System

Abstract

A system is provided.SOLUTION: The system includes a means for collecting voice data, a means for converting the voice data into text data, a means for acquiring specific information based on the text data, and a means for providing the specific information to a user by voice.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Current digital devices, especially smartphones, offer many functions, but they are difficult to use for the elderly and those who are not adept at using digital devices, widening the digital divide. Furthermore, because a certain level of technical knowledge and skills is required to use digital devices effectively, these people often experience psychological barriers. This limits their opportunities to obtain important information, creating a problem. The objective of this invention is to eliminate the digital divide and psychological barriers resulting from the difficulty of using digital devices, enabling all users to enjoy the benefits of digital devices. [Means for solving the problem]

[0005] The present invention provides a digital device, particularly a smartphone, that can be easily operated using user voice input. By providing a means for collecting voice data and converting it into text data, the user can obtain information simply by speaking to the device. The device also provides a means for obtaining necessary information based on the text data and providing it to the user via voice. Furthermore, by selecting specific operation icons, messages can be easily sent and information can be obtained, and voice input is also used in these operation processes, reducing the burden on the user. This simplifies the use of digital devices, providing a system that can be easily operated even by people who are not comfortable using digital devices. Furthermore, by providing a means for analyzing voice data on the server side and obtaining necessary information, real-time information acquisition becomes possible.

[0006] "Voice data" refers to voices uttered by a user collected as digital signals.

[0007] "Text data" is data that has been analyzed and converted into character string information.

[0008] "Specific information" refers to information such as news and messages that is obtained from the server based on the content requested by the user.

[0009] "Providing the user with voice" means conveying the acquired information to the user using voice synthesis technology.

[0010] "GUI" is an abbreviation for graphical user interface, and refers to a screen that allows users to operate visually.

[0011] A "tap event" is an event that detects the action of a user touching the screen of a digital device with a finger.

[0012] "News Retrieval API" means an application programming interface used to retrieve news information from external news services.

[0013] "Speech synthesis" is a technology that converts text data into voice data and plays it back as sound through a speaker.

[0014] A "speech recognition engine" is a software or hardware system that analyzes voice data and converts it into text data.

[0015] "Server" refers to a computer system for analyzing voice data, acquiring information, and processing it.

[0016] "Digital device" refers to electronic devices such as smartphones and tablets, including those that are interactively operated by users. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The system of the present invention utilizes speech recognition and speech synthesis technology to enable users to easily operate digital devices. This system includes means for collecting speech data, means for converting the speech data into text data, means for acquiring specific information, and means for providing the information to the user by voice.

[0039] Overall system configuration

[0040] The system consists of the following main components:

[0041] Devices (terminals) operated by users

[0042] server

[0043] Speech Recognition Engine

[0044] Speech synthesis engine

[0045] News retrieval API or other information retrieval services

[0046] Program processing flow

[0047] Speech recognition and information acquisition

[0048] 1. The user issues a voice command

[0049] The user speaks to the device and says, "Tell me the latest news."

[0050] 2. The device captures the audio data

[0051] The device's microphone collects the user's voice and stores it as audio data.

[0052] 3. The device sends the audio data to the server

[0053] The device sends the collected voice data to the server.

[0054] 4. The server analyzes the audio data

[0055] The server uses a speech recognition engine to convert the voice data into text data.

[0056] Based on the parsed text data, the server sends an API request to retrieve specific information the user desires, such as the latest news.

[0057] 5. The server retrieves the information and sends it to the device.

[0058] The server obtains the necessary information from the news acquisition API and sends that information to the terminal.

[0059] 6. The device provides information aloud

[0060] The terminal uses a speech synthesis engine to provide the acquired news information to the user by voice.

[0061] Specific examples

[0062] Example 1: Getting news by voice command

[0063] The user speaks to the device saying, "Tell me the latest news." The device's microphone captures the voice and sends it to the server. The server uses speech recognition technology to convert the voice into text and sends a request to the news acquisition API. The latest news information is acquired, sent from the server to the device, and provided to the user as audio by a speech synthesis engine.

[0064] Example 2: Sending a message using simplified touch controls

[0065] The user taps the "Send Message" icon on the screen. An input screen appears and the user types a message by voice, such as "Good morning, how are you?" The device captures the voice and sends it to the server. The server uses a speech recognition engine to convert the voice into text and sends the text message to the device. The message is displayed on the device, and the user can confirm it by tapping the send button, and the message is sent.

[0066] In this way, this system utilizes the user's voice input to make the operation of digital devices intuitive and simple, allowing even people who are not good at using digital devices to easily obtain information and enjoy the benefits of digital devices.

[0067] The processing flow will be explained below.

[0068] Processing steps for getting news by voice command

[0069] Step 1:

[0070] The user speaks to the device and says, "Tell me the latest news."

[0071] Step 2:

[0072] The device captures audio data through the microphone and temporarily stores the audio data in a buffer.

[0073] Step 3:

[0074] The voice data stored on the device is sent to a server via the Internet.

[0075] Step 4:

[0076] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[0077] Step 5:

[0078] The server analyzes the text data and understands the command "get the latest news."

[0079] Step 6:

[0080] The server sends a request to the news retrieval API to retrieve the latest news information.

[0081] Step 7:

[0082] The news information acquired by the server is converted into a data format for audio output and sent to the terminal.

[0083] Step 8:

[0084] The news information received by the device is passed to a speech synthesis engine, converted into audio data, and played over the speaker.

[0085] Step 9:

[0086] The user listens to the latest news information broadcast over the speaker.

[0087] Processing steps for sending a message using simplified touch

[0088] Step 1:

[0089] A user taps the "Send Message" icon on the screen of a digital device.

[0090] Step 2:

[0091] The device detects the tap event and displays a message input screen for voice input.

[0092] Step 3:

[0093] The user speaks to the displayed message screen and inputs the message content, saying "Good morning, how are you?"

[0094] Step 4:

[0095] The device captures audio input through the microphone and temporarily stores the audio data in a buffer.

[0096] Step 5:

[0097] The voice data stored on the device is sent to a server via the Internet.

[0098] Step 6:

[0099] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[0100] Step 7:

[0101] The server sends the converted text data to the terminal.

[0102] Step 8:

[0103] The text data received by the terminal is displayed on the screen and the user is asked, "Do you want to send this message?"

[0104] Step 9:

[0105] The user taps the "Send" button on the confirmation screen.

[0106] Step 10:

[0107] The terminal transmits the confirmed text message again to the server, and the server transmits the message to the designated recipient.

[0108] Example 1

[0109] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0110] In today's world, operating digital devices is necessary in many situations, but these operations are often complex and unintuitive for users. In particular, conventional systems often lack accuracy and immediacy when inputting or retrieving information using voice. Furthermore, when operations are complex and require advanced skills, they pose a high barrier to entry for users unfamiliar with the technology. Given this background, there is a demand for the development of systems that use voice recognition and speech synthesis technologies to enable users to intuitively operate digital devices.

[0111] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0112] In this invention, the server includes means for a user to issue a voice command, means for a terminal to capture voice data, means for transmitting the voice data to the server, means for the server to convert the voice data into text data using a voice recognition engine, means for transmitting an API request to acquire specific information based on the text data, means for transmitting the specific information to the terminal, and means for the terminal to provide the specific information to the user by voice using a voice synthesis engine. This enables a user to intuitively and easily operate a digital device through voice commands and acquire necessary information by voice.

[0113] A "means for a user to issue voice commands" is an interface that allows a user to input instructions or requests by voice into a digital device.

[0114] "Means for the terminal to capture voice data" refers to the function of a microphone installed in a digital device to collect the user's voice and store it as digital voice data.

[0115] The "means for transmitting the audio data to the server" is a function for transferring audio data from the digital device to the server via network communication.

[0116] "Means for the server to convert voice data into text data using a voice recognition engine" refers to the processing ability of the server to convert received voice data into text using voice recognition technology.

[0117] The "means of sending an API request to obtain specific information based on the text data" is an operation of sending a request to an external service to obtain specific information based on the converted text data.

[0118] The "means for transmitting the specific information to the terminal" is a function for transmitting the information acquired by the server to the digital device via network communication.

[0119] "Means for the terminal to provide the user with the specific information by voice using a voice synthesis engine" refers to a function in which a digital device uses voice synthesis technology to convert acquired information into voice and convey it to the user.

[0120] The system of the present invention enables users to easily operate digital devices using speech recognition and speech synthesis technology. The system consists of the following main components: a device (terminal) operated by the user, a server, a speech recognition engine, a speech synthesis engine, and a news retrieval API or other information retrieval service.

[0121] Terminals include devices such as smartphones, tablets, and smart speakers. These devices use built-in microphones to capture voice data and send it to a server via the Internet. The server converts the voice data into text data using a speech recognition engine (e.g., Google® Cloud Speech-to-Text). The server then sends a request to an information acquisition API (e.g., NewsAPI) based on the text data to acquire the required information. The acquired information is then sent back to the terminal, and the terminal uses a speech synthesis engine (e.g., Amazon Polly) to provide the acquired information to the user via voice.

[0122] Specific examples

[0123] Example 1: Getting news by voice command

[0124] The user speaks to the device saying, "Tell me the latest news." The device's microphone captures the audio and sends it to the server. The server uses Google Cloud Speech-to-Text to convert the audio into text. Based on the text, the server requests the latest news information from the News API. The news information obtained from the News API is sent to the device in JSON format. The device uses Amazon Polly to convert the acquired news information into audio and provides it to the user through the speaker.

[0125] Example 2: Sending a message using simplified touch controls

[0126] The user taps the "Send Message" icon displayed on the smartphone screen. On the displayed input screen, the user voice-inputs "Good morning, how are you?" The device captures this voice and sends it to the server. The server uses a voice recognition engine to convert the voice into text and sends the text to the device. After checking the displayed message, the user taps the send button to send the message.

[0127] Hardware and software used

[0128] Hardware: User devices (terminals), servers

[0129] software:

[0130] Speech recognition engine: Google Cloud Speech-to-Text

[0131] Speech synthesis engine: Amazon Polly

[0132] Information acquisition API:NewsAPI

[0133] This system allows users to intuitively and easily operate digital devices through voice commands and instantly obtain the information they need. For example, users can obtain stock price information by voice simply by uttering a prompt such as "How are the stock prices today?". Users can also easily send messages and perform various operations through the GUI. This makes it easy for even users who are not familiar with technology to operate digital devices.

[0134] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0135] Processing flow

[0136] Step 1: User issues a voice command

[0137] The user issues a voice command to the device, such as "Tell me the latest news."

[0138] Input: User's voice

[0139] Output: Audio data

[0140] Specific operation: The user speaks into a device such as a smartphone or tablet, and the audio is input into the microphone.

[0141] Step 2: The device captures the audio data

[0142] The device's microphone captures the user's voice data and stores it in digital form.

[0143] Input: User's voice

[0144] Output: Digital audio data

[0145] Specific operation: The device's built-in microphone collects audio and temporarily stores it as digital data in the internal memory.

[0146] Step 3: The device sends the audio data to the server

[0147] The device transmits the captured audio data to a server via the Internet.

[0148] Input: Digital audio data

[0149] Output: Sending audio data to the server

[0150] What happens: Audio data is split into network packets and sent over the Internet to a server.

[0151] Step 4: The server analyzes the audio data

[0152] The server uses a speech recognition engine to convert the voice data into text data, and then sends an API request to retrieve specific information based on the converted text data.

[0153] Input: Digital audio data

[0154] Output: Text data and API request transmission

[0155] How it works: A speech recognition engine on the server analyzes the voice data and converts it into text, such as "Tell me the latest news." An HTTP message is then generated and sent to send a request to the News API.

[0156] Step 5: The server retrieves the information and sends it to the device

[0157] The server receives news information obtained from the NewsAPI in JSON format and sends it to the terminal.

[0158] Input: API request and retrieved information

[0159] Output: News information sent to the terminal in JSON format

[0160] Specific operation: The server converts the news data obtained from the NewsAPI into JSON format and sends it to the terminal via the network.

[0161] Step 6: The device provides information aloud

[0162] The terminal uses a speech synthesis engine to convert the acquired news information into speech and provide it to the user.

[0163] Input: News information in JSON format

[0164] Output: Audio data and audio presented to the user

[0165] How it works: The device parses the JSON-formatted news data, and the speech synthesis engine converts it into speech, which is then played back through the device's speaker.

[0166] (Application example 1)

[0167] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0168] On modern online shopping sites, users must navigate through multiple screens and input information to efficiently obtain a wide variety of information, making operation cumbersome. Visually impaired users and those unfamiliar with technology have particular difficulties when searching for products, checking order status, or browsing product reviews. Given this background, there was a demand for a more intuitive and convenient way to obtain information.

[0169] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0170] In this invention, the server includes means for converting voice data into text data, means for acquiring specific information, means for providing the specific information to the user by voice, means for the user to search for products using a voice command, means for acquiring search results based on the voice command, and means for providing the search results to the user by voice, thereby enabling the user to intuitively search for products, check order status, and obtain product reviews using voice.

[0171] "Audio data" is a recording of sounds made by a user into a digital device.

[0172] "Text data" is voice data that has been analyzed and converted into text information.

[0173] "Specific information" is the necessary data that is obtained based on the user's voice command.

[0174] "Product search" is the process of searching for a specified product based on a voice command.

[0175] "Search results" is a list of information obtained through the product search process.

[0176] A "GUI" is a type of user interface that allows users to operate a device using visual elements such as icons and buttons.

[0177] "Voice input" refers to a user giving voice instructions to a digital device.

[0178] "Capture" refers to the collection of audio data using a digital device's microphone.

[0179] A "server" is a computer system that receives and processes requests from digital devices that are clients.

[0180] "Speech synthesis" is a technology that converts text data back into voice data and outputs it as voice.

[0181] "Product reviews" are evaluations and impressions written by users who have purchased a product about its usability and quality.

[0182] "Order Status" is the current processing status of the product ordered by the user.

[0183] "API" stands for Application Program Interface, a set of rules and procedures that allow different software programs to communicate with each other.

[0184] The system of this invention consists of the following components: a device (terminal) operated by the user, a server, a voice recognition engine, a voice synthesis engine, and an API service for product searches, order status confirmation, and product review acquisition.

[0185] Overall system configuration

[0186] 1. Acquiring voice input

[0187] When a user speaks into a device such as a smartphone, saying "Find the latest smartphone," the device's microphone captures the voice, and the captured voice data is sent from the device to the server.

[0188] 2. Speech Recognition and Text Conversion

[0189] The server converts the voice data into text data using a speech recognition engine, such as the Google Cloud Speech-to-Text API or Amazon Transcribe.

[0190] 3. Text data analysis and information acquisition

[0191] The server parses the text data, understands the user's command, and then sends a request to the appropriate API, for example, to an e-commerce API for product search, or to an order management API for order status check.

[0192] 4. Speech synthesis and provision of information

[0193] The information acquired by the server is converted into voice data using a speech synthesis engine such as Google Cloud Text-to-Speech API and sent to the device, which then plays the voice data and provides the information to the user.

[0194] Specific examples

[0195] Specific examples of product searches

[0196] When a user says to the device, "Search for the latest smartphone," the microphone captures the voice data. The voice data is sent to the server, where it is converted into text data by a voice recognition engine. The server analyzes the text data and obtains information about the latest smartphones from an e-commerce API. The resulting search results are converted into voice data by a voice synthesis engine and provided to the user via the device.

[0197] Example of checking order status

[0198] When a user speaks to the device, asking, "What's the status of my order?", the microphone similarly captures the voice data. The voice data is sent to the server and converted into text data. The server then sends a request to the order management API to obtain the order status. The obtained information is converted into voice data by a speech synthesis engine and communicated to the user via the device.

[0199] Prompt Sentence Examples

[0200] "Write a program that receives a voice command to search for a product and responds with the search results in voice. Specifically, the program will allow the user to issue a voice command such as "Tell me about the latest smartphone," convert the command into text using voice recognition, and return the retrieved information in voice."

[0201] As mentioned above, this system utilizes user voice control to enable intuitive and easy product searches, order status checks, and product reviews, making it easy to use even for people who are not comfortable using digital devices.

[0202] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0203] Step 1:

[0204] The user issues a voice command, for example, "Find the latest smartphone," which generates voice data.

[0205] Step 2:

[0206] The device captures the voice data. The device's microphone collects the user's voice and stores it as digital voice data. The captured voice data becomes the input.

[0207] Step 3:

[0208] The device sends the voice data to the server. The device sends the collected voice data to the server via the network. The input is the voice data, and the output is the data sent to the server.

[0209] Step 4:

[0210] The server converts the voice data into text data. The server uses a speech recognition engine such as Google Cloud Speech-to-Text API or Amazon Transcribe to convert the received voice data into text data. The input is voice data, and the output is text data.

[0211] Step 5:

[0212] The server parses the text data and sends a request to the appropriate API. The server extracts the user's command from the parsed text data and sends an information retrieval request to, for example, an e-commerce API or an order management API. The input is text data and the output is an API request.

[0213] Step 6:

[0214] An API provides information in response to a request. E-commerce APIs and order management APIs return specific information, such as product details or order status, based on a server request. The input is the API request, and the output is information data.

[0215] Step 7:

[0216] The server converts the acquired information into voice data. The server uses a speech synthesis engine such as Google Cloud Text-to-Speech API to convert the acquired information data into voice data. The input is information data, and the output is voice data.

[0217] Step 8:

[0218] The server sends the audio data to the terminal. The server then sends the converted audio data to the terminal via the network. The input is the audio data, and the output is the data sent to the terminal.

[0219] Step 9:

[0220] The terminal plays back the audio data and provides information to the user. The terminal plays back the received audio data so that the user can hear the information. The input is audio data and the output is audio information.

[0221] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0222] The present invention not only provides the ability to easily operate digital devices by leveraging the user's voice input, but also combines it with an emotion engine that recognizes the user's emotions from their voice, thereby adapting the information and responses provided to the user depending on their emotional state.

[0223] Overall system configuration

[0224] The system consists of the following main components:

[0225] Devices (terminals) operated by users

[0226] server

[0227] Speech Recognition Engine

[0228] Speech synthesis engine

[0229] News retrieval API or other information retrieval services

[0230] Emotion Engine

[0231] Program processing flow

[0232] Speech recognition, emotion recognition, information acquisition

[0233] 1. The user issues a voice command

[0234] The user speaks to the device and says, "Tell me the latest news."

[0235] 2. The device captures the audio data

[0236] The device's microphone collects the user's voice and stores it as audio data.

