system

Abstract

Provide a system. A means for a user to input information by voice input; a terminal means for acquiring voice data from a user; a server means for converting the acquired voice data into text data; A means for analyzing the text data and obtaining information in response to a user request; a server means for converting the acquired information into voice data; terminal means for playing back audio data to a user; A system including:

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] For elderly people living alone or those requiring care, obtaining daily information and managing their health can be a significant burden. Furthermore, they often have difficulty operating tablets or smartphones. In these circumstances, there is a need for a system that allows them to easily obtain information and manage their health status via voice. Furthermore, they need an effective means of communication with family members and medical staff who live far away. However, current systems do not adequately satisfy these needs, so new solutions are needed to support users' safe and secure lives. [Means for solving the problem]

[0005] The present invention solves the above problem by providing a system including a means for a user to input information by voice input, a terminal means for acquiring voice data from the user, a server means for converting the acquired voice data into text data, a means for analyzing the text data and acquiring information in response to a user request, a server means for converting the acquired information into voice data, and a terminal means for playing the voice data back to the user.

[0006] Furthermore, by providing a terminal means for acquiring the user's health information through voice input, a means for converting the voice data into text data and recording the user's health information, a means for storing the recorded health information on a server, and a means for notifying medical staff or family members as necessary, the user's health condition can be managed efficiently and necessary information can be shared with relevant parties.

[0007] Furthermore, by providing a system that includes a means for obtaining news and weather information in response to user requests and converting the obtained information into voice data and providing it to the user, necessary information can be obtained quickly and easily using only voice, thereby realizing an information acquisition and health management platform that can be used intuitively by the elderly and those requiring care.

[0008] "User" refers to the elderly, people in need of care, or their family members or related medical staff who use the system.

[0009] "Voice input" is a means by which a user gives information or instructions to a system by voice via a microphone.

[0010] The "terminal means" is a device including hardware and software that allows a user to input voice and play back voice data.

[0011] "Voice data" refers to data in digital format that represents information input by voice by a user.

[0012] "Server means" refers to a computer system for processing, analyzing, converting, and storing voice data, and for acquiring various information.

[0013] "Text data" refers to data in which voice data is converted into a character string by the server means.

[0014] A "natural language processing engine" is software or hardware that converts voice data into text data and then analyzes the text data to understand user requests.

[0015] A "speech synthesis engine" is software or hardware for converting text data into voice data.

[0016] "News information" refers to information including the latest news content provided to users.

[0017] "Weather Information" means up-to-date weather information provided to users.

[0018] "Health information" refers to data related to the user's health condition, such as physical condition, medication status, dietary details, and the like.

[0019] "Medical staff" refers to professionals such as doctors and nurses who support users' health management and treatment. [Brief explanation of the drawings]

[0020] [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

[0021] 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.

[0022] First, the terms used in the following description will be explained.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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."

[0041] The present invention is a system including a means for a user to input information by voice input, a terminal means for acquiring voice data from the user, a server means for converting the acquired voice data into text data, a means for analyzing the text data and acquiring information in response to a user request, a server means for converting the acquired information into voice data, and a terminal means for playing the voice data back to the user. The operation of the system will be specifically described below.

[0042] User voice input

[0043] For example, a user might say, "Tell me the weather today." This speech is captured through the microphone of the device (e.g., a tablet or smart device). The device encodes the captured voice data into a processable format in real time and then sends it to the server.

[0044] Analyzing voice data and obtaining information

[0045] The server receives the voice data sent from the device. The server uses a voice recognition engine to convert the received voice data into text data. It then uses a natural language processing engine to analyze the text data and understand the user's request. In this example, it determines that the request is to "provide weather information."

[0046] The server then accesses the weather API to retrieve the latest weather information, identifying relevant weather information based on the user's location and preferences.

[0047] Converting acquired information into audio data and playing it back

[0048] The server uses a speech synthesis engine to convert the acquired weather information into voice data. The speech synthesis engine converts text data (e.g., "Today's weather is sunny") into natural-sounding voice and sends it to the terminal in the form of voice data.

[0049] The device receives the voice data sent from the server and plays it back to the user using the built-in speaker, allowing the user to hear the information "Today's weather is sunny."

[0050] Management and sharing of health information

[0051] As another example, consider the case where a user says, "Record my health status today." The device captures the voice data and sends it to the server. The server uses a speech recognition engine to convert the voice data into text data and record the user's health status.

[0052] The server stores the recorded health information in a database and sends notifications to medical staff or family members as needed, such as "Your health condition has been recorded. Please refer to the database for details."

[0053] This system allows users to obtain information and manage their health status using only their voice. In addition, it allows for quick sharing of information with medical staff and family members, helping to support users' safety and security. News and other daily information can also be provided in the same way, improving the user's quality of life.

[0054] The processing flow will be explained below.

[0055] Program processing flow

[0056] Example of checking the news

[0057] Step 1:

[0058] User: Say "Tell me the latest news." The user speaks into a tablet or smart device.

[0059] Step 2:

[0060] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[0061] Step 3:

[0062] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[0063] Step 4:

[0064] Server: Receives the voice data. The server confirms that the data has been received.

[0065] Step 5:

[0066] Server: Converts the voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data, such as "Tell me about the latest news."

[0067] Step 6:

[0068] Server: A natural language processing engine analyzes the text data and determines whether the user is looking for the latest news.

[0069] Step 7:

[0070] Server: Accesses the news information API to obtain the latest news data, makes an API request, and receives response data.

[0071] Step 8:

[0072] Server: Converts the acquired news data into a text format. For example, it creates text in the format "Today's main news is..."

[0073] Step 9:

[0074] Server: Converts text data into voice data using a speech synthesis engine. The synthesized voice data is generated as "Today's main news is..."

[0075] Step 10:

[0076] Server: Sends the generated voice data to the terminal. Confirms the data transmission.

[0077] Step 11:

[0078] Terminal: Receives audio data. Checks the received data and encodes it.

[0079] Step 12:

[0080] Device: Play audio data through the speaker. Output so that the user can hear "Today's main news is..."

[0081] Health status record example

[0082] Step 1:

[0083] User: Say "Record my health status today." The user speaks into a tablet or smart device.

[0084] Step 2:

[0085] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[0086] Step 3:

[0087] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[0088] Step 4:

[0089] Server: Receives the voice data. The server confirms that the data has been received.

[0090] Step 5:

[0091] Server: Converts voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data such as "Please record today's health condition."

[0092] Step 6:

[0093] Server: Analyzes the text data using a natural language processing engine and determines that the user wants to record their health status.

[0094] Step 7:

[0095] Server: Save the text data in a database. Save the message "Record your health condition today" as the user's health record.

[0096] Step 8:

[0097] Server: Based on the stored health data, it sends notifications to medical staff and family members as needed. For example, it sends a notification that "the user's health status has been updated."

[0098] In this way, specific operations are performed at each processing step, from user voice input to information acquisition and recording of health information.

[0099] Example 1

[0100] 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."

[0101] Currently, there are many systems that use voice to input, process, and output information, but most of them have limited functionality and are difficult to meet the diverse needs of users.In addition, there is a problem that a single system cannot meet the various needs, such as fast and accurate processing of voice data, management of health information, and acquisition of information from external sources.

[0102] 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.

[0103] In this invention, the server includes means for converting voice data into text data, means for analyzing the text data and acquiring information in response to a user request, and means for converting the acquired information into voice data, thereby enabling acquisition of a variety of information using voice input.

[0104] "Voice input" is a method in which a user inputs information using their voice.

[0105] "Voice data" means data that is a digital representation of a user's voice.

[0106] A "terminal" is a device that acquires voice data and transmits it to a server.

[0107] "Encoding" is the process of converting audio data into a format that is easier to process.

[0108] A "server" is a computer system that processes voice data and provides information in response to user requests.

[0109] "Text data" is data obtained by converting voice data into a character string format.

[0110] "Natural language processing" is a technology that analyzes text data and understands human language.

[0111] "Speech synthesis" is the process of converting text data into speech data.

[0112] "Notification information" is data used to notify other users or systems of important information.

[0113] "Health Information" is data relating to a user's health condition.

[0114] "External sources" are external databases or APIs that provide weather or news information.

[0115] "User" means a person who uses this system to input and obtain information.

[0116] MODE FOR CARRYING OUT THE INVENTION

[0117] The present invention provides a system that includes a means for users to input information by voice input, converts the acquired voice data into text data, analyzes it to acquire information, and then converts it back into voice data to provide.

[0118] Acquiring voice input

[0119] For example, a user might say, "Tell me the weather today." The device captures the user's voice through a microphone and converts it into digital audio data. This audio data is encoded in real time and sent to a server. Capturing and encoding uses commonly available hardware and software.

[0120] Audio data processing

[0121] The server receives the voice data sent from the device. It converts the voice data into text data using a speech recognition engine (for example, the Google (registered trademark) Speech-to-Text API is generally available). The generated text data is then analyzed by a natural language processing engine (for example, the OpenAI (registered trademark) language model GPT) to understand the user's request. This analysis may result in a decision to, for example, "provide weather information."

[0122] Acquiring information and converting it into audio data

[0123] Based on the request received from the user, the server accesses an external information source (e.g., a weather information API, typically the OpenWeatherMap API) to obtain the latest weather information. The obtained weather information is converted into voice data using a speech synthesis engine (e.g., typically Amazon Polly). Text data (e.g., "Today's weather is sunny") is converted into natural-sounding speech by a voice collection engine.

[0124] Providing audio data

[0125] The server sends the generated voice data to the device. The device receives the voice data and plays it back to the user through the built-in speaker. This allows the user to hear the information aloud, such as "Today's weather is sunny."

[0126] Health information management and notification

[0127] As another example, if a user says, "Record my health condition today," this voice data is also captured and sent to the server. The server uses a voice recognition engine to convert the voice data into text data, which is then analyzed and recorded as health information. The recorded health information is stored in a database, and notifications are sent to medical staff and family members as needed. These notifications include content such as, "Your health condition has been recorded. Please refer to the database for details."

[0128] Example prompt

[0129] Examples of generated AI prompts to parse user input:

[0130] Convert the following speech data into text and parse the request: 'What's the weather like today?'

[0131] Example of a generative AI prompt for recording health status:

[0132] Convert the following audio data into text and record the health information in a database: 'Record my health status today.'

[0133] This invention allows users to obtain various information by voice input and manage health information efficiently. In addition, the information can be promptly provided to users through fast and accurate information processing via the server.

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

[0135] Step 1:

[0136] The user says, "What's the weather today?" This initiates voice input. The device captures the user's voice through the built-in microphone and converts it into digital audio data. The input of this step is an audio signal, and the output is digital audio data. Specifically, the microphone device collects audio waveforms and encodes them into a digital format (e.g., PCM format).

[0137] Step 2:

[0138] The device encodes the captured digital audio data into an appropriate format in real time and sends it to the server. The input of this step is the digital audio data, and the output is the audio data sent to the server. The specific operation is a process of using the device's network interface to send the data to the server via the TCP / IP protocol, etc.

[0139] Step 3:

[0140] The server receives the voice data sent from the terminal. The received data is stored in temporary storage. The input of this step is the voice data sent to the server, and the output is the voice data stored in the temporary storage. The specific operation is the process of receiving data via the server's network interface and storing it in the storage system.

[0141] Step 4:

[0142] The server converts the voice data into text data using a voice recognition engine. A common voice recognition API (e.g., Google Speech-to-Text) can be used as the engine. The input for this step is the voice data stored in temporary storage, and the output is text data. The conversion process analyzes the voice waveform data and generates a corresponding string.

[0143] Step 5:

[0144] The server uses a natural language processing engine to analyze the text data and identify the user's request. Typically, an engine like OpenAI GPT can be used. The input for this step is the text data, and the output is the user's request. Specifically, this involves the process in which a natural language analysis algorithm analyzes the text and recognizes requests such as "provide weather information."

[0145] Step 6:

[0146] In response to a user request, the server accesses an external information source (e.g., a weather information API) to obtain the latest information. The input to this step is the user's request, and the output is the obtained information (e.g., a weather forecast). The specific operation is the process of sending an HTTP request to an API endpoint and receiving information as a response.

[0147] Step 7:

[0148] The server uses a speech synthesis engine (e.g., Amazon Polly) to convert the acquired information into speech data. The input of this step is the acquired text information, and the output is the generated speech data. Specifically, the synthesis engine analyzes the text and generates it as a speech waveform.

[0149] Step 8:

[0150] The server sends the generated voice data to the terminal. The input of this step is the generated voice data, and the output is the voice data sent to the terminal. The specific operation is the process of sending the voice data through the network interface of the server.

[0151] Step 9:

[0152] The terminal receives the audio data sent from the server and plays it using the built-in speaker. The input of this step is the received audio data, and the output is playing audio information to the user. Specifically, it includes an operation of outputting an audio waveform using the audio playback system of the terminal.

[0153] (Application example 1)

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

[0155] In traditional factories, production management and inventory status checks are often done manually, which can reduce work efficiency. It can also be difficult for workers to quickly obtain the information they need, resulting in communication delays. Efficiently managing and obtaining health and other daily information is also a challenge, and a system to address these issues is needed.

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

[0157] In this invention, the server includes a means for converting voice data into text data, a means for analyzing the text data and acquiring information in response to a user's request, and a means for converting the acquired information into voice data. This allows users to efficiently manage production and check inventory status within a factory through voice input. It also allows for the rapid acquisition and management of health information and other daily information, improving work efficiency and accelerating information sharing.

