] "Vibration means" refers to means for generating vibration to attract the attention of passengers based on the identified acoustic warning.

[0289] "Means for visually displaying" refers to means for visually showing the generated character information through a display or the like.

[0290] The system for implementing the present invention aims to provide safe movement for passengers with hearing impairments by acquiring an acoustic signal, analyzing it to generate character information, and visually presenting it to the user.

[0291] The terminal is equipped with a high-sensitivity microphone to acquire ambient sound as an acoustic signal. The acoustic signal is transmitted to the server in real time. The server receives the acoustic signal and performs analysis to identify the sound type using an AI model and a voice analysis engine (e.g., TensorFlow or PyTorch). As a result, specific acoustic warnings (e.g., ambulance sirens, collision prevention alarms) are identified.

[0292] After that, the server generates character information based on the identified sound type and transmits the generated character information to the terminal. The terminal visually displays the received character information on a display and gives a warning to the user using the vibration means as necessary. As a result, important ambient sound information can be obtained without relying on hearing.

[0293] As a concrete example, if an autonomous vehicle detects an ambulance siren while passing through an intersection, the system will generate text information such as "An ambulance is approaching" and display it on the screen. The terminal will also vibrate slightly to alert the passenger. An example of a prompt message to be input to the generation AI model used in this case is: "Analyze the surrounding sounds as auditory data and generate the following warning message: An ambulance siren has been detected."

[0294] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0295] Step 1:

[0296] The device uses a microphone to pick up ambient sounds and converts them into digital data as acoustic signals. This digital data becomes the input. The device then sends this acoustic signal to the server.

[0297] Step 2:

[0298] The server receives acoustic signals transmitted from the terminal. Based on this input, the server analyzes the acoustic signals using an AI model (e.g., TensorFlow or PyTorch). Data calculations include spectral analysis of the sound to identify the type of sound and determine the category of the sound. The output is information about the identified type of sound.

[0299] Step 3:

[0300] The server generates text information based on the identified sound type. The input is the sound type identified in the previous step, and the output is text information to notify the user. A generative AI model is used to convert the data into text. A prompt sentence is used as input to the model; for example, "Analyze ambient sounds as auditory data and generate the following warning message: Ambulance siren sound detected."

[0301] Step 4:

[0302] The server sends the generated character information to the terminal. The input is the generated character information, and the output is the notification message to the terminal.

[0303] Step 5:

[0304] The terminal visually displays the received character information on the display. Also, when the type of sound requires a warning, the terminal activates a warning using vibration means. The input is the character information notification from the server, and the outputs are the display and vibration. As a specific operation, display "An ambulance is approaching" on the display, and the terminal vibrates slightly to prompt the user's attention.

[0305] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion recognition model 59 and perform specific processing using the user's emotion.

[0306] The present invention realizes information provision according to the user's emotional state by combining an emotion engine with a system in which a user with hearing impairment visually acquires information related to sound. The basic system configuration is acquisition, analysis, visualization of acoustic data, and user notification, but it also enables sensing the user's emotion and optimizing the response.

[0307] First, the user terminal collects ambient sound with a microphone to obtain acoustic data. This data is sent to the server in real time. In this process, the terminal also collects data for recognizing the user's emotion. For example, estimate the emotion from facial expressions and voice tones via a camera or a microphone.

[0308] The server analyzes the acoustic data sent from the terminal using an AI model. Here, the sound is classified into specific categories to identify the type of sound. Furthermore, the emotion engine analyzes the emotion data from the user to identify the emotional state. The emotion engine recognizes basic emotions such as joy, sadness, and surprise and determines what kind of feedback is optimal.

[0309] Based on the analysis results, the server adjusts the generated text information. For example, if a user is feeling anxious, reassuring information can be added. This text information is displayed visually through the user interface. In addition to providing regular information, the generated information is presented in a format that is most easily received by the user.

[0310] Ultimately, the user device receives the generated text information and provides optimal visual feedback based on the user's emotional state, and potentially supplementary information through vibration. For example, if an emergency warning sound is detected and the user is startled, the device might display a message such as "Please be careful, stay calm" and vibrate to further alert the user.

[0311] In this way, the present invention not only provides users with hearing impairments with information about the type of sound, but also has a form that enables flexible responses in accordance with their emotions. This can improve the user's safety and quality of life.

[0312] The following describes the processing flow.

[0313] Step 1:

[0314] The user terminal samples ambient sounds using its built-in microphone and stores the acoustic data in a buffer. It also captures the user's facial expressions and voice tone using a camera and voice input to acquire emotional data.

[0315] Step 2:

[0316] The user terminal packets the acquired acoustic and emotional data at specific time intervals and sends them to the server. This transmission process is performed in real time, ensuring that all data is transferred without fail.

[0317] Step 3:

[0318] The server inputs acoustic data into a speech recognition model and analyzes the characteristics of the sounds in the data. It extracts sound features from the analysis results and classifies the sounds into specific categories based on them.

[0319] Step 4:

[0320] The server inputs emotional data into the emotion engine to recognize the user's emotional state. The emotion engine analyzes multiple emotional components to identify major emotions such as joy, sadness, and surprise.

[0321] Step 5:

[0322] The server integrates the analyzed sound type with the user's emotional state to optimize the generated text information. For example, if a warning sound is analyzed and the server recognizes that the user is surprised, it will generate a message such as "Please stay calm and evacuate."

[0323] Step 6:

[0324] The server sends optimized text information to the user's terminal. This communication is rapid, minimizing information delays.

[0325] Step 7:

[0326] The user terminal processes text information received from the server and displays it on the user interface. The information is visually highlighted with colors and icons corresponding to the user's emotional state.

[0327] Step 8:

[0328] The user's device will notify them using vibration as needed. Effective feedback tailored to urgency and emotion is implemented to ensure the user's attention is captured.

[0329] Through this series of processes, the system makes it easier for the user to understand surrounding sound information and provides considerate responses that are tailored to their emotions.

[0330] (Example 2)

[0331] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0332] For users with hearing impairments to obtain real-time information about sound and take appropriate action based on that information, feedback is needed that takes into account not only the surrounding acoustic conditions but also their own emotional state. However, existing technologies only identify and visually display the type of sound, and are not sufficient to provide information that takes into account the user's emotional changes. Furthermore, there has been a challenge in adequately addressing situations where immediacy and ease of understanding are required in information provision.

[0333] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0334] In this invention, the server includes means for acquiring acoustic data, means for analyzing the acquired acoustic data and identifying the type of sound, means for analyzing the user's facial expressions and voice data and identifying their emotional state, means for generating text information based on the identified type of sound and emotional state, means for visually displaying the generated text information, and means for additionally providing the generated text information as vibrations. This enables a user with a hearing impairment to instantly grasp the type of sound and provide visual and tactile feedback that takes into account their emotional response to that sound.

[0335] "Acoustic data" refers to information about sound acquired from the surrounding environment, and is collected in a format that can be processed as an electronic signal.

[0336] "Analysis" refers to the process of processing collected acoustic and emotional data to extract specific information, and is carried out using generative AI models.

[0337] "Emotional state" refers to information that indicates the user's current psychological response, and is estimated from facial expressions and tone of voice.

[0338] "Text information" refers to visual textual information generated based on analyzed acoustic data and emotional states, and is provided in a format that is easy for the user to understand.

[0339] "Visual display" refers to the act of showing generated text information to the user via a display or screen.

[0340] "Provided as vibration" refers to a means of conveying generated information to the user through vibration, and is used as haptic feedback.

[0341] This invention is a system for users with hearing impairments to visually acquire information about their surroundings and receive emotionally responsive feedback. Users can receive information on a daily basis using a special terminal. This document describes the specific hardware and software used, as well as the data processing procedures.

[0342] The device uses a microphone to collect ambient sounds in real time. This data is temporarily stored in the device's internal memory as acoustic data. Simultaneously, it uses a camera and additional sensors to detect the user's facial expressions and voice tone, collecting this as emotion data. The device uses a wireless communication module to transmit this data to a server.

[0343] The server analyzes the received acoustic data using a generative AI model. This analysis classifies the sounds into specific types and, if necessary, into categories. Furthermore, an emotion engine analyzes the user's emotional data to identify emotional states such as joy, sadness, and surprise. Based on these analysis results, the server generates optimal text information according to the prompt.