[0237] 3. The device sends the audio data to the server

[0238] The device sends the collected voice data to the server.

[0239] 4. The server analyzes the audio data

[0240] The server uses a speech recognition engine to convert the voice data into text data.

[0241] 5. The server analyzes emotions using an emotion engine

[0242] The server recognizes the user's emotional state (happiness, sadness, anger, surprise, etc.) based on the voice data.

[0243] 6. The server analyzes the text data and obtains the necessary information.

[0244] The server sends a request to the news retrieval API based on the analyzed text data.

[0245] 7. Adapt the information acquired by the server according to emotions

[0246] The server adapts the retrieved news information according to the user's emotional state, for example, if the user is sad, it will prioritize positive news.

[0247] 8. The server sends the information to the device

[0248] The server transmits the adapted news information to the terminal.

[0249] 9. Device provides adapted information by voice

[0250] The terminal uses a speech synthesis engine to provide the acquired news information to the user by voice.

[0251] Specific examples

[0252] Example 1: Get news by voice command and adapt according to emotions

[0253] The user speaks to the device, saying, "Tell me the latest news." The device's microphone captures the voice and sends it to the server. The server uses a speech recognition engine to convert the voice into text and an emotion engine to analyze the user's emotions. If the server determines that the user is sad, it sends a request to the news acquisition API and prioritizes the retrieved news information to be more positive. The adapted news information is then sent to the device, where it is provided to the user as audio by a speech synthesis engine.

[0254] Example 2: Sending messages with simplified touch controls and reviewing the content based on emotions

[0255] The user taps the "Send Message" icon on the screen. An input screen appears and the user types a message by voice, such as "Good morning, how are you?" The device captures the voice and sends it to the server. The server uses a speech recognition engine and emotion engine to convert the voice into text and analyzes the user's emotion. The server sends the converted text message to the device and displays a confirmation message corresponding to the emotion when it is displayed on the screen. For example, if the user is angry, an additional confirmation such as "Are you sure this is the correct message?" is displayed. After the user confirms, the message is sent by tapping the "Send" button.

[0256] By taking into account the user's emotional state, the system provides more personalized information and responses, improving the user experience and making digital devices easier to use.

[0257] The processing flow will be explained below.

[0258] Processing steps for getting news by voice command and adapting it according to emotions

[0259] Step 1:

[0260] The user speaks to the device and says, "Tell me the latest news."

[0261] Step 2:

[0262] The device captures audio data through the microphone and temporarily stores the audio data in a buffer.

[0263] Step 3:

[0264] The voice data stored on the device is sent to a server via the Internet.

[0265] Step 4:

[0266] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[0267] Step 5:

[0268] The server analyzes the text data and understands the user's request: "Tell me the latest news."

[0269] Step 6:

[0270] The server uses an emotion engine to analyze the user's emotional state (e.g., joy, sadness, anger, surprise) from the voice data.

[0271] Step 7:

[0272] The server sends a request to a news acquisition API based on the text data to acquire the latest news information.

[0273] Step 8:

[0274] The server analyzes the news information it receives and adjusts the content it provides based on the user's emotions. For example, if the user is sad, it will prioritize positive news.

[0275] Step 9:

[0276] The server converts the adapted news information into a data format for voice output and transmits it to the terminal.

[0277] Step 10:

[0278] The news information received by the device is passed to a speech synthesis engine, converted into audio data, and played over the speaker.

[0279] Step 11:

[0280] The user listens to the latest news information broadcast over the speaker.

[0281] Steps for sending messages with simplified touch controls and reviewing them based on emotions

[0282] Step 1:

[0283] A user taps the "Send Message" icon on the screen of a digital device.

[0284] Step 2:

[0285] The device detects the tap event and displays a message input screen for voice input.

[0286] Step 3:

[0287] The user speaks to the displayed message screen and inputs the message content, saying "Good morning, how are you?"

[0288] Step 4:

[0289] The device captures audio input through the microphone and temporarily stores the audio data in a buffer.

[0290] Step 5:

[0291] The voice data stored on the device is sent to a server via the Internet.

[0292] Step 6:

[0293] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[0294] Step 7:

[0295] The server analyzes the text data converted by the voice recognition engine and recognizes the content of the user's message.

[0296] Step 8:

[0297] The server uses an emotion engine to analyze the user's emotional state from the voice data.

[0298] Step 9:

[0299] The server sends text data to the terminal, which displays it on the screen.

[0300] Step 10:

[0301] The device displays a confirmation message such as "Are you sure you want this message?" based on the user's emotional state.

[0302] Step 11:

[0303] The user taps the "Send" button on the confirmation screen.

[0304] Step 12:

[0305] The terminal transmits the confirmed text message again to the server, and the server transmits the message to the designated recipient.

[0306] Example 2

[0307] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0308] In recent years, many digital devices have been designed to be operated by voice commands. However, these systems provide information without considering the user's emotional state, limiting the user experience. Another issue is that simply providing information obtained from voice input without consideration of the user's emotional state does not allow for an appropriate response based on the user's emotions. The present invention aims to provide a system that analyzes a user's voice input and their emotional state, enabling more personalized information delivery.

[0309] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0310] In this invention, the server includes means for converting voice data into text data, means for analyzing the user's emotional state based on the text data, means for acquiring specific information based on the text data and the user's emotional state, means for adapting the acquired information to the user's emotional state, and means for providing the adapted information to the user by voice, thereby enabling adaptive information provision according to the user's emotional state.

[0311] "Voice data" is voice information collected from a user in digital form.

[0312] "Text data" is information obtained by converting voice data into characters.

[0313] A "voice recognition engine" is a software or hardware function that converts voice data into text data.

[0314] An "emotion recognition engine" is a software or hardware function that analyzes and identifies a user's emotional state from text and voice data.

[0315] The "specific information" is content obtained based on the user's voice input and emotional state, such as news information and weather information.

[0316] "Adapting" means optimizing the information retrieved based on the user's emotional state, for example prioritizing positive information if the user is sad.

[0317] A "speech synthesis engine" is a software or hardware function for outputting text data as voice.

[0318] An "information acquisition service" is a means of collecting necessary information using external APIs and databases.

[0319] The present invention not only leverages the user's voice input to provide the ability to easily operate digital devices, but also combines it with an emotion engine that recognizes the user's emotions from their voice, thereby adapting the information and responses provided to the user based on their emotional state, resulting in a personalized user experience.

[0320] Overall system configuration

[0321] The system consists of the following main components:

[0322] Devices (terminals) operated by users

[0323] server

[0324] Speech Recognition Engine

[0325] Emotion Recognition Engine

[0326] Speech synthesis engine

[0327] News retrieval API or other information retrieval services

[0328] Hardware and software used

[0329] 1. Speech recognition engine: To convert voice data into text data, common speech recognition software is used, such as Google Cloud Speech-to-Text API.

[0330] 2. Emotion Recognition Engine: Use an engine to analyze the user's emotional state from text and voice data, such as IBM Watson® Tone Analyzer.

[0331] 3. Speech synthesis engine: Uses an engine to convert text data into speech, such as Amazon Polly.

[0332] 4. Information Retrieval Services: Used to retrieve news and other related information. An example is NewsAPI.org.

[0333] Specific processing of the program

[0334] Let's use the example of a user speaking to a device, saying, "Tell me the latest news." First, the user speaks to the device. The device uses its built-in microphone to collect voice data and stores it as digital data. The device then sends the collected voice data to a server. The server uses the Google Cloud Speech-to-Text API to convert the voice data into text data.

[0335] The server then uses IBM Watson Tone Analyzer to analyze the user's emotional state based on the text and audio data. Based on the analyzed text data, the server sends a request to a news retrieval API (e.g., NewsAPI.org) to retrieve the latest news information. The server then adapts the retrieved news information according to the user's emotional state. For example, if the user is sad, it will prioritize positive news.

[0336] The server then sends the final adapted news information to the device, which then uses Amazon Polly to convert the news information into speech, which is then presented to the user through the device's speaker.

[0337] Specific examples

[0338] Example 1: Get news by voice command and adapt according to emotions

[0339] The user speaks to the device, saying, "Tell me the latest news." The device's microphone captures the audio and sends it to the server. The server converts the audio into text using the Google Cloud Speech-to-Text API and analyzes the user's emotions using IBM Watson Tone Analyzer. If the server determines that the user is sad, it sends a request to NewsAPI.org to prioritize positive news. The retrieved news is then formatted and sent to the device. The device then converts the news into audio using Amazon Polly, which is finally played from the speaker.

[0340] Prompt Sentence Examples

[0341] "You are designing a system to control digital devices that a user talks to. The system will analyze the user's voice and emotional state and provide adaptive responses based on the emotion. Please name the steps involved and the specific hardware and software you will use."

[0342] This allows the present invention to take into account the user's emotional state and provide more personalized responses, improving the user's experience of operating a digital device.

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

[0344] Step 1:

[0345] The user issues a voice command

[0346] The user speaks to the device, saying "Tell me the latest news." The input is the user's voice, which triggers the system to start. The output is the voice data input to the device's microphone. Specifically, the user speaks into the device's microphone, and the voice is captured as an analog signal.

[0347] Step 2:

[0348] The device captures the audio data

[0349] The device's microphone collects the user's voice as digital voice data. The input is the user's analog voice, and the output is digital voice data. Specifically, the device's built-in microphone converts the analog voice signal into digital data. This data is temporarily stored in the device's memory.

[0350] Step 3:

[0351] The device sends the audio data to the server.

[0352] The terminal transmits the collected digital audio data to a server via the Internet. The input is the captured digital audio data, and the output is the audio data that arrives at the server. Specifically, the terminal transmits data packets to the server using the HTTPS protocol, and the server receives the audio data.

[0353] Step 4:

[0354] The server analyzes the audio data

[0355] The server uses a speech recognition engine (e.g., Google Cloud Speech-to-Text API) to convert the voice data into text data. The input is digital voice data, and the output is text data. Specifically, the server sends the voice data to the API, and the speech recognition engine analyzes it and returns it as a string.

[0356] Step 5:

[0357] The server analyzes emotions using an emotion engine.

[0358] The server uses an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotional state based on the text and voice data. The input is the converted text and voice data, and the output is parameters of the user's emotional state (happiness, sadness, etc.). Specifically, the server passes the text data to the emotion recognition engine and receives the emotion parameters as the analysis result.

[0359] Step 6:

[0360] The server analyzes the text data and obtains the necessary information.

[0361] The server retrieves specific information based on the parsed text data. In this process, a request is sent to an information retrieval service (e.g., a news retrieval API). The input is the parsed text data, and the output is the retrieved specific information (e.g., news articles). Specifically, the server analyzes the content of the text data, generates an appropriate search query, sends it to the API, and receives the returned information.

[0362] Step 7:

[0363] Adapting the information acquired by the server according to emotions

[0364] The server adapts the information it acquires based on the user's emotional state. The input is news information and the user's emotional parameters, and the output is adapted news information. Specifically, the server uses the user's emotional parameters to filter information, such as prioritizing positive information.

[0365] Step 8:

[0366] The server sends the information to the device

[0367] The server sends the adapted news information to the device. The input is the adapted news information, and the output is the state it has reached on the device. Specifically, the server packets the information in JSON format and sends it to the device using the HTTPS protocol.

[0368] Step 9:

[0369] The device provides adapted information via voice

[0370] The device uses a speech synthesis engine (e.g., Amazon Polly) to convert the adapted news information into speech. The input is the news information received from the server, and the output is the generated speech data. Specifically, the device sends text data to the speech synthesis engine, and the generated audio file is played back from the speaker and provided to the user.

[0371] Through these processing steps, personalized information provision according to the user's emotional state is realized.

[0372] (Application example 2)

[0373] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0374] In recent years, advances in speech recognition technology have enabled users to operate devices by voice. However, conventional speech recognition systems have had the problem of being unable to adapt responses to the user's intentions and emotions because they do not take the user's emotional state into account. Furthermore, particularly in security services, systems that ignore the user's emotional state have difficulty responding quickly and appropriately to emergencies and ensuring the user's safety. Therefore, there is a need for systems that can improve the operability of digital devices and enhance the user experience by recognizing the user's emotional state and providing appropriate information and responses accordingly.

[0375] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting voice data, means for converting the voice data into text data, means for acquiring specific information based on the text data, means for providing the specific information to the user by voice, means for analyzing the user's emotional state based on the voice data, and means for adapting the acquired information based on the emotional state. This makes it possible to provide appropriate information and responses according to the user's emotional state, improving the operability of digital devices and enabling quick and appropriate responses, particularly in security services.

[0376] "Audio Data" means a digital recording of a user's audio signals made by a user to a device.

[0377] "Text data" is character string data generated by analyzing voice data, and represents the content of a user's speech as text information.

[0378] "Specific information" refers to necessary data or knowledge acquired based on a user's request or instruction, and refers to specific content such as news or weather information.

[0379] "Emotional state" refers to the emotional state of the user that can be inferred from the tone and pattern of the user's voice, and includes emotional responses such as joy, sadness, anger, and anxiety.

[0380] "Speech recognition" is a technology that analyzes voice data and recognizes its content as text data.

[0381] "Speech synthesis" is a technology that analyzes text data, reconstructs it into natural speech, and provides it to the user as audio information.

[0382] "Emotion analysis" is a technology that recognizes and classifies a user's emotional state from voice data.

[0383] "Adaptation" is the process of adjusting acquired information and system responses to the user's emotional state, providing a more personalized response.

[0384] A "system" is a set of programs and hardware for executing a series of processes such as collecting, analyzing, providing information, analyzing emotions, and adapting voice data.

[0385] Basic system configuration

[0386] This invention is a system that captures voice data, analyzes the user's emotions based on that data, and provides adaptive responses. The main components used are as follows:

[0387] 1. Device: A device such as a smartphone or smart speaker that captures the user's voice. The device is equipped with a microphone.

[0388] 2. Server: Analyzes voice data, recognizes emotions, acquires information, and adapts.

[0389] 3. Speech recognition engine: Software that converts voice data into text data.

[0390] 4. Speech synthesis engine: Software that reconstructs text data as speech data.

[0391] 5. Emotion Engine: Software for recognizing and classifying a user's emotional state from voice data.

[0392] 6. News API and other information retrieval services: External services for retrieving specific information.

[0393] System processing explanation in natural language

[0394] The device captures the user's voice input with a microphone and sends the voice data to the server, which then uses a speech recognition engine (e.g., a speech recognition service provided as an API) to convert the voice data into text data, and then uses an emotion engine to analyze the user's voice for emotion.

[0395] Based on the analyzed text data, the server sends requests to news retrieval APIs and other information retrieval services to obtain the necessary information. The retrieved information is then adapted according to the user's emotional state. For example, if the user is feeling anxious, reassurance information and emergency prevention information will be provided first.

[0396] The adapted information is converted into voice data by a speech synthesis engine and provided to the user via the device. Through this series of processes, the user can receive appropriate information and responses adapted to their emotional state.

[0397] The specific hardware and software used

[0398] Smartphone: A device that is always carried by the user and has a microphone for capturing voice input.

[0399] Server: Responsible for all data analysis and information acquisition. Often uses cloud services.

[0400] Speech Recognition Engine: A speech recognition service such as the Google Speech-to-Text API.

[0401] Text-to-speech engine: A text-to-speech service like the Google Text-to-Speech API.

[0402] Emotion Engine: Dedicated software for Emotion Recognition.

[0403] News retrieval API: A news service (e.g., NewsAPI).

[0404] Specific examples

[0405] Example 1

[0406] When a user feels that "something is strange" on a dark street, they speak into their smartphone saying, "Something is strange." This voice data is captured by the device's microphone and sent to the server. The server converts the voice into text using a voice recognition engine and analyzes the emotion of anxiety using an emotion engine. If it determines that suspicious person detection is necessary, the server immediately notifies the user, saying, "A suspicious person has been detected. Please ensure your safety."

[0407] Example 2

[0408] When a user suddenly feels fear, the emotion engine recognizes this fear and automatically calls a pre-registered emergency contact. A message generated by the speech synthesis engine, "This is an emergency! Please contact us immediately," is sent, helping the user quickly ensure safety.

[0409] Prompt Sentence Examples

[0410] An example prompt is:

[0411] "I want to build a voice assistant app that can detect suspicious people and notify contacts based on your emotions. How can I implement a system that can respond appropriately when the user feels anxious or scared?"

[0412] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0413] Step 1:

[0414] The user issues a voice command

[0415] The user speaks to the device saying, "Something's wrong."

[0416] Input: User's voice

[0417] Output: Audio data (digital format)

[0418] Step 2:

[0419] The device captures the audio data

[0420] The device's microphone collects the user's voice and stores it as audio data.

[0421] Input: User's voice

[0422] Output: Audio data

[0423] Step 3:

[0424] The device sends the audio data to the server.

[0425] The collected voice data is sent to a server via the Internet.

[0426] Input: Audio data

[0427] Output: Audio data sent to the server

[0428] Step 4:

[0429] The server analyzes the audio data

[0430] The server uses a speech recognition engine to convert the voice data into text data.

[0431] Input: Audio data

[0432] Output: Text data

[0433] Step 5:

[0434] The server analyzes emotions using an emotion engine.

[0435] The server uses an emotion engine to recognize the user's emotional state (e.g., anxiety, fear) from the text data and voice features.

[0436] Input: Text data and audio features

[0437] Output: Emotional state (e.g., anxiety)

[0438] Step 6:

[0439] The server analyzes the text data and obtains the necessary information.

[0440] The server sends a request to a news retrieval API or similar to obtain the necessary information.

[0441] Input: Text data

[0442] Output: Specific information obtained

[0443] Step 7:

[0444] Adapting the information acquired by the server according to emotions

[0445] The server adjusts the information it receives based on the user's emotional state. For example, if the user is feeling anxious, it will prioritize information about reassurance and emergency measures.

[0446] Input: specific information and emotional state obtained

[0447] Output: Adapted information

[0448] Step 8:

[0449] The server synthesizes the adapted information into voice.

[0450] The server uses a speech synthesis engine to generate the adapted information as voice data.

[0451] Input: Adapted information

[0452] Output: Audio data

[0453] Step 9:

[0454] The server sends the audio data to the device.

[0455] The server transmits the generated voice data to the terminal.

[0456] Input: Audio data

[0457] Output: Audio data sent to the device

[0458] Step 10:

[0459] The device provides adapted information via voice

[0460] The terminal reproduces the received audio data and provides it to the user as audio.