[0158] "User" means a person who uses the system to obtain information by voice input.

[0159] "Voice input" is a method of inputting information using voice data uttered by the user.

[0160] "Terminal means" is a device that captures audio data and transmits it to a server.

[0161] The "server means" is a device that processes data sent from a terminal and acquires information.

[0162] "Text data" is character information converted from voice data.

[0163] The "means for obtaining information" is a function for obtaining the information required by the user based on the analyzed text data.

[0164] The "means for converting into audio data" is a function for converting acquired information into audio format.

[0165] "A means for checking production management and inventory status within a factory by voice input" is a means for a user to check production management and inventory status within a factory by voice input.

[0166] "Health Information" is data relating to a user's health condition.

[0167] "Means for saving on a server" is a function for saving acquired information.

[0168] "Means of notification" is a function that sends information to users and related persons.

[0169] "News" refers to current events and information.

[0170] "Weather information" is data about the current weather and weather forecast.

[0171] This invention is a system that allows users to obtain information through voice input, and specific embodiments thereof are described below. The system converts voice data into text data and obtains and provides information in response to user requests. In particular, the present invention has a means for efficiently managing production and checking inventory status within a factory.

[0172] System Overview

[0173] 1. Acquiring voice input

[0174] The device is equipped with a microphone to capture user voice input: when a user says something like, "What is the current production line status?" or "What is the inventory status of part number 123?", the voice data is captured in real time.

[0175] 2. Audio data conversion

[0176] The acquired voice data is sent to the server, where it is converted into text data using a voice recognition engine called speech_recognition.

[0177] 3. Text data analysis and information acquisition

[0178] The server then uses a natural language processing engine to analyze the converted text data, understand the user's request, and executes API access or database queries to obtain information on the status of a production line or inventory, for example.

[0179] 4. Converting information into audio data

[0180] The acquired information is converted into voice data using the gtts (Google Text-to-Speech) library. In this process, text data (e.g., "The current production line is operating normally") is converted into natural-sounding speech.

[0181] 5. Playing audio data

[0182] The terminal receives the voice data sent from the server and plays it back to the user using the built-in speaker, allowing the user to obtain the necessary information by voice.

[0183] Specific examples

[0184] Factory production management

[0185] Imagine the following instructions being given in a factory:

[0186] Example instruction 1: "What is the status of the production line?"

[0187] → Robot replies: "The current production line is operating normally."

[0188] Example instruction 2: "What is the stock status of part number 123?"

[0189] → The robot responds: "We only have 20 units of part number 123 left in stock."

[0190] Prompt Sentence Examples

[0191] By inputting the following prompt sentence into the generative AI model, an appropriate response will be generated:

[0192] Example prompt: "Create a program that uses a voice interface to instruct a robot to check production management status and inventory status at the factory."

[0193] Hardware and software used

[0194] Hardware: Microphone, speaker, or robot with built-in microphone and speaker

[0195] Software: speech_recognition (speech recognition library), gtts (Google Text-to-Speech library), mpg321 (audio playback software)

[0196] In this way, the present invention provides a system that realizes efficient production management and inventory status confirmation within a factory, and quickly acquires and provides information through user voice input.

[0197] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0198] Step 1:

[0199] The device receives the user's voice input.

[0200] Input: User speech (e.g., "What's the status of the production line?").

[0201] What it does: Captures audio data using the device's microphone and encodes it in real time into a processable format.

[0202] Output: The encoded audio data.

[0203] Step 2:

[0204] The terminal transmits the acquired voice data to the server.

[0205] Input: Encoded audio data.

[0206] What it does: Sends encoded audio data over the network to a server.

[0207] Output: Audio data transferred to the server.

[0208] Step 3:

[0209] The server converts the voice data into text data.

[0210] Input: The transmitted audio data.

[0211] How it works: Converts audio data into text using the speech_recognition library.

[0212] Output: The converted text data (e.g., "What is the status of the production line?").

[0213] Step 4:

[0214] The server parses the text data and understands the request.

[0215] Input: Text data.

[0216] How it works: It uses a natural language processing engine to parse what the user is asking.

[0217] Output: The request (e.g., "Get the status of the production line").

[0218] Step 5:

[0219] The server retrieves information based on the user's request.

[0220] Input: Request content.

[0221] What it does: Accesses databases and APIs to get production line status and inventory status.

[0222] Output: The information obtained (e.g., "The current production line is operating normally.").

[0223] Step 6:

[0224] The server converts the acquired information into audio data.

[0225] Input: The information obtained.

[0226] Operation: Converts text data into audio data using the gtts library.

[0227] Output: The generated audio data.

[0228] Step 7:

[0229] The terminal receives and plays back the audio data transmitted from the server.

[0230] Input: The generated audio data.

[0231] What it does: Receives audio data over the network and plays it back to the user using the built-in speaker.

[0232] Output: A spoken response to the user (e.g., "The current production line is operating normally.").

[0233] 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.

[0234] The present invention is a system that includes a means for a user to input information by voice input, a terminal means for acquiring voice data from the user, a server means for converting the acquired voice data into text data, a means for analyzing the text data and acquiring information in response to a user request, a server means for converting the acquired information into voice data, and a terminal means for playing the voice data back to the user. Furthermore, it is combined with an emotion engine that recognizes emotions from the user's voice data. The detailed operation of this system is described below.

[0235] User voice input

[0236] For example, a user might say, "Tell me today's news." This speech is captured through the microphone of the device (e.g., a tablet or smart device). The device encodes the captured voice data in real time, converts it into a binary format, and sends it to the server.

[0237] Analyzing voice data and obtaining information

[0238] The server receives the voice data sent from the device. It uses a voice recognition engine to convert the received voice data into text data. It then uses a natural language processing engine to analyze the text data and understand the user's request. In this example, it determines that the user is requesting "news delivery."

[0239] Next, the server accesses the news information API to obtain the latest news data, makes an API request, and receives response data.

[0240] Converting acquired information into audio data and playing it back

[0241] The server converts the acquired news data into text format, then uses a speech synthesis engine to convert this text data into voice data, which is then sent to the terminal in voice data format.

[0242] The device receives the audio data sent from the server and plays it back to the user using the built-in speaker. The user can hear information such as "Today's news is..."

[0243] Recognizing and responding to user emotions

[0244] The server simultaneously analyzes the user's emotions using an emotion engine while recognizing the voice. For example, if the user speaks in a "tired voice," the emotion engine will recognize this as "fatigue."

[0245] Based on the results of emotion recognition, the server will adjust its response, for example, if the user is tired, it will add a thoughtful comment such as "Here's the latest news. Please take it easy today."

[0246] If necessary, the recognized emotional information can be notified to medical staff or family members. In this case, the server can send an alert saying, "The user seems tired."

[0247] Recording and Notification of Health Information

[0248] Similarly, if the user says, "Record my health condition today," the device captures the voice and sends it to the server. The server then converts the text data using a speech recognition engine, analyzes it, and records it as health information. It also uses an emotion engine to recognize the user's emotions and notify medical staff or family members as necessary.

[0249] Specific examples

[0250] For example, if a user says, "I'm very tired right now," the device captures this speech and sends the data to the server. The server then converts it into text data using a speech recognition engine and analyzes the meaning of "tired." At the same time, the emotion engine recognizes the "feeling of fatigue" and generates voice data in a gentle tone saying, "Please take a rest," which is then sent to the user via the device. The server then sends notifications to medical staff and family members depending on the situation.

[0251] In this way, this system enables two-way communication using voice and emotions, and can better understand and respond to the user's needs, providing comprehensive support for the elderly and those requiring care to live their daily lives with peace of mind.

[0252] The processing flow will be explained below.

[0253] News confirmation and emotion recognition processing flow

[0254] Step 1:

[0255] User: Say "Tell me the latest news." The user speaks into a tablet or smart device.

[0256] Step 2:

[0257] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[0258] Step 3:

[0259] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[0260] Step 4:

[0261] Server: Receives the voice data. The server confirms that the data has been received.

[0262] Step 5:

[0263] Server: Converts the voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data, such as "Tell me about the latest news."

[0264] Step 6:

[0265] Server: A natural language processing engine analyzes the text data and determines whether the user is looking for the latest news.

[0266] Step 7:

[0267] Server: Accesses the news information API to obtain the latest news data, makes an API request, and receives response data.

[0268] Step 8:

[0269] Server: Converts the acquired news data into a text format. For example, it creates text in the format "Today's main news is..."

[0270] Step 9:

[0271] Server: Converts text data into voice data using a speech synthesis engine. The synthesized voice data is generated as "Today's main news is..."

[0272] Step 10:

[0273] Server: Sends the generated voice data to the terminal. Confirms the data transmission.

[0274] Step 11:

[0275] Terminal: Receives audio data. Checks the received data and encodes it.

[0276] Step 12:

[0277] Device: Play audio data through the speaker. Output so that the user can hear "Today's main news is..."

[0278] Health status recording and emotion recognition process

[0279] Step 1:

[0280] User: Say "Record my health status today." The user speaks into a tablet or smart device.

[0281] Step 2:

[0282] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[0283] Step 3:

[0284] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[0285] Step 4:

[0286] Server: Receives the voice data. The server confirms that the data has been received.

[0287] Step 5:

[0288] Server: Converts voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data such as "Please record today's health condition."

[0289] Step 6:

[0290] Server: Analyzes the text data using a natural language processing engine and determines that the user wants to record their health status.

[0291] Step 7:

[0292] Server: Save the text data in a database. Save the message "Record your health condition today" as the user's health record.

[0293] Step 8:

[0294] Server: Analyzes the user's emotions using an emotion engine based on the stored health information. For example, if the user says "I'm tired," the emotion engine will recognize this as "fatigue."

[0295] Step 9:

[0296] Server: Adjust the response based on the emotion engine's recognition results. For example, if the user is tired, add a message saying "Take a good rest."

[0297] Step 10:

[0298] Server: Convert the response message into voice data. Using a voice synthesis engine, generate the voice data "Please take a good rest."

[0299] Step 11:

[0300] Server: Sends the generated voice data to the terminal. Confirms the data transmission.

[0301] Step 12:

[0302] Terminal: Receives and encodes audio data.

[0303] Step 13:

[0304] Device: Plays audio data through the speaker, outputting "Please take a good rest" so that the user can hear it.

[0305] Step 14:

[0306] Server: Notifies medical staff or family members of the recognized emotion information, for example, by sending an alert saying, "The user seems tired."

[0307] In this way, a system that combines an emotion engine can perform a series of processes, from acquiring information from the user's voice input to responding while taking into account the user's emotional state.

[0308] Example 2

[0309] 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."

[0310] Conventional voice assistant systems mainly respond simply to the user's voice input, and lack the ability to appropriately recognize the user's emotions and health status and adjust responses accordingly. In particular, there is a lack of comprehensive support for the elderly and those requiring care to live their daily lives with peace of mind.

[0311] 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.

[0312] In this invention, the server includes: means for a user to input information by voice input; terminal means for acquiring voice data from the user; server means for converting the acquired voice data into text data; means for analyzing the text data and acquiring information according to the user's request; server means for converting the acquired information into voice data; terminal means for playing the voice data back to the user; server means including an emotion engine for recognizing emotions from the user's voice data; and means for adjusting response content based on the results of emotion recognition. This makes it possible to provide appropriate responses that take into account the user's emotions and health condition, enabling comprehensive support to enable the elderly and those requiring care to live their daily lives with peace of mind.

[0313] "Voice input" is a means by which a user inputs information as voice.

[0314] A "terminal" is a device that acquires voice data from a user and transmits it to a server.

[0315] A "server" is a device that converts acquired voice data into text data, analyzes and acquires information, and responds to the user.

[0316] A "voice recognition engine" is software for converting voice data into text data.

[0317] A "natural language processing engine" is software that analyzes text data and understands user requests.

[0318] "Information acquisition means" refers to a means for acquiring information from an external information source in response to a user request.

[0319] A "speech synthesis engine" is software for converting text data into voice data.

[0320] The "emotion engine" is software that recognizes emotions from the user's voice data.

[0321] The "response content adjustment means" is a means for adjusting the response content based on the result of emotion recognition.

[0322] "Health Information" means information relating to a user's health condition.

[0323] "Means of notification" refers to the means of notifying medical staff and family members of information as necessary.

[0324] "News Information API" is an external API that obtains the latest news information.

[0325] "Voice data" refers to data in which the user's voice is encoded as a digital signal.

[0326] "Text data" refers to character data obtained by converting voice data.

[0327] The present invention is a system in which a user inputs information by voice, and includes the following components: Through this system, the user is supported in obtaining daily information and managing their health.

[0328] User voice input

[0329] For example, a user may say, "Tell me today's news." The user's voice input is captured through the microphone of the device (e.g., tablet or smart device). The device converts the captured voice into a digital signal, encodes the voice data into a binary format, and then sends it to the server.

[0330] Receiving and converting audio data

[0331] The server receives the voice data sent from the device and converts the received voice data into text data using a speech recognition engine (e.g., Google Cloud Speech-to-Text API).The server then analyzes the text data using a natural language processing engine (e.g., IBM Watson (registered trademark) NLU) to understand the user's request.

[0332] Obtaining information

[0333] In response to a user request, the server accesses a news information API (e.g., NewsAPI) to obtain the latest news data. If the user wishes to record their health status, the server similarly converts the voice to text and records and saves it as health information.

[0334] Converting acquired information into audio data

[0335] The server uses a speech synthesis engine (e.g., Amazon Polly) to convert the acquired news data into audio data, which is then sent to the device and played back to the user.