[0344] For example, if the sound of a dog barking is detected while walking in a park, the user's surprise is estimated. When the sound is identified as "dog barking," the server generates a message saying, "It looks like you're playing with your dog. Please stay calm and enjoy yourself." This message is sent back to the user's device, where it is displayed visually and the device vibrates slightly to attract the user's attention.

[0345] An example of a prompt to input into the generation AI model would be something like, "Check which sounds are being analyzed in the surroundings and generate the most appropriate text based on the user's emotional state."

[0346] By implementing this system, users with hearing impairments can carry out their daily activities with peace of mind through feedback.

[0347] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0348] Step 1:

[0349] The device uses a microphone to collect ambient sounds and records them as acoustic data. This acoustic data is collected in real time and temporarily stored in the device's internal memory. The camera and sensors are activated to detect the user's facial expressions and voice tone, collecting emotional data. This emotional data is also temporarily stored within the device. Inputs include audio and images from the microphone and camera, while outputs are acoustic and emotional data for analysis.

[0350] Step 2:

[0351] The terminal transmits collected acoustic and emotional data to the server. A wireless communication module is used to transfer the data to the server in real time. The input consists of acoustic and emotional data within the terminal, and the output is the transfer of this data to the server.

[0352] Step 3:

[0353] The server inputs the received acoustic data into a generating AI model for analysis. This analysis process classifies the sounds into specific categories and identifies the types of sounds. Additionally, an emotion engine analyzes emotional data to identify the user's emotional state. The input consists of acoustic data and emotional data sent to the server, while the output is the identification of sound types and emotional states.

[0354] Step 4:

[0355] The server generates optimal text information using prompts based on the analysis results. For example, following a prompt such as "Check which sounds are being analyzed in the surroundings and generate optimal text based on the user's emotional state," the AI ​​model generates text corresponding to the sounds and emotions. The input is the type of sound and the emotional state, and the output is text information for the user.

[0356] Step 5:

[0357] The terminal receives text information sent from the server and displays it visually. It provides complementary feedback via vibration as needed. Input is text information from the server, and output is the presentation of visual and tactile information to the user. Specifically, the terminal displays messages on the screen and activates a vibration motor as needed.

[0358] (Application Example 2)

[0359] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0360] To make the virtual shopping experience more comfortable for users with hearing impairments, it is necessary not only to acquire and visualize ambient sound information but also to provide information tailored to the user's emotional state. However, current systems lack methods to appropriately recognize user emotions and optimize information, resulting in challenges in improving the ease of information reception and user satisfaction.

[0361] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0362] In this invention, the server includes means for analyzing acoustic information and identifying the type of sound, means for detecting the user's emotional state, and means for adjusting textual information based on the emotional state. This makes it possible to not only visualize acoustic information for users with hearing impairments, but also to provide optimal information tailored to the user's emotions.

[0363] "Acoustic information" refers to sound vibration data within a space, which is acquired through sensors such as microphones.

[0364] "Analysis" refers to the process of breaking down acquired acoustic information and emotional state data to clarify their characteristics and types.

[0365] "Sound type" refers to the distinction between ambient sounds, conversation sounds, alarm sounds, etc., identified from analyzed acoustic information, and classifies their properties.

[0366] "Textual information" refers to information in text format generated based on the type of sound analyzed, and is provided to the user as visual feedback.

[0367] "Emotional state" refers to the state of psychological emotions estimated from the user's facial expressions and voice, and includes emotions such as joy and anxiety.

[0368] "Adjustment" refers to modifying text information generated according to the user's emotional state, and displaying it in a way that is easiest for the user to understand and accept.

[0369] "Visually displaying" refers to providing generated text information in a way that users can see using a display device such as a screen.

[0370] "Vibration means" refers to a device or function that notifies the user through vibration as physical feedback based on generated text information.

[0371] This invention is a system aimed at enabling users with hearing impairments to comfortably enjoy shopping in virtual stores. The embodiments of this system will be described in detail below.

[0372] First, the user terminal is equipped with a microphone to acquire acoustic information and a camera to detect the user's emotional state. This terminal transmits the acoustic information and the user's emotional data to the server in real time.

[0373] The server performs a process of analyzing acoustic information and identifying the type of sound. This acoustic analysis utilizes cloud-based acoustic analysis AI (for example, a service that converts speech to text). Furthermore, the user's emotional state is analyzed using an emotion analysis engine (for example, a service that estimates emotions from facial expressions and voice). This analysis allows the server to identify the user's psychological state and generate emotionally appropriate feedback.

[0374] The generated text information is adjusted by the server based on the user's emotional state. For example, if the user is excited, the product recommendation list can be expanded and relaxing messages can be added. The adjusted text information is displayed visually on the user's terminal and, if necessary, physically notified by vibration. This allows the user to accurately perceive ambient sound information within the virtual store while receiving information tailored to their emotional state.

[0375] For example, even if a user has difficulty hearing announcements about special offers in the store, this system will display the offer information as text. Furthermore, if the user is emotionally unstable, a message such as "Please calm down and take a look" will be added to make the user experience more comfortable.

[0376] Furthermore, an example of a prompt to the generation AI model when building this system is, "Convert the surrounding audio into text and generate a message to display based on the user's emotional state." This ensures that the system functions properly and provides information that is relevant to the user's emotions.

[0377] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0378] Step 1:

[0379] The user terminal acquires ambient acoustic information using its built-in microphone. Simultaneously, it captures the user's facial expressions with a camera to acquire emotion data. This data is sent to the server as input. The output consists of the transmitted acoustic information and emotion data.

[0380] Step 2:

[0381] The server uses an acoustic analysis AI to analyze the received acoustic information. This analysis process classifies sounds based on their characteristics. The input is acoustic information, and the output is the identification of the type of sound. Specifically, it classifies common sounds such as ambient sounds and alarms.

[0382] Step 3:

[0383] Simultaneously, the server uses an emotion analysis engine to analyze the user's emotional data. The input data includes facial expressions and tone of voice. This process involves data processing to identify the user's emotional state as output. Emotional states are classified into categories such as excitement, anxiety, and joy.

[0384] Step 4:

[0385] The server generates and adjusts text information based on the identified sound type and the user's emotional state. In this step, the results of acoustic information analysis and emotion analysis are taken as input, and text information is created using a generative AI model. The output is the adjusted text information.

[0386] Step 5:

[0387] The adjusted text information is transmitted to the user's terminal. The terminal visually displays this text information on its screen. In addition, it provides physical notification to the user using vibration if necessary. This allows the user to receive information and announcements within the virtual store, improving the experience.

[0388] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0389] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0390] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0391] [Third Embodiment]

[0392] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0393] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0394] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0395] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0396] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0397] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0398] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0399] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0400] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0401] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0402] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0403] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0404] This invention provides a system that allows users with hearing impairments to visually obtain information about sound. The system is realized by collecting acoustic data, analyzing the sound to recognize specific types of sound, and providing the user with information in text format.

[0405] First, the user terminal uses a microphone to detect ambient sounds and acquires acoustic data. This data is then transmitted to the server in real time. The terminal uses an internet connection to transfer the data, ensuring that the audio data reaches the server efficiently.

[0406] The server receives acoustic data transmitted from the user's terminal. An AI model for speech recognition and analysis is built on the server to analyze the characteristics of each sound and classify it. By mapping sounds to specific categories, the server identifies the specific type of sound (e.g., car engine sound, ambulance siren sound, fire alarm sound, etc.).

[0407] Based on the analysis, the server generates text describing the identified sound types. This text is in a concise and easy-to-understand format, and the information is displayed visually through the user interface.

[0408] Next, the generated text information is sent back to the user's terminal and notified to the user. The notification is displayed as text on the screen and, in important cases, is also provided as feedback via vibration. For example, if the terminal detects a sound that is the siren of an emergency vehicle, the terminal will display "Emergency vehicle approaching" and warn the user with vibration.

[0409] For example, when a device detects the sound of a car engine, the server analyzes the sound and generates the text "Engine started." This allows the user to instantly receive auditory information about the engine sound as visual information.

[0410] This system is designed to enable users with hearing impairments to live safely and to quickly obtain important auditory information, especially in their daily lives.