[0461] Input: Audio data

[0462] Output: Audio information presented to the user

[0463] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0464] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0465] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0466] [Second embodiment]

[0467] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0468] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0469] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0470] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0471] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0472] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0473] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0474] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0475] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0476] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0477] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0478] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0479] The system of the present invention utilizes speech recognition and speech synthesis technology to enable users to easily operate digital devices. This system includes means for collecting speech data, means for converting the speech data into text data, means for acquiring specific information, and means for providing the information to the user by voice.

[0480] Overall system configuration

[0481] The system consists of the following main components:

[0482] Devices (terminals) operated by users

[0483] server

[0484] Speech Recognition Engine

[0485] Speech synthesis engine

[0486] News retrieval API or other information retrieval services

[0487] Program processing flow

[0488] Speech recognition and information acquisition

[0489] 1. The user issues a voice command

[0490] The user speaks to the device and says, "Tell me the latest news."

[0491] 2. The device captures the audio data

[0492] The device's microphone collects the user's voice and stores it as audio data.

[0493] 3. The device sends the audio data to the server

[0494] The device sends the collected voice data to the server.

[0495] 4. The server analyzes the audio data

[0496] The server uses a speech recognition engine to convert the voice data into text data.

[0497] Based on the parsed text data, the server sends an API request to retrieve specific information the user desires, such as the latest news.

[0498] 5. The server retrieves the information and sends it to the device.

[0499] The server obtains the necessary information from the news acquisition API and sends that information to the terminal.

[0500] 6. The device provides information aloud

[0501] The terminal uses a speech synthesis engine to provide the acquired news information to the user by voice.

[0502] Specific examples

[0503] Example 1: Getting news by voice command

[0504] The user speaks to the device saying, "Tell me the latest news." The device's microphone captures the voice and sends it to the server. The server uses speech recognition technology to convert the voice into text and sends a request to the news acquisition API. The latest news information is acquired, sent from the server to the device, and provided to the user as audio by a speech synthesis engine.

[0505] Example 2: Sending a message using simplified touch controls

[0506] The user taps the "Send Message" icon on the screen. An input screen appears and the user types a message by voice, such as "Good morning, how are you?" The device captures the voice and sends it to the server. The server uses a speech recognition engine to convert the voice into text and sends the text message to the device. The message is displayed on the device, and the user can confirm it by tapping the send button, and the message is sent.

[0507] In this way, this system utilizes the user's voice input to make the operation of digital devices intuitive and simple, allowing even people who are not good at using digital devices to easily obtain information and enjoy the benefits of digital devices.

[0508] The processing flow will be explained below.

[0509] Processing steps for getting news by voice command

[0510] Step 1:

[0511] The user speaks to the device and says, "Tell me the latest news."

[0512] Step 2:

[0513] The device captures audio data through the microphone and temporarily stores the audio data in a buffer.

[0514] Step 3:

[0515] The voice data stored on the device is sent to a server via the Internet.

[0516] Step 4:

[0517] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[0518] Step 5:

[0519] The server analyzes the text data and understands the command "get the latest news."

[0520] Step 6:

[0521] The server sends a request to the news retrieval API to retrieve the latest news information.

[0522] Step 7:

[0523] The news information acquired by the server is converted into a data format for audio output and sent to the terminal.

[0524] Step 8:

[0525] The news information received by the device is passed to a speech synthesis engine, converted into audio data, and played over the speaker.

[0526] Step 9:

[0527] The user listens to the latest news information broadcast over the speaker.

[0528] Processing steps for sending a message using simplified touch

[0529] Step 1:

[0530] A user taps the "Send Message" icon on the screen of a digital device.

[0531] Step 2:

[0532] The device detects the tap event and displays a message input screen for voice input.

[0533] Step 3:

[0534] The user speaks to the displayed message screen and inputs the message content, saying "Good morning, how are you?"

[0535] Step 4:

[0536] The device captures audio input through the microphone and temporarily stores the audio data in a buffer.

[0537] Step 5:

[0538] The voice data stored on the device is sent to a server via the Internet.

[0539] Step 6:

[0540] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[0541] Step 7:

[0542] The server sends the converted text data to the terminal.

[0543] Step 8:

[0544] The text data received by the terminal is displayed on the screen and the user is asked, "Do you want to send this message?"

[0545] Step 9:

[0546] The user taps the "Send" button on the confirmation screen.

[0547] Step 10:

[0548] The terminal transmits the confirmed text message again to the server, and the server transmits the message to the designated recipient.

[0549] Example 1

[0550] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0551] In today's world, operating digital devices is necessary in many situations, but these operations are often complex and unintuitive for users. In particular, conventional systems often lack accuracy and immediacy when inputting or retrieving information using voice. Furthermore, when operations are complex and require advanced skills, they pose a high barrier to entry for users unfamiliar with the technology. Given this background, there is a demand for the development of systems that use voice recognition and speech synthesis technologies to enable users to intuitively operate digital devices.

[0552] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0553] In this invention, the server includes means for a user to issue a voice command, means for a terminal to capture voice data, means for transmitting the voice data to the server, means for the server to convert the voice data into text data using a voice recognition engine, means for transmitting an API request to acquire specific information based on the text data, means for transmitting the specific information to the terminal, and means for the terminal to provide the specific information to the user by voice using a voice synthesis engine. This enables a user to intuitively and easily operate a digital device through voice commands and acquire necessary information by voice.

[0554] A "means for a user to issue voice commands" is an interface that allows a user to input instructions or requests by voice into a digital device.

[0555] "Means for the terminal to capture voice data" refers to the function of a microphone installed in a digital device to collect the user's voice and store it as digital voice data.

[0556] The "means for transmitting the audio data to the server" is a function for transferring audio data from the digital device to the server via network communication.

[0557] "Means for the server to convert voice data into text data using a voice recognition engine" refers to the processing ability of the server to convert received voice data into text using voice recognition technology.

[0558] The "means of sending an API request to obtain specific information based on the text data" is an operation of sending a request to an external service to obtain specific information based on the converted text data.

[0559] The "means for transmitting the specific information to the terminal" is a function for transmitting the information acquired by the server to the digital device via network communication.

[0560] "Means for the terminal to provide the user with the specific information by voice using a voice synthesis engine" refers to a function in which a digital device uses voice synthesis technology to convert acquired information into voice and convey it to the user.

[0561] The system of the present invention enables users to easily operate digital devices using speech recognition and speech synthesis technology. The system consists of the following main components: a device (terminal) operated by the user, a server, a speech recognition engine, a speech synthesis engine, and a news retrieval API or other information retrieval service.

[0562] Terminals include devices such as smartphones, tablets, and smart speakers. These devices use built-in microphones to capture voice data and send it to a server via the Internet. The server converts the voice data into text data using a speech recognition engine (e.g., Google Cloud Speech-to-Text). The server then sends a request to an information retrieval API (e.g., NewsAPI) based on the text data to retrieve the required information. The retrieved information is then sent back to the terminal, where it uses a speech synthesis engine (e.g., Amazon Polly) to provide the retrieved information to the user via voice.

[0563] Specific examples

[0564] Example 1: Getting news by voice command

[0565] The user speaks to the device saying, "Tell me the latest news." The device's microphone captures the audio and sends it to the server. The server uses Google Cloud Speech-to-Text to convert the audio into text. Based on the text, the server requests the latest news information from the News API. The news information obtained from the News API is sent to the device in JSON format. The device uses Amazon Polly to convert the acquired news information into audio and provides it to the user through the speaker.

[0566] Example 2: Sending a message using simplified touch controls

[0567] The user taps the "Send Message" icon displayed on the smartphone screen. On the displayed input screen, the user voice-inputs "Good morning, how are you?" The device captures this voice and sends it to the server. The server uses a voice recognition engine to convert the voice into text and sends the text to the device. After checking the displayed message, the user taps the send button to send the message.

[0568] Hardware and software used

[0569] Hardware: User devices (terminals), servers

[0570] software:

[0571] Speech recognition engine: Google Cloud Speech-to-Text

[0572] Speech synthesis engine: Amazon Polly

[0573] Information acquisition API:NewsAPI

[0574] This system allows users to intuitively and easily operate digital devices through voice commands and instantly obtain the information they need. For example, users can obtain stock price information by voice simply by uttering a prompt such as "How are the stock prices today?". Users can also easily send messages and perform various operations through the GUI. This makes it easy for even users who are not familiar with technology to operate digital devices.

[0575] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0576] Processing flow

[0577] Step 1: User issues a voice command

[0578] The user issues a voice command to the device, such as "Tell me the latest news."

[0579] Input: User's voice

[0580] Output: Audio data

[0581] Specific operation: The user speaks into a device such as a smartphone or tablet, and the audio is input into the microphone.

[0582] Step 2: The device captures the audio data

[0583] The device's microphone captures the user's voice data and stores it in digital form.

[0584] Input: User's voice

[0585] Output: Digital audio data

[0586] Specific operation: The device's built-in microphone collects audio and temporarily stores it as digital data in the internal memory.

[0587] Step 3: The device sends the audio data to the server

[0588] The device transmits the captured audio data to a server via the Internet.

[0589] Input: Digital audio data

[0590] Output: Sending audio data to the server

[0591] What happens: Audio data is split into network packets and sent over the Internet to a server.

[0592] Step 4: The server analyzes the audio data

[0593] The server uses a speech recognition engine to convert the voice data into text data, and then sends an API request to retrieve specific information based on the converted text data.

[0594] Input: Digital audio data

[0595] Output: Text data and API request transmission

[0596] How it works: A speech recognition engine on the server analyzes the voice data and converts it into text, such as "Tell me the latest news." An HTTP message is then generated and sent to send a request to the News API.

[0597] Step 5: The server retrieves the information and sends it to the device

[0598] The server receives news information obtained from the NewsAPI in JSON format and sends it to the terminal.

[0599] Input: API request and retrieved information

[0600] Output: News information sent to the terminal in JSON format

[0601] Specific operation: The server converts the news data obtained from the NewsAPI into JSON format and sends it to the terminal via the network.

[0602] Step 6: The device provides information aloud

[0603] The terminal uses a speech synthesis engine to convert the acquired news information into speech and provide it to the user.

[0604] Input: News information in JSON format

[0605] Output: Audio data and audio presented to the user

[0606] How it works: The device parses the JSON-formatted news data, and the speech synthesis engine converts it into speech, which is then played back through the device's speaker.

[0607] (Application example 1)

[0608] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0609] On modern online shopping sites, users must navigate through multiple screens and input information to efficiently obtain a wide variety of information, making operation cumbersome. Visually impaired users and those unfamiliar with technology have particular difficulties when searching for products, checking order status, or browsing product reviews. Given this background, there was a demand for a more intuitive and convenient way to obtain information.

[0610] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0611] In this invention, the server includes means for converting voice data into text data, means for acquiring specific information, means for providing the specific information to the user by voice, means for the user to search for products using a voice command, means for acquiring search results based on the voice command, and means for providing the search results to the user by voice, thereby enabling the user to intuitively search for products, check order status, and obtain product reviews using voice.

[0612] "Audio data" is a recording of sounds made by a user into a digital device.

[0613] "Text data" is voice data that has been analyzed and converted into text information.

[0614] "Specific information" is the necessary data that is obtained based on the user's voice command.

[0615] "Product search" is the process of searching for a specified product based on a voice command.

[0616] "Search results" is a list of information obtained through the product search process.

[0617] A "GUI" is a type of user interface that allows users to operate a device using visual elements such as icons and buttons.

[0618] "Voice input" refers to a user giving voice instructions to a digital device.

[0619] "Capture" refers to the collection of audio data using a digital device's microphone.

[0620] A "server" is a computer system that receives and processes requests from digital devices that are clients.

[0621] "Speech synthesis" is a technology that converts text data back into voice data and outputs it as voice.

[0622] "Product reviews" are evaluations and impressions written by users who have purchased a product about its usability and quality.

[0623] "Order Status" is the current processing status of the product ordered by the user.

[0624] "API" stands for Application Program Interface, a set of rules and procedures that allow different software programs to communicate with each other.

[0625] The system of this invention consists of the following components: a device (terminal) operated by the user, a server, a voice recognition engine, a voice synthesis engine, and an API service for product searches, order status confirmation, and product review acquisition.

[0626] Overall system configuration

[0627] 1. Acquiring voice input

[0628] When a user speaks into a device such as a smartphone, saying "Find the latest smartphone," the device's microphone captures the voice, and the captured voice data is sent from the device to the server.

[0629] 2. Speech Recognition and Text Conversion

[0630] The server converts the voice data into text data using a speech recognition engine, such as the Google Cloud Speech-to-Text API or Amazon Transcribe.

[0631] 3. Text data analysis and information acquisition

[0632] The server parses the text data, understands the user's command, and then sends a request to the appropriate API, for example, to an e-commerce API for product search, or to an order management API for order status check.

[0633] 4. Speech synthesis and provision of information

[0634] The information acquired by the server is converted into voice data using a speech synthesis engine such as Google Cloud Text-to-Speech API and sent to the device, which then plays the voice data and provides the information to the user.

[0635] Specific examples

[0636] Specific examples of product searches

[0637] When a user says to the device, "Search for the latest smartphone," the microphone captures the voice data. The voice data is sent to the server, where it is converted into text data by a voice recognition engine. The server analyzes the text data and obtains information about the latest smartphones from an e-commerce API. The resulting search results are converted into voice data by a voice synthesis engine and provided to the user via the device.

[0638] Example of checking order status

[0639] When a user speaks to the device, asking, "What's the status of my order?", the microphone similarly captures the voice data. The voice data is sent to the server and converted into text data. The server then sends a request to the order management API to obtain the order status. The obtained information is converted into voice data by a speech synthesis engine and communicated to the user via the device.

[0640] Prompt Sentence Examples

[0641] "Write a program that receives a voice command to search for a product and responds with the search results in voice. Specifically, the program will allow the user to issue a voice command such as "Tell me about the latest smartphone," convert the command into text using voice recognition, and return the retrieved information in voice."

[0642] As mentioned above, this system utilizes user voice control to enable intuitive and easy product searches, order status checks, and product reviews, making it easy to use even for people who are not comfortable using digital devices.

[0643] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0644] Step 1:

[0645] The user issues a voice command, for example, "Find the latest smartphone," which generates voice data.

[0646] Step 2:

[0647] The device captures the voice data. The device's microphone collects the user's voice and stores it as digital voice data. The captured voice data becomes the input.

[0648] Step 3:

[0649] The device sends the voice data to the server. The device sends the collected voice data to the server via the network. The input is the voice data, and the output is the data sent to the server.

[0650] Step 4:

[0651] The server converts the voice data into text data. The server uses a speech recognition engine such as Google Cloud Speech-to-Text API or Amazon Transcribe to convert the received voice data into text data. The input is voice data, and the output is text data.

[0652] Step 5:

[0653] The server parses the text data and sends a request to the appropriate API. The server extracts the user's command from the parsed text data and sends an information retrieval request to, for example, an e-commerce API or an order management API. The input is text data and the output is an API request.

[0654] Step 6:

[0655] An API provides information in response to a request. E-commerce APIs and order management APIs return specific information, such as product details or order status, based on a server request. The input is the API request, and the output is information data.

[0656] Step 7:

[0657] The server converts the acquired information into voice data. The server uses a speech synthesis engine such as Google Cloud Text-to-Speech API to convert the acquired information data into voice data. The input is information data, and the output is voice data.

[0658] Step 8:

[0659] The server sends the audio data to the terminal. The server then sends the converted audio data to the terminal via the network. The input is the audio data, and the output is the data sent to the terminal.

[0660] Step 9:

[0661] The terminal plays back the audio data and provides information to the user. The terminal plays back the received audio data so that the user can hear the information. The input is audio data and the output is audio information.

[0662] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0663] The present invention not only provides the ability to easily operate digital devices by leveraging the user's voice input, but also combines it with an emotion engine that recognizes the user's emotions from their voice, thereby adapting the information and responses provided to the user depending on their emotional state.

[0664] Overall system configuration

[0665] The system consists of the following main components:

[0666] Devices (terminals) operated by users

[0667] server

[0668] Speech Recognition Engine

[0669] Speech synthesis engine

[0670] News retrieval API or other information retrieval services

[0671] Emotion Engine

[0672] Program processing flow

[0673] Speech recognition, emotion recognition, information acquisition

[0674] 1. The user issues a voice command

[0675] The user speaks to the device and says, "Tell me the latest news."

[0676] 2. The device captures the audio data

[0677] The device's microphone collects the user's voice and stores it as audio data.

[0678] 3. The device sends the audio data to the server

[0679] The device sends the collected voice data to the server.

[0680] 4. The server analyzes the audio data

[0681] The server uses a speech recognition engine to convert the voice data into text data.

[0682] 5. The server analyzes emotions using an emotion engine

[0683] The server recognizes the user's emotional state (happiness, sadness, anger, surprise, etc.) based on the voice data.

[0684] 6. The server analyzes the text data and obtains the necessary information.

[0685] The server sends a request to the news retrieval API based on the analyzed text data.

[0686] 7. Adapt the information acquired by the server according to emotions

[0687] The server adapts the retrieved news information according to the user's emotional state, for example, if the user is sad, it will prioritize positive news.

[0688] 8. The server sends the information to the device

[0689] The server transmits the adapted news information to the terminal.

[0690] 9. Device provides adapted information by voice

[0691] The terminal uses a speech synthesis engine to provide the acquired news information to the user by voice.

[0692] Specific examples

[0693] Example 1: Get news by voice command and adapt according to emotions

[0694] The user speaks to the device, saying, "Tell me the latest news." The device's microphone captures the voice and sends it to the server. The server uses a speech recognition engine to convert the voice into text and an emotion engine to analyze the user's emotions. If the server determines that the user is sad, it sends a request to the news acquisition API and prioritizes the retrieved news information to be more positive. The adapted news information is then sent to the device, where it is provided to the user as audio by a speech synthesis engine.

[0695] Example 2: Sending messages with simplified touch controls and reviewing the content based on emotions

[0696] The user taps the "Send Message" icon on the screen. An input screen appears and the user types a message by voice, such as "Good morning, how are you?" The device captures the voice and sends it to the server. The server uses a speech recognition engine and emotion engine to convert the voice into text and analyzes the user's emotion. The server sends the converted text message to the device and displays a confirmation message corresponding to the emotion when it is displayed on the screen. For example, if the user is angry, an additional confirmation such as "Are you sure this is the correct message?" is displayed. After the user confirms, the message is sent by tapping the "Send" button.