[0336] Recognizing and responding to user emotions

[0337] The server uses an emotion engine (e.g., Affectiva) to simultaneously recognize the voice and analyze the user's emotions. For example, if the server determines that the user sounds tired, it adjusts the response and provides a thoughtful comment such as "Please take a rest" in a gentle tone. In some cases, it may also notify medical staff or family members.

[0338] Specific examples

[0339] For example, if a user says, "I'm very tired right now," the device captures this voice, converts it into a digital signal, and sends it to the server. The server then uses a speech recognition engine to convert the voice data into text data and analyzes the meaning of "tired." At the same time, the emotion engine recognizes the "feeling of fatigue." The server then generates voice data in a gentle tone saying, "Please take a rest," and sends it to the device. The device then plays this voice data to the user. Additionally, it may send notifications to medical staff or family members depending on the situation.

[0340] Examples of prompt statements

[0341] "A user says they want to know today's news. How does the system respond?"

[0342] “If a user says they are tired, what sentiment analysis does the system perform and how does it respond?”

[0343] "Please explain the process your system goes through to record the user's health status."

[0344] In this way, the present invention uses a system that combines voice recognition, natural language processing, and emotion analysis, enabling responses that are adapted to the diverse needs of users and providing comprehensive support, particularly for the elderly and those requiring care.

[0345] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0346] Step 1:

[0347] For example, a user might say, "Tell me today's news." This speech is captured through the device's microphone. The device converts the speech into a digital signal and encodes the speech data into a binary format. The input is the user's speech, and the output is the encoded speech data. The device then sends the encoded speech data to the server.

[0348] Step 2:

[0349] The server receives the voice data sent from the terminal. The input is encoded voice data. The server uses a voice recognition engine to convert the received voice data into text data. The output at this stage is text data. General voice recognition software is used as the voice recognition engine.

[0350] Step 3:

[0351] The server uses a natural language processing engine to analyze the text data and understand the user's request. The input is text data, and the output is the analyzed user request. Specifically, the server determines that the text data requests "provision of news." This allows the server to proceed to the next information acquisition step.

[0352] Step 4:

[0353] The server queries external information sources in response to user requests. The input is the parsed request content. The server accesses the news information API and sends an API request. As a result, it receives the latest news data. The output is the news data.

[0354] Step 5:

[0355] The server formats the acquired news data into text format. The input is news data, and the output is formatted text data. Furthermore, a speech synthesis engine is used to convert the formatted text data into voice data. The output is converted voice data.

[0356] Step 6:

[0357] The server sends the converted audio data to the device. The device decodes the received audio data and plays it back to the user through the built-in speaker. The input is the converted audio data, and the output is the audio playback. The user can hear information such as "Today's news is..." by voice.

[0358] Step 7:

[0359] The server simultaneously recognizes the voice and uses an emotion engine to analyze the user's emotions. The input is voice data, and the output is analyzed emotion information. For example, if the user's voice is judged to sound tired, the emotion engine will recognize "fatigue."

[0360] Step 8:

[0361] The server adjusts the response content based on the emotion recognition results. The input is the analyzed emotion information, and the output is the adjusted response content. For example, if the user is tired, a thoughtful comment such as "Here's the latest news. Please take it easy today and don't push yourself too hard" is added to the voice data.

[0362] Step 9:

[0363] If necessary, the server notifies medical staff or family members of the recognized emotion information. The input is the analyzed emotion information, and the output is the notification content. For example, it sends a message saying, "The user seems tired."

[0364] Step 10:

[0365] Similarly, when a user says, "Record my health condition today," the device captures the voice and sends it to the server. The server uses a voice recognition engine to convert the voice data into text data, analyzes it, and records it as health information. The input is voice data, and the output is the recorded health data. The emotion engine also recognizes the user's emotions.

[0366] (Application example 2)

[0367] 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."

[0368] In conventional factory robot systems, it was difficult to accurately recognize voice instructions from workers and quickly and accurately execute those instructions. Furthermore, systems that could grasp the emotional state of workers and respond accordingly were not sufficiently developed. As a result, it was not possible to improve worker stress management or work efficiency. Furthermore, if a worker was fatigued or stressed, not taking appropriate action could lead to a decrease in work safety.

[0369] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0370] In this invention, the server includes a means for acquiring voice data and converting it into text data, a means for acquiring information in response to a user request, a means for converting the acquired information into voice data, a means including an emotion engine for analyzing the voice data and recognizing the user's emotion, and a means for adjusting the response content in accordance with the recognized emotion. This enables prompt and accurate execution of voice-input instructions and appropriate responses according to the worker's emotional state, contributing to improved work efficiency and ensuring safety.

[0371] "User" refers to a person who uses the system to provide information by voice input.

[0372] "Voice input" refers to a user speaking through a voice capture device such as a microphone.

[0373] "Terminal" refers to the device that receives voice data from the user and transmits it to the server.

[0374] "Voice Data" means information that is a digital representation of the voice uttered by a User.

[0375] "Text data" refers to data in a format in which voice data has been converted into text.

[0376] The term "server" refers to a device that processes acquired voice data, converts it into text data, and further analyzes the text data to acquire information.

[0377] An "emotion engine" refers to software or a system that analyzes a user's emotions from voice data and expresses them as digital data.

[0378] "Means of obtaining information" refers to the process of obtaining the necessary information from external APIs or databases based on user requests.

[0379] "Means for adjusting response content" refers to the ability to appropriately change the information provided or the content of responses based on the user's emotional state.

[0380] "News information" refers to information about current events and important topics.

[0381] "Medical staff" refers to professionals who manage users' health information.

[0382] "Family Member" refers to individuals who have a close relationship with the User.

[0383] MODE FOR CARRYING OUT THE INVENTION

[0384] This invention is a system that utilizes voice input and emotion recognition to improve the efficiency of factory work and enable responses according to the emotional state of workers. Specific embodiments of this system are described below.

[0385] Hardware and Software Configuration

[0386] The system utilizes the following hardware and software:

[0387] Hardware: microphones, speakers, factory robots.

[0388] Software: speech_recognition, robot_controller, text_to_speech, emotion_recognition, alert_system.

[0389] Acquiring and converting audio data

[0390] The user inputs commands such as "move the part" by voice through a microphone. The device captures the voice data, encodes it in real time, and sends it to the server. The server then converts the voice data into text data using the speech_recognition engine.

[0391] Text data analysis and response

[0392] The server analyzes the received text data and understands the user's request. For example, it may obtain an instruction such as "move a part" as a result of the analysis. Then, it uses the robot_controller to send a command to the factory robot to perform the requested action.

[0393] Emotion recognition and response regulation

[0394] At the same time, the server uses emotion_recognition to analyze emotions from the user's voice data. If the user speaks in a tired voice, the emotion engine detects "fatigue." In this case, to adjust the response, it uses alert_system to generate a message such as "Please take a break," converts it into voice data, and plays it back to the user through the device. The text_to_speech engine converts the text generated by the server into voice data.

[0395] Acquisition and provision of information

[0396] When a user makes a voice request such as "Tell me today's news," the server similarly converts the voice data into text data and determines that the request is for news. Next, the server accesses the news information API to obtain the latest news data, converts it into voice data using the text_to_speech engine, and provides it to the user via the device.

[0397] Specific examples

[0398] For example, if a user utters a prompt phrase such as "Please move the part," the system will analyze it and give specific movement instructions to a factory robot. If a worker says, "I'm very tired right now," the system will analyze the voice, recognize the emotion, and generate and play an alert saying, "Please take a break."

[0399] Example prompt sentence:

[0400] Please move the parts.

[0401] "Do you think you need a break?"

[0402] "Please stop what you're doing now."

[0403] The above is a specific embodiment for carrying out the present invention. This invention enables operation by voice input and realizes responses according to the emotional state. This improves work efficiency and ensures the safety of the worker.

[0404] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0405] Step 1:

[0406] The user inputs information through voice input. Input: The user gives a voice command (e.g., "move the part"). To perform a specific action, the user speaks the command into the microphone.

[0407] Step 2:

[0408] The device receives voice data from the user. Input: User's voice. Output: Digital voice data. Specifically, the microphone captures the voice and encodes the voice data.

[0409] Step 3:

[0410] The device transmits the encoded voice data to the server in real time. Input: Digital voice data. Output: Voice data transmitted to the server. Specifically, the device transmits the voice data to the server via the network.

[0411] Step 4:

[0412] The server converts the received voice data into text data using a speech recognition engine. Input: Voice data. Output: Text data (e.g., "Move the part"). Specifically, the server starts the speech_recognition engine and converts the voice data into text.

[0413] Step 5:

[0414] The server analyzes the text data to understand the user's request. Input: Text data. Output: Request content (e.g., "Move the part"). Specifically, the server uses a natural language processing engine to analyze the text data and extract the request content.

[0415] Step 6:

[0416] The server generates instructions for the factory robot based on the request and controls the robot. Input: Request. Output: Robot control command. For specific operations, the server uses robot_controller to generate commands that instruct the specific robot operations and sends them to the robot.

[0417] Step 7:

[0418] The server simultaneously recognizes the user's emotions from the voice data. Input: Voice data. Output: Emotion data (e.g., "fatigue"). Specifically, the server uses the emotion_recognition engine to analyze the voice data and detect the user's emotional state.

[0419] Step 8:

[0420] The server adjusts the response content based on the emotion recognition results. Input: Emotion data, request content. Output: Adjusted response message (e.g., "Move the parts. Please take a break."). Specifically, the server generates an additional message depending on the emotion recognition results.

[0421] Step 9:

[0422] The server converts the tailored response message from text to audio data and sends it to the device. Input: Tailored response message. Output: Audio data. Specifically, the server uses the text_to_speech engine to convert the text message into audio data and then sends it to the device.

[0423] Step 10:

[0424] The device plays the received audio data to the user. Input: Audio data. Output: Audio response to the user. Specifically, the device uses a speaker to play the audio data to the user.

[0425] Through the above steps, the factory robot operates based on the user's voice input and provides an appropriate response according to the user's emotional state.

[0426] 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.

[0427] 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.

[0428] 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.

[0429] [Second embodiment]

[0430] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0431] 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.

[0432] 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).

[0433] 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.

[0434] 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.

[0435] 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).

[0436] 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.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] 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.

[0441] 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."

[0442] The present invention is a system including a means for a user to input information by voice input, a terminal means for acquiring voice data from the user, a server means for converting the acquired voice data into text data, a means for analyzing the text data and acquiring information in response to a user request, a server means for converting the acquired information into voice data, and a terminal means for playing the voice data back to the user. The operation of the system will be specifically described below.

[0443] User voice input

[0444] For example, a user might say, "Tell me the weather today." This speech is captured through the microphone of the device (e.g., a tablet or smart device). The device encodes the captured voice data into a processable format in real time and then sends it to the server.

[0445] Analyzing voice data and obtaining information

[0446] The server receives the voice data sent from the device. The server uses a voice recognition engine to convert the received voice data into text data. It then uses a natural language processing engine to analyze the text data and understand the user's request. In this example, it determines that the request is to "provide weather information."

[0447] The server then accesses the weather API to retrieve the latest weather information, identifying relevant weather information based on the user's location and preferences.

[0448] Converting acquired information into audio data and playing it back

[0449] The server uses a speech synthesis engine to convert the acquired weather information into voice data. The speech synthesis engine converts text data (e.g., "Today's weather is sunny") into natural-sounding voice and sends it to the terminal in the form of voice data.

[0450] The device receives the voice data sent from the server and plays it back to the user using the built-in speaker, allowing the user to hear the information "Today's weather is sunny."

[0451] Management and sharing of health information

[0452] As another example, consider the case where a user says, "Record my health status today." The device captures the voice data and sends it to the server. The server uses a speech recognition engine to convert the voice data into text data and record the user's health status.

[0453] The server stores the recorded health information in a database and sends notifications to medical staff or family members as needed, such as "Your health condition has been recorded. Please refer to the database for details."

[0454] This system allows users to obtain information and manage their health status using only their voice. In addition, it allows for quick sharing of information with medical staff and family members, helping to support users' safety and security. News and other daily information can also be provided in the same way, improving the user's quality of life.

[0455] The processing flow will be explained below.

[0456] Program processing flow

[0457] Example of checking the news

[0458] Step 1:

[0459] User: Say "Tell me the latest news." The user speaks into a tablet or smart device.

[0460] Step 2:

[0461] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[0462] Step 3:

[0463] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[0464] Step 4:

[0465] Server: Receives the voice data. The server confirms that the data has been received.

[0466] Step 5:

[0467] Server: Converts the voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data, such as "Tell me about the latest news."

[0468] Step 6:

[0469] Server: A natural language processing engine analyzes the text data and determines whether the user is looking for the latest news.

[0470] Step 7:

[0471] Server: Accesses the news information API to obtain the latest news data, makes an API request, and receives response data.

[0472] Step 8:

[0473] Server: Converts the acquired news data into a text format. For example, it creates text in the format "Today's main news is..."

[0474] Step 9:

[0475] Server: Converts text data into voice data using a speech synthesis engine. The synthesized voice data is generated as "Today's main news is..."

[0476] Step 10:

[0477] Server: Sends the generated voice data to the terminal. Confirms the data transmission.

[0478] Step 11:

[0479] Terminal: Receives audio data. Checks the received data and encodes it.

[0480] Step 12:

[0481] Device: Play audio data through the speaker. Output so that the user can hear "Today's main news is..."

[0482] Health status record example

[0483] Step 1:

[0484] User: Say "Record my health status today." The user speaks into a tablet or smart device.