[0411] The following describes the processing flow.

[0412] Step 1:

[0413] The user terminal samples ambient sound using its built-in microphone and periodically saves the audio data to a buffer. The saved audio data is then prepared for processing in short timeframes.

[0414] Step 2:

[0415] The user terminal converts buffered voice data into packets at regular intervals (e.g., every 2 seconds) and sends them to the server over the internet. Data transfer is designed to minimize communication delays.

[0416] Step 3:

[0417] The server receives audio data packets from the user's terminal and inputs the data into the AI ​​speech recognition model. The speech recognition model analyzes the characteristics of the data and extracts the sound features.

[0418] Step 4:

[0419] The server classifies the data into specific categories (e.g., engine sounds, siren sounds) based on the characteristics of the analyzed sound. Based on this classification information, it generates text information corresponding to the type of sound recognized.

[0420] Step 5:

[0421] The server sends the generated text information to the user's terminal using a lightweight communication protocol (e.g., JSON). The information is transferred quickly and can be received by the user immediately.

[0422] Step 6:

[0423] The user terminal processes text information received from the server and displays it on the user interface. The information is organized and displayed on the screen in a visually easy-to-understand manner.

[0424] Step 7:

[0425] The user's device uses additional notification methods (vibration or alarm) depending on the importance of the information to alert the user. In urgent situations, vibration and other functions are used to complement visual notifications.

[0426] In this way, users can obtain important information about sound visually and tactilely, enabling them to make appropriate judgments and take appropriate actions.

[0427] (Example 1)

[0428] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0429] There is a need for a system that allows users with hearing impairments to safely and quickly obtain auditory information and support important decision-making in daily life. However, conventional technologies are insufficient in identifying sounds and providing information, and a more accurate means of information transmission is required.

[0430] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0431] In this invention, the server includes a device for collecting sound wave data, a device for analyzing the collected sound wave data and identifying sound attributes, and a device for generating textual information based on the identified sound attributes. This enables users with hearing impairments to instantly understand the characteristics of various sounds and quickly obtain visual information.

[0432] "Sound wave data" refers to information obtained by acquiring and recording ambient sounds as digital signals.

[0433] "Device" refers to a configuration that includes hardware or software for performing a specific function.

[0434] "Analysis" refers to the process of extracting features from data and converting them into information that is appropriate for a specific purpose.

[0435] "Sound attributes" refer to identifiable features used to identify and classify the type and characteristics of a sound.

[0436] "Identification" refers to distinguishing items from analyzed data that meet specific criteria.

[0437] "Textual information" refers to a string of characters that is understandable to humans and generated based on the analysis results.

[0438] "To output information visually" means to display information visually and provide it in a way that users can see and understand.

[0439] A "computer system" refers to a collection of hardware and software that allows various devices to work together to perform a specific task.

[0440] "Classification" refers to the process of assigning analyzed data to predefined categories.

[0441] "To inform" refers to notifying the target person of information and urging them to pay attention.

[0442] A "vibration device" refers to a device that has the function of transmitting information to the user by utilizing physical vibrations.

[0443] This invention is a system that allows users with hearing impairments to visually acquire information about their surrounding sounds. Specifically, it consists of a user terminal, a server, and software corresponding to each of these functions.

[0444] The user terminal acquires sound wave data using a built-in or external microphone. The acquired data is transmitted to the server via wireless communication technology (e.g., Wi-Fi or Bluetooth). The data is transferred in real time, and data compression techniques are used to minimize latency.

[0445] The server is equipped with a generative AI model for analyzing received sound wave data. This AI model uses data analysis algorithms to identify sound attributes and categorize sounds into specific groups. Sound attributes include frequency components, volume, tone, etc. Based on the analysis results, the server generates textual information that describes the identified sound attributes. The generated textual information is then formatted using natural language processing techniques to create a concise and user-friendly format.

[0446] The generated text information is sent back to the user's terminal and displayed visually on the screen. Simultaneously, the terminal's vibration device is used to notify the user of important information. This vibration device attracts the user's attention, especially when there is highly urgent information.

[0447] As a concrete example, consider a scenario where a user's device detects the sound of a car engine. This sound is sent to a server, where a generative AI model generates the text message "Engine started." This allows the user to visually obtain this information immediately.

[0448] Examples of prompts to input into a generative AI model include "Analyze this sound data and tell me what kind of sound it is" and "Classify the following sounds and generate text to provide to the user."

[0449] This system transmits auditory information to the user through sight and touch, enabling users with hearing impairments to live their daily lives safely and comfortably.

[0450] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0451] Step 1:

[0452] The device acquires ambient sound wave data through its built-in microphone. This sound wave data is input as an analog signal and converted into digital data through digital signal processing. Specifically, the sound waves are sampled, quantized, and output as binary data.

[0453] Step 2:

[0454] The terminal transmits the acquired digital sound wave data to the server via the internet. By applying a data compression algorithm before transmission, unnecessary data is removed, resulting in efficient data transfer. This step is completed when the compressed digital data reaches the server.

[0455] Step 3:

[0456] The server decompresses the received compressed digital data and performs audio analysis. The sound wave data is input to an AI model, which analyzes the characteristics of the sound. Specifically, it extracts features such as frequency components, volume, and tone, identifies the data based on these, and outputs the attributes of a specific sound.

[0457] Step 4:

[0458] The server inputs data into a classification algorithm based on the sound's attributes, classifying the sound into a specific category (e.g., car engine sound, siren sound, etc.). After the classification process, qualitative data output regarding the sound category is obtained.

[0459] Step 5:

[0460] The server generates text information for the user based on the identified sound category information. A generative AI model uses natural language processing to create descriptive text. Specifically, text such as "Vehicle engine started" or "Emergency vehicle approaching" is generated and prepared to be sent from the server to the terminal.

[0461] Step 6:

[0462] The device receives text information sent from the server and displays it on the screen. The display format is optimized so that the user can visually confirm this information. Additionally, in the case of important notifications, the device's vibration function activates to provide tactile feedback to the user.

[0463] Step 7:

[0464] Users receive textual information and vibrations displayed on their devices, allowing them to instantly understand auditory information through both sight and touch. This process enables them to accurately perceive auditory information in their daily lives and take necessary actions quickly.

[0465] (Application Example 1)

[0466] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0467] In autonomous vehicles, passengers with hearing impairments may be unable to perceive important auditory information from their surroundings, compromising safety and a sense of security. Therefore, a system is needed that can visually and effectively communicate audible warnings tailored to the vehicle's situation.

[0468] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0469] In this invention, the server includes means for acquiring acoustic signals, means for analyzing the acquired acoustic signals and identifying the type of sound, and means for generating textual information based on the identified type of sound. This makes it possible for passengers with hearing impairments in an autonomous vehicle to visually obtain surrounding acoustic information and enhance their awareness of important situations.

[0470] An "acoustic signal" is a signal that converts ambient sound into an electrical signal and makes it into an analyzable format.

[0471] A "sound type" is a classification of sound based on analyzed acoustic signals.

[0472] "Character information" refers to visual string information generated based on a specific type of sound.

[0473] "Vibration means" refers to means of generating vibrations to attract the attention of passengers based on a specified audible warning.

[0474] "Means of visual display" refers to means of visually showing generated textual information through a display or similar device.

[0475] The system implementing this invention aims to provide safe travel for passengers with hearing impairments by acquiring and analyzing acoustic signals to generate textual information and presenting it visually to the user.

[0476] The terminal is equipped with a high-sensitivity microphone that captures ambient sounds as acoustic signals. These acoustic signals are transmitted to a server in real time. The server receives the acoustic signals and uses an AI model and a speech analysis engine (e.g., TensorFlow or PyTorch) to analyze them and identify the type of sound. This allows for the identification of specific acoustic warnings (e.g., ambulance sirens, collision avoidance alarms).

[0477] Subsequently, the server generates text information based on the identified sound type and sends the generated text information to the terminal. The terminal visually displays the received text information on its screen and, if necessary, uses vibration to warn the user. This allows users to obtain important ambient sound information without relying on their hearing.