[0697] By taking into account the user's emotional state, the system provides more personalized information and responses, improving the user experience and making digital devices easier to use.

[0698] The processing flow will be explained below.

[0699] Processing steps for getting news by voice command and adapting it according to emotions

[0700] Step 1:

[0701] The user speaks to the device and says, "Tell me the latest news."

[0702] Step 2:

[0703] The device captures audio data through the microphone and temporarily stores the audio data in a buffer.

[0704] Step 3:

[0705] The voice data stored on the device is sent to a server via the Internet.

[0706] Step 4:

[0707] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[0708] Step 5:

[0709] The server analyzes the text data and understands the user's request: "Tell me the latest news."

[0710] Step 6:

[0711] The server uses an emotion engine to analyze the user's emotional state (e.g., joy, sadness, anger, surprise) from the voice data.

[0712] Step 7:

[0713] The server sends a request to a news acquisition API based on the text data to acquire the latest news information.

[0714] Step 8:

[0715] The server analyzes the news information it receives and adjusts the content it provides based on the user's emotions. For example, if the user is sad, it will prioritize positive news.

[0716] Step 9:

[0717] The server converts the adapted news information into a data format for voice output and transmits it to the terminal.

[0718] Step 10:

[0719] The news information received by the device is passed to a speech synthesis engine, converted into audio data, and played over the speaker.

[0720] Step 11:

[0721] The user listens to the latest news information broadcast over the speaker.

[0722] Steps for sending messages with simplified touch controls and reviewing them based on emotions

[0723] Step 1:

[0724] A user taps the "Send Message" icon on the screen of a digital device.

[0725] Step 2:

[0726] The device detects the tap event and displays a message input screen for voice input.

[0727] Step 3:

[0728] The user speaks to the displayed message screen and inputs the message content, saying "Good morning, how are you?"

[0729] Step 4:

[0730] The device captures audio input through the microphone and temporarily stores the audio data in a buffer.

[0731] Step 5:

[0732] The voice data stored on the device is sent to a server via the Internet.

[0733] Step 6:

[0734] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[0735] Step 7:

[0736] The server analyzes the text data converted by the voice recognition engine and recognizes the content of the user's message.

[0737] Step 8:

[0738] The server uses an emotion engine to analyze the user's emotional state from the voice data.

[0739] Step 9:

[0740] The server sends text data to the terminal, which displays it on the screen.

[0741] Step 10:

[0742] The device displays a confirmation message such as "Are you sure you want this message?" based on the user's emotional state.

[0743] Step 11:

[0744] The user taps the "Send" button on the confirmation screen.

[0745] Step 12:

[0746] The terminal transmits the confirmed text message again to the server, and the server transmits the message to the designated recipient.

[0747] Example 2

[0748] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0749] In recent years, many digital devices have been designed to be operated by voice commands. However, these systems provide information without considering the user's emotional state, limiting the user experience. Another issue is that simply providing information obtained from voice input without consideration of the user's emotional state does not allow for an appropriate response based on the user's emotions. The present invention aims to provide a system that analyzes a user's voice input and their emotional state, enabling more personalized information delivery.

[0750] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0751] In this invention, the server includes means for converting voice data into text data, means for analyzing the user's emotional state based on the text data, means for acquiring specific information based on the text data and the user's emotional state, means for adapting the acquired information to the user's emotional state, and means for providing the adapted information to the user by voice, thereby enabling adaptive information provision according to the user's emotional state.

[0752] "Voice data" is voice information collected from a user in digital form.

[0753] "Text data" is information obtained by converting voice data into characters.

[0754] A "voice recognition engine" is a software or hardware function that converts voice data into text data.

[0755] An "emotion recognition engine" is a software or hardware function that analyzes and identifies a user's emotional state from text and voice data.

[0756] The "specific information" is content obtained based on the user's voice input and emotional state, such as news information and weather information.

[0757] "Adapting" means optimizing the information retrieved based on the user's emotional state, for example prioritizing positive information if the user is sad.

[0758] A "speech synthesis engine" is a software or hardware function for outputting text data as voice.

[0759] An "information acquisition service" is a means of collecting necessary information using external APIs and databases.

[0760] The present invention not only leverages the user's voice input to provide the ability to easily operate digital devices, but also combines it with an emotion engine that recognizes the user's emotions from their voice, thereby adapting the information and responses provided to the user based on their emotional state, resulting in a personalized user experience.

[0761] Overall system configuration

[0762] The system consists of the following main components:

[0763] Devices (terminals) operated by users

[0764] server

[0765] Speech Recognition Engine

[0766] Emotion Recognition Engine

[0767] Speech synthesis engine

[0768] News retrieval API or other information retrieval services

[0769] Hardware and software used

[0770] 1. Speech recognition engine: To convert voice data into text data, common speech recognition software is used, such as Google Cloud Speech-to-Text API.

[0771] 2. Emotion recognition engine: Uses an engine to analyze the user's emotional state from text and voice data. An example is IBM Watson Tone Analyzer.

[0772] 3. Speech synthesis engine: Uses an engine to convert text data into speech, such as Amazon Polly.

[0773] 4. Information Retrieval Services: Used to retrieve news and other related information. An example is NewsAPI.org.

[0774] Specific processing of the program

[0775] Let's use the example of a user speaking to a device, saying, "Tell me the latest news." First, the user speaks to the device. The device uses its built-in microphone to collect voice data and stores it as digital data. The device then sends the collected voice data to a server. The server uses the Google Cloud Speech-to-Text API to convert the voice data into text data.

[0776] The server then uses IBM Watson Tone Analyzer to analyze the user's emotional state based on the text and audio data. Based on the analyzed text data, the server sends a request to a news retrieval API (e.g., NewsAPI.org) to retrieve the latest news information. The server then adapts the retrieved news information according to the user's emotional state. For example, if the user is sad, it will prioritize positive news.

[0777] The server then sends the final adapted news information to the device, which then uses Amazon Polly to convert the news information into speech, which is then presented to the user through the device's speaker.

[0778] Specific examples

[0779] Example 1: Get news by voice command and adapt according to emotions

[0780] The user speaks to the device, saying, "Tell me the latest news." The device's microphone captures the audio and sends it to the server. The server converts the audio into text using the Google Cloud Speech-to-Text API and analyzes the user's emotions using IBM Watson Tone Analyzer. If the server determines that the user is sad, it sends a request to NewsAPI.org to prioritize positive news. The retrieved news is then formatted and sent to the device. The device then converts the news into audio using Amazon Polly, which is finally played from the speaker.

[0781] Prompt Sentence Examples

[0782] "You are designing a system to control digital devices that a user talks to. The system will analyze the user's voice and emotional state and provide adaptive responses based on the emotion. Please name the steps involved and the specific hardware and software you will use."

[0783] This allows the present invention to take into account the user's emotional state and provide more personalized responses, improving the user's experience of operating a digital device.

[0784] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0785] Step 1:

[0786] The user issues a voice command

[0787] The user speaks to the device, saying "Tell me the latest news." The input is the user's voice, which triggers the system to start. The output is the voice data input to the device's microphone. Specifically, the user speaks into the device's microphone, and the voice is captured as an analog signal.

[0788] Step 2:

[0789] The device captures the audio data

[0790] The device's microphone collects the user's voice as digital voice data. The input is the user's analog voice, and the output is digital voice data. Specifically, the device's built-in microphone converts the analog voice signal into digital data. This data is temporarily stored in the device's memory.

[0791] Step 3:

[0792] The device sends the audio data to the server.

[0793] The terminal transmits the collected digital audio data to a server via the Internet. The input is the captured digital audio data, and the output is the audio data that arrives at the server. Specifically, the terminal transmits data packets to the server using the HTTPS protocol, and the server receives the audio data.

[0794] Step 4:

[0795] The server analyzes the audio data

[0796] The server uses a speech recognition engine (e.g., Google Cloud Speech-to-Text API) to convert the voice data into text data. The input is digital voice data, and the output is text data. Specifically, the server sends the voice data to the API, and the speech recognition engine analyzes it and returns it as a string.

[0797] Step 5:

[0798] The server analyzes emotions using an emotion engine.

[0799] The server uses an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotional state based on the text and voice data. The input is the converted text and voice data, and the output is parameters of the user's emotional state (happiness, sadness, etc.). Specifically, the server passes the text data to the emotion recognition engine and receives the emotion parameters as the analysis result.

[0800] Step 6:

[0801] The server analyzes the text data and obtains the necessary information.

[0802] The server retrieves specific information based on the parsed text data. In this process, a request is sent to an information retrieval service (e.g., a news retrieval API). The input is the parsed text data, and the output is the retrieved specific information (e.g., news articles). Specifically, the server analyzes the content of the text data, generates an appropriate search query, sends it to the API, and receives the returned information.

[0803] Step 7:

[0804] Adapting the information acquired by the server according to emotions

[0805] The server adapts the information it acquires based on the user's emotional state. The input is news information and the user's emotional parameters, and the output is adapted news information. Specifically, the server uses the user's emotional parameters to filter information, such as prioritizing positive information.

[0806] Step 8:

[0807] The server sends the information to the device

[0808] The server sends the adapted news information to the device. The input is the adapted news information, and the output is the state it has reached on the device. Specifically, the server packets the information in JSON format and sends it to the device using the HTTPS protocol.

[0809] Step 9:

[0810] The device provides adapted information via voice

[0811] The device uses a speech synthesis engine (e.g., Amazon Polly) to convert the adapted news information into speech. The input is the news information received from the server, and the output is the generated speech data. Specifically, the device sends text data to the speech synthesis engine, and the generated audio file is played back from the speaker and provided to the user.

[0812] Through these processing steps, personalized information provision according to the user's emotional state is realized.

[0813] (Application example 2)

[0814] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0815] In recent years, advances in speech recognition technology have enabled users to operate devices by voice. However, conventional speech recognition systems have had the problem of being unable to adapt responses to the user's intentions and emotions because they do not take the user's emotional state into account. Furthermore, particularly in security services, systems that ignore the user's emotional state have difficulty responding quickly and appropriately to emergencies and ensuring the user's safety. Therefore, there is a need for systems that can improve the operability of digital devices and enhance the user experience by recognizing the user's emotional state and providing appropriate information and responses accordingly.

[0816] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting voice data, means for converting the voice data into text data, means for acquiring specific information based on the text data, means for providing the specific information to the user by voice, means for analyzing the user's emotional state based on the voice data, and means for adapting the acquired information based on the emotional state. This makes it possible to provide appropriate information and responses according to the user's emotional state, improving the operability of digital devices and enabling quick and appropriate responses, particularly in security services.

[0817] "Audio Data" means a digital recording of a user's audio signals made by a user to a device.

[0818] "Text data" is character string data generated by analyzing voice data, and represents the content of a user's speech as text information.

[0819] "Specific information" refers to necessary data or knowledge acquired based on a user's request or instruction, and refers to specific content such as news or weather information.

[0820] "Emotional state" refers to the emotional state of the user that can be inferred from the tone and pattern of the user's voice, and includes emotional responses such as joy, sadness, anger, and anxiety.

[0821] "Speech recognition" is a technology that analyzes voice data and recognizes its content as text data.

[0822] "Speech synthesis" is a technology that analyzes text data, reconstructs it into natural speech, and provides it to the user as audio information.

[0823] "Emotion analysis" is a technology that recognizes and classifies a user's emotional state from voice data.

[0824] "Adaptation" is the process of adjusting acquired information and system responses to the user's emotional state, providing a more personalized response.

[0825] A "system" is a set of programs and hardware for executing a series of processes such as collecting, analyzing, providing information, analyzing emotions, and adapting voice data.

[0826] Basic system configuration

[0827] This invention is a system that captures voice data, analyzes the user's emotions based on that data, and provides adaptive responses. The main components used are as follows:

[0828] 1. Device: A device such as a smartphone or smart speaker that captures the user's voice. The device is equipped with a microphone.

[0829] 2. Server: Analyzes voice data, recognizes emotions, acquires information, and adapts.

[0830] 3. Speech recognition engine: Software that converts voice data into text data.

[0831] 4. Speech synthesis engine: Software that reconstructs text data as speech data.

[0832] 5. Emotion Engine: Software for recognizing and classifying a user's emotional state from voice data.

[0833] 6. News API and other information retrieval services: External services for retrieving specific information.

[0834] System processing explanation in natural language

[0835] The device captures the user's voice input with a microphone and sends the voice data to the server, which then uses a speech recognition engine (e.g., a speech recognition service provided as an API) to convert the voice data into text data, and then uses an emotion engine to analyze the user's voice for emotion.

[0836] Based on the analyzed text data, the server sends requests to news retrieval APIs and other information retrieval services to obtain the necessary information. The retrieved information is then adapted according to the user's emotional state. For example, if the user is feeling anxious, reassurance information and emergency prevention information will be provided first.

[0837] The adapted information is converted into voice data by a speech synthesis engine and provided to the user via the device. Through this series of processes, the user can receive appropriate information and responses adapted to their emotional state.

[0838] The specific hardware and software used

[0839] Smartphone: A device that is always carried by the user and has a microphone for capturing voice input.

[0840] Server: Responsible for all data analysis and information acquisition. Often uses cloud services.

[0841] Speech Recognition Engine: A speech recognition service such as the Google Speech-to-Text API.

[0842] Text-to-speech engine: A text-to-speech service like the Google Text-to-Speech API.

[0843] Emotion Engine: Dedicated software for Emotion Recognition.

[0844] News retrieval API: A news service (e.g., NewsAPI).

[0845] Specific examples

[0846] Example 1

[0847] When a user feels that "something is strange" on a dark street, they speak into their smartphone saying, "Something is strange." This voice data is captured by the device's microphone and sent to the server. The server converts the voice into text using a voice recognition engine and analyzes the emotion of anxiety using an emotion engine. If it determines that suspicious person detection is necessary, the server immediately notifies the user, saying, "A suspicious person has been detected. Please ensure your safety."

[0848] Example 2

[0849] When a user suddenly feels fear, the emotion engine recognizes this fear and automatically calls a pre-registered emergency contact. A message generated by the speech synthesis engine, "This is an emergency! Please contact us immediately," is sent, helping the user quickly ensure safety.

[0850] Prompt Sentence Examples

[0851] An example prompt is:

[0852] "I want to build a voice assistant app that can detect suspicious people and notify contacts based on your emotions. How can I implement a system that can respond appropriately when the user feels anxious or scared?"

[0853] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0854] Step 1:

[0855] The user issues a voice command

[0856] The user speaks to the device saying, "Something's wrong."

[0857] Input: User's voice

[0858] Output: Audio data (digital format)

[0859] Step 2:

[0860] The device captures the audio data

[0861] The device's microphone collects the user's voice and stores it as audio data.

[0862] Input: User's voice

[0863] Output: Audio data

[0864] Step 3:

[0865] The device sends the audio data to the server.

[0866] The collected voice data is sent to a server via the Internet.

[0867] Input: Audio data

[0868] Output: Audio data sent to the server

[0869] Step 4:

[0870] The server analyzes the audio data

[0871] The server uses a speech recognition engine to convert the voice data into text data.

[0872] Input: Audio data

[0873] Output: Text data

[0874] Step 5:

[0875] The server analyzes emotions using an emotion engine.

[0876] The server uses an emotion engine to recognize the user's emotional state (e.g., anxiety, fear) from the text data and voice features.

[0877] Input: Text data and audio features

[0878] Output: Emotional state (e.g., anxiety)

[0879] Step 6:

[0880] The server analyzes the text data and obtains the necessary information.

[0881] The server sends a request to a news retrieval API or similar to obtain the necessary information.

[0882] Input: Text data

[0883] Output: Specific information obtained

[0884] Step 7:

[0885] Adapting the information acquired by the server according to emotions

[0886] The server adjusts the information it receives based on the user's emotional state. For example, if the user is feeling anxious, it will prioritize information about reassurance and emergency measures.

[0887] Input: specific information and emotional state obtained

[0888] Output: Adapted information

[0889] Step 8:

[0890] The server synthesizes the adapted information into voice.

[0891] The server uses a speech synthesis engine to generate the adapted information as voice data.

[0892] Input: Adapted information

[0893] Output: Audio data

[0894] Step 9:

[0895] The server sends the audio data to the device.

[0896] The server transmits the generated voice data to the terminal.

[0897] Input: Audio data

[0898] Output: Audio data sent to the device

[0899] Step 10:

[0900] The device provides adapted information via voice

[0901] The terminal reproduces the received audio data and provides it to the user as audio.

[0902] Input: Audio data

[0903] Output: Audio information presented to the user

[0904] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0905] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0906] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0907] [Third embodiment]

[0908] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0909] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0910] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0911] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0912] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0913] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0914] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0915] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0916] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0917] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0918] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0919] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0920] The system of the present invention utilizes speech recognition and speech synthesis technology to enable users to easily operate digital devices. This system includes means for collecting speech data, means for converting the speech data into text data, means for acquiring specific information, and means for providing the information to the user by voice.

[0921] Overall system configuration

[0922] The system consists of the following main components:

[0923] Devices (terminals) operated by users

[0924] server

[0925] Speech Recognition Engine

[0926] Speech synthesis engine

[0927] News retrieval API or other information retrieval services

[0928] Program processing flow

[0929] Speech recognition and information acquisition

[0930] 1. The user issues a voice command

[0931] The user speaks to the device and says, "Tell me the latest news."

[0932] 2. The device captures the audio data

[0933] The device's microphone collects the user's voice and stores it as audio data.

[0934] 3. The device sends the audio data to the server

[0935] The device sends the collected voice data to the server.

[0936] 4. The server analyzes the audio data

[0937] The server uses a speech recognition engine to convert the voice data into text data.

[0938] Based on the parsed text data, the server sends an API request to retrieve specific information the user desires, such as the latest news.

[0939] 5. The server retrieves the information and sends it to the device.

[0940] The server obtains the necessary information from the news acquisition API and sends that information to the terminal.

[0941] 6. The device provides information aloud

[0942] The terminal uses a speech synthesis engine to provide the acquired news information to the user by voice.

[0943] Specific examples

[0944] Example 1: Getting news by voice command

[0945] The user speaks to the device saying, "Tell me the latest news." The device's microphone captures the voice and sends it to the server. The server uses speech recognition technology to convert the voice into text and sends a request to the news acquisition API. The latest news information is acquired, sent from the server to the device, and provided to the user as audio by a speech synthesis engine.