[0485] Step 2:

[0486] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[0487] Step 3:

[0488] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[0489] Step 4:

[0490] Server: Receives the voice data. The server confirms that the data has been received.

[0491] Step 5:

[0492] Server: Converts voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data such as "Please record today's health condition."

[0493] Step 6:

[0494] Server: Analyzes the text data using a natural language processing engine and determines that the user wants to record their health status.

[0495] Step 7:

[0496] Server: Save the text data in a database. Save the message "Record your health condition today" as the user's health record.

[0497] Step 8:

[0498] Server: Based on the stored health data, it sends notifications to medical staff and family members as needed. For example, it sends a notification that "the user's health status has been updated."

[0499] In this way, specific operations are performed at each processing step, from user voice input to information acquisition and recording of health information.

[0500] Example 1

[0501] 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."

[0502] Currently, there are many systems that use voice to input, process, and output information, but most of them have limited functionality and are difficult to meet the diverse needs of users.In addition, there is a problem that a single system cannot meet the various needs, such as fast and accurate processing of voice data, management of health information, and acquisition of information from external sources.

[0503] 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.

[0504] In this invention, the server includes means for converting voice data into text data, means for analyzing the text data and acquiring information in response to a user request, and means for converting the acquired information into voice data, thereby enabling acquisition of a variety of information using voice input.

[0505] "Voice input" is a method in which a user inputs information using their voice.

[0506] "Voice data" means data that is a digital representation of a user's voice.

[0507] A "terminal" is a device that acquires voice data and transmits it to a server.

[0508] "Encoding" is the process of converting audio data into a format that is easier to process.

[0509] A "server" is a computer system that processes voice data and provides information in response to user requests.

[0510] "Text data" is data obtained by converting voice data into a character string format.

[0511] "Natural language processing" is a technology that analyzes text data and understands human language.

[0512] "Speech synthesis" is the process of converting text data into speech data.

[0513] "Notification information" is data used to notify other users or systems of important information.

[0514] "Health Information" is data relating to a user's health condition.

[0515] "External sources" are external databases or APIs that provide weather or news information.

[0516] "User" means a person who uses this system to input and obtain information.

[0517] MODE FOR CARRYING OUT THE INVENTION

[0518] The present invention provides a system that includes a means for users to input information by voice input, converts the acquired voice data into text data, analyzes it to acquire information, and then converts it back into voice data to provide.

[0519] Acquiring voice input

[0520] For example, a user might say, "Tell me the weather today." The device captures the user's voice through a microphone and converts it into digital audio data. This audio data is encoded in real time and sent to a server. Capturing and encoding uses commonly available hardware and software.

[0521] Audio data processing

[0522] The server receives the voice data sent from the device. It converts the voice data into text data using a speech recognition engine (for example, the Google Speech-to-Text API is generally available). The generated text data is then analyzed by a natural language processing engine (for example, OpenAI's GPT language model is generally used) to understand the user's request. This analysis may result in a decision to, for example, "provide weather information."

[0523] Acquiring information and converting it into audio data

[0524] Based on the request received from the user, the server accesses an external information source (e.g., a weather information API, typically the OpenWeatherMap API) to obtain the latest weather information. The obtained weather information is converted into voice data using a speech synthesis engine (e.g., typically Amazon Polly). Text data (e.g., "Today's weather is sunny") is converted into natural-sounding speech by a voice collection engine.

[0525] Providing audio data

[0526] The server sends the generated voice data to the device. The device receives the voice data and plays it back to the user through the built-in speaker. This allows the user to hear the information aloud, such as "Today's weather is sunny."

[0527] Health information management and notification

[0528] As another example, if a user says, "Record my health condition today," this voice data is also captured and sent to the server. The server uses a voice recognition engine to convert the voice data into text data, which is then analyzed and recorded as health information. The recorded health information is stored in a database, and notifications are sent to medical staff and family members as needed. These notifications include content such as, "Your health condition has been recorded. Please refer to the database for details."

[0529] Example prompt

[0530] Examples of generated AI prompts to parse user input:

[0531] Convert the following speech data into text and parse the request: 'What's the weather like today?'

[0532] Example of a generative AI prompt for recording health status:

[0533] Convert the following audio data into text and record the health information in a database: 'Record my health status today.'

[0534] This invention allows users to obtain various information by voice input and manage health information efficiently. In addition, the information can be promptly provided to users through fast and accurate information processing via the server.

[0535] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0536] Step 1:

[0537] The user says, "What's the weather today?" This initiates voice input. The device captures the user's voice through the built-in microphone and converts it into digital audio data. The input of this step is an audio signal, and the output is digital audio data. Specifically, the microphone device collects audio waveforms and encodes them into a digital format (e.g., PCM format).

[0538] Step 2:

[0539] The device encodes the captured digital audio data into an appropriate format in real time and sends it to the server. The input of this step is the digital audio data, and the output is the audio data sent to the server. The specific operation is a process of using the device's network interface to send the data to the server via the TCP / IP protocol, etc.

[0540] Step 3:

[0541] The server receives the voice data sent from the terminal. The received data is stored in temporary storage. The input of this step is the voice data sent to the server, and the output is the voice data stored in the temporary storage. The specific operation is the process of receiving data via the server's network interface and storing it in the storage system.

[0542] Step 4:

[0543] The server converts the voice data into text data using a voice recognition engine. A common voice recognition API (e.g., Google Speech-to-Text) can be used as the engine. The input for this step is the voice data stored in temporary storage, and the output is text data. The conversion process analyzes the voice waveform data and generates a corresponding string.

[0544] Step 5:

[0545] The server uses a natural language processing engine to analyze the text data and identify the user's request. Typically, an engine like OpenAI GPT can be used. The input for this step is the text data, and the output is the user's request. Specifically, this involves the process in which a natural language analysis algorithm analyzes the text and recognizes requests such as "provide weather information."

[0546] Step 6:

[0547] In response to a user request, the server accesses an external information source (e.g., a weather information API) to obtain the latest information. The input to this step is the user's request, and the output is the obtained information (e.g., a weather forecast). The specific operation is the process of sending an HTTP request to an API endpoint and receiving information as a response.

[0548] Step 7:

[0549] The server uses a speech synthesis engine (e.g., Amazon Polly) to convert the acquired information into speech data. The input of this step is the acquired text information, and the output is the generated speech data. Specifically, the synthesis engine analyzes the text and generates it as a speech waveform.

[0550] Step 8:

[0551] The server sends the generated voice data to the terminal. The input of this step is the generated voice data, and the output is the voice data sent to the terminal. The specific operation is the process of sending the voice data through the network interface of the server.

[0552] Step 9:

[0553] The terminal receives the audio data sent from the server and plays it using the built-in speaker. The input of this step is the received audio data, and the output is playing audio information to the user. Specifically, it includes an operation of outputting an audio waveform using the audio playback system of the terminal.

[0554] (Application example 1)

[0555] 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."

[0556] In traditional factories, production management and inventory status checks are often done manually, which can reduce work efficiency. It can also be difficult for workers to quickly obtain the information they need, resulting in communication delays. Efficiently managing and obtaining health and other daily information is also a challenge, and a system to address these issues is needed.

[0557] 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.

[0558] In this invention, the server includes a means for converting voice data into text data, a means for analyzing the text data and acquiring information in response to a user's request, and a means for converting the acquired information into voice data. This allows users to efficiently manage production and check inventory status within a factory through voice input. It also allows for the rapid acquisition and management of health information and other daily information, improving work efficiency and accelerating information sharing.

[0559] "User" means a person who uses the system to obtain information by voice input.

[0560] "Voice input" is a method of inputting information using voice data uttered by the user.

[0561] "Terminal means" is a device that captures audio data and transmits it to a server.

[0562] The "server means" is a device that processes data sent from a terminal and acquires information.

[0563] "Text data" is character information converted from voice data.

[0564] The "means for obtaining information" is a function for obtaining the information required by the user based on the analyzed text data.

[0565] The "means for converting into audio data" is a function for converting acquired information into audio format.

[0566] "A means for checking production management and inventory status within a factory by voice input" is a means for a user to check production management and inventory status within a factory by voice input.

[0567] "Health Information" is data relating to a user's health condition.

[0568] "Means for saving on a server" is a function for saving acquired information.

[0569] "Means of notification" is a function that sends information to users and related persons.

[0570] "News" refers to current events and information.

[0571] "Weather information" is data about the current weather and weather forecast.

[0572] This invention is a system that allows users to obtain information through voice input, and specific embodiments thereof are described below. The system converts voice data into text data and obtains and provides information in response to user requests. In particular, the present invention has a means for efficiently managing production and checking inventory status within a factory.

[0573] System Overview

[0574] 1. Acquiring voice input

[0575] The device is equipped with a microphone to capture user voice input: when a user says something like, "What is the current production line status?" or "What is the inventory status of part number 123?", the voice data is captured in real time.

[0576] 2. Audio data conversion

[0577] The acquired voice data is sent to the server, where it is converted into text data using a voice recognition engine called speech_recognition.

[0578] 3. Text data analysis and information acquisition

[0579] The server then uses a natural language processing engine to analyze the converted text data, understand the user's request, and executes API access or database queries to obtain information on the status of a production line or inventory, for example.

[0580] 4. Converting information into audio data

[0581] The acquired information is converted into voice data using the gtts (Google Text-to-Speech) library. In this process, text data (e.g., "The current production line is operating normally") is converted into natural-sounding speech.

[0582] 5. Playing audio data

[0583] The terminal receives the voice data sent from the server and plays it back to the user using the built-in speaker, allowing the user to obtain the necessary information by voice.

[0584] Specific examples

[0585] Factory production management

[0586] Imagine the following instructions being given in a factory:

[0587] Example instruction 1: "What is the status of the production line?"

[0588] → Robot replies: "The current production line is operating normally."

[0589] Example instruction 2: "What is the stock status of part number 123?"

[0590] → The robot responds: "We only have 20 units of part number 123 left in stock."

[0591] Prompt Sentence Examples

[0592] By inputting the following prompt sentence into the generative AI model, an appropriate response will be generated:

[0593] Example prompt: "Create a program that uses a voice interface to instruct a robot to check production management status and inventory status at the factory."

[0594] Hardware and software used

[0595] Hardware: Microphone, speaker, or robot with built-in microphone and speaker

[0596] Software: speech_recognition (speech recognition library), gtts (Google Text-to-Speech library), mpg321 (audio playback software)

[0597] In this way, the present invention provides a system that realizes efficient production management and inventory status confirmation within a factory, and quickly acquires and provides information through user voice input.

[0598] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0599] Step 1:

[0600] The device receives the user's voice input.

[0601] Input: User speech (e.g., "What's the status of the production line?").

[0602] What it does: Captures audio data using the device's microphone and encodes it in real time into a processable format.

[0603] Output: The encoded audio data.

[0604] Step 2:

[0605] The terminal transmits the acquired voice data to the server.

[0606] Input: Encoded audio data.

[0607] What it does: Sends encoded audio data over the network to a server.

[0608] Output: Audio data transferred to the server.

[0609] Step 3:

[0610] The server converts the voice data into text data.

[0611] Input: The transmitted audio data.

[0612] How it works: Converts audio data into text using the speech_recognition library.

[0613] Output: The converted text data (e.g., "What is the status of the production line?").

[0614] Step 4:

[0615] The server parses the text data and understands the request.

[0616] Input: Text data.

[0617] How it works: It uses a natural language processing engine to parse what the user is asking.

[0618] Output: The request (e.g., "Get the status of the production line").

[0619] Step 5:

[0620] The server retrieves information based on the user's request.

[0621] Input: Request content.

[0622] What it does: Accesses databases and APIs to get production line status and inventory status.

[0623] Output: The information obtained (e.g., "The current production line is operating normally.").

[0624] Step 6:

[0625] The server converts the acquired information into audio data.

[0626] Input: The information obtained.

[0627] Operation: Converts text data into audio data using the gtts library.

[0628] Output: The generated audio data.

[0629] Step 7:

[0630] The terminal receives and plays back the audio data transmitted from the server.

[0631] Input: The generated audio data.

[0632] What it does: Receives audio data over the network and plays it back to the user using the built-in speaker.

[0633] Output: A spoken response to the user (e.g., "The current production line is operating normally.").

[0634] 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.

[0635] The present invention is a system that includes a means for a user to input information by voice input, a terminal means for acquiring voice data from the user, a server means for converting the acquired voice data into text data, a means for analyzing the text data and acquiring information in response to a user request, a server means for converting the acquired information into voice data, and a terminal means for playing the voice data back to the user. Furthermore, it is combined with an emotion engine that recognizes emotions from the user's voice data. The detailed operation of this system is described below.

[0636] User voice input

[0637] For example, a user might say, "Tell me today's news." This speech is captured through the microphone of the device (e.g., a tablet or smart device). The device encodes the captured voice data in real time, converts it into a binary format, and sends it to the server.

[0638] Analyzing voice data and obtaining information

[0639] The server receives the voice data sent from the device. It uses a voice recognition engine to convert the received voice data into text data. It then uses a natural language processing engine to analyze the text data and understand the user's request. In this example, it determines that the user is requesting "news delivery."

[0640] Next, the server accesses the news information API to obtain the latest news data, makes an API request, and receives response data.

[0641] Converting acquired information into audio data and playing it back

[0642] The server converts the acquired news data into text format, then uses a speech synthesis engine to convert this text data into voice data, which is then sent to the terminal in voice data format.