[0478] As a concrete example, if an autonomous vehicle detects an ambulance siren while passing through an intersection, the system will generate text information such as "An ambulance is approaching" and display it on the screen. The terminal will also vibrate slightly to alert the passenger. An example of a prompt message to be input to the generation AI model used in this case is: "Analyze the surrounding sounds as auditory data and generate the following warning message: An ambulance siren has been detected."

[0479] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0480] Step 1:

[0481] The device uses a microphone to pick up ambient sounds and converts them into digital data as acoustic signals. This digital data becomes the input. The device then sends this acoustic signal to the server.

[0482] Step 2:

[0483] The server receives acoustic signals transmitted from the terminal. Based on this input, the server analyzes the acoustic signals using an AI model (e.g., TensorFlow or PyTorch). Data calculations include spectral analysis of the sound to identify the type of sound and determine the category of the sound. The output is information about the identified type of sound.

[0484] Step 3:

[0485] The server generates text information based on the identified sound type. The input is the sound type identified in the previous step, and the output is text information to notify the user. A generative AI model is used to convert the data into text. A prompt sentence is used as input to the model; for example, "Analyze ambient sounds as auditory data and generate the following warning message: Ambulance siren sound detected."

[0486] Step 4:

[0487] The server sends the generated character information to the terminal. The input is the generated character information, and the output is a notification message sent to the terminal.

[0488] Step 5:

[0489] The terminal visually displays received text information on its screen. Furthermore, if the sound type indicates a warning is necessary, the terminal uses vibration to trigger the warning. Input is text information notification from the server, and output is display and vibration. For example, the screen might display "Ambulance approaching," and the terminal would vibrate slightly to alert the user.

[0490] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0491] This invention combines a system for visually acquiring sound-related information for users with hearing impairments with an emotion engine to provide information tailored to the user's emotional state. The basic system configuration involves acquiring, analyzing, visualizing, and notifying the user of acoustic data, but it also enables sensing the user's emotions and optimizing the response.

[0492] First, the user's device collects ambient sounds using a microphone and acquires acoustic data. This data is transmitted to the server in real time. During this process, the device also collects data to recognize the user's emotions. For example, emotions are estimated from facial expressions and tone of voice via the camera and microphone.

[0493] The server analyzes the acoustic data transmitted from the terminal using an AI model. Here, the sounds are classified into specific categories and the type of sound is identified. Furthermore, the emotion engine analyzes the emotional data from the user and identifies the emotional state. The emotion engine recognizes basic emotions such as joy, sadness, and surprise, and determines what kind of feedback is optimal.

[0494] Based on the analysis results, the server adjusts the generated text information. For example, if a user is feeling anxious, reassuring information can be added. This text information is displayed visually through the user interface. In addition to providing regular information, the generated information is presented in a format that is most easily received by the user.

[0495] Ultimately, the user device receives the generated text information and provides optimal visual feedback based on the user's emotional state, and potentially supplementary information through vibration. For example, if an emergency warning sound is detected and the user is startled, the device might display a message such as "Please be careful, stay calm" and vibrate to further alert the user.

[0496] In this way, the present invention not only provides users with hearing impairments with information about the type of sound, but also has a form that enables flexible responses in accordance with their emotions. This can improve the user's safety and quality of life.

[0497] The following describes the processing flow.

[0498] Step 1:

[0499] The user terminal samples ambient sounds using its built-in microphone and stores the acoustic data in a buffer. It also captures the user's facial expressions and voice tone using a camera and voice input to acquire emotional data.

[0500] Step 2:

[0501] The user terminal packets the acquired acoustic and emotional data at specific time intervals and sends them to the server. This transmission process is performed in real time, ensuring that all data is transferred without fail.

[0502] Step 3:

[0503] The server inputs acoustic data into a speech recognition model and analyzes the characteristics of the sounds in the data. It extracts sound features from the analysis results and classifies the sounds into specific categories based on them.

[0504] Step 4:

[0505] The server inputs emotional data into the emotion engine to recognize the user's emotional state. The emotion engine analyzes multiple emotional components to identify major emotions such as joy, sadness, and surprise.

[0506] Step 5:

[0507] The server integrates the analyzed sound type with the user's emotional state to optimize the generated text information. For example, if a warning sound is analyzed and the server recognizes that the user is surprised, it will generate a message such as "Please stay calm and evacuate."

[0508] Step 6:

[0509] The server sends optimized text information to the user's terminal. This communication is rapid, minimizing information delays.

[0510] Step 7:

[0511] The user terminal processes text information received from the server and displays it on the user interface. The information is visually highlighted with colors and icons corresponding to the user's emotional state.

[0512] Step 8:

[0513] The user's device will notify them using vibration as needed. Effective feedback tailored to urgency and emotion is implemented to ensure the user's attention is captured.

[0514] Through this series of processes, the system makes it easier for the user to understand surrounding sound information and provides considerate responses that are tailored to their emotions.

[0515] (Example 2)

[0516] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0517] For users with hearing impairments to obtain real-time information about sound and take appropriate action based on that information, feedback is needed that takes into account not only the surrounding acoustic conditions but also their own emotional state. However, existing technologies only identify and visually display the type of sound, and are not sufficient to provide information that takes into account the user's emotional changes. Furthermore, there has been a challenge in adequately addressing situations where immediacy and ease of understanding are required in information provision.

[0518] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0519] In this invention, the server includes means for acquiring acoustic data, means for analyzing the acquired acoustic data and identifying the type of sound, means for analyzing the user's facial expressions and voice data and identifying their emotional state, means for generating text information based on the identified type of sound and emotional state, means for visually displaying the generated text information, and means for additionally providing the generated text information as vibrations. This enables a user with a hearing impairment to instantly grasp the type of sound and provide visual and tactile feedback that takes into account their emotional response to that sound.

[0520] "Acoustic data" refers to information about sound acquired from the surrounding environment, and is collected in a format that can be processed as an electronic signal.

[0521] "Analysis" refers to the process of processing collected acoustic and emotional data to extract specific information, and is carried out using generative AI models.

[0522] "Emotional state" refers to information that indicates the user's current psychological response, and is estimated from facial expressions and tone of voice.

[0523] "Text information" refers to visual textual information generated based on analyzed acoustic data and emotional states, and is provided in a format that is easy for the user to understand.

[0524] "Visual display" refers to the act of showing generated text information to the user via a display or screen.

[0525] "Provided as vibration" refers to a means of conveying generated information to the user through vibration, and is used as haptic feedback.

[0526] This invention is a system for users with hearing impairments to visually acquire information about their surroundings and receive emotionally responsive feedback. Users can receive information on a daily basis using a special terminal. This document describes the specific hardware and software used, as well as the data processing procedures.

[0527] The device uses a microphone to collect ambient sounds in real time. This data is temporarily stored in the device's internal memory as acoustic data. Simultaneously, it uses a camera and additional sensors to detect the user's facial expressions and voice tone, collecting this as emotion data. The device uses a wireless communication module to transmit this data to a server.

[0528] The server analyzes the received acoustic data using a generative AI model. This analysis classifies the sounds into specific types and, if necessary, into categories. Furthermore, an emotion engine analyzes the user's emotional data to identify emotional states such as joy, sadness, and surprise. Based on these analysis results, the server generates optimal text information according to the prompt.

[0529] For example, if the sound of a dog barking is detected while walking in a park, the user's surprise is estimated. When the sound is identified as "dog barking," the server generates a message saying, "It looks like you're playing with your dog. Please stay calm and enjoy yourself." This message is sent back to the user's device, where it is displayed visually and the device vibrates slightly to attract the user's attention.

[0530] An example of a prompt to input into the generation AI model would be something like, "Check which sounds are being analyzed in the surroundings and generate the most appropriate text based on the user's emotional state."

[0531] By implementing this system, users with hearing impairments can carry out their daily activities with peace of mind through feedback.

[0532] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0533] Step 1:

[0534] The device uses a microphone to collect ambient sounds and records them as acoustic data. This acoustic data is collected in real time and temporarily stored in the device's internal memory. The camera and sensors are activated to detect the user's facial expressions and voice tone, collecting emotional data. This emotional data is also temporarily stored within the device. Inputs include audio and images from the microphone and camera, while outputs are acoustic and emotional data for analysis.