[0946] Example 2: Sending a message using simplified touch controls

[0947] The user taps the "Send Message" icon on the screen. An input screen appears and the user types a message by voice, such as "Good morning, how are you?" The device captures the voice and sends it to the server. The server uses a speech recognition engine to convert the voice into text and sends the text message to the device. The message is displayed on the device, and the user can confirm it by tapping the send button, and the message is sent.

[0948] In this way, this system utilizes the user's voice input to make the operation of digital devices intuitive and simple, allowing even people who are not good at using digital devices to easily obtain information and enjoy the benefits of digital devices.

[0949] The processing flow will be explained below.

[0950] Processing steps for getting news by voice command

[0951] Step 1:

[0952] The user speaks to the device and says, "Tell me the latest news."

[0953] Step 2:

[0954] The device captures audio data through the microphone and temporarily stores the audio data in a buffer.

[0955] Step 3:

[0956] The voice data stored on the device is sent to a server via the Internet.

[0957] Step 4:

[0958] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[0959] Step 5:

[0960] The server analyzes the text data and understands the command "get the latest news."

[0961] Step 6:

[0962] The server sends a request to the news retrieval API to retrieve the latest news information.

[0963] Step 7:

[0964] The news information acquired by the server is converted into a data format for audio output and sent to the terminal.

[0965] Step 8:

[0966] The news information received by the device is passed to a speech synthesis engine, converted into audio data, and played over the speaker.

[0967] Step 9:

[0968] The user listens to the latest news information broadcast over the speaker.

[0969] Processing steps for sending a message using simplified touch

[0970] Step 1:

[0971] A user taps the "Send Message" icon on the screen of a digital device.

[0972] Step 2:

[0973] The device detects the tap event and displays a message input screen for voice input.

[0974] Step 3:

[0975] The user speaks to the displayed message screen and inputs the message content, saying "Good morning, how are you?"

[0976] Step 4:

[0977] The device captures audio input through the microphone and temporarily stores the audio data in a buffer.

[0978] Step 5:

[0979] The voice data stored on the device is sent to a server via the Internet.

[0980] Step 6:

[0981] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[0982] Step 7:

[0983] The server sends the converted text data to the terminal.

[0984] Step 8:

[0985] The text data received by the terminal is displayed on the screen and the user is asked, "Do you want to send this message?"

[0986] Step 9:

[0987] The user taps the "Send" button on the confirmation screen.

[0988] Step 10:

[0989] The terminal transmits the confirmed text message again to the server, and the server transmits the message to the designated recipient.

[0990] Example 1

[0991] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0992] In today's world, operating digital devices is necessary in many situations, but these operations are often complex and unintuitive for users. In particular, conventional systems often lack accuracy and immediacy when inputting or retrieving information using voice. Furthermore, when operations are complex and require advanced skills, they pose a high barrier to entry for users unfamiliar with the technology. Given this background, there is a demand for the development of systems that use voice recognition and speech synthesis technologies to enable users to intuitively operate digital devices.

[0993] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0994] In this invention, the server includes means for a user to issue a voice command, means for a terminal to capture voice data, means for transmitting the voice data to the server, means for the server to convert the voice data into text data using a voice recognition engine, means for transmitting an API request to acquire specific information based on the text data, means for transmitting the specific information to the terminal, and means for the terminal to provide the specific information to the user by voice using a voice synthesis engine. This enables a user to intuitively and easily operate a digital device through voice commands and acquire necessary information by voice.

[0995] A "means for a user to issue voice commands" is an interface that allows a user to input instructions or requests by voice into a digital device.

[0996] "Means for the terminal to capture voice data" refers to the function of a microphone installed in a digital device to collect the user's voice and store it as digital voice data.

[0997] The "means for transmitting the audio data to the server" is a function for transferring audio data from the digital device to the server via network communication.

[0998] "Means for the server to convert voice data into text data using a voice recognition engine" refers to the processing ability of the server to convert received voice data into text using voice recognition technology.

[0999] The "means of sending an API request to obtain specific information based on the text data" is an operation of sending a request to an external service to obtain specific information based on the converted text data.

[1000] The "means for transmitting the specific information to the terminal" is a function for transmitting the information acquired by the server to the digital device via network communication.

[1001] "Means for the terminal to provide the user with the specific information by voice using a voice synthesis engine" refers to a function in which a digital device uses voice synthesis technology to convert acquired information into voice and convey it to the user.

[1002] The system of the present invention enables users to easily operate digital devices using speech recognition and speech synthesis technology. The system consists of the following main components: a device (terminal) operated by the user, a server, a speech recognition engine, a speech synthesis engine, and a news retrieval API or other information retrieval service.

[1003] Terminals include devices such as smartphones, tablets, and smart speakers. These devices use built-in microphones to capture voice data and send it to a server via the Internet. The server converts the voice data into text data using a speech recognition engine (e.g., Google Cloud Speech-to-Text). The server then sends a request to an information retrieval API (e.g., NewsAPI) based on the text data to retrieve the required information. The retrieved information is then sent back to the terminal, where it uses a speech synthesis engine (e.g., Amazon Polly) to provide the retrieved information to the user via voice.

[1004] Specific examples

[1005] Example 1: Getting news by voice command

[1006] The user speaks to the device saying, "Tell me the latest news." The device's microphone captures the audio and sends it to the server. The server uses Google Cloud Speech-to-Text to convert the audio into text. Based on the text, the server requests the latest news information from the News API. The news information obtained from the News API is sent to the device in JSON format. The device uses Amazon Polly to convert the acquired news information into audio and provides it to the user through the speaker.

[1007] Example 2: Sending a message using simplified touch controls

[1008] The user taps the "Send Message" icon displayed on the smartphone screen. On the displayed input screen, the user voice-inputs "Good morning, how are you?" The device captures this voice and sends it to the server. The server uses a voice recognition engine to convert the voice into text and sends the text to the device. After checking the displayed message, the user taps the send button to send the message.

[1009] Hardware and software used

[1010] Hardware: User devices (terminals), servers

[1011] software:

[1012] Speech recognition engine: Google Cloud Speech-to-Text

[1013] Speech synthesis engine: Amazon Polly

[1014] Information acquisition API:NewsAPI

[1015] This system allows users to intuitively and easily operate digital devices through voice commands and instantly obtain the information they need. For example, users can obtain stock price information by voice simply by uttering a prompt such as "How are the stock prices today?". Users can also easily send messages and perform various operations through the GUI. This makes it easy for even users who are not familiar with technology to operate digital devices.

[1016] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1017] Processing flow

[1018] Step 1: User issues a voice command

[1019] The user issues a voice command to the device, such as "Tell me the latest news."

[1020] Input: User's voice

[1021] Output: Audio data

[1022] Specific operation: The user speaks into a device such as a smartphone or tablet, and the audio is input into the microphone.

[1023] Step 2: The device captures the audio data

[1024] The device's microphone captures the user's voice data and stores it in digital form.

[1025] Input: User's voice

[1026] Output: Digital audio data

[1027] Specific operation: The device's built-in microphone collects audio and temporarily stores it as digital data in the internal memory.

[1028] Step 3: The device sends the audio data to the server

[1029] The device transmits the captured audio data to a server via the Internet.

[1030] Input: Digital audio data

[1031] Output: Sending audio data to the server

[1032] What happens: Audio data is split into network packets and sent over the Internet to a server.

[1033] Step 4: The server analyzes the audio data

[1034] The server uses a speech recognition engine to convert the voice data into text data, and then sends an API request to retrieve specific information based on the converted text data.

[1035] Input: Digital audio data

[1036] Output: Text data and API request transmission

[1037] How it works: A speech recognition engine on the server analyzes the voice data and converts it into text, such as "Tell me the latest news." An HTTP message is then generated and sent to send a request to the News API.

[1038] Step 5: The server retrieves the information and sends it to the device

[1039] The server receives news information obtained from the NewsAPI in JSON format and sends it to the terminal.

[1040] Input: API request and retrieved information

[1041] Output: News information sent to the terminal in JSON format

[1042] Specific operation: The server converts the news data obtained from the NewsAPI into JSON format and sends it to the terminal via the network.

[1043] Step 6: The device provides information aloud

[1044] The terminal uses a speech synthesis engine to convert the acquired news information into speech and provide it to the user.

[1045] Input: News information in JSON format

[1046] Output: Audio data and audio presented to the user

[1047] How it works: The device parses the JSON-formatted news data, and the speech synthesis engine converts it into speech, which is then played back through the device's speaker.

[1048] (Application example 1)

[1049] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1050] On modern online shopping sites, users must navigate through multiple screens and input information to efficiently obtain a wide variety of information, making operation cumbersome. Visually impaired users and those unfamiliar with technology have particular difficulties when searching for products, checking order status, or browsing product reviews. Given this background, there was a demand for a more intuitive and convenient way to obtain information.

[1051] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1052] In this invention, the server includes means for converting voice data into text data, means for acquiring specific information, means for providing the specific information to the user by voice, means for the user to search for products using a voice command, means for acquiring search results based on the voice command, and means for providing the search results to the user by voice, thereby enabling the user to intuitively search for products, check order status, and obtain product reviews using voice.

[1053] "Audio data" is a recording of sounds made by a user into a digital device.

[1054] "Text data" is voice data that has been analyzed and converted into text information.

[1055] "Specific information" is the necessary data that is obtained based on the user's voice command.

[1056] "Product search" is the process of searching for a specified product based on a voice command.

[1057] "Search results" is a list of information obtained through the product search process.

[1058] A "GUI" is a type of user interface that allows users to operate a device using visual elements such as icons and buttons.

[1059] "Voice input" refers to a user giving voice instructions to a digital device.

[1060] "Capture" refers to the collection of audio data using a digital device's microphone.

[1061] A "server" is a computer system that receives and processes requests from digital devices that are clients.

[1062] "Speech synthesis" is a technology that converts text data back into voice data and outputs it as voice.

[1063] "Product reviews" are evaluations and impressions written by users who have purchased a product about its usability and quality.

[1064] "Order Status" is the current processing status of the product ordered by the user.

[1065] "API" stands for Application Program Interface, a set of rules and procedures that allow different software programs to communicate with each other.

[1066] The system of this invention consists of the following components: a device (terminal) operated by the user, a server, a voice recognition engine, a voice synthesis engine, and an API service for product searches, order status confirmation, and product review acquisition.

[1067] Overall system configuration

[1068] 1. Acquiring voice input

[1069] When a user speaks into a device such as a smartphone, saying "Find the latest smartphone," the device's microphone captures the voice, and the captured voice data is sent from the device to the server.

[1070] 2. Speech Recognition and Text Conversion

[1071] The server converts the voice data into text data using a speech recognition engine, such as the Google Cloud Speech-to-Text API or Amazon Transcribe.

[1072] 3. Text data analysis and information acquisition

[1073] The server parses the text data, understands the user's command, and then sends a request to the appropriate API, for example, to an e-commerce API for product search, or to an order management API for order status check.

[1074] 4. Speech synthesis and provision of information

[1075] The information acquired by the server is converted into voice data using a speech synthesis engine such as Google Cloud Text-to-Speech API and sent to the device, which then plays the voice data and provides the information to the user.

[1076] Specific examples

[1077] Specific examples of product searches

[1078] When a user says to the device, "Search for the latest smartphone," the microphone captures the voice data. The voice data is sent to the server, where it is converted into text data by a voice recognition engine. The server analyzes the text data and obtains information about the latest smartphones from an e-commerce API. The resulting search results are converted into voice data by a voice synthesis engine and provided to the user via the device.

[1079] Example of checking order status

[1080] When a user speaks to the device, asking, "What's the status of my order?", the microphone similarly captures the voice data. The voice data is sent to the server and converted into text data. The server then sends a request to the order management API to obtain the order status. The obtained information is converted into voice data by a speech synthesis engine and communicated to the user via the device.

[1081] Prompt Sentence Examples

[1082] "Write a program that receives a voice command to search for a product and responds with the search results in voice. Specifically, the program will allow the user to issue a voice command such as "Tell me about the latest smartphone," convert the command into text using voice recognition, and return the retrieved information in voice."

[1083] As mentioned above, this system utilizes user voice control to enable intuitive and easy product searches, order status checks, and product reviews, making it easy to use even for people who are not comfortable using digital devices.

[1084] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1085] Step 1:

[1086] The user issues a voice command, for example, "Find the latest smartphone," which generates voice data.

[1087] Step 2:

[1088] The device captures the voice data. The device's microphone collects the user's voice and stores it as digital voice data. The captured voice data becomes the input.

[1089] Step 3:

[1090] The device sends the voice data to the server. The device sends the collected voice data to the server via the network. The input is the voice data, and the output is the data sent to the server.

[1091] Step 4:

[1092] The server converts the voice data into text data. The server uses a speech recognition engine such as Google Cloud Speech-to-Text API or Amazon Transcribe to convert the received voice data into text data. The input is voice data, and the output is text data.

[1093] Step 5:

[1094] The server parses the text data and sends a request to the appropriate API. The server extracts the user's command from the parsed text data and sends an information retrieval request to, for example, an e-commerce API or an order management API. The input is text data and the output is an API request.

[1095] Step 6:

[1096] An API provides information in response to a request. E-commerce APIs and order management APIs return specific information, such as product details or order status, based on a server request. The input is the API request, and the output is information data.

[1097] Step 7:

[1098] The server converts the acquired information into voice data. The server uses a speech synthesis engine such as Google Cloud Text-to-Speech API to convert the acquired information data into voice data. The input is information data, and the output is voice data.

[1099] Step 8:

[1100] The server sends the audio data to the terminal. The server then sends the converted audio data to the terminal via the network. The input is the audio data, and the output is the data sent to the terminal.

[1101] Step 9:

[1102] The terminal plays back the audio data and provides information to the user. The terminal plays back the received audio data so that the user can hear the information. The input is audio data and the output is audio information.

[1103] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1104] The present invention not only provides the ability to easily operate digital devices by leveraging the user's voice input, but also combines it with an emotion engine that recognizes the user's emotions from their voice, thereby adapting the information and responses provided to the user depending on their emotional state.

[1105] Overall system configuration

[1106] The system consists of the following main components:

[1107] Devices (terminals) operated by users

[1108] server

[1109] Speech Recognition Engine

[1110] Speech synthesis engine

[1111] News retrieval API or other information retrieval services

[1112] Emotion Engine

[1113] Program processing flow

[1114] Speech recognition, emotion recognition, information acquisition

[1115] 1. The user issues a voice command

[1116] The user speaks to the device and says, "Tell me the latest news."

[1117] 2. The device captures the audio data

[1118] The device's microphone collects the user's voice and stores it as audio data.

[1119] 3. The device sends the audio data to the server

[1120] The device sends the collected voice data to the server.

[1121] 4. The server analyzes the audio data

[1122] The server uses a speech recognition engine to convert the voice data into text data.

[1123] 5. The server analyzes emotions using an emotion engine

[1124] The server recognizes the user's emotional state (happiness, sadness, anger, surprise, etc.) based on the voice data.

[1125] 6. The server analyzes the text data and obtains the necessary information.

[1126] The server sends a request to the news retrieval API based on the analyzed text data.

[1127] 7. Adapt the information acquired by the server according to emotions

[1128] The server adapts the retrieved news information according to the user's emotional state, for example, if the user is sad, it will prioritize positive news.

[1129] 8. The server sends the information to the device

[1130] The server transmits the adapted news information to the terminal.

[1131] 9. Device provides adapted information by voice

[1132] The terminal uses a speech synthesis engine to provide the acquired news information to the user by voice.

[1133] Specific examples

[1134] Example 1: Get news by voice command and adapt according to emotions

[1135] The user speaks to the device, saying, "Tell me the latest news." The device's microphone captures the voice and sends it to the server. The server uses a speech recognition engine to convert the voice into text and an emotion engine to analyze the user's emotions. If the server determines that the user is sad, it sends a request to the news acquisition API and prioritizes the retrieved news information to be more positive. The adapted news information is then sent to the device, where it is provided to the user as audio by a speech synthesis engine.

[1136] Example 2: Sending messages with simplified touch controls and reviewing the content based on emotions

[1137] The user taps the "Send Message" icon on the screen. An input screen appears and the user types a message by voice, such as "Good morning, how are you?" The device captures the voice and sends it to the server. The server uses a speech recognition engine and emotion engine to convert the voice into text and analyzes the user's emotion. The server sends the converted text message to the device and displays a confirmation message corresponding to the emotion when it is displayed on the screen. For example, if the user is angry, an additional confirmation such as "Are you sure this is the correct message?" is displayed. After the user confirms, the message is sent by tapping the "Send" button.

[1138] By taking into account the user's emotional state, the system provides more personalized information and responses, improving the user experience and making digital devices easier to use.

[1139] The processing flow will be explained below.

[1140] Processing steps for getting news by voice command and adapting it according to emotions

[1141] Step 1:

[1142] The user speaks to the device and says, "Tell me the latest news."

[1143] Step 2:

[1144] The device captures audio data through the microphone and temporarily stores the audio data in a buffer.

[1145] Step 3:

[1146] The voice data stored on the device is sent to a server via the Internet.

[1147] Step 4:

[1148] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[1149] Step 5:

[1150] The server analyzes the text data and understands the user's request: "Tell me the latest news."

[1151] Step 6:

[1152] The server uses an emotion engine to analyze the user's emotional state (e.g., joy, sadness, anger, surprise) from the voice data.

[1153] Step 7:

[1154] The server sends a request to a news acquisition API based on the text data to acquire the latest news information.

[1155] Step 8:

[1156] The server analyzes the news information it receives and adjusts the content it provides based on the user's emotions. For example, if the user is sad, it will prioritize positive news.

[1157] Step 9:

[1158] The server converts the adapted news information into a data format for voice output and transmits it to the terminal.

[1159] Step 10:

[1160] The news information received by the device is passed to a speech synthesis engine, converted into audio data, and played over the speaker.

[1161] Step 11:

[1162] The user listens to the latest news information broadcast over the speaker.

[1163] Steps for sending messages with simplified touch controls and reviewing them based on emotions

[1164] Step 1:

[1165] A user taps the "Send Message" icon on the screen of a digital device.

[1166] Step 2:

[1167] The device detects the tap event and displays a message input screen for voice input.

[1168] Step 3:

[1169] The user speaks to the displayed message screen and inputs the message content, saying "Good morning, how are you?"

[1170] Step 4:

[1171] The device captures audio input through the microphone and temporarily stores the audio data in a buffer.

[1172] Step 5:

[1173] The voice data stored on the device is sent to a server via the Internet.