[0643] The device receives the audio data sent from the server and plays it back to the user using the built-in speaker. The user can hear information such as "Today's news is..."

[0644] Recognizing and responding to user emotions

[0645] The server simultaneously analyzes the user's emotions using an emotion engine while recognizing the voice. For example, if the user speaks in a "tired voice," the emotion engine will recognize this as "fatigue."

[0646] Based on the results of emotion recognition, the server will adjust its response, for example, if the user is tired, it will add a thoughtful comment such as "Here's the latest news. Please take it easy today."

[0647] If necessary, the recognized emotional information can be notified to medical staff or family members. In this case, the server can send an alert saying, "The user seems tired."

[0648] Recording and Notification of Health Information

[0649] Similarly, if the user says, "Record my health condition today," the device captures the voice and sends it to the server. The server then converts the text data using a speech recognition engine, analyzes it, and records it as health information. It also uses an emotion engine to recognize the user's emotions and notify medical staff or family members as necessary.

[0650] Specific examples

[0651] For example, if a user says, "I'm very tired right now," the device captures this speech and sends the data to the server. The server then converts it into text data using a speech recognition engine and analyzes the meaning of "tired." At the same time, the emotion engine recognizes the "feeling of fatigue" and generates voice data in a gentle tone saying, "Please take a rest," which is then sent to the user via the device. The server then sends notifications to medical staff and family members depending on the situation.

[0652] In this way, this system enables two-way communication using voice and emotions, and can better understand and respond to the user's needs, providing comprehensive support for the elderly and those requiring care to live their daily lives with peace of mind.

[0653] The processing flow will be explained below.

[0654] News confirmation and emotion recognition processing flow

[0655] Step 1:

[0656] User: Say "Tell me the latest news." The user speaks into a tablet or smart device.

[0657] Step 2:

[0658] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[0659] Step 3:

[0660] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[0661] Step 4:

[0662] Server: Receives the voice data. The server confirms that the data has been received.

[0663] Step 5:

[0664] Server: Converts the voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data, such as "Tell me about the latest news."

[0665] Step 6:

[0666] Server: A natural language processing engine analyzes the text data and determines whether the user is looking for the latest news.

[0667] Step 7:

[0668] Server: Accesses the news information API to obtain the latest news data, makes an API request, and receives response data.

[0669] Step 8:

[0670] Server: Converts the acquired news data into a text format. For example, it creates text in the format "Today's main news is..."

[0671] Step 9:

[0672] Server: Converts text data into voice data using a speech synthesis engine. The synthesized voice data is generated as "Today's main news is..."

[0673] Step 10:

[0674] Server: Sends the generated voice data to the terminal. Confirms the data transmission.

[0675] Step 11:

[0676] Terminal: Receives audio data. Checks the received data and encodes it.

[0677] Step 12:

[0678] Device: Play audio data through the speaker. Output so that the user can hear "Today's main news is..."

[0679] Health status recording and emotion recognition process

[0680] Step 1:

[0681] User: Say "Record my health status today." The user speaks into a tablet or smart device.

[0682] Step 2:

[0683] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[0684] Step 3:

[0685] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[0686] Step 4:

[0687] Server: Receives the voice data. The server confirms that the data has been received.

[0688] Step 5:

[0689] Server: Converts voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data such as "Please record today's health condition."

[0690] Step 6:

[0691] Server: Analyzes the text data using a natural language processing engine and determines that the user wants to record their health status.

[0692] Step 7:

[0693] Server: Save the text data in a database. Save the message "Record your health condition today" as the user's health record.

[0694] Step 8:

[0695] Server: Analyzes the user's emotions using an emotion engine based on the stored health information. For example, if the user says "I'm tired," the emotion engine will recognize this as "fatigue."

[0696] Step 9:

[0697] Server: Adjust the response based on the emotion engine's recognition results. For example, if the user is tired, add a message saying "Take a good rest."

[0698] Step 10:

[0699] Server: Convert the response message into voice data. Using a voice synthesis engine, generate the voice data "Please take a good rest."

[0700] Step 11:

[0701] Server: Sends the generated voice data to the terminal. Confirms the data transmission.

[0702] Step 12:

[0703] Terminal: Receives and encodes audio data.

[0704] Step 13:

[0705] Device: Plays audio data through the speaker, outputting "Please take a good rest" so that the user can hear it.

[0706] Step 14:

[0707] Server: Notifies medical staff or family members of the recognized emotion information, for example, by sending an alert saying, "The user seems tired."

[0708] In this way, a system that combines an emotion engine can perform a series of processes, from acquiring information from the user's voice input to responding while taking into account the user's emotional state.

[0709] Example 2

[0710] 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."

[0711] Conventional voice assistant systems mainly respond simply to the user's voice input, and lack the ability to appropriately recognize the user's emotions and health status and adjust responses accordingly. In particular, there is a lack of comprehensive support for the elderly and those requiring care to live their daily lives with peace of mind.

[0712] 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.

[0713] In this invention, the server includes: means for a user to input information by voice input; terminal means for acquiring voice data from the user; server means for converting the acquired voice data into text data; means for analyzing the text data and acquiring information according to the user's request; server means for converting the acquired information into voice data; terminal means for playing the voice data back to the user; server means including an emotion engine for recognizing emotions from the user's voice data; and means for adjusting response content based on the results of emotion recognition. This makes it possible to provide appropriate responses that take into account the user's emotions and health condition, enabling comprehensive support to enable the elderly and those requiring care to live their daily lives with peace of mind.

[0714] "Voice input" is a means by which a user inputs information as voice.

[0715] A "terminal" is a device that acquires voice data from a user and transmits it to a server.

[0716] A "server" is a device that converts acquired voice data into text data, analyzes and acquires information, and responds to the user.

[0717] A "voice recognition engine" is software for converting voice data into text data.

[0718] A "natural language processing engine" is software that analyzes text data and understands user requests.

[0719] "Information acquisition means" refers to a means for acquiring information from an external information source in response to a user request.

[0720] A "speech synthesis engine" is software for converting text data into voice data.

[0721] The "emotion engine" is software that recognizes emotions from the user's voice data.

[0722] The "response content adjustment means" is a means for adjusting the response content based on the result of emotion recognition.

[0723] "Health Information" means information relating to a user's health condition.

[0724] "Means of notification" refers to the means of notifying medical staff and family members of information as necessary.

[0725] "News Information API" is an external API that obtains the latest news information.

[0726] "Voice data" refers to data in which the user's voice is encoded as a digital signal.

[0727] "Text data" refers to character data obtained by converting voice data.

[0728] The present invention is a system in which a user inputs information by voice, and includes the following components: Through this system, the user is supported in obtaining daily information and managing their health.

[0729] User voice input

[0730] For example, a user may say, "Tell me today's news." The user's voice input is captured through the microphone of the device (e.g., tablet or smart device). The device converts the captured voice into a digital signal, encodes the voice data into a binary format, and then sends it to the server.

[0731] Receiving and converting audio data

[0732] The server receives the voice data sent from the device and converts it into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text API).The server then analyzes the text using a natural language processing engine (e.g., IBM Watson NLU) to understand the user's request.

[0733] Obtaining information

[0734] In response to a user request, the server accesses a news information API (e.g., NewsAPI) to obtain the latest news data. If the user wishes to record their health status, the server similarly converts the voice to text and records and saves it as health information.

[0735] Converting acquired information into audio data

[0736] The server uses a speech synthesis engine (e.g., Amazon Polly) to convert the acquired news data into audio data, which is then sent to the device and played back to the user.

[0737] Recognizing and responding to user emotions

[0738] The server uses an emotion engine (e.g., Affectiva) to simultaneously recognize the voice and analyze the user's emotions. For example, if the server determines that the user sounds tired, it adjusts the response and provides a thoughtful comment such as "Please take a rest" in a gentle tone. In some cases, it may also notify medical staff or family members.

[0739] Specific examples

[0740] For example, if a user says, "I'm very tired right now," the device captures this voice, converts it into a digital signal, and sends it to the server. The server then uses a speech recognition engine to convert the voice data into text data and analyzes the meaning of "tired." At the same time, the emotion engine recognizes the "feeling of fatigue." The server then generates voice data in a gentle tone saying, "Please take a rest," and sends it to the device. The device then plays this voice data to the user. Additionally, it may send notifications to medical staff or family members depending on the situation.

[0741] Examples of prompt statements

[0742] "A user says they want to know today's news. How does the system respond?"

[0743] “If a user says they are tired, what sentiment analysis does the system perform and how does it respond?”

[0744] "Please explain the process your system goes through to record the user's health status."

[0745] In this way, the present invention uses a system that combines voice recognition, natural language processing, and emotion analysis, enabling responses that are adapted to the diverse needs of users and providing comprehensive support, particularly for the elderly and those requiring care.

[0746] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0747] Step 1:

[0748] For example, a user might say, "Tell me today's news." This speech is captured through the device's microphone. The device converts the speech into a digital signal and encodes the speech data into a binary format. The input is the user's speech, and the output is the encoded speech data. The device then sends the encoded speech data to the server.

[0749] Step 2:

[0750] The server receives the voice data sent from the terminal. The input is encoded voice data. The server uses a voice recognition engine to convert the received voice data into text data. The output at this stage is text data. General voice recognition software is used as the voice recognition engine.

[0751] Step 3:

[0752] The server uses a natural language processing engine to analyze the text data and understand the user's request. The input is text data, and the output is the analyzed user request. Specifically, the server determines that the text data requests "provision of news." This allows the server to proceed to the next information acquisition step.

[0753] Step 4:

[0754] The server queries external information sources in response to user requests. The input is the parsed request content. The server accesses the news information API and sends an API request. As a result, it receives the latest news data. The output is the news data.

[0755] Step 5:

[0756] The server formats the acquired news data into text format. The input is news data, and the output is formatted text data. Furthermore, a speech synthesis engine is used to convert the formatted text data into voice data. The output is converted voice data.

[0757] Step 6:

[0758] The server sends the converted audio data to the device. The device decodes the received audio data and plays it back to the user through the built-in speaker. The input is the converted audio data, and the output is the audio playback. The user can hear information such as "Today's news is..." by voice.

[0759] Step 7:

[0760] The server simultaneously recognizes the voice and uses an emotion engine to analyze the user's emotions. The input is voice data, and the output is analyzed emotion information. For example, if the user's voice is judged to sound tired, the emotion engine will recognize "fatigue."

[0761] Step 8:

[0762] The server adjusts the response content based on the emotion recognition results. The input is the analyzed emotion information, and the output is the adjusted response content. For example, if the user is tired, a thoughtful comment such as "Here's the latest news. Please take it easy today and don't push yourself too hard" is added to the voice data.

[0763] Step 9:

[0764] If necessary, the server notifies medical staff or family members of the recognized emotion information. The input is the analyzed emotion information, and the output is the notification content. For example, it sends a message saying, "The user seems tired."

[0765] Step 10:

[0766] Similarly, when a user says, "Record my health condition today," the device captures the voice and sends it to the server. The server uses a voice recognition engine to convert the voice data into text data, analyzes it, and records it as health information. The input is voice data, and the output is the recorded health data. The emotion engine also recognizes the user's emotions.

[0767] (Application example 2)

[0768] 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."

[0769] In conventional factory robot systems, it was difficult to accurately recognize voice instructions from workers and quickly and accurately execute those instructions. Furthermore, systems that could grasp the emotional state of workers and respond accordingly were not sufficiently developed. As a result, it was not possible to improve worker stress management or work efficiency. Furthermore, if a worker was fatigued or stressed, not taking appropriate action could lead to a decrease in work safety.

[0770] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0771] In this invention, the server includes a means for acquiring voice data and converting it into text data, a means for acquiring information in response to a user request, a means for converting the acquired information into voice data, a means including an emotion engine for analyzing the voice data and recognizing the user's emotion, and a means for adjusting the response content in accordance with the recognized emotion. This enables prompt and accurate execution of voice-input instructions and appropriate responses according to the worker's emotional state, contributing to improved work efficiency and ensuring safety.

[0772] "User" refers to a person who uses the system to provide information by voice input.

[0773] "Voice input" refers to a user speaking through a voice capture device such as a microphone.

[0774] "Terminal" refers to the device that receives voice data from the user and transmits it to the server.

[0775] "Voice Data" means information that is a digital representation of the voice uttered by a User.

[0776] "Text data" refers to data in a format in which voice data has been converted into text.

[0777] The term "server" refers to a device that processes acquired voice data, converts it into text data, and further analyzes the text data to acquire information.

[0778] An "emotion engine" refers to software or a system that analyzes a user's emotions from voice data and expresses them as digital data.

[0779] "Means of obtaining information" refers to the process of obtaining the necessary information from external APIs or databases based on user requests.

[0780] "Means for adjusting response content" refers to the ability to appropriately change the information provided or the content of responses based on the user's emotional state.

[0781] "News information" refers to information about current events and important topics.

[0782] "Medical staff" refers to professionals who manage users' health information.

[0783] "Family Member" refers to individuals who have a close relationship with the User.

[0784] MODE FOR CARRYING OUT THE INVENTION

[0785] This invention is a system that utilizes voice input and emotion recognition to improve the efficiency of factory work and enable responses according to the emotional state of workers. Specific embodiments of this system are described below.

[0786] Hardware and Software Configuration

[0787] The system utilizes the following hardware and software:

[0788] Hardware: microphones, speakers, factory robots.

[0789] Software: speech_recognition, robot_controller, text_to_speech, emotion_recognition, alert_system.