[0535] Step 2:

[0536] The terminal transmits collected acoustic and emotional data to the server. A wireless communication module is used to transfer the data to the server in real time. The input consists of acoustic and emotional data within the terminal, and the output is the transfer of this data to the server.

[0537] Step 3:

[0538] The server inputs the received acoustic data into a generating AI model for analysis. This analysis process classifies the sounds into specific categories and identifies the types of sounds. Additionally, an emotion engine analyzes emotional data to identify the user's emotional state. The input consists of acoustic data and emotional data sent to the server, while the output is the identification of sound types and emotional states.

[0539] Step 4:

[0540] The server generates optimal text information using prompts based on the analysis results. For example, following a prompt such as "Check which sounds are being analyzed in the surroundings and generate optimal text based on the user's emotional state," the AI ​​model generates text corresponding to the sounds and emotions. The input is the type of sound and the emotional state, and the output is text information for the user.

[0541] Step 5:

[0542] The terminal receives text information sent from the server and displays it visually. It provides complementary feedback via vibration as needed. Input is text information from the server, and output is the presentation of visual and tactile information to the user. Specifically, the terminal displays messages on the screen and activates a vibration motor as needed.

[0543] (Application Example 2)

[0544] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0545] To make the virtual shopping experience more comfortable for users with hearing impairments, it is necessary not only to acquire and visualize ambient sound information but also to provide information tailored to the user's emotional state. However, current systems lack methods to appropriately recognize user emotions and optimize information, resulting in challenges in improving the ease of information reception and user satisfaction.

[0546] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0547] In this invention, the server includes means for analyzing acoustic information and identifying the type of sound, means for detecting the user's emotional state, and means for adjusting textual information based on the emotional state. This makes it possible to not only visualize acoustic information for users with hearing impairments, but also to provide optimal information tailored to the user's emotions.

[0548] "Acoustic information" refers to sound vibration data within a space, which is acquired through sensors such as microphones.

[0549] "Analysis" refers to the process of breaking down acquired acoustic information and emotional state data to clarify their characteristics and types.

[0550] "Sound type" refers to the distinction between ambient sounds, conversation sounds, alarm sounds, etc., identified from analyzed acoustic information, and classifies their properties.

[0551] "Textual information" refers to information in text format generated based on the type of sound analyzed, and is provided to the user as visual feedback.

[0552] "Emotional state" refers to the state of psychological emotions estimated from the user's facial expressions and voice, and includes emotions such as joy and anxiety.

[0553] "Adjustment" refers to modifying text information generated according to the user's emotional state, and displaying it in a way that is easiest for the user to understand and accept.

[0554] "Visually displaying" refers to providing generated text information in a way that users can see using a display device such as a screen.

[0555] "Vibration means" refers to a device or function that notifies the user through vibration as physical feedback based on generated text information.

[0556] This invention is a system aimed at enabling users with hearing impairments to comfortably enjoy shopping in virtual stores. The embodiments of this system will be described in detail below.

[0557] First, the user terminal is equipped with a microphone to acquire acoustic information and a camera to detect the user's emotional state. This terminal transmits the acoustic information and the user's emotional data to the server in real time.

[0558] The server performs a process of analyzing acoustic information and identifying the type of sound. This acoustic analysis utilizes cloud-based acoustic analysis AI (for example, a service that converts speech to text). Furthermore, the user's emotional state is analyzed using an emotion analysis engine (for example, a service that estimates emotions from facial expressions and voice). This analysis allows the server to identify the user's psychological state and generate emotionally appropriate feedback.

[0559] The generated text information is adjusted by the server based on the user's emotional state. For example, if the user is excited, the product recommendation list can be expanded and relaxing messages can be added. The adjusted text information is displayed visually on the user's terminal and, if necessary, physically notified by vibration. This allows the user to accurately perceive ambient sound information within the virtual store while receiving information tailored to their emotional state.

[0560] For example, even if a user has difficulty hearing announcements about special offers in the store, this system will display the offer information as text. Furthermore, if the user is emotionally unstable, a message such as "Please calm down and take a look" will be added to make the user experience more comfortable.

[0561] Furthermore, an example of a prompt to the generation AI model when building this system is, "Convert the surrounding audio into text and generate a message to display based on the user's emotional state." This ensures that the system functions properly and provides information that is relevant to the user's emotions.

[0562] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0563] Step 1:

[0564] The user terminal acquires ambient acoustic information using its built-in microphone. Simultaneously, it captures the user's facial expressions with a camera to acquire emotion data. This data is sent to the server as input. The output consists of the transmitted acoustic information and emotion data.

[0565] Step 2:

[0566] The server uses an acoustic analysis AI to analyze the received acoustic information. This analysis process classifies sounds based on their characteristics. The input is acoustic information, and the output is the identification of the type of sound. Specifically, it classifies common sounds such as ambient sounds and alarms.

[0567] Step 3:

[0568] Simultaneously, the server uses an emotion analysis engine to analyze the user's emotional data. The input data includes facial expressions and tone of voice. This process involves data processing to identify the user's emotional state as output. Emotional states are classified into categories such as excitement, anxiety, and joy.

[0569] Step 4:

[0570] The server generates and adjusts text information based on the identified sound type and the user's emotional state. In this step, the results of acoustic information analysis and emotion analysis are taken as input, and text information is created using a generative AI model. The output is the adjusted text information.

[0571] Step 5:

[0572] The adjusted text information is transmitted to the user's terminal. The terminal visually displays this text information on its screen. In addition, it provides physical notification to the user using vibration if necessary. This allows the user to receive information and announcements within the virtual store, improving the experience.

[0573] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0574] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0575] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0576] [Fourth Embodiment]

[0577] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0578] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0579] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0580] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0581] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0582] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0583] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0584] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors in the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0585] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0586] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0587] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0588] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0589] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0590] This invention provides a system that allows users with hearing impairments to visually obtain information about sound. The system is realized by collecting acoustic data, analyzing the sound to recognize specific types of sound, and providing the user with information in text format.

[0591] First, the user terminal uses a microphone to detect ambient sounds and acquires acoustic data. This data is then transmitted to the server in real time. The terminal uses an internet connection to transfer the data, ensuring that the audio data reaches the server efficiently.

[0592] The server receives acoustic data transmitted from the user's terminal. An AI model for speech recognition and analysis is built on the server to analyze the characteristics of each sound and classify it. By mapping sounds to specific categories, the server identifies the specific type of sound (e.g., car engine sound, ambulance siren sound, fire alarm sound, etc.).

[0593] Based on the analysis, the server generates text describing the identified sound types. This text is in a concise and easy-to-understand format, and the information is displayed visually through the user interface.

[0594] Next, the generated text information is sent back to the user's terminal and notified to the user. The notification is displayed as text on the screen and, in important cases, is also provided as feedback via vibration. For example, if the terminal detects a sound that is the siren of an emergency vehicle, the terminal will display "Emergency vehicle approaching" and warn the user with vibration.

[0595] For example, when a device detects the sound of a car engine, the server analyzes the sound and generates the text "Engine started." This allows the user to instantly receive auditory information about the engine sound as visual information.

[0596] This system is designed to enable users with hearing impairments to live safely and to quickly obtain important auditory information, especially in their daily lives.

[0597] The following describes the processing flow.

[0598] Step 1:

[0599] The user terminal samples ambient sound using its built-in microphone and periodically saves the audio data to a buffer. The saved audio data is then prepared for processing in short timeframes.

[0600] Step 2:

[0601] The user terminal converts buffered voice data into packets at regular intervals (e.g., every 2 seconds) and sends them to the server over the internet. Data transfer is designed to minimize communication delays.

[0602] Step 3:

[0603] The server receives audio data packets from the user's terminal and inputs the data into the AI ​​speech recognition model. The speech recognition model analyzes the characteristics of the data and extracts the sound features.

[0604] Step 4:

[0605] The server classifies the data into specific categories (e.g., engine sounds, siren sounds) based on the characteristics of the analyzed sound. Based on this classification information, it generates text information corresponding to the type of sound recognized.

[0606] Step 5:

[0607] The server sends the generated text information to the user's terminal using a lightweight communication protocol (e.g., JSON). The information is transferred quickly and can be received by the user immediately.