[1174] Step 6:

[1175] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[1176] Step 7:

[1177] The server analyzes the text data converted by the voice recognition engine and recognizes the content of the user's message.

[1178] Step 8:

[1179] The server uses an emotion engine to analyze the user's emotional state from the voice data.

[1180] Step 9:

[1181] The server sends text data to the terminal, which displays it on the screen.

[1182] Step 10:

[1183] The device displays a confirmation message such as "Are you sure you want this message?" based on the user's emotional state.

[1184] Step 11:

[1185] The user taps the "Send" button on the confirmation screen.

[1186] Step 12:

[1187] The terminal transmits the confirmed text message again to the server, and the server transmits the message to the designated recipient.

[1188] Example 2

[1189] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1190] In recent years, many digital devices have been designed to be operated by voice commands. However, these systems provide information without considering the user's emotional state, limiting the user experience. Another issue is that simply providing information obtained from voice input without consideration of the user's emotional state does not allow for an appropriate response based on the user's emotions. The present invention aims to provide a system that analyzes a user's voice input and their emotional state, enabling more personalized information delivery.

[1191] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1192] In this invention, the server includes means for converting voice data into text data, means for analyzing the user's emotional state based on the text data, means for acquiring specific information based on the text data and the user's emotional state, means for adapting the acquired information to the user's emotional state, and means for providing the adapted information to the user by voice, thereby enabling adaptive information provision according to the user's emotional state.

[1193] "Voice data" is voice information collected from a user in digital form.

[1194] "Text data" is information obtained by converting voice data into characters.

[1195] A "voice recognition engine" is a software or hardware function that converts voice data into text data.

[1196] An "emotion recognition engine" is a software or hardware function that analyzes and identifies a user's emotional state from text and voice data.

[1197] The "specific information" is content obtained based on the user's voice input and emotional state, such as news information and weather information.

[1198] "Adapting" means optimizing the information retrieved based on the user's emotional state, for example prioritizing positive information if the user is sad.

[1199] A "speech synthesis engine" is a software or hardware function for outputting text data as voice.

[1200] An "information acquisition service" is a means of collecting necessary information using external APIs and databases.

[1201] The present invention not only leverages the user's voice input to provide the ability to easily operate digital devices, but also combines it with an emotion engine that recognizes the user's emotions from their voice, thereby adapting the information and responses provided to the user based on their emotional state, resulting in a personalized user experience.

[1202] Overall system configuration

[1203] The system consists of the following main components:

[1204] Devices (terminals) operated by users

[1205] server

[1206] Speech Recognition Engine

[1207] Emotion Recognition Engine

[1208] Speech synthesis engine

[1209] News retrieval API or other information retrieval services

[1210] Hardware and software used

[1211] 1. Speech recognition engine: To convert voice data into text data, common speech recognition software is used, such as Google Cloud Speech-to-Text API.

[1212] 2. Emotion recognition engine: Uses an engine to analyze the user's emotional state from text and voice data. An example is IBM Watson Tone Analyzer.

[1213] 3. Speech synthesis engine: Uses an engine to convert text data into speech, such as Amazon Polly.

[1214] 4. Information Retrieval Services: Used to retrieve news and other related information. An example is NewsAPI.org.

[1215] Specific processing of the program

[1216] Let's use the example of a user speaking to a device, saying, "Tell me the latest news." First, the user speaks to the device. The device uses its built-in microphone to collect voice data and stores it as digital data. The device then sends the collected voice data to a server. The server uses the Google Cloud Speech-to-Text API to convert the voice data into text data.

[1217] The server then uses IBM Watson Tone Analyzer to analyze the user's emotional state based on the text and audio data. Based on the analyzed text data, the server sends a request to a news retrieval API (e.g., NewsAPI.org) to retrieve the latest news information. The server then adapts the retrieved news information according to the user's emotional state. For example, if the user is sad, it will prioritize positive news.

[1218] The server then sends the final adapted news information to the device, which then uses Amazon Polly to convert the news information into speech, which is then presented to the user through the device's speaker.

[1219] Specific examples

[1220] Example 1: Get news by voice command and adapt according to emotions

[1221] The user speaks to the device, saying, "Tell me the latest news." The device's microphone captures the audio and sends it to the server. The server converts the audio into text using the Google Cloud Speech-to-Text API and analyzes the user's emotions using IBM Watson Tone Analyzer. If the server determines that the user is sad, it sends a request to NewsAPI.org to prioritize positive news. The retrieved news is then formatted and sent to the device. The device then converts the news into audio using Amazon Polly, which is finally played from the speaker.

[1222] Prompt Sentence Examples

[1223] "You are designing a system to control digital devices that a user talks to. The system will analyze the user's voice and emotional state and provide adaptive responses based on the emotion. Please name the steps involved and the specific hardware and software you will use."

[1224] This allows the present invention to take into account the user's emotional state and provide more personalized responses, improving the user's experience of operating a digital device.

[1225] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1226] Step 1:

[1227] The user issues a voice command

[1228] The user speaks to the device, saying "Tell me the latest news." The input is the user's voice, which triggers the system to start. The output is the voice data input to the device's microphone. Specifically, the user speaks into the device's microphone, and the voice is captured as an analog signal.

[1229] Step 2:

[1230] The device captures the audio data

[1231] The device's microphone collects the user's voice as digital voice data. The input is the user's analog voice, and the output is digital voice data. Specifically, the device's built-in microphone converts the analog voice signal into digital data. This data is temporarily stored in the device's memory.

[1232] Step 3:

[1233] The device sends the audio data to the server.

[1234] The terminal transmits the collected digital audio data to a server via the Internet. The input is the captured digital audio data, and the output is the audio data that arrives at the server. Specifically, the terminal transmits data packets to the server using the HTTPS protocol, and the server receives the audio data.

[1235] Step 4:

[1236] The server analyzes the audio data

[1237] The server uses a speech recognition engine (e.g., Google Cloud Speech-to-Text API) to convert the voice data into text data. The input is digital voice data, and the output is text data. Specifically, the server sends the voice data to the API, and the speech recognition engine analyzes it and returns it as a string.

[1238] Step 5:

[1239] The server analyzes emotions using an emotion engine.

[1240] The server uses an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotional state based on the text and voice data. The input is the converted text and voice data, and the output is parameters of the user's emotional state (happiness, sadness, etc.). Specifically, the server passes the text data to the emotion recognition engine and receives the emotion parameters as the analysis result.

[1241] Step 6:

[1242] The server analyzes the text data and obtains the necessary information.

[1243] The server retrieves specific information based on the parsed text data. In this process, a request is sent to an information retrieval service (e.g., a news retrieval API). The input is the parsed text data, and the output is the retrieved specific information (e.g., news articles). Specifically, the server analyzes the content of the text data, generates an appropriate search query, sends it to the API, and receives the returned information.

[1244] Step 7:

[1245] Adapting the information acquired by the server according to emotions

[1246] The server adapts the information it acquires based on the user's emotional state. The input is news information and the user's emotional parameters, and the output is adapted news information. Specifically, the server uses the user's emotional parameters to filter information, such as prioritizing positive information.

[1247] Step 8:

[1248] The server sends the information to the device

[1249] The server sends the adapted news information to the device. The input is the adapted news information, and the output is the state it has reached on the device. Specifically, the server packets the information in JSON format and sends it to the device using the HTTPS protocol.

[1250] Step 9:

[1251] The device provides adapted information via voice

[1252] The device uses a speech synthesis engine (e.g., Amazon Polly) to convert the adapted news information into speech. The input is the news information received from the server, and the output is the generated speech data. Specifically, the device sends text data to the speech synthesis engine, and the generated audio file is played back from the speaker and provided to the user.

[1253] Through these processing steps, personalized information provision according to the user's emotional state is realized.

[1254] (Application example 2)

[1255] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1256] In recent years, advances in speech recognition technology have enabled users to operate devices by voice. However, conventional speech recognition systems have had the problem of being unable to adapt responses to the user's intentions and emotions because they do not take the user's emotional state into account. Furthermore, particularly in security services, systems that ignore the user's emotional state have difficulty responding quickly and appropriately to emergencies and ensuring the user's safety. Therefore, there is a need for systems that can improve the operability of digital devices and enhance the user experience by recognizing the user's emotional state and providing appropriate information and responses accordingly.

[1257] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting voice data, means for converting the voice data into text data, means for acquiring specific information based on the text data, means for providing the specific information to the user by voice, means for analyzing the user's emotional state based on the voice data, and means for adapting the acquired information based on the emotional state. This makes it possible to provide appropriate information and responses according to the user's emotional state, improving the operability of digital devices and enabling quick and appropriate responses, particularly in security services.

[1258] "Audio Data" means a digital recording of a user's audio signals made by a user to a device.

[1259] "Text data" is character string data generated by analyzing voice data, and represents the content of a user's speech as text information.

[1260] "Specific information" refers to necessary data or knowledge acquired based on a user's request or instruction, and refers to specific content such as news or weather information.

[1261] "Emotional state" refers to the emotional state of the user that can be inferred from the tone and pattern of the user's voice, and includes emotional responses such as joy, sadness, anger, and anxiety.

[1262] "Speech recognition" is a technology that analyzes voice data and recognizes its content as text data.

[1263] "Speech synthesis" is a technology that analyzes text data, reconstructs it into natural speech, and provides it to the user as audio information.

[1264] "Emotion analysis" is a technology that recognizes and classifies a user's emotional state from voice data.

[1265] "Adaptation" is the process of adjusting acquired information and system responses to the user's emotional state, providing a more personalized response.

[1266] A "system" is a set of programs and hardware for executing a series of processes such as collecting, analyzing, providing information, analyzing emotions, and adapting voice data.

[1267] Basic system configuration

[1268] This invention is a system that captures voice data, analyzes the user's emotions based on that data, and provides adaptive responses. The main components used are as follows:

[1269] 1. Device: A device such as a smartphone or smart speaker that captures the user's voice. The device is equipped with a microphone.

[1270] 2. Server: Analyzes voice data, recognizes emotions, acquires information, and adapts.

[1271] 3. Speech recognition engine: Software that converts voice data into text data.

[1272] 4. Speech synthesis engine: Software that reconstructs text data as speech data.

[1273] 5. Emotion Engine: Software for recognizing and classifying a user's emotional state from voice data.

[1274] 6. News API and other information retrieval services: External services for retrieving specific information.

[1275] System processing explanation in natural language

[1276] The device captures the user's voice input with a microphone and sends the voice data to the server, which then uses a speech recognition engine (e.g., a speech recognition service provided as an API) to convert the voice data into text data, and then uses an emotion engine to analyze the user's voice for emotion.

[1277] Based on the analyzed text data, the server sends requests to news retrieval APIs and other information retrieval services to obtain the necessary information. The retrieved information is then adapted according to the user's emotional state. For example, if the user is feeling anxious, reassurance information and emergency prevention information will be provided first.

[1278] The adapted information is converted into voice data by a speech synthesis engine and provided to the user via the device. Through this series of processes, the user can receive appropriate information and responses adapted to their emotional state.

[1279] The specific hardware and software used

[1280] Smartphone: A device that is always carried by the user and has a microphone for capturing voice input.

[1281] Server: Responsible for all data analysis and information acquisition. Often uses cloud services.

[1282] Speech Recognition Engine: A speech recognition service such as the Google Speech-to-Text API.

[1283] Text-to-speech engine: A text-to-speech service like the Google Text-to-Speech API.

[1284] Emotion Engine: Dedicated software for Emotion Recognition.

[1285] News retrieval API: A news service (e.g., NewsAPI).

[1286] Specific examples

[1287] Example 1

[1288] When a user feels that "something is strange" on a dark street, they speak into their smartphone saying, "Something is strange." This voice data is captured by the device's microphone and sent to the server. The server converts the voice into text using a voice recognition engine and analyzes the emotion of anxiety using an emotion engine. If it determines that suspicious person detection is necessary, the server immediately notifies the user, saying, "A suspicious person has been detected. Please ensure your safety."

[1289] Example 2

[1290] When a user suddenly feels fear, the emotion engine recognizes this fear and automatically calls a pre-registered emergency contact. A message generated by the speech synthesis engine, "This is an emergency! Please contact us immediately," is sent, helping the user quickly ensure safety.

[1291] Prompt Sentence Examples

[1292] An example prompt is:

[1293] "I want to build a voice assistant app that can detect suspicious people and notify contacts based on your emotions. How can I implement a system that can respond appropriately when the user feels anxious or scared?"

[1294] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1295] Step 1:

[1296] The user issues a voice command

[1297] The user speaks to the device saying, "Something's wrong."

[1298] Input: User's voice

[1299] Output: Audio data (digital format)

[1300] Step 2:

[1301] The device captures the audio data

[1302] The device's microphone collects the user's voice and stores it as audio data.

[1303] Input: User's voice

[1304] Output: Audio data

[1305] Step 3:

[1306] The device sends the audio data to the server.

[1307] The collected voice data is sent to a server via the Internet.

[1308] Input: Audio data

[1309] Output: Audio data sent to the server

[1310] Step 4:

[1311] The server analyzes the audio data

[1312] The server uses a speech recognition engine to convert the voice data into text data.

[1313] Input: Audio data

[1314] Output: Text data

[1315] Step 5:

[1316] The server analyzes emotions using an emotion engine.

[1317] The server uses an emotion engine to recognize the user's emotional state (e.g., anxiety, fear) from the text data and voice features.

[1318] Input: Text data and audio features

[1319] Output: Emotional state (e.g., anxiety)

[1320] Step 6:

[1321] The server analyzes the text data and obtains the necessary information.

[1322] The server sends a request to a news retrieval API or similar to obtain the necessary information.

[1323] Input: Text data

[1324] Output: Specific information obtained

[1325] Step 7:

[1326] Adapting the information acquired by the server according to emotions

[1327] The server adjusts the information it receives based on the user's emotional state. For example, if the user is feeling anxious, it will prioritize information about reassurance and emergency measures.

[1328] Input: specific information and emotional state obtained

[1329] Output: Adapted information

[1330] Step 8:

[1331] The server synthesizes the adapted information into voice.

[1332] The server uses a speech synthesis engine to generate the adapted information as voice data.

[1333] Input: Adapted information

[1334] Output: Audio data

[1335] Step 9:

[1336] The server sends the audio data to the device.

[1337] The server transmits the generated voice data to the terminal.

[1338] Input: Audio data

[1339] Output: Audio data sent to the device

[1340] Step 10:

[1341] The device provides adapted information via voice

[1342] The terminal reproduces the received audio data and provides it to the user as audio.

[1343] Input: Audio data

[1344] Output: Audio information presented to the user

[1345] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1346] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1347] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1348] [Fourth embodiment]

[1349] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1350] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1351] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1352] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1353] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1354] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1355] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1356] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1357] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1358] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1359] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1360] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1361] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1362] The system of the present invention utilizes speech recognition and speech synthesis technology to enable users to easily operate digital devices. This system includes means for collecting speech data, means for converting the speech data into text data, means for acquiring specific information, and means for providing the information to the user by voice.

[1363] Overall system configuration

[1364] The system consists of the following main components:

[1365] Devices (terminals) operated by users

[1366] server

[1367] Speech Recognition Engine

[1368] Speech synthesis engine

[1369] News retrieval API or other information retrieval services

[1370] Program processing flow

[1371] Speech recognition and information acquisition

[1372] 1. The user issues a voice command

[1373] The user speaks to the device and says, "Tell me the latest news."

[1374] 2. The device captures the audio data

[1375] The device's microphone collects the user's voice and stores it as audio data.

[1376] 3. The device sends the audio data to the server

[1377] The device sends the collected voice data to the server.

[1378] 4. The server analyzes the audio data

[1379] The server uses a speech recognition engine to convert the voice data into text data.

[1380] Based on the parsed text data, the server sends an API request to retrieve specific information the user desires, such as the latest news.

[1381] 5. The server retrieves the information and sends it to the device.

[1382] The server obtains the necessary information from the news acquisition API and sends that information to the terminal.

[1383] 6. The device provides information aloud

[1384] The terminal uses a speech synthesis engine to provide the acquired news information to the user by voice.

[1385] Specific examples

[1386] Example 1: Getting news by voice command

[1387] The user speaks to the device saying, "Tell me the latest news." The device's microphone captures the voice and sends it to the server. The server uses speech recognition technology to convert the voice into text and sends a request to the news acquisition API. The latest news information is acquired, sent from the server to the device, and provided to the user as audio by a speech synthesis engine.

[1388] Example 2: Sending a message using simplified touch controls

[1389] The user taps the "Send Message" icon on the screen. An input screen appears and the user types a message by voice, such as "Good morning, how are you?" The device captures the voice and sends it to the server. The server uses a speech recognition engine to convert the voice into text and sends the text message to the device. The message is displayed on the device, and the user can confirm it by tapping the send button, and the message is sent.

[1390] In this way, this system utilizes the user's voice input to make the operation of digital devices intuitive and simple, allowing even people who are not good at using digital devices to easily obtain information and enjoy the benefits of digital devices.

[1391] The processing flow will be explained below.

[1392] Processing steps for getting news by voice command

[1393] Step 1:

[1394] The user speaks to the device and says, "Tell me the latest news."

[1395] Step 2:

[1396] The device captures audio data through the microphone and temporarily stores the audio data in a buffer.

[1397] Step 3:

[1398] The voice data stored on the device is sent to a server via the Internet.

[1399] Step 4:

[1400] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[1401] Step 5:

[1402] The server analyzes the text data and understands the command "get the latest news."

[1403] Step 6:

[1404] The server sends a request to the news retrieval API to retrieve the latest news information.

[1405] Step 7:

[1406] The news information acquired by the server is converted into a data format for audio output and sent to the terminal.

[1407] Step 8:

[1408] The news information received by the device is passed to a speech synthesis engine, converted into audio data, and played over the speaker.

[1409] Step 9:

[1410] The user listens to the latest news information broadcast over the speaker.

[1411] Processing steps for sending a message using simplified touch

[1412] Step 1:

[1413] A user taps the "Send Message" icon on the screen of a digital device.

[1414] Step 2:

[1415] The device detects the tap event and displays a message input screen for voice input.

[1416] Step 3:

[1417] The user speaks to the displayed message screen and inputs the message content, saying "Good morning, how are you?"

[1418] Step 4:

[1419] The device captures audio input through the microphone and temporarily stores the audio data in a buffer.

[1420] Step 5:

[1421] The voice data stored on the device is sent to a server via the Internet.