[0790] Acquiring and converting audio data

[0791] The user inputs commands such as "move the part" by voice through a microphone. The device captures the voice data, encodes it in real time, and sends it to the server. The server then converts the voice data into text data using the speech_recognition engine.

[0792] Text data analysis and response

[0793] The server analyzes the received text data and understands the user's request. For example, it may obtain an instruction such as "move a part" as a result of the analysis. Then, it uses the robot_controller to send a command to the factory robot to perform the requested action.

[0794] Emotion recognition and response regulation

[0795] At the same time, the server uses emotion_recognition to analyze emotions from the user's voice data. If the user speaks in a tired voice, the emotion engine detects "fatigue." In this case, to adjust the response, it uses alert_system to generate a message such as "Please take a break," converts it into voice data, and plays it back to the user through the device. The text_to_speech engine converts the text generated by the server into voice data.

[0796] Acquisition and provision of information

[0797] When a user makes a voice request such as "Tell me today's news," the server similarly converts the voice data into text data and determines that the request is for news. Next, the server accesses the news information API to obtain the latest news data, converts it into voice data using the text_to_speech engine, and provides it to the user via the device.

[0798] Specific examples

[0799] For example, if a user utters a prompt phrase such as "Please move the part," the system will analyze it and give specific movement instructions to a factory robot. If a worker says, "I'm very tired right now," the system will analyze the voice, recognize the emotion, and generate and play an alert saying, "Please take a break."

[0800] Example prompt sentence:

[0801] Please move the parts.

[0802] "Do you think you need a break?"

[0803] "Please stop what you're doing now."

[0804] The above is a specific embodiment for carrying out the present invention. This invention enables operation by voice input and realizes responses according to the emotional state. This improves work efficiency and ensures the safety of the worker.

[0805] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0806] Step 1:

[0807] The user inputs information through voice input. Input: The user gives a voice command (e.g., "move the part"). To perform a specific action, the user speaks the command into the microphone.

[0808] Step 2:

[0809] The device receives voice data from the user. Input: User's voice. Output: Digital voice data. Specifically, the microphone captures the voice and encodes the voice data.

[0810] Step 3:

[0811] The device transmits the encoded voice data to the server in real time. Input: Digital voice data. Output: Voice data transmitted to the server. Specifically, the device transmits the voice data to the server via the network.

[0812] Step 4:

[0813] The server converts the received voice data into text data using a speech recognition engine. Input: Voice data. Output: Text data (e.g., "Move the part"). Specifically, the server starts the speech_recognition engine and converts the voice data into text.

[0814] Step 5:

[0815] The server analyzes the text data to understand the user's request. Input: Text data. Output: Request content (e.g., "Move the part"). Specifically, the server uses a natural language processing engine to analyze the text data and extract the request content.

[0816] Step 6:

[0817] The server generates instructions for the factory robot based on the request and controls the robot. Input: Request. Output: Robot control command. For specific operations, the server uses robot_controller to generate commands that instruct the specific robot operations and sends them to the robot.

[0818] Step 7:

[0819] The server simultaneously recognizes the user's emotions from the voice data. Input: Voice data. Output: Emotion data (e.g., "fatigue"). Specifically, the server uses the emotion_recognition engine to analyze the voice data and detect the user's emotional state.

[0820] Step 8:

[0821] The server adjusts the response content based on the emotion recognition results. Input: Emotion data, request content. Output: Adjusted response message (e.g., "Move the parts. Please take a break."). Specifically, the server generates an additional message depending on the emotion recognition results.

[0822] Step 9:

[0823] The server converts the tailored response message from text to audio data and sends it to the device. Input: Tailored response message. Output: Audio data. Specifically, the server uses the text_to_speech engine to convert the text message into audio data and then sends it to the device.

[0824] Step 10:

[0825] The device plays the received audio data to the user. Input: Audio data. Output: Audio response to the user. Specifically, the device uses a speaker to play the audio data to the user.

[0826] Through the above steps, the factory robot operates based on the user's voice input and provides an appropriate response according to the user's emotional state.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] [Third embodiment]

[0831] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0832] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0833] 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).

[0834] 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.

[0835] 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.

[0836] 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).

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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."

[0843] The present invention is a system including a means for a user to input information by voice input, a terminal means for acquiring voice data from the user, a server means for converting the acquired voice data into text data, a means for analyzing the text data and acquiring information in response to a user request, a server means for converting the acquired information into voice data, and a terminal means for playing the voice data back to the user. The operation of the system will be specifically described below.

[0844] User voice input

[0845] For example, a user might say, "Tell me the weather today." This speech is captured through the microphone of the device (e.g., a tablet or smart device). The device encodes the captured voice data into a processable format in real time and then sends it to the server.

[0846] Analyzing voice data and obtaining information

[0847] The server receives the voice data sent from the device. The server uses a voice recognition engine to convert the received voice data into text data. It then uses a natural language processing engine to analyze the text data and understand the user's request. In this example, it determines that the request is to "provide weather information."

[0848] The server then accesses the weather API to retrieve the latest weather information, identifying relevant weather information based on the user's location and preferences.

[0849] Converting acquired information into audio data and playing it back

[0850] The server uses a speech synthesis engine to convert the acquired weather information into voice data. The speech synthesis engine converts text data (e.g., "Today's weather is sunny") into natural-sounding voice and sends it to the terminal in the form of voice data.

[0851] The device receives the voice data sent from the server and plays it back to the user using the built-in speaker, allowing the user to hear the information "Today's weather is sunny."

[0852] Management and sharing of health information

[0853] As another example, consider the case where a user says, "Record my health status today." The device captures the voice data and sends it to the server. The server uses a speech recognition engine to convert the voice data into text data and record the user's health status.

[0854] The server stores the recorded health information in a database and sends notifications to medical staff or family members as needed, such as "Your health condition has been recorded. Please refer to the database for details."

[0855] This system allows users to obtain information and manage their health status using only their voice. In addition, it allows for quick sharing of information with medical staff and family members, helping to support users' safety and security. News and other daily information can also be provided in the same way, improving the user's quality of life.

[0856] The processing flow will be explained below.

[0857] Program processing flow

[0858] Example of checking the news

[0859] Step 1:

[0860] User: Say "Tell me the latest news." The user speaks into a tablet or smart device.

[0861] Step 2:

[0862] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[0863] Step 3:

[0864] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[0865] Step 4:

[0866] Server: Receives the voice data. The server confirms that the data has been received.

[0867] Step 5:

[0868] Server: Converts the voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data, such as "Tell me about the latest news."

[0869] Step 6:

[0870] Server: A natural language processing engine analyzes the text data and determines whether the user is looking for the latest news.

[0871] Step 7:

[0872] Server: Accesses the news information API to obtain the latest news data, makes an API request, and receives response data.

[0873] Step 8:

[0874] Server: Converts the acquired news data into a text format. For example, it creates text in the format "Today's main news is..."

[0875] Step 9:

[0876] Server: Converts text data into voice data using a speech synthesis engine. The synthesized voice data is generated as "Today's main news is..."

[0877] Step 10:

[0878] Server: Sends the generated voice data to the terminal. Confirms the data transmission.

[0879] Step 11:

[0880] Terminal: Receives audio data. Checks the received data and encodes it.

[0881] Step 12:

[0882] Device: Play audio data through the speaker. Output so that the user can hear "Today's main news is..."

[0883] Health status record example

[0884] Step 1:

[0885] User: Say "Record my health status today." The user speaks into a tablet or smart device.

[0886] Step 2:

[0887] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[0888] Step 3:

[0889] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[0890] Step 4:

[0891] Server: Receives the voice data. The server confirms that the data has been received.

[0892] Step 5:

[0893] Server: Converts voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data such as "Please record today's health condition."

[0894] Step 6:

[0895] Server: Analyzes the text data using a natural language processing engine and determines that the user wants to record their health status.

[0896] Step 7:

[0897] Server: Save the text data in a database. Save the message "Record your health condition today" as the user's health record.

[0898] Step 8:

[0899] Server: Based on the stored health data, it sends notifications to medical staff and family members as needed. For example, it sends a notification that "the user's health status has been updated."

[0900] In this way, specific operations are performed at each processing step, from user voice input to information acquisition and recording of health information.

[0901] Example 1

[0902] 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."

[0903] Currently, there are many systems that use voice to input, process, and output information, but most of them have limited functionality and are difficult to meet the diverse needs of users.In addition, there is a problem that a single system cannot meet the various needs, such as fast and accurate processing of voice data, management of health information, and acquisition of information from external sources.

[0904] 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.

[0905] In this invention, the server includes means for converting voice data into text data, means for analyzing the text data and acquiring information in response to a user request, and means for converting the acquired information into voice data, thereby enabling acquisition of a variety of information using voice input.

[0906] "Voice input" is a method in which a user inputs information using their voice.

[0907] "Voice data" means data that is a digital representation of a user's voice.

[0908] A "terminal" is a device that acquires voice data and transmits it to a server.

[0909] "Encoding" is the process of converting audio data into a format that is easier to process.

[0910] A "server" is a computer system that processes voice data and provides information in response to user requests.

[0911] "Text data" is data obtained by converting voice data into a character string format.

[0912] "Natural language processing" is a technology that analyzes text data and understands human language.

[0913] "Speech synthesis" is the process of converting text data into speech data.

[0914] "Notification information" is data used to notify other users or systems of important information.

[0915] "Health Information" is data relating to a user's health condition.

[0916] "External sources" are external databases or APIs that provide weather or news information.

[0917] "User" means a person who uses this system to input and obtain information.

[0918] MODE FOR CARRYING OUT THE INVENTION

[0919] The present invention provides a system that includes a means for users to input information by voice input, converts the acquired voice data into text data, analyzes it to acquire information, and then converts it back into voice data to provide.

[0920] Acquiring voice input

[0921] For example, a user might say, "Tell me the weather today." The device captures the user's voice through a microphone and converts it into digital audio data. This audio data is encoded in real time and sent to a server. Capturing and encoding uses commonly available hardware and software.

[0922] Audio data processing

[0923] The server receives the voice data sent from the device. It converts the voice data into text data using a speech recognition engine (for example, the Google Speech-to-Text API is generally available). The generated text data is then analyzed by a natural language processing engine (for example, OpenAI's GPT language model is generally used) to understand the user's request. This analysis may result in a decision to, for example, "provide weather information."

[0924] Acquiring information and converting it into audio data

[0925] Based on the request received from the user, the server accesses an external information source (e.g., a weather information API, typically the OpenWeatherMap API) to obtain the latest weather information. The obtained weather information is converted into voice data using a speech synthesis engine (e.g., typically Amazon Polly). Text data (e.g., "Today's weather is sunny") is converted into natural-sounding speech by a voice collection engine.

[0926] Providing audio data

[0927] The server sends the generated voice data to the device. The device receives the voice data and plays it back to the user through the built-in speaker. This allows the user to hear the information aloud, such as "Today's weather is sunny."

[0928] Health information management and notification

[0929] As another example, if a user says, "Record my health condition today," this voice data is also captured and sent to the server. The server uses a voice recognition engine to convert the voice data into text data, which is then analyzed and recorded as health information. The recorded health information is stored in a database, and notifications are sent to medical staff and family members as needed. These notifications include content such as, "Your health condition has been recorded. Please refer to the database for details."

[0930] Example prompt

[0931] Examples of generated AI prompts to parse user input:

[0932] Convert the following speech data into text and parse the request: 'What's the weather like today?'

[0933] Example of a generative AI prompt for recording health status:

[0934] Convert the following audio data into text and record the health information in a database: 'Record my health status today.'

[0935] This invention allows users to obtain various information by voice input and manage health information efficiently. In addition, the information can be promptly provided to users through fast and accurate information processing via the server.

[0936] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0937] Step 1:

[0938] The user says, "What's the weather today?" This initiates voice input. The device captures the user's voice through the built-in microphone and converts it into digital audio data. The input of this step is an audio signal, and the output is digital audio data. Specifically, the microphone device collects audio waveforms and encodes them into a digital format (e.g., PCM format).

[0939] Step 2:

[0940] The device encodes the captured digital audio data into an appropriate format in real time and sends it to the server. The input of this step is the digital audio data, and the output is the audio data sent to the server. The specific operation is a process of using the device's network interface to send the data to the server via the TCP / IP protocol, etc.

[0941] Step 3:

[0942] The server receives the voice data sent from the terminal. The received data is stored in temporary storage. The input of this step is the voice data sent to the server, and the output is the voice data stored in the temporary storage. The specific operation is the process of receiving data via the server's network interface and storing it in the storage system.

[0943] Step 4:

[0944] The server converts the voice data into text data using a voice recognition engine. A common voice recognition API (e.g., Google Speech-to-Text) can be used as the engine. The input for this step is the voice data stored in temporary storage, and the output is text data. The conversion process analyzes the voice waveform data and generates a corresponding string.

[0945] Step 5:

[0946] The server uses a natural language processing engine to analyze the text data and identify the user's request. Typically, an engine like OpenAI GPT can be used. The input for this step is the text data, and the output is the user's request. Specifically, this involves the process in which a natural language analysis algorithm analyzes the text and recognizes requests such as "provide weather information."

[0947] Step 6:

[0948] In response to a user request, the server accesses an external information source (e.g., a weather information API) to obtain the latest information. The input to this step is the user's request, and the output is the obtained information (e.g., a weather forecast). The specific operation is the process of sending an HTTP request to an API endpoint and receiving information as a response.