[0608] Step 6:

[0609] The user terminal processes text information received from the server and displays it on the user interface. The information is organized and displayed on the screen in a visually easy-to-understand manner.

[0610] Step 7:

[0611] The user's device uses additional notification methods (vibration or alarm) depending on the importance of the information to alert the user. In urgent situations, vibration and other functions are used to complement visual notifications.

[0612] In this way, users can obtain important information about sound visually and tactilely, enabling them to make appropriate judgments and take appropriate actions.

[0613] (Example 1)

[0614] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0615] There is a need for a system that allows users with hearing impairments to safely and quickly obtain auditory information and support important decision-making in daily life. However, conventional technologies are insufficient in identifying sounds and providing information, and a more accurate means of information transmission is required.

[0616] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0617] In this invention, the server includes a device for collecting sound wave data, a device for analyzing the collected sound wave data and identifying sound attributes, and a device for generating textual information based on the identified sound attributes. This enables users with hearing impairments to instantly understand the characteristics of various sounds and quickly obtain visual information.

[0618] "Sound wave data" refers to information obtained by acquiring and recording ambient sounds as digital signals.

[0619] "Device" refers to a configuration that includes hardware or software for performing a specific function.

[0620] "Analysis" refers to the process of extracting features from data and converting them into information that is appropriate for a specific purpose.

[0621] "Sound attributes" refer to identifiable features used to identify and classify the type and characteristics of a sound.

[0622] "Identification" refers to distinguishing items from analyzed data that meet specific criteria.

[0623] "Textual information" refers to a string of characters that is understandable to humans and generated based on the analysis results.

[0624] "To output information visually" means to display information visually and provide it in a way that users can see and understand.

[0625] A "computer system" refers to a collection of hardware and software that allows various devices to work together to perform a specific task.

[0626] "Classification" refers to the process of assigning analyzed data to predefined categories.

[0627] "To inform" refers to notifying the target person of information and urging them to pay attention.

[0628] A "vibration device" refers to a device that has the function of transmitting information to the user by utilizing physical vibrations.

[0629] This invention is a system that allows users with hearing impairments to visually acquire information about their surrounding sounds. Specifically, it consists of a user terminal, a server, and software corresponding to each of these functions.

[0630] The user terminal acquires sound wave data using a built-in or external microphone. The acquired data is transmitted to the server via wireless communication technology (e.g., Wi-Fi or Bluetooth). The data is transferred in real time, and data compression techniques are used to minimize latency.

[0631] The server is equipped with a generative AI model for analyzing received sound wave data. This AI model uses data analysis algorithms to identify sound attributes and categorize sounds into specific groups. Sound attributes include frequency components, volume, tone, etc. Based on the analysis results, the server generates textual information that describes the identified sound attributes. The generated textual information is then formatted using natural language processing techniques to create a concise and user-friendly format.

[0632] The generated text information is sent back to the user's terminal and displayed visually on the screen. Simultaneously, the terminal's vibration device is used to notify the user of important information. This vibration device attracts the user's attention, especially when there is highly urgent information.

[0633] As a concrete example, consider a scenario where a user's device detects the sound of a car engine. This sound is sent to a server, where a generative AI model generates the text message "Engine started." This allows the user to visually obtain this information immediately.

[0634] Examples of prompts to input into a generative AI model include "Analyze this sound data and tell me what kind of sound it is" and "Classify the following sounds and generate text to provide to the user."

[0635] This system transmits auditory information to the user through sight and touch, enabling users with hearing impairments to live their daily lives safely and comfortably.

[0636] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0637] Step 1:

[0638] The device acquires ambient sound wave data through its built-in microphone. This sound wave data is input as an analog signal and converted into digital data through digital signal processing. Specifically, the sound waves are sampled, quantized, and output as binary data.

[0639] Step 2:

[0640] The terminal transmits the acquired digital sound wave data to the server via the internet. By applying a data compression algorithm before transmission, unnecessary data is removed, resulting in efficient data transfer. This step is completed when the compressed digital data reaches the server.

[0641] Step 3:

[0642] The server decompresses the received compressed digital data and performs audio analysis. The sound wave data is input to an AI model, which analyzes the characteristics of the sound. Specifically, it extracts features such as frequency components, volume, and tone, identifies the data based on these, and outputs the attributes of a specific sound.

[0643] Step 4:

[0644] The server inputs data into a classification algorithm based on the sound's attributes, classifying the sound into a specific category (e.g., car engine sound, siren sound, etc.). After the classification process, qualitative data output regarding the sound category is obtained.

[0645] Step 5:

[0646] The server generates text information for the user based on the identified sound category information. A generative AI model uses natural language processing to create descriptive text. Specifically, text such as "Vehicle engine started" or "Emergency vehicle approaching" is generated and prepared to be sent from the server to the terminal.

[0647] Step 6:

[0648] The device receives text information sent from the server and displays it on the screen. The display format is optimized so that the user can visually confirm this information. Additionally, in the case of important notifications, the device's vibration function activates to provide tactile feedback to the user.

[0649] Step 7:

[0650] Users receive textual information and vibrations displayed on their devices, allowing them to instantly understand auditory information through both sight and touch. This process enables them to accurately perceive auditory information in their daily lives and take necessary actions quickly.

[0651] (Application Example 1)

[0652] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0653] In autonomous vehicles, passengers with hearing impairments may be unable to perceive important auditory information from their surroundings, compromising safety and a sense of security. Therefore, a system is needed that can visually and effectively communicate audible warnings tailored to the vehicle's situation.

[0654] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0655] In this invention, the server includes means for acquiring acoustic signals, means for analyzing the acquired acoustic signals and identifying the type of sound, and means for generating textual information based on the identified type of sound. This makes it possible for passengers with hearing impairments in an autonomous vehicle to visually obtain surrounding acoustic information and enhance their awareness of important situations.

[0656] An "acoustic signal" is a signal that converts ambient sound into an electrical signal and makes it into an analyzable format.

[0657] A "sound type" is a classification of sound based on analyzed acoustic signals.

[0658] "Character information" refers to visual string information generated based on a specific type of sound.

[0659] "Vibration means" refers to means of generating vibrations to attract the attention of passengers based on a specified audible warning.

[0660] "Means of visual display" refers to means of visually showing generated textual information through a display or similar device.

[0661] The system implementing this invention aims to provide safe travel for passengers with hearing impairments by acquiring and analyzing acoustic signals to generate textual information and presenting it visually to the user.

[0662] The terminal is equipped with a high-sensitivity microphone that captures ambient sounds as acoustic signals. These acoustic signals are transmitted to a server in real time. The server receives the acoustic signals and uses an AI model and a speech analysis engine (e.g., TensorFlow or PyTorch) to analyze them and identify the type of sound. This allows for the identification of specific acoustic warnings (e.g., ambulance sirens, collision avoidance alarms).

[0663] Subsequently, the server generates text information based on the identified sound type and sends the generated text information to the terminal. The terminal visually displays the received text information on its screen and, if necessary, uses vibration to warn the user. This allows users to obtain important ambient sound information without relying on their hearing.

[0664] As a concrete example, if an autonomous vehicle detects an ambulance siren while passing through an intersection, the system will generate text information such as "An ambulance is approaching" and display it on the screen. The terminal will also vibrate slightly to alert the passenger. An example of a prompt message to be input to the generation AI model used in this case is: "Analyze the surrounding sounds as auditory data and generate the following warning message: An ambulance siren has been detected."

[0665] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0666] Step 1:

[0667] The device uses a microphone to pick up ambient sounds and converts them into digital data as acoustic signals. This digital data becomes the input. The device then sends this acoustic signal to the server.

[0668] Step 2:

[0669] The server receives acoustic signals transmitted from the terminal. Based on this input, the server analyzes the acoustic signals using an AI model (e.g., TensorFlow or PyTorch). Data calculations include spectral analysis of the sound to identify the type of sound and determine the category of the sound. The output is information about the identified type of sound.

[0670] Step 3:

[0671] The server generates text information based on the identified sound type. The input is the sound type identified in the previous step, and the output is text information to notify the user. A generative AI model is used to convert the data into text. A prompt sentence is used as input to the model; for example, "Analyze ambient sounds as auditory data and generate the following warning message: Ambulance siren sound detected."