[1422] Step 6:

[1423] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[1424] Step 7:

[1425] The server sends the converted text data to the terminal.

[1426] Step 8:

[1427] The text data received by the terminal is displayed on the screen and the user is asked, "Do you want to send this message?"

[1428] Step 9:

[1429] The user taps the "Send" button on the confirmation screen.

[1430] Step 10:

[1431] The terminal transmits the confirmed text message again to the server, and the server transmits the message to the designated recipient.

[1432] Example 1

[1433] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1434] In today's world, operating digital devices is necessary in many situations, but these operations are often complex and unintuitive for users. In particular, conventional systems often lack accuracy and immediacy when inputting or retrieving information using voice. Furthermore, when operations are complex and require advanced skills, they pose a high barrier to entry for users unfamiliar with the technology. Given this background, there is a demand for the development of systems that use voice recognition and speech synthesis technologies to enable users to intuitively operate digital devices.

[1435] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1436] In this invention, the server includes means for a user to issue a voice command, means for a terminal to capture voice data, means for transmitting the voice data to the server, means for the server to convert the voice data into text data using a voice recognition engine, means for transmitting an API request to acquire specific information based on the text data, means for transmitting the specific information to the terminal, and means for the terminal to provide the specific information to the user by voice using a voice synthesis engine. This enables a user to intuitively and easily operate a digital device through voice commands and acquire necessary information by voice.

[1437] A "means for a user to issue voice commands" is an interface that allows a user to input instructions or requests by voice into a digital device.

[1438] "Means for the terminal to capture voice data" refers to the function of a microphone installed in a digital device to collect the user's voice and store it as digital voice data.

[1439] The "means for transmitting the audio data to the server" is a function for transferring audio data from the digital device to the server via network communication.

[1440] "Means for the server to convert voice data into text data using a voice recognition engine" refers to the processing ability of the server to convert received voice data into text using voice recognition technology.

[1441] The "means of sending an API request to obtain specific information based on the text data" is an operation of sending a request to an external service to obtain specific information based on the converted text data.

[1442] The "means for transmitting the specific information to the terminal" is a function for transmitting the information acquired by the server to the digital device via network communication.

[1443] "Means for the terminal to provide the user with the specific information by voice using a voice synthesis engine" refers to a function in which a digital device uses voice synthesis technology to convert acquired information into voice and convey it to the user.

[1444] The system of the present invention enables users to easily operate digital devices using speech recognition and speech synthesis technology. The system consists of the following main components: a device (terminal) operated by the user, a server, a speech recognition engine, a speech synthesis engine, and a news retrieval API or other information retrieval service.

[1445] Terminals include devices such as smartphones, tablets, and smart speakers. These devices use built-in microphones to capture voice data and send it to a server via the Internet. The server converts the voice data into text data using a speech recognition engine (e.g., Google Cloud Speech-to-Text). The server then sends a request to an information retrieval API (e.g., NewsAPI) based on the text data to retrieve the required information. The retrieved information is then sent back to the terminal, where it uses a speech synthesis engine (e.g., Amazon Polly) to provide the retrieved information to the user via voice.

[1446] Specific examples

[1447] Example 1: Getting news by voice command

[1448] The user speaks to the device saying, "Tell me the latest news." The device's microphone captures the audio and sends it to the server. The server uses Google Cloud Speech-to-Text to convert the audio into text. Based on the text, the server requests the latest news information from the News API. The news information obtained from the News API is sent to the device in JSON format. The device uses Amazon Polly to convert the acquired news information into audio and provides it to the user through the speaker.

[1449] Example 2: Sending a message using simplified touch controls

[1450] The user taps the "Send Message" icon displayed on the smartphone screen. On the displayed input screen, the user voice-inputs "Good morning, how are you?" The device captures this voice and sends it to the server. The server uses a voice recognition engine to convert the voice into text and sends the text to the device. After checking the displayed message, the user taps the send button to send the message.

[1451] Hardware and software used

[1452] Hardware: User devices (terminals), servers

[1453] software:

[1454] Speech recognition engine: Google Cloud Speech-to-Text

[1455] Speech synthesis engine: Amazon Polly

[1456] Information acquisition API:NewsAPI

[1457] This system allows users to intuitively and easily operate digital devices through voice commands and instantly obtain the information they need. For example, users can obtain stock price information by voice simply by uttering a prompt such as "How are the stock prices today?". Users can also easily send messages and perform various operations through the GUI. This makes it easy for even users who are not familiar with technology to operate digital devices.

[1458] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1459] Processing flow

[1460] Step 1: User issues a voice command

[1461] The user issues a voice command to the device, such as "Tell me the latest news."

[1462] Input: User's voice

[1463] Output: Audio data

[1464] Specific operation: The user speaks into a device such as a smartphone or tablet, and the audio is input into the microphone.

[1465] Step 2: The device captures the audio data

[1466] The device's microphone captures the user's voice data and stores it in digital form.

[1467] Input: User's voice

[1468] Output: Digital audio data

[1469] Specific operation: The device's built-in microphone collects audio and temporarily stores it as digital data in the internal memory.

[1470] Step 3: The device sends the audio data to the server

[1471] The device transmits the captured audio data to a server via the Internet.

[1472] Input: Digital audio data

[1473] Output: Sending audio data to the server

[1474] What happens: Audio data is split into network packets and sent over the Internet to a server.

[1475] Step 4: The server analyzes the audio data

[1476] The server uses a speech recognition engine to convert the voice data into text data, and then sends an API request to retrieve specific information based on the converted text data.

[1477] Input: Digital audio data

[1478] Output: Text data and API request transmission

[1479] How it works: A speech recognition engine on the server analyzes the voice data and converts it into text, such as "Tell me the latest news." An HTTP message is then generated and sent to send a request to the News API.

[1480] Step 5: The server retrieves the information and sends it to the device

[1481] The server receives news information obtained from the NewsAPI in JSON format and sends it to the terminal.

[1482] Input: API request and retrieved information

[1483] Output: News information sent to the terminal in JSON format

[1484] Specific operation: The server converts the news data obtained from the NewsAPI into JSON format and sends it to the terminal via the network.

[1485] Step 6: The device provides information aloud

[1486] The terminal uses a speech synthesis engine to convert the acquired news information into speech and provide it to the user.

[1487] Input: News information in JSON format

[1488] Output: Audio data and audio presented to the user

[1489] How it works: The device parses the JSON-formatted news data, and the speech synthesis engine converts it into speech, which is then played back through the device's speaker.

[1490] (Application example 1)

[1491] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1492] On modern online shopping sites, users must navigate through multiple screens and input information to efficiently obtain a wide variety of information, making operation cumbersome. Visually impaired users and those unfamiliar with technology have particular difficulties when searching for products, checking order status, or browsing product reviews. Given this background, there was a demand for a more intuitive and convenient way to obtain information.

[1493] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1494] In this invention, the server includes means for converting voice data into text data, means for acquiring specific information, means for providing the specific information to the user by voice, means for the user to search for products using a voice command, means for acquiring search results based on the voice command, and means for providing the search results to the user by voice, thereby enabling the user to intuitively search for products, check order status, and obtain product reviews using voice.

[1495] "Audio data" is a recording of sounds made by a user into a digital device.

[1496] "Text data" is voice data that has been analyzed and converted into text information.

[1497] "Specific information" is the necessary data that is obtained based on the user's voice command.

[1498] "Product search" is the process of searching for a specified product based on a voice command.

[1499] "Search results" is a list of information obtained through the product search process.

[1500] A "GUI" is a type of user interface that allows users to operate a device using visual elements such as icons and buttons.

[1501] "Voice input" refers to a user giving voice instructions to a digital device.

[1502] "Capture" refers to the collection of audio data using a digital device's microphone.

[1503] A "server" is a computer system that receives and processes requests from digital devices that are clients.

[1504] "Speech synthesis" is a technology that converts text data back into voice data and outputs it as voice.

[1505] "Product reviews" are evaluations and impressions written by users who have purchased a product about its usability and quality.

[1506] "Order Status" is the current processing status of the product ordered by the user.

[1507] "API" stands for Application Program Interface, a set of rules and procedures that allow different software programs to communicate with each other.

[1508] The system of this invention consists of the following components: a device (terminal) operated by the user, a server, a voice recognition engine, a voice synthesis engine, and an API service for product searches, order status confirmation, and product review acquisition.

[1509] Overall system configuration

[1510] 1. Acquiring voice input

[1511] When a user speaks into a device such as a smartphone, saying "Find the latest smartphone," the device's microphone captures the voice, and the captured voice data is sent from the device to the server.

[1512] 2. Speech Recognition and Text Conversion

[1513] The server converts the voice data into text data using a speech recognition engine, such as the Google Cloud Speech-to-Text API or Amazon Transcribe.

[1514] 3. Text data analysis and information acquisition

[1515] The server parses the text data, understands the user's command, and then sends a request to the appropriate API, for example, to an e-commerce API for product search, or to an order management API for order status check.

[1516] 4. Speech synthesis and provision of information

[1517] The information acquired by the server is converted into voice data using a speech synthesis engine such as Google Cloud Text-to-Speech API and sent to the device, which then plays the voice data and provides the information to the user.

[1518] Specific examples

[1519] Specific examples of product searches

[1520] When a user says to the device, "Search for the latest smartphone," the microphone captures the voice data. The voice data is sent to the server, where it is converted into text data by a voice recognition engine. The server analyzes the text data and obtains information about the latest smartphones from an e-commerce API. The resulting search results are converted into voice data by a voice synthesis engine and provided to the user via the device.

[1521] Example of checking order status

[1522] When a user speaks to the device, asking, "What's the status of my order?", the microphone similarly captures the voice data. The voice data is sent to the server and converted into text data. The server then sends a request to the order management API to obtain the order status. The obtained information is converted into voice data by a speech synthesis engine and communicated to the user via the device.

[1523] Prompt Sentence Examples

[1524] "Write a program that receives a voice command to search for a product and responds with the search results in voice. Specifically, the program will allow the user to issue a voice command such as "Tell me about the latest smartphone," convert the command into text using voice recognition, and return the retrieved information in voice."

[1525] As mentioned above, this system utilizes user voice control to enable intuitive and easy product searches, order status checks, and product reviews, making it easy to use even for people who are not comfortable using digital devices.

[1526] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1527] Step 1:

[1528] The user issues a voice command, for example, "Find the latest smartphone," which generates voice data.

[1529] Step 2:

[1530] The device captures the voice data. The device's microphone collects the user's voice and stores it as digital voice data. The captured voice data becomes the input.

[1531] Step 3:

[1532] The device sends the voice data to the server. The device sends the collected voice data to the server via the network. The input is the voice data, and the output is the data sent to the server.

[1533] Step 4:

[1534] The server converts the voice data into text data. The server uses a speech recognition engine such as Google Cloud Speech-to-Text API or Amazon Transcribe to convert the received voice data into text data. The input is voice data, and the output is text data.

[1535] Step 5:

[1536] The server parses the text data and sends a request to the appropriate API. The server extracts the user's command from the parsed text data and sends an information retrieval request to, for example, an e-commerce API or an order management API. The input is text data and the output is an API request.

[1537] Step 6:

[1538] An API provides information in response to a request. E-commerce APIs and order management APIs return specific information, such as product details or order status, based on a server request. The input is the API request, and the output is information data.

[1539] Step 7:

[1540] The server converts the acquired information into voice data. The server uses a speech synthesis engine such as Google Cloud Text-to-Speech API to convert the acquired information data into voice data. The input is information data, and the output is voice data.

[1541] Step 8:

[1542] The server sends the audio data to the terminal. The server then sends the converted audio data to the terminal via the network. The input is the audio data, and the output is the data sent to the terminal.

[1543] Step 9:

[1544] The terminal plays back the audio data and provides information to the user. The terminal plays back the received audio data so that the user can hear the information. The input is audio data and the output is audio information.

[1545] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1546] The present invention not only provides the ability to easily operate digital devices by leveraging the user's voice input, but also combines it with an emotion engine that recognizes the user's emotions from their voice, thereby adapting the information and responses provided to the user depending on their emotional state.

[1547] Overall system configuration

[1548] The system consists of the following main components:

[1549] Devices (terminals) operated by users

[1550] server

[1551] Speech Recognition Engine

[1552] Speech synthesis engine

[1553] News retrieval API or other information retrieval services

[1554] Emotion Engine

[1555] Program processing flow

[1556] Speech recognition, emotion recognition, information acquisition

[1557] 1. The user issues a voice command

[1558] The user speaks to the device and says, "Tell me the latest news."

[1559] 2. The device captures the audio data

[1560] The device's microphone collects the user's voice and stores it as audio data.

[1561] 3. The device sends the audio data to the server

[1562] The device sends the collected voice data to the server.

[1563] 4. The server analyzes the audio data

[1564] The server uses a speech recognition engine to convert the voice data into text data.

[1565] 5. The server analyzes emotions using an emotion engine

[1566] The server recognizes the user's emotional state (happiness, sadness, anger, surprise, etc.) based on the voice data.

[1567] 6. The server analyzes the text data and obtains the necessary information.

[1568] The server sends a request to the news retrieval API based on the analyzed text data.

[1569] 7. Adapt the information acquired by the server according to emotions

[1570] The server adapts the retrieved news information according to the user's emotional state, for example, if the user is sad, it will prioritize positive news.

[1571] 8. The server sends the information to the device

[1572] The server transmits the adapted news information to the terminal.

[1573] 9. Device provides adapted information by voice

[1574] The terminal uses a speech synthesis engine to provide the acquired news information to the user by voice.

[1575] Specific examples

[1576] Example 1: Get news by voice command and adapt according to emotions

[1577] The user speaks to the device, saying, "Tell me the latest news." The device's microphone captures the voice and sends it to the server. The server uses a speech recognition engine to convert the voice into text and an emotion engine to analyze the user's emotions. If the server determines that the user is sad, it sends a request to the news acquisition API and prioritizes the retrieved news information to be more positive. The adapted news information is then sent to the device, where it is provided to the user as audio by a speech synthesis engine.

[1578] Example 2: Sending messages with simplified touch controls and reviewing the content based on emotions

[1579] The user taps the "Send Message" icon on the screen. An input screen appears and the user types a message by voice, such as "Good morning, how are you?" The device captures the voice and sends it to the server. The server uses a speech recognition engine and emotion engine to convert the voice into text and analyzes the user's emotion. The server sends the converted text message to the device and displays a confirmation message corresponding to the emotion when it is displayed on the screen. For example, if the user is angry, an additional confirmation such as "Are you sure this is the correct message?" is displayed. After the user confirms, the message is sent by tapping the "Send" button.

[1580] By taking into account the user's emotional state, the system provides more personalized information and responses, improving the user experience and making digital devices easier to use.

[1581] The processing flow will be explained below.

[1582] Processing steps for getting news by voice command and adapting it according to emotions

[1583] Step 1:

[1584] The user speaks to the device and says, "Tell me the latest news."

[1585] Step 2:

[1586] The device captures audio data through the microphone and temporarily stores the audio data in a buffer.

[1587] Step 3:

[1588] The voice data stored on the device is sent to a server via the Internet.

[1589] Step 4:

[1590] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[1591] Step 5:

[1592] The server analyzes the text data and understands the user's request: "Tell me the latest news."

[1593] Step 6:

[1594] The server uses an emotion engine to analyze the user's emotional state (e.g., joy, sadness, anger, surprise) from the voice data.

[1595] Step 7:

[1596] The server sends a request to a news acquisition API based on the text data to acquire the latest news information.

[1597] Step 8:

[1598] The server analyzes the news information it receives and adjusts the content it provides based on the user's emotions. For example, if the user is sad, it will prioritize positive news.

[1599] Step 9:

[1600] The server converts the adapted news information into a data format for voice output and transmits it to the terminal.

[1601] Step 10:

[1602] The news information received by the device is passed to a speech synthesis engine, converted into audio data, and played over the speaker.

[1603] Step 11:

[1604] The user listens to the latest news information broadcast over the speaker.

[1605] Steps for sending messages with simplified touch controls and reviewing them based on emotions

[1606] Step 1:

[1607] A user taps the "Send Message" icon on the screen of a digital device.

[1608] Step 2:

[1609] The device detects the tap event and displays a message input screen for voice input.

[1610] Step 3:

[1611] The user speaks to the displayed message screen and inputs the message content, saying "Good morning, how are you?"

[1612] Step 4:

[1613] The device captures audio input through the microphone and temporarily stores the audio data in a buffer.

[1614] Step 5:

[1615] The voice data stored on the device is sent to a server via the Internet.

[1616] Step 6:

[1617] The server passes the received voice data to a voice recognition engine, which converts the voice data into text data.

[1618] Step 7:

[1619] The server analyzes the text data converted by the voice recognition engine and recognizes the content of the user's message.

[1620] Step 8:

[1621] The server uses an emotion engine to analyze the user's emotional state from the voice data.

[1622] Step 9:

[1623] The server sends text data to the terminal, which displays it on the screen.

[1624] Step 10:

[1625] The device displays a confirmation message such as "Are you sure you want this message?" based on the user's emotional state.

[1626] Step 11:

[1627] The user taps the "Send" button on the confirmation screen.

[1628] Step 12:

[1629] The terminal transmits the confirmed text message again to the server, and the server transmits the message to the designated recipient.

[1630] Example 2

[1631] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1632] In recent years, many digital devices have been designed to be operated by voice commands. However, these systems provide information without considering the user's emotional state, limiting the user experience. Another issue is that simply providing information obtained from voice input without consideration of the user's emotional state does not allow for an appropriate response based on the user's emotions. The present invention aims to provide a system that analyzes a user's voice input and their emotional state, enabling more personalized information delivery.

[1633] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1634] In this invention, the server includes means for converting voice data into text data, means for analyzing the user's emotional state based on the text data, means for acquiring specific information based on the text data and the user's emotional state, means for adapting the acquired information to the user's emotional state, and means for providing the adapted information to the user by voice, thereby enabling adaptive information provision according to the user's emotional state.

[1635] "Voice data" is voice information collected from a user in digital form.

[1636] "Text data" is information obtained by converting voice data into characters.

[1637] A "voice recognition engine" is a software or hardware function that converts voice data into text data.

[1638] An "emotion recognition engine" is a software or hardware function that analyzes and identifies a user's emotional state from text and voice data.

[1639] The "specific information" is content obtained based on the user's voice input and emotional state, such as news information and weather information.

[1640] "Adapting" means optimizing the information retrieved based on the user's emotional state, for example prioritizing positive information if the user is sad.