[0949] Step 7:

[0950] The server uses a speech synthesis engine (e.g., Amazon Polly) to convert the acquired information into speech data. The input of this step is the acquired text information, and the output is the generated speech data. Specifically, the synthesis engine analyzes the text and generates it as a speech waveform.

[0951] Step 8:

[0952] The server sends the generated voice data to the terminal. The input of this step is the generated voice data, and the output is the voice data sent to the terminal. The specific operation is the process of sending the voice data through the network interface of the server.

[0953] Step 9:

[0954] The terminal receives the audio data sent from the server and plays it using the built-in speaker. The input of this step is the received audio data, and the output is playing audio information to the user. Specifically, it includes an operation of outputting an audio waveform using the audio playback system of the terminal.

[0955] (Application example 1)

[0956] 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."

[0957] In traditional factories, production management and inventory status checks are often done manually, which can reduce work efficiency. It can also be difficult for workers to quickly obtain the information they need, resulting in communication delays. Efficiently managing and obtaining health and other daily information is also a challenge, and a system to address these issues is needed.

[0958] 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.

[0959] In this invention, the server includes a means for converting voice data into text data, a means for analyzing the text data and acquiring information in response to a user's request, and a means for converting the acquired information into voice data. This allows users to efficiently manage production and check inventory status within a factory through voice input. It also allows for the rapid acquisition and management of health information and other daily information, improving work efficiency and accelerating information sharing.

[0960] "User" means a person who uses the system to obtain information by voice input.

[0961] "Voice input" is a method of inputting information using voice data uttered by the user.

[0962] "Terminal means" is a device that captures audio data and transmits it to a server.

[0963] The "server means" is a device that processes data sent from a terminal and acquires information.

[0964] "Text data" is character information converted from voice data.

[0965] The "means for obtaining information" is a function for obtaining the information required by the user based on the analyzed text data.

[0966] The "means for converting into audio data" is a function for converting acquired information into audio format.

[0967] "A means for checking production management and inventory status within a factory by voice input" is a means for a user to check production management and inventory status within a factory by voice input.

[0968] "Health Information" is data relating to a user's health condition.

[0969] "Means for saving on a server" is a function for saving acquired information.

[0970] "Means of notification" is a function that sends information to users and related persons.

[0971] "News" refers to current events and information.

[0972] "Weather information" is data about the current weather and weather forecast.

[0973] This invention is a system that allows users to obtain information through voice input, and specific embodiments thereof are described below. The system converts voice data into text data and obtains and provides information in response to user requests. In particular, the present invention has a means for efficiently managing production and checking inventory status within a factory.

[0974] System Overview

[0975] 1. Acquiring voice input

[0976] The device is equipped with a microphone to capture user voice input: when a user says something like, "What is the current production line status?" or "What is the inventory status of part number 123?", the voice data is captured in real time.

[0977] 2. Audio data conversion

[0978] The acquired voice data is sent to the server, where it is converted into text data using a voice recognition engine called speech_recognition.

[0979] 3. Text data analysis and information acquisition

[0980] The server then uses a natural language processing engine to analyze the converted text data, understand the user's request, and executes API access or database queries to obtain information on the status of a production line or inventory, for example.

[0981] 4. Converting information into audio data

[0982] The acquired information is converted into voice data using the gtts (Google Text-to-Speech) library. In this process, text data (e.g., "The current production line is operating normally") is converted into natural-sounding speech.

[0983] 5. Playing audio data

[0984] The terminal receives the voice data sent from the server and plays it back to the user using the built-in speaker, allowing the user to obtain the necessary information by voice.

[0985] Specific examples

[0986] Factory production management

[0987] Imagine the following instructions being given in a factory:

[0988] Example instruction 1: "What is the status of the production line?"

[0989] → Robot replies: "The current production line is operating normally."

[0990] Example instruction 2: "What is the stock status of part number 123?"

[0991] → The robot responds: "We only have 20 units of part number 123 left in stock."

[0992] Prompt Sentence Examples

[0993] By inputting the following prompt sentence into the generative AI model, an appropriate response will be generated:

[0994] Example prompt: "Create a program that uses a voice interface to instruct a robot to check production management status and inventory status at the factory."

[0995] Hardware and software used

[0996] Hardware: Microphone, speaker, or robot with built-in microphone and speaker

[0997] Software: speech_recognition (speech recognition library), gtts (Google Text-to-Speech library), mpg321 (audio playback software)

[0998] In this way, the present invention provides a system that realizes efficient production management and inventory status confirmation within a factory, and quickly acquires and provides information through user voice input.

[0999] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1000] Step 1:

[1001] The device receives the user's voice input.

[1002] Input: User speech (e.g., "What's the status of the production line?").

[1003] What it does: Captures audio data using the device's microphone and encodes it in real time into a processable format.

[1004] Output: The encoded audio data.

[1005] Step 2:

[1006] The terminal transmits the acquired voice data to the server.

[1007] Input: Encoded audio data.

[1008] What it does: Sends encoded audio data over the network to a server.

[1009] Output: Audio data transferred to the server.

[1010] Step 3:

[1011] The server converts the voice data into text data.

[1012] Input: The transmitted audio data.

[1013] How it works: Converts audio data into text using the speech_recognition library.

[1014] Output: The converted text data (e.g., "What is the status of the production line?").

[1015] Step 4:

[1016] The server parses the text data and understands the request.

[1017] Input: Text data.

[1018] How it works: It uses a natural language processing engine to parse what the user is asking.

[1019] Output: The request (e.g., "Get the status of the production line").

[1020] Step 5:

[1021] The server retrieves information based on the user's request.

[1022] Input: Request content.

[1023] What it does: Accesses databases and APIs to get production line status and inventory status.

[1024] Output: The information obtained (e.g., "The current production line is operating normally.").

[1025] Step 6:

[1026] The server converts the acquired information into audio data.

[1027] Input: The information obtained.

[1028] Operation: Converts text data into audio data using the gtts library.

[1029] Output: The generated audio data.

[1030] Step 7:

[1031] The terminal receives and plays back the audio data transmitted from the server.

[1032] Input: The generated audio data.

[1033] What it does: Receives audio data over the network and plays it back to the user using the built-in speaker.

[1034] Output: A spoken response to the user (e.g., "The current production line is operating normally.").

[1035] 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.

[1036] The present invention is a system that includes a means for a user to input information by voice input, a terminal means for acquiring voice data from the user, a server means for converting the acquired voice data into text data, a means for analyzing the text data and acquiring information in response to a user request, a server means for converting the acquired information into voice data, and a terminal means for playing the voice data back to the user. Furthermore, it is combined with an emotion engine that recognizes emotions from the user's voice data. The detailed operation of this system is described below.

[1037] User voice input

[1038] For example, a user might say, "Tell me today's news." This speech is captured through the microphone of the device (e.g., a tablet or smart device). The device encodes the captured voice data in real time, converts it into a binary format, and sends it to the server.

[1039] Analyzing voice data and obtaining information

[1040] The server receives the voice data sent from the device. It uses a voice recognition engine to convert the received voice data into text data. It then uses a natural language processing engine to analyze the text data and understand the user's request. In this example, it determines that the user is requesting "news delivery."

[1041] Next, the server accesses the news information API to obtain the latest news data, makes an API request, and receives response data.

[1042] Converting acquired information into audio data and playing it back

[1043] The server converts the acquired news data into text format, then uses a speech synthesis engine to convert this text data into voice data, which is then sent to the terminal in voice data format.

[1044] The device receives the audio data sent from the server and plays it back to the user using the built-in speaker. The user can hear information such as "Today's news is..."

[1045] Recognizing and responding to user emotions

[1046] The server simultaneously analyzes the user's emotions using an emotion engine while recognizing the voice. For example, if the user speaks in a "tired voice," the emotion engine will recognize this as "fatigue."

[1047] Based on the results of emotion recognition, the server will adjust its response, for example, if the user is tired, it will add a thoughtful comment such as "Here's the latest news. Please take it easy today."

[1048] If necessary, the recognized emotional information can be notified to medical staff or family members. In this case, the server can send an alert saying, "The user seems tired."

[1049] Recording and Notification of Health Information

[1050] Similarly, if the user says, "Record my health condition today," the device captures the voice and sends it to the server. The server then converts the text data using a speech recognition engine, analyzes it, and records it as health information. It also uses an emotion engine to recognize the user's emotions and notify medical staff or family members as necessary.

[1051] Specific examples

[1052] For example, if a user says, "I'm very tired right now," the device captures this speech and sends the data to the server. The server then converts it into text data using a speech recognition engine and analyzes the meaning of "tired." At the same time, the emotion engine recognizes the "feeling of fatigue" and generates voice data in a gentle tone saying, "Please take a rest," which is then sent to the user via the device. The server then sends notifications to medical staff and family members depending on the situation.

[1053] In this way, this system enables two-way communication using voice and emotions, and can better understand and respond to the user's needs, providing comprehensive support for the elderly and those requiring care to live their daily lives with peace of mind.

[1054] The processing flow will be explained below.

[1055] News confirmation and emotion recognition processing flow

[1056] Step 1:

[1057] User: Say "Tell me the latest news." The user speaks into a tablet or smart device.

[1058] Step 2:

[1059] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[1060] Step 3:

[1061] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[1062] Step 4:

[1063] Server: Receives the voice data. The server confirms that the data has been received.

[1064] Step 5:

[1065] Server: Converts the voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data, such as "Tell me about the latest news."

[1066] Step 6:

[1067] Server: A natural language processing engine analyzes the text data and determines whether the user is looking for the latest news.

[1068] Step 7:

[1069] Server: Accesses the news information API to obtain the latest news data, makes an API request, and receives response data.

[1070] Step 8:

[1071] Server: Converts the acquired news data into a text format. For example, it creates text in the format "Today's main news is..."

[1072] Step 9:

[1073] Server: Converts text data into voice data using a speech synthesis engine. The synthesized voice data is generated as "Today's main news is..."

[1074] Step 10:

[1075] Server: Sends the generated voice data to the terminal. Confirms the data transmission.

[1076] Step 11:

[1077] Terminal: Receives audio data. Checks the received data and encodes it.

[1078] Step 12:

[1079] Device: Play audio data through the speaker. Output so that the user can hear "Today's main news is..."

[1080] Health status recording and emotion recognition process

[1081] Step 1:

[1082] User: Say "Record my health status today." The user speaks into a tablet or smart device.

[1083] Step 2:

[1084] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[1085] Step 3:

[1086] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[1087] Step 4:

[1088] Server: Receives the voice data. The server confirms that the data has been received.

[1089] Step 5:

[1090] Server: Converts voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data such as "Please record today's health condition."

[1091] Step 6:

[1092] Server: Analyzes the text data using a natural language processing engine and determines that the user wants to record their health status.

[1093] Step 7:

[1094] Server: Save the text data in a database. Save the message "Record your health condition today" as the user's health record.

[1095] Step 8:

[1096] Server: Analyzes the user's emotions using an emotion engine based on the stored health information. For example, if the user says "I'm tired," the emotion engine will recognize this as "fatigue."

[1097] Step 9:

[1098] Server: Adjust the response based on the emotion engine's recognition results. For example, if the user is tired, add a message saying "Take a good rest."

[1099] Step 10:

[1100] Server: Convert the response message into voice data. Using a voice synthesis engine, generate the voice data "Please take a good rest."

[1101] Step 11:

[1102] Server: Sends the generated voice data to the terminal. Confirms the data transmission.

[1103] Step 12:

[1104] Terminal: Receives and encodes audio data.

[1105] Step 13:

[1106] Device: Plays audio data through the speaker, outputting "Please take a good rest" so that the user can hear it.

[1107] Step 14:

[1108] Server: Notifies medical staff or family members of the recognized emotion information, for example, by sending an alert saying, "The user seems tired."

[1109] In this way, a system that combines an emotion engine can perform a series of processes, from acquiring information from the user's voice input to responding while taking into account the user's emotional state.

[1110] Example 2

[1111] 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."

[1112] Conventional voice assistant systems mainly respond simply to the user's voice input, and lack the ability to appropriately recognize the user's emotions and health status and adjust responses accordingly. In particular, there is a lack of comprehensive support for the elderly and those requiring care to live their daily lives with peace of mind.

[1113] 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.

[1114] In this invention, the server includes: means for a user to input information by voice input; terminal means for acquiring voice data from the user; server means for converting the acquired voice data into text data; means for analyzing the text data and acquiring information according to the user's request; server means for converting the acquired information into voice data; terminal means for playing the voice data back to the user; server means including an emotion engine for recognizing emotions from the user's voice data; and means for adjusting response content based on the results of emotion recognition. This makes it possible to provide appropriate responses that take into account the user's emotions and health condition, enabling comprehensive support to enable the elderly and those requiring care to live their daily lives with peace of mind.

[1115] "Voice input" is a means by which a user inputs information as voice.

[1116] A "terminal" is a device that acquires voice data from a user and transmits it to a server.

[1117] A "server" is a device that converts acquired voice data into text data, analyzes and acquires information, and responds to the user.

[1118] A "voice recognition engine" is software for converting voice data into text data.

[1119] A "natural language processing engine" is software that analyzes text data and understands user requests.

[1120] "Information acquisition means" refers to a means for acquiring information from an external information source in response to a user request.

[1121] A "speech synthesis engine" is software for converting text data into voice data.

[1122] The "emotion engine" is software that recognizes emotions from the user's voice data.

[1123] The "response content adjustment means" is a means for adjusting the response content based on the result of emotion recognition.

[1124] "Health Information" means information relating to a user's health condition.

[1125] "Means of notification" refers to the means of notifying medical staff and family members of information as necessary.