[0672] Step 4:

[0673] The server sends the generated character information to the terminal. The input is the generated character information, and the output is a notification message sent to the terminal.

[0674] Step 5:

[0675] The terminal visually displays received text information on its screen. Furthermore, if the sound type indicates a warning is necessary, the terminal uses vibration to trigger the warning. Input is text information notification from the server, and output is display and vibration. For example, the screen might display "Ambulance approaching," and the terminal would vibrate slightly to alert the user.

[0676] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0677] This invention combines a system for visually acquiring sound-related information for users with hearing impairments with an emotion engine to provide information tailored to the user's emotional state. The basic system configuration involves acquiring, analyzing, visualizing, and notifying the user of acoustic data, but it also enables sensing the user's emotions and optimizing the response.

[0678] First, the user's device collects ambient sounds using a microphone and acquires acoustic data. This data is transmitted to the server in real time. During this process, the device also collects data to recognize the user's emotions. For example, emotions are estimated from facial expressions and tone of voice via the camera and microphone.

[0679] The server analyzes the acoustic data transmitted from the terminal using an AI model. Here, the sounds are classified into specific categories and the type of sound is identified. Furthermore, the emotion engine analyzes the emotional data from the user and identifies the emotional state. The emotion engine recognizes basic emotions such as joy, sadness, and surprise, and determines what kind of feedback is optimal.

[0680] Based on the analysis results, the server adjusts the generated text information. For example, if a user is feeling anxious, reassuring information can be added. This text information is displayed visually through the user interface. In addition to providing regular information, the generated information is presented in a format that is most easily received by the user.

[0681] Ultimately, the user device receives the generated text information and provides optimal visual feedback based on the user's emotional state, and potentially supplementary information through vibration. For example, if an emergency warning sound is detected and the user is startled, the device might display a message such as "Please be careful, stay calm" and vibrate to further alert the user.

[0682] In this way, the present invention not only provides users with hearing impairments with information about the type of sound, but also has a form that enables flexible responses in accordance with their emotions. This can improve the user's safety and quality of life.

[0683] The following describes the processing flow.

[0684] Step 1:

[0685] The user terminal samples ambient sounds using its built-in microphone and stores the acoustic data in a buffer. It also captures the user's facial expressions and voice tone using a camera and voice input to acquire emotional data.

[0686] Step 2:

[0687] The user terminal packets the acquired acoustic and emotional data at specific time intervals and sends them to the server. This transmission process is performed in real time, ensuring that all data is transferred without fail.

[0688] Step 3:

[0689] The server inputs acoustic data into a speech recognition model and analyzes the characteristics of the sounds in the data. It extracts sound features from the analysis results and classifies the sounds into specific categories based on them.

[0690] Step 4:

[0691] The server inputs emotional data into the emotion engine to recognize the user's emotional state. The emotion engine analyzes multiple emotional components to identify major emotions such as joy, sadness, and surprise.

[0692] Step 5:

[0693] The server integrates the analyzed sound type with the user's emotional state to optimize the generated text information. For example, if a warning sound is analyzed and the server recognizes that the user is surprised, it will generate a message such as "Please stay calm and evacuate."

[0694] Step 6:

[0695] The server sends optimized text information to the user's terminal. This communication is rapid, minimizing information delays.

[0696] Step 7:

[0697] The user terminal processes text information received from the server and displays it on the user interface. The information is visually highlighted with colors and icons corresponding to the user's emotional state.

[0698] Step 8:

[0699] The user's device will notify them using vibration as needed. Effective feedback tailored to urgency and emotion is implemented to ensure the user's attention is captured.

[0700] Through this series of processes, the system makes it easier for the user to understand surrounding sound information and provides considerate responses that are tailored to their emotions.

[0701] (Example 2)

[0702] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0703] For users with hearing impairments to obtain real-time information about sound and take appropriate action based on that information, feedback is needed that takes into account not only the surrounding acoustic conditions but also their own emotional state. However, existing technologies only identify and visually display the type of sound, and are not sufficient to provide information that takes into account the user's emotional changes. Furthermore, there has been a challenge in adequately addressing situations where immediacy and ease of understanding are required in information provision.

[0704] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0705] In this invention, the server includes means for acquiring acoustic data, means for analyzing the acquired acoustic data and identifying the type of sound, means for analyzing the user's facial expressions and voice data and identifying their emotional state, means for generating text information based on the identified type of sound and emotional state, means for visually displaying the generated text information, and means for additionally providing the generated text information as vibrations. This enables a user with a hearing impairment to instantly grasp the type of sound and provide visual and tactile feedback that takes into account their emotional response to that sound.

[0706] "Acoustic data" refers to information about sound acquired from the surrounding environment, and is collected in a format that can be processed as an electronic signal.

[0707] "Analysis" refers to the process of processing collected acoustic and emotional data to extract specific information, and is carried out using generative AI models.

[0708] "Emotional state" refers to information that indicates the user's current psychological response, and is estimated from facial expressions and tone of voice.

[0709] "Text information" refers to visual textual information generated based on analyzed acoustic data and emotional states, and is provided in a format that is easy for the user to understand.

[0710] "Visual display" refers to the act of showing generated text information to the user via a display or screen.

[0711] "Provided as vibration" refers to a means of conveying generated information to the user through vibration, and is used as haptic feedback.

[0712] This invention is a system for users with hearing impairments to visually acquire information about their surroundings and receive emotionally responsive feedback. Users can receive information on a daily basis using a special terminal. This document describes the specific hardware and software used, as well as the data processing procedures.

[0713] The device uses a microphone to collect ambient sounds in real time. This data is temporarily stored in the device's internal memory as acoustic data. Simultaneously, it uses a camera and additional sensors to detect the user's facial expressions and voice tone, collecting this as emotion data. The device uses a wireless communication module to transmit this data to a server.

[0714] The server analyzes the received acoustic data using a generative AI model. This analysis classifies the sounds into specific types and, if necessary, into categories. Furthermore, an emotion engine analyzes the user's emotional data to identify emotional states such as joy, sadness, and surprise. Based on these analysis results, the server generates optimal text information according to the prompt.

[0715] For example, if the sound of a dog barking is detected while walking in a park, the user's surprise is estimated. When the sound is identified as "dog barking," the server generates a message saying, "It looks like you're playing with your dog. Please stay calm and enjoy yourself." This message is sent back to the user's device, where it is displayed visually and the device vibrates slightly to attract the user's attention.

[0716] An example of a prompt to input into the generation AI model would be something like, "Check which sounds are being analyzed in the surroundings and generate the most appropriate text based on the user's emotional state."

[0717] By implementing this system, users with hearing impairments can carry out their daily activities with peace of mind through feedback.

[0718] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0719] Step 1:

[0720] The device uses a microphone to collect ambient sounds and records them as acoustic data. This acoustic data is collected in real time and temporarily stored in the device's internal memory. The camera and sensors are activated to detect the user's facial expressions and voice tone, collecting emotional data. This emotional data is also temporarily stored within the device. Inputs include audio and images from the microphone and camera, while outputs are acoustic and emotional data for analysis.

[0721] Step 2:

[0722] The terminal transmits collected acoustic and emotional data to the server. A wireless communication module is used to transfer the data to the server in real time. The input consists of acoustic and emotional data within the terminal, and the output is the transfer of this data to the server.

[0723] Step 3:

[0724] The server inputs the received acoustic data into a generating AI model for analysis. This analysis process classifies the sounds into specific categories and identifies the types of sounds. Additionally, an emotion engine analyzes emotional data to identify the user's emotional state. The input consists of acoustic data and emotional data sent to the server, while the output is the identification of sound types and emotional states.

[0725] Step 4:

[0726] The server generates optimal text information using prompts based on the analysis results. For example, following a prompt such as "Check which sounds are being analyzed in the surroundings and generate optimal text based on the user's emotional state," the AI ​​model generates text corresponding to the sounds and emotions. The input is the type of sound and the emotional state, and the output is text information for the user.

[0727] Step 5:

[0728] The terminal receives text information sent from the server and displays it visually. It provides complementary feedback via vibration as needed. Input is text information from the server, and output is the presentation of visual and tactile information to the user. Specifically, the terminal displays messages on the screen and activates a vibration motor as needed.