[1641] A "speech synthesis engine" is a software or hardware function for outputting text data as voice.

[1642] An "information acquisition service" is a means of collecting necessary information using external APIs and databases.

[1643] The present invention not only leverages the user's voice input to provide the ability to easily operate digital devices, but also combines it with an emotion engine that recognizes the user's emotions from their voice, thereby adapting the information and responses provided to the user based on their emotional state, resulting in a personalized user experience.

[1644] Overall system configuration

[1645] The system consists of the following main components:

[1646] Devices (terminals) operated by users

[1647] server

[1648] Speech Recognition Engine

[1649] Emotion Recognition Engine

[1650] Speech synthesis engine

[1651] News retrieval API or other information retrieval services

[1652] Hardware and software used

[1653] 1. Speech recognition engine: To convert voice data into text data, common speech recognition software is used, such as Google Cloud Speech-to-Text API.

[1654] 2. Emotion recognition engine: Uses an engine to analyze the user's emotional state from text and voice data. An example is IBM Watson Tone Analyzer.

[1655] 3. Speech synthesis engine: Uses an engine to convert text data into speech, such as Amazon Polly.

[1656] 4. Information Retrieval Services: Used to retrieve news and other related information. An example is NewsAPI.org.

[1657] Specific processing of the program

[1658] Let's use the example of a user speaking to a device, saying, "Tell me the latest news." First, the user speaks to the device. The device uses its built-in microphone to collect voice data and stores it as digital data. The device then sends the collected voice data to a server. The server uses the Google Cloud Speech-to-Text API to convert the voice data into text data.

[1659] The server then uses IBM Watson Tone Analyzer to analyze the user's emotional state based on the text and audio data. Based on the analyzed text data, the server sends a request to a news retrieval API (e.g., NewsAPI.org) to retrieve the latest news information. The server then adapts the retrieved news information according to the user's emotional state. For example, if the user is sad, it will prioritize positive news.

[1660] The server then sends the final adapted news information to the device, which then uses Amazon Polly to convert the news information into speech, which is then presented to the user through the device's speaker.

[1661] Specific examples

[1662] Example 1: Get news by voice command and adapt according to emotions

[1663] The user speaks to the device, saying, "Tell me the latest news." The device's microphone captures the audio and sends it to the server. The server converts the audio into text using the Google Cloud Speech-to-Text API and analyzes the user's emotions using IBM Watson Tone Analyzer. If the server determines that the user is sad, it sends a request to NewsAPI.org to prioritize positive news. The retrieved news is then formatted and sent to the device. The device then converts the news into audio using Amazon Polly, which is finally played from the speaker.

[1664] Prompt Sentence Examples

[1665] "You are designing a system to control digital devices that a user talks to. The system will analyze the user's voice and emotional state and provide adaptive responses based on the emotion. Please name the steps involved and the specific hardware and software you will use."

[1666] This allows the present invention to take into account the user's emotional state and provide more personalized responses, improving the user's experience of operating a digital device.

[1667] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1668] Step 1:

[1669] The user issues a voice command

[1670] The user speaks to the device, saying "Tell me the latest news." The input is the user's voice, which triggers the system to start. The output is the voice data input to the device's microphone. Specifically, the user speaks into the device's microphone, and the voice is captured as an analog signal.

[1671] Step 2:

[1672] The device captures the audio data

[1673] The device's microphone collects the user's voice as digital voice data. The input is the user's analog voice, and the output is digital voice data. Specifically, the device's built-in microphone converts the analog voice signal into digital data. This data is temporarily stored in the device's memory.

[1674] Step 3:

[1675] The device sends the audio data to the server.

[1676] The terminal transmits the collected digital audio data to a server via the Internet. The input is the captured digital audio data, and the output is the audio data that arrives at the server. Specifically, the terminal transmits data packets to the server using the HTTPS protocol, and the server receives the audio data.

[1677] Step 4:

[1678] The server analyzes the audio data

[1679] The server uses a speech recognition engine (e.g., Google Cloud Speech-to-Text API) to convert the voice data into text data. The input is digital voice data, and the output is text data. Specifically, the server sends the voice data to the API, and the speech recognition engine analyzes it and returns it as a string.

[1680] Step 5:

[1681] The server analyzes emotions using an emotion engine.

[1682] The server uses an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotional state based on the text and voice data. The input is the converted text and voice data, and the output is parameters of the user's emotional state (happiness, sadness, etc.). Specifically, the server passes the text data to the emotion recognition engine and receives the emotion parameters as the analysis result.

[1683] Step 6:

[1684] The server analyzes the text data and obtains the necessary information.

[1685] The server retrieves specific information based on the parsed text data. In this process, a request is sent to an information retrieval service (e.g., a news retrieval API). The input is the parsed text data, and the output is the retrieved specific information (e.g., news articles). Specifically, the server analyzes the content of the text data, generates an appropriate search query, sends it to the API, and receives the returned information.

[1686] Step 7:

[1687] Adapting the information acquired by the server according to emotions

[1688] The server adapts the information it acquires based on the user's emotional state. The input is news information and the user's emotional parameters, and the output is adapted news information. Specifically, the server uses the user's emotional parameters to filter information, such as prioritizing positive information.

[1689] Step 8:

[1690] The server sends the information to the device

[1691] The server sends the adapted news information to the device. The input is the adapted news information, and the output is the state it has reached on the device. Specifically, the server packets the information in JSON format and sends it to the device using the HTTPS protocol.

[1692] Step 9:

[1693] The device provides adapted information via voice

[1694] The device uses a speech synthesis engine (e.g., Amazon Polly) to convert the adapted news information into speech. The input is the news information received from the server, and the output is the generated speech data. Specifically, the device sends text data to the speech synthesis engine, and the generated audio file is played back from the speaker and provided to the user.

[1695] Through these processing steps, personalized information provision according to the user's emotional state is realized.

[1696] (Application example 2)

[1697] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1698] In recent years, advances in speech recognition technology have enabled users to operate devices by voice. However, conventional speech recognition systems have had the problem of being unable to adapt responses to the user's intentions and emotions because they do not take the user's emotional state into account. Furthermore, particularly in security services, systems that ignore the user's emotional state have difficulty responding quickly and appropriately to emergencies and ensuring the user's safety. Therefore, there is a need for systems that can improve the operability of digital devices and enhance the user experience by recognizing the user's emotional state and providing appropriate information and responses accordingly.

[1699] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting voice data, means for converting the voice data into text data, means for acquiring specific information based on the text data, means for providing the specific information to the user by voice, means for analyzing the user's emotional state based on the voice data, and means for adapting the acquired information based on the emotional state. This makes it possible to provide appropriate information and responses according to the user's emotional state, improving the operability of digital devices and enabling quick and appropriate responses, particularly in security services.

[1700] "Audio Data" means a digital recording of a user's audio signals made by a user to a device.

[1701] "Text data" is character string data generated by analyzing voice data, and represents the content of a user's speech as text information.

[1702] "Specific information" refers to necessary data or knowledge acquired based on a user's request or instruction, and refers to specific content such as news or weather information.

[1703] "Emotional state" refers to the emotional state of the user that can be inferred from the tone and pattern of the user's voice, and includes emotional responses such as joy, sadness, anger, and anxiety.

[1704] "Speech recognition" is a technology that analyzes voice data and recognizes its content as text data.

[1705] "Speech synthesis" is a technology that analyzes text data, reconstructs it into natural speech, and provides it to the user as audio information.

[1706] "Emotion analysis" is a technology that recognizes and classifies a user's emotional state from voice data.

[1707] "Adaptation" is the process of adjusting acquired information and system responses to the user's emotional state, providing a more personalized response.

[1708] A "system" is a set of programs and hardware for executing a series of processes such as collecting, analyzing, providing information, analyzing emotions, and adapting voice data.

[1709] Basic system configuration

[1710] This invention is a system that captures voice data, analyzes the user's emotions based on that data, and provides adaptive responses. The main components used are as follows:

[1711] 1. Device: A device such as a smartphone or smart speaker that captures the user's voice. The device is equipped with a microphone.

[1712] 2. Server: Analyzes voice data, recognizes emotions, acquires information, and adapts.

[1713] 3. Speech recognition engine: Software that converts voice data into text data.

[1714] 4. Speech synthesis engine: Software that reconstructs text data as speech data.

[1715] 5. Emotion Engine: Software for recognizing and classifying a user's emotional state from voice data.

[1716] 6. News API and other information retrieval services: External services for retrieving specific information.

[1717] System processing explanation in natural language

[1718] The device captures the user's voice input with a microphone and sends the voice data to the server, which then uses a speech recognition engine (e.g., a speech recognition service provided as an API) to convert the voice data into text data, and then uses an emotion engine to analyze the user's voice for emotion.

[1719] Based on the analyzed text data, the server sends requests to news retrieval APIs and other information retrieval services to obtain the necessary information. The retrieved information is then adapted according to the user's emotional state. For example, if the user is feeling anxious, reassurance information and emergency prevention information will be provided first.

[1720] The adapted information is converted into voice data by a speech synthesis engine and provided to the user via the device. Through this series of processes, the user can receive appropriate information and responses adapted to their emotional state.

[1721] The specific hardware and software used

[1722] Smartphone: A device that is always carried by the user and has a microphone for capturing voice input.

[1723] Server: Responsible for all data analysis and information acquisition. Often uses cloud services.

[1724] Speech Recognition Engine: A speech recognition service such as the Google Speech-to-Text API.

[1725] Text-to-speech engine: A text-to-speech service like the Google Text-to-Speech API.

[1726] Emotion Engine: Dedicated software for Emotion Recognition.

[1727] News retrieval API: A news service (e.g., NewsAPI).

[1728] Specific examples

[1729] Example 1

[1730] When a user feels that "something is strange" on a dark street, they speak into their smartphone saying, "Something is strange." This voice data is captured by the device's microphone and sent to the server. The server converts the voice into text using a voice recognition engine and analyzes the emotion of anxiety using an emotion engine. If it determines that suspicious person detection is necessary, the server immediately notifies the user, saying, "A suspicious person has been detected. Please ensure your safety."

[1731] Example 2

[1732] When a user suddenly feels fear, the emotion engine recognizes this fear and automatically calls a pre-registered emergency contact. A message generated by the speech synthesis engine, "This is an emergency! Please contact us immediately," is sent, helping the user quickly ensure safety.

[1733] Prompt Sentence Examples

[1734] An example prompt is:

[1735] "I want to build a voice assistant app that can detect suspicious people and notify contacts based on your emotions. How can I implement a system that can respond appropriately when the user feels anxious or scared?"

[1736] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1737] Step 1:

[1738] The user issues a voice command

[1739] The user speaks to the device saying, "Something's wrong."

[1740] Input: User's voice

[1741] Output: Audio data (digital format)

[1742] Step 2:

[1743] The device captures the audio data

[1744] The device's microphone collects the user's voice and stores it as audio data.

[1745] Input: User's voice

[1746] Output: Audio data

[1747] Step 3:

[1748] The device sends the audio data to the server.

[1749] The collected voice data is sent to a server via the Internet.

[1750] Input: Audio data

[1751] Output: Audio data sent to the server

[1752] Step 4:

[1753] The server analyzes the audio data

[1754] The server uses a speech recognition engine to convert the voice data into text data.

[1755] Input: Audio data

[1756] Output: Text data

[1757] Step 5:

[1758] The server analyzes emotions using an emotion engine.

[1759] The server uses an emotion engine to recognize the user's emotional state (e.g., anxiety, fear) from the text data and voice features.

[1760] Input: Text data and audio features

[1761] Output: Emotional state (e.g., anxiety)

[1762] Step 6:

[1763] The server analyzes the text data and obtains the necessary information.

[1764] The server sends a request to a news retrieval API or similar to obtain the necessary information.

[1765] Input: Text data

[1766] Output: Specific information obtained

[1767] Step 7:

[1768] Adapting the information acquired by the server according to emotions

[1769] The server adjusts the information it receives based on the user's emotional state. For example, if the user is feeling anxious, it will prioritize information about reassurance and emergency measures.

[1770] Input: specific information and emotional state obtained

[1771] Output: Adapted information

[1772] Step 8:

[1773] The server synthesizes the adapted information into voice.

[1774] The server uses a speech synthesis engine to generate the adapted information as voice data.

[1775] Input: Adapted information

[1776] Output: Audio data

[1777] Step 9:

[1778] The server sends the audio data to the device.

[1779] The server transmits the generated voice data to the terminal.

[1780] Input: Audio data

[1781] Output: Audio data sent to the device

[1782] Step 10:

[1783] The device provides adapted information via voice

[1784] The terminal reproduces the received audio data and provides it to the user as audio.

[1785] Input: Audio data

[1786] Output: Audio information presented to the user

[1787] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1788] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1789] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1790] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1791] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1792] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1793] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1794] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1795] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1796] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1797] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1798] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1799] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1800] 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.

[1801] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1802] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1803] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1804] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1805] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1806] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1807] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1808] The following is further disclosed regarding the above embodiment.

[1809] (Claim 1)

[1810] means for collecting audio data;

[1811] means for converting the voice data into text data;

[1812] means for acquiring specific information based on the text data;

[1813] means for providing the specific information to a user by voice;

[1814] A system including:

[1815] (Claim 2)

[1816] a means for a user to select an input icon through a GUI;

[1817] means for capturing and transmitting user voice input to a server;

[1818] means for the server to convert the speech into text and have the user review the text;

[1819] means for sending a user-reviewed text message;

[1820] 10. The system of claim 1, comprising:

[1821] (Claim 3)

[1822] means for the server to send requests to a news retrieval API or other information retrieval service;

[1823] means for synthesizing the information acquired from the server into voice and providing it to a user;

[1824] 10. The system of claim 1, comprising:

[1825] "Example 1"

[1826] (Claim 1)

[1827] a means for a user to issue a voice command;

[1828] a means for the terminal to capture audio data;

[1829] means for transmitting the voice data to a server;

[1830] A means for the server to convert the voice data into text data using a voice recognition engine;

[1831] means for sending an API request to obtain specific information based on the text data;

[1832] means for transmitting the specific information to a terminal;

[1833] a means for providing the specific information to a user by voice using a voice synthesis engine in the terminal;

[1834] A system including:

[1835] (Claim 2)

[1836] a means for a user to select an input icon through a GUI;

[1837] means for capturing and transmitting user voice input to a server;

[1838] means for the server to convert the speech into text and have the user review the text;

[1839] means for sending a user-reviewed text message;

[1840] 10. The system of claim 1, comprising:

[1841] (Claim 3)

[1842] means for the server to send requests to a news retrieval API or other information retrieval service;

[1843] means for synthesizing the information acquired from the server into voice and providing it to a user;

[1844] 10. The system of claim 1, comprising:

[1845] "Application Example 1"

[1846] (Claim 1)

[1847] means for collecting audio data;

[1848] means for converting the voice data into text data;

[1849] means for acquiring specific information based on the text data;

[1850] means for providing the specific information to a user by voice;

[1851] a means for users to search for products using voice commands;

[1852] means for obtaining search results based on the voice command;

[1853] means for providing the search results to the user by voice;

[1854] A system including:

[1855] (Claim 2)

[1856] a means for a user to select an input icon through a GUI;

[1857] means for capturing and transmitting user voice input to a server;

[1858] means for the server to convert the speech into text and have the user review the text;

[1859] means for sending a user-reviewed text message;

[1860] A means for the server to send a request to a product review acquisition API or other information acquisition service;

[1861] a means for synthesizing the product reviews acquired from the server into voice and providing the synthesized voice to a user;

[1862] 10. The system of claim 1, comprising:

[1863] (Claim 3)

[1864] means for the server to send a request to an order status API or other information retrieval service;

[1865] means for synthesizing the order status information obtained from the server into voice and providing it to the user;

[1866] 10. The system of claim 1, comprising:

[1867] "Example 2: Combining Emotion Engines"

[1868] (Claim 1)

[1869] means for collecting audio data;

[1870] means for converting the voice data into text data (using a voice recognition engine);

[1871] A means for analyzing the user's emotional state based on the text data (using an emotion recognition engine);

[1872] means for obtaining specific information based on the text data and an emotional state;

[1873] means for adapting the acquired information to the emotional state of the user;

[1874] means for providing said adapted information to a user audibly (using a speech synthesis engine);

[1875] A system including:

[1876] (Claim 2)

[1877] a means for a user to select an input icon through a GUI;

[1878] means for capturing and transmitting user voice input to a server;

[1879] means for the server to convert speech to text, analyze emotional state, and prompt the user to confirm;

[1880] means for sending a user-reviewed text message;

[1881] 10. The system of claim 1, comprising:

[1882] (Claim 3)

[1883] a means for the server to send a request to an information acquisition service;

[1884] means for adapting the information acquired from the server to the emotional state of the user, synthesizing the speech, and providing the speech to the user;

[1885] 10. The system of claim 1, comprising:

[1886] "Application example 2 when combining emotion engines"

[1887] (Claim 1)

[1888] means for collecting audio data;

[1889] means for converting the voice data into text data;

[1890] means for acquiring specific information based on the text data;

[1891] means for providing the specific information to a user by voice;

[1892] means for analyzing the emotional state of a user based on the voice data;

[1893] means for adapting the acquired information based on said emotional state;

[1894] A system including:

[1895] (Claim 2)

[1896] a means for a user to select an input icon through a GUI;

[1897] means for capturing and transmitting user voice input to a server;

[1898] means for the server to convert the speech into text and have the user review the text;

[1899] means for sending a user-reviewed text message;

[1900] means for providing an adapted response to the user depending on the emotional state;

[1901] 10. The system of claim 1, comprising:

[1902] (Claim 3)

[1903] means for the server to send requests to a news retrieval API or other information retrieval service;

[1904] means for prioritizing information obtained from the server according to an emotional state;

[1905] means for synthesizing the information acquired from the server into voice and providing it to a user;

[1906] 10. The system of claim 1, comprising: [Explanation of symbols]

[1907] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for collecting audio data; means for converting the voice data into text data; means for acquiring specific information based on the text data; means for providing the specific information to a user by voice; A system including:

2. a means for a user to select an input icon through a GUI; means for capturing and transmitting user voice input to a server; means for the server to convert the speech into text and have the user review the text; means for sending a user-reviewed text message; The system of claim 1 , comprising:

3. means for the server to send requests to a news retrieval API or other information retrieval service; means for synthesizing the information acquired from the server into voice and providing it to a user; The system of claim 1 , comprising:

Images