[0729] (Application Example 2)

[0730] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0731] To make the virtual shopping experience more comfortable for users with hearing impairments, it is necessary not only to acquire and visualize ambient sound information but also to provide information tailored to the user's emotional state. However, current systems lack methods to appropriately recognize user emotions and optimize information, resulting in challenges in improving the ease of information reception and user satisfaction.

[0732] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0733] In this invention, the server includes means for analyzing acoustic information and identifying the type of sound, means for detecting the user's emotional state, and means for adjusting textual information based on the emotional state. This makes it possible to not only visualize acoustic information for users with hearing impairments, but also to provide optimal information tailored to the user's emotions.

[0734] "Acoustic information" refers to sound vibration data within a space, which is acquired through sensors such as microphones.

[0735] "Analysis" refers to the process of breaking down acquired acoustic information and emotional state data to clarify their characteristics and types.

[0736] "Sound type" refers to the distinction between ambient sounds, conversation sounds, alarm sounds, etc., identified from analyzed acoustic information, and classifies their properties.

[0737] "Textual information" refers to information in text format generated based on the type of sound analyzed, and is provided to the user as visual feedback.

[0738] "Emotional state" refers to the state of psychological emotions estimated from the user's facial expressions and voice, and includes emotions such as joy and anxiety.

[0739] "Adjustment" refers to modifying text information generated according to the user's emotional state, and displaying it in a way that is easiest for the user to understand and accept.

[0740] "Visually displaying" refers to providing generated text information in a way that users can see using a display device such as a screen.

[0741] "Vibration means" refers to a device or function that notifies the user through vibration as physical feedback based on generated text information.

[0742] This invention is a system aimed at enabling users with hearing impairments to comfortably enjoy shopping in virtual stores. The embodiments of this system will be described in detail below.

[0743] First, the user terminal is equipped with a microphone to acquire acoustic information and a camera to detect the user's emotional state. This terminal transmits the acoustic information and the user's emotional data to the server in real time.

[0744] The server performs a process of analyzing acoustic information and identifying the type of sound. This acoustic analysis utilizes cloud-based acoustic analysis AI (for example, a service that converts speech to text). Furthermore, the user's emotional state is analyzed using an emotion analysis engine (for example, a service that estimates emotions from facial expressions and voice). This analysis allows the server to identify the user's psychological state and generate emotionally appropriate feedback.

[0745] The generated text information is adjusted by the server based on the user's emotional state. For example, if the user is excited, the product recommendation list can be expanded and relaxing messages can be added. The adjusted text information is displayed visually on the user's terminal and, if necessary, physically notified by vibration. This allows the user to accurately perceive ambient sound information within the virtual store while receiving information tailored to their emotional state.

[0746] For example, even if a user has difficulty hearing announcements about special offers in the store, this system will display the offer information as text. Furthermore, if the user is emotionally unstable, a message such as "Please calm down and take a look" will be added to make the user experience more comfortable.

[0747] Furthermore, an example of a prompt to the generation AI model when building this system is, "Convert the surrounding audio into text and generate a message to display based on the user's emotional state." This ensures that the system functions properly and provides information that is relevant to the user's emotions.

[0748] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0749] Step 1:

[0750] The user terminal acquires ambient acoustic information using its built-in microphone. Simultaneously, it captures the user's facial expressions with a camera to acquire emotion data. This data is sent to the server as input. The output consists of the transmitted acoustic information and emotion data.

[0751] Step 2:

[0752] The server uses an acoustic analysis AI to analyze the received acoustic information. This analysis process classifies sounds based on their characteristics. The input is acoustic information, and the output is the identification of the type of sound. Specifically, it classifies common sounds such as ambient sounds and alarms.

[0753] Step 3:

[0754] Simultaneously, the server uses an emotion analysis engine to analyze the user's emotional data. The input data includes facial expressions and tone of voice. This process involves data processing to identify the user's emotional state as output. Emotional states are classified into categories such as excitement, anxiety, and joy.

[0755] Step 4:

[0756] The server generates and adjusts text information based on the identified sound type and the user's emotional state. In this step, the results of acoustic information analysis and emotion analysis are taken as input, and text information is created using a generative AI model. The output is the adjusted text information.

[0757] Step 5:

[0758] The adjusted text information is transmitted to the user's terminal. The terminal visually displays this text information on its screen. In addition, it provides physical notification to the user using vibration if necessary. This allows the user to receive information and announcements within the virtual store, improving the experience.

[0759] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0760] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0761] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0762] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0763] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0764] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0765] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0766] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0767] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0768] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0769] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0770] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0771] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0772] 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.

[0773] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0774] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0775] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0776] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0777] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0778] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0779] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0780] The following is further disclosed regarding the embodiments described above.

[0781] (Claim 1)

[0782] Means for acquiring acoustic data,

[0783] A means of analyzing acquired acoustic data to identify the type of sound,

[0784] A means for generating text information based on the identified type of sound,

[0785] A means of visually displaying the generated text information,

[0786] A system that includes this.

[0787] (Claim 2)

[0788] The system according to claim 1, further comprising means for classifying acoustic data into specific categories.

[0789] (Claim 3)

[0790] The system according to claim 1, further comprising vibration means for notifying the user of the generated text information.

[0791] "Example 1"

[0792] (Claim 1)

[0793] A device for collecting sound wave data,

[0794] A device that analyzes collected sound wave data and identifies the attributes of sound,

[0795] A device that generates character information based on the attributes of identified sounds,

[0796] A device that visually outputs the generated character information,

[0797] A computer system including a computer system.

[0798] (Claim 2)

[0799] The computer system according to claim 1, further comprising a device for classifying sound wave data into specific categories.

[0800] (Claim 3)

[0801] The computer system according to claim 1, further comprising a vibration device for notifying the user of the generated character information.

[0802] "Application Example 1"

[0803] (Claim 1)

[0804] Means for acquiring acoustic signals,

[0805] A means for analyzing acquired acoustic signals and identifying sound types,

[0806] A means for generating character information based on the identified sound type,

[0807] A means of visually displaying the generated text information,

[0808] A vibration means for analyzing acoustic signals to identify specific acoustic warnings and notifying passengers,

[0809] A system that includes this.

[0810] (Claim 2)

[0811] The system according to claim 1, further comprising means for organizing acoustic signals into specific classifications.

[0812] (Claim 3)

[0813] The system according to claim 1, further comprising means for providing vibration feedback to attract the passenger's attention based on identified audible warnings.

[0814] "Example 2 of combining an emotion engine"

[0815] (Claim 1)

[0816] Means for acquiring acoustic data,

[0817] A means of analyzing acquired acoustic data to identify the type of sound,

[0818] A means for analyzing the user's facial expressions and voice data to identify their emotional state,

[0819] A means for generating text information based on the identified sound type and emotional state,

[0820] A means of visually displaying the generated text information,

[0821] A means of providing the generated text information as additional vibrations,

[0822] A system that includes this.

[0823] (Claim 2)

[0824] The system according to claim 1, further comprising means for classifying acoustic data into specific categories.

[0825] (Claim 3)

[0826] The system according to claim 1, further comprising means for adjusting the feedback generated in accordance with the acquired emotional state of the user.

[0827] "Application example 2 when combining with an emotional engine"

[0828] (Claim 1)

[0829] Means for acquiring acoustic information,

[0830] A means for analyzing acquired acoustic information and identifying the type of sound,

[0831] A means for generating textual information based on the identified type of sound,

[0832] A means of detecting the user's emotional state,

[0833] A means for adjusting text information generated based on detected emotional states,

[0834] A means of visually displaying the adjusted text information,

[0835] A system that includes this.

[0836] (Claim 2)

[0837] The system according to claim 1, further comprising means for classifying acoustic information into specific categories.

[0838] (Claim 3)

[0839] The system according to claim 1, further comprising vibration means for notifying the user of the adjusted character information. [Explanation of Symbols]

[0840] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means for acquiring acoustic data, A means of analyzing acquired acoustic data to identify the type of sound, A means for generating text information based on the identified type of sound, A means of visually displaying the generated text information, A system that includes this.

2. The system according to claim 1, further comprising means for classifying acoustic data into specific categories.

3. The system according to claim 1, further comprising vibration means for notifying the user of the generated text information.

Images