[1126] "News Information API" is an external API that obtains the latest news information.

[1127] "Voice data" refers to data in which the user's voice is encoded as a digital signal.

[1128] "Text data" refers to character data obtained by converting voice data.

[1129] The present invention is a system in which a user inputs information by voice, and includes the following components: Through this system, the user is supported in obtaining daily information and managing their health.

[1130] User voice input

[1131] For example, a user may say, "Tell me today's news." The user's voice input is captured through the microphone of the device (e.g., tablet or smart device). The device converts the captured voice into a digital signal, encodes the voice data into a binary format, and then sends it to the server.

[1132] Receiving and converting audio data

[1133] The server receives the voice data sent from the device and converts it into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text API).The server then analyzes the text using a natural language processing engine (e.g., IBM Watson NLU) to understand the user's request.

[1134] Obtaining information

[1135] In response to a user request, the server accesses a news information API (e.g., NewsAPI) to obtain the latest news data. If the user wishes to record their health status, the server similarly converts the voice to text and records and saves it as health information.

[1136] Converting acquired information into audio data

[1137] The server uses a speech synthesis engine (e.g., Amazon Polly) to convert the acquired news data into audio data, which is then sent to the device and played back to the user.

[1138] Recognizing and responding to user emotions

[1139] The server uses an emotion engine (e.g., Affectiva) to simultaneously recognize the voice and analyze the user's emotions. For example, if the server determines that the user sounds tired, it adjusts the response and provides a thoughtful comment such as "Please take a rest" in a gentle tone. In some cases, it may also notify medical staff or family members.

[1140] Specific examples

[1141] For example, if a user says, "I'm very tired right now," the device captures this voice, converts it into a digital signal, and sends it to the server. The server then uses a speech recognition engine to convert the voice data into text data and analyzes the meaning of "tired." At the same time, the emotion engine recognizes the "feeling of fatigue." The server then generates voice data in a gentle tone saying, "Please take a rest," and sends it to the device. The device then plays this voice data to the user. Additionally, it may send notifications to medical staff or family members depending on the situation.

[1142] Examples of prompt statements

[1143] "A user says they want to know today's news. How does the system respond?"

[1144] “If a user says they are tired, what sentiment analysis does the system perform and how does it respond?”

[1145] "Please explain the process your system goes through to record the user's health status."

[1146] In this way, the present invention uses a system that combines voice recognition, natural language processing, and emotion analysis, enabling responses that are adapted to the diverse needs of users and providing comprehensive support, particularly for the elderly and those requiring care.

[1147] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1148] Step 1:

[1149] For example, a user might say, "Tell me today's news." This speech is captured through the device's microphone. The device converts the speech into a digital signal and encodes the speech data into a binary format. The input is the user's speech, and the output is the encoded speech data. The device then sends the encoded speech data to the server.

[1150] Step 2:

[1151] The server receives the voice data sent from the terminal. The input is encoded voice data. The server uses a voice recognition engine to convert the received voice data into text data. The output at this stage is text data. General voice recognition software is used as the voice recognition engine.

[1152] Step 3:

[1153] The server uses a natural language processing engine to analyze the text data and understand the user's request. The input is text data, and the output is the analyzed user request. Specifically, the server determines that the text data requests "provision of news." This allows the server to proceed to the next information acquisition step.

[1154] Step 4:

[1155] The server queries external information sources in response to user requests. The input is the parsed request content. The server accesses the news information API and sends an API request. As a result, it receives the latest news data. The output is the news data.

[1156] Step 5:

[1157] The server formats the acquired news data into text format. The input is news data, and the output is formatted text data. Furthermore, a speech synthesis engine is used to convert the formatted text data into voice data. The output is converted voice data.

[1158] Step 6:

[1159] The server sends the converted audio data to the device. The device decodes the received audio data and plays it back to the user through the built-in speaker. The input is the converted audio data, and the output is the audio playback. The user can hear information such as "Today's news is..." by voice.

[1160] Step 7:

[1161] The server simultaneously recognizes the voice and uses an emotion engine to analyze the user's emotions. The input is voice data, and the output is analyzed emotion information. For example, if the user's voice is judged to sound tired, the emotion engine will recognize "fatigue."

[1162] Step 8:

[1163] The server adjusts the response content based on the emotion recognition results. The input is the analyzed emotion information, and the output is the adjusted response content. For example, if the user is tired, a thoughtful comment such as "Here's the latest news. Please take it easy today and don't push yourself too hard" is added to the voice data.

[1164] Step 9:

[1165] If necessary, the server notifies medical staff or family members of the recognized emotion information. The input is the analyzed emotion information, and the output is the notification content. For example, it sends a message saying, "The user seems tired."

[1166] Step 10:

[1167] Similarly, when a user says, "Record my health condition today," the device captures the voice and sends it to the server. The server uses a voice recognition engine to convert the voice data into text data, analyzes it, and records it as health information. The input is voice data, and the output is the recorded health data. The emotion engine also recognizes the user's emotions.

[1168] (Application example 2)

[1169] 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."

[1170] In conventional factory robot systems, it was difficult to accurately recognize voice instructions from workers and quickly and accurately execute those instructions. Furthermore, systems that could grasp the emotional state of workers and respond accordingly were not sufficiently developed. As a result, it was not possible to improve worker stress management or work efficiency. Furthermore, if a worker was fatigued or stressed, not taking appropriate action could lead to a decrease in work safety.

[1171] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1172] In this invention, the server includes a means for acquiring voice data and converting it into text data, a means for acquiring information in response to a user request, a means for converting the acquired information into voice data, a means including an emotion engine for analyzing the voice data and recognizing the user's emotion, and a means for adjusting the response content in accordance with the recognized emotion. This enables prompt and accurate execution of voice-input instructions and appropriate responses according to the worker's emotional state, contributing to improved work efficiency and ensuring safety.

[1173] "User" refers to a person who uses the system to provide information by voice input.

[1174] "Voice input" refers to a user speaking through a voice capture device such as a microphone.

[1175] "Terminal" refers to the device that receives voice data from the user and transmits it to the server.

[1176] "Voice Data" means information that is a digital representation of the voice uttered by a User.

[1177] "Text data" refers to data in a format in which voice data has been converted into text.

[1178] The term "server" refers to a device that processes acquired voice data, converts it into text data, and further analyzes the text data to acquire information.

[1179] An "emotion engine" refers to software or a system that analyzes a user's emotions from voice data and expresses them as digital data.

[1180] "Means of obtaining information" refers to the process of obtaining the necessary information from external APIs or databases based on user requests.

[1181] "Means for adjusting response content" refers to the ability to appropriately change the information provided or the content of responses based on the user's emotional state.

[1182] "News information" refers to information about current events and important topics.

[1183] "Medical staff" refers to professionals who manage users' health information.

[1184] "Family Member" refers to individuals who have a close relationship with the User.

[1185] MODE FOR CARRYING OUT THE INVENTION

[1186] This invention is a system that utilizes voice input and emotion recognition to improve the efficiency of factory work and enable responses according to the emotional state of workers. Specific embodiments of this system are described below.

[1187] Hardware and Software Configuration

[1188] The system utilizes the following hardware and software:

[1189] Hardware: microphones, speakers, factory robots.

[1190] Software: speech_recognition, robot_controller, text_to_speech, emotion_recognition, alert_system.

[1191] Acquiring and converting audio data

[1192] The user inputs commands such as "move the part" by voice through a microphone. The device captures the voice data, encodes it in real time, and sends it to the server. The server then converts the voice data into text data using the speech_recognition engine.

[1193] Text data analysis and response

[1194] The server analyzes the received text data and understands the user's request. For example, it may obtain an instruction such as "move a part" as a result of the analysis. Then, it uses the robot_controller to send a command to the factory robot to perform the requested action.

[1195] Emotion recognition and response regulation

[1196] At the same time, the server uses emotion_recognition to analyze emotions from the user's voice data. If the user speaks in a tired voice, the emotion engine detects "fatigue." In this case, to adjust the response, it uses alert_system to generate a message such as "Please take a break," converts it into voice data, and plays it back to the user through the device. The text_to_speech engine converts the text generated by the server into voice data.

[1197] Acquisition and provision of information

[1198] When a user makes a voice request such as "Tell me today's news," the server similarly converts the voice data into text data and determines that the request is for news. Next, the server accesses the news information API to obtain the latest news data, converts it into voice data using the text_to_speech engine, and provides it to the user via the device.

[1199] Specific examples

[1200] For example, if a user utters a prompt phrase such as "Please move the part," the system will analyze it and give specific movement instructions to a factory robot. If a worker says, "I'm very tired right now," the system will analyze the voice, recognize the emotion, and generate and play an alert saying, "Please take a break."

[1201] Example prompt sentence:

[1202] Please move the parts.

[1203] "Do you think you need a break?"

[1204] "Please stop what you're doing now."

[1205] The above is a specific embodiment for carrying out the present invention. This invention enables operation by voice input and realizes responses according to the emotional state. This improves work efficiency and ensures the safety of the worker.

[1206] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1207] Step 1:

[1208] The user inputs information through voice input. Input: The user gives a voice command (e.g., "move the part"). To perform a specific action, the user speaks the command into the microphone.

[1209] Step 2:

[1210] The device receives voice data from the user. Input: User's voice. Output: Digital voice data. Specifically, the microphone captures the voice and encodes the voice data.

[1211] Step 3:

[1212] The device transmits the encoded voice data to the server in real time. Input: Digital voice data. Output: Voice data transmitted to the server. Specifically, the device transmits the voice data to the server via the network.

[1213] Step 4:

[1214] The server converts the received voice data into text data using a speech recognition engine. Input: Voice data. Output: Text data (e.g., "Move the part"). Specifically, the server starts the speech_recognition engine and converts the voice data into text.

[1215] Step 5:

[1216] The server analyzes the text data to understand the user's request. Input: Text data. Output: Request content (e.g., "Move the part"). Specifically, the server uses a natural language processing engine to analyze the text data and extract the request content.

[1217] Step 6:

[1218] The server generates instructions for the factory robot based on the request and controls the robot. Input: Request. Output: Robot control command. For specific operations, the server uses robot_controller to generate commands that instruct the specific robot operations and sends them to the robot.

[1219] Step 7:

[1220] The server simultaneously recognizes the user's emotions from the voice data. Input: Voice data. Output: Emotion data (e.g., "fatigue"). Specifically, the server uses the emotion_recognition engine to analyze the voice data and detect the user's emotional state.

[1221] Step 8:

[1222] The server adjusts the response content based on the emotion recognition results. Input: Emotion data, request content. Output: Adjusted response message (e.g., "Move the parts. Please take a break."). Specifically, the server generates an additional message depending on the emotion recognition results.

[1223] Step 9:

[1224] The server converts the tailored response message from text to audio data and sends it to the device. Input: Tailored response message. Output: Audio data. Specifically, the server uses the text_to_speech engine to convert the text message into audio data and then sends it to the device.

[1225] Step 10:

[1226] The device plays the received audio data to the user. Input: Audio data. Output: Audio response to the user. Specifically, the device uses a speaker to play the audio data to the user.

[1227] Through the above steps, the factory robot operates based on the user's voice input and provides an appropriate response according to the user's emotional state.

[1228] 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.

[1229] 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.

[1230] 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.

[1231] [Fourth embodiment]

[1232] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1233] 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.

[1234] 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).

[1235] 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.

[1236] 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.

[1237] 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).

[1238] 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.

[1239] 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.

[1240] 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.

[1241] 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.

[1242] 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.

[1243] 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.

[1244] 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."

[1245] The present invention is a system including a means for a user to input information by voice input, a terminal means for acquiring voice data from the user, a server means for converting the acquired voice data into text data, a means for analyzing the text data and acquiring information in response to a user request, a server means for converting the acquired information into voice data, and a terminal means for playing the voice data back to the user. The operation of the system will be specifically described below.

[1246] User voice input

[1247] For example, a user might say, "Tell me the weather today." This speech is captured through the microphone of the device (e.g., a tablet or smart device). The device encodes the captured voice data into a processable format in real time and then sends it to the server.

[1248] Analyzing voice data and obtaining information

[1249] The server receives the voice data sent from the device. The server uses a voice recognition engine to convert the received voice data into text data. It then uses a natural language processing engine to analyze the text data and understand the user's request. In this example, it determines that the request is to "provide weather information."

[1250] The server then accesses the weather API to retrieve the latest weather information, identifying relevant weather information based on the user's location and preferences.

[1251] Converting acquired information into audio data and playing it back

[1252] The server uses a speech synthesis engine to convert the acquired weather information into voice data. The speech synthesis engine converts text data (e.g., "Today's weather is sunny") into natural-sounding voice and sends it to the terminal in the form of voice data.

[1253] The device receives the voice data sent from the server and plays it back to the user using the built-in speaker, allowing the user to hear the information "Today's weather is sunny."

[1254] Management and sharing of health information

[1255] As another example, consider the case where a user says, "Record my health status today." The device captures the voice data and sends it to the server. The server uses a speech recognition engine to convert the voice data into text data and record the user's health status.

[1256] The server stores the recorded health information in a database and sends notifications to medical staff or family members as needed, such as "Your health condition has been recorded. Please refer to the database for details."

[1257] This system allows users to obtain information and manage their health status using only their voice. In addition, it allows for quick sharing of information with medical staff and family members, helping to support users' safety and security. News and other daily information can also be provided in the same way, improving the user's quality of life.

[1258] The processing flow will be explained below.

[1259] Program processing flow

[1260] Example of checking the news

[1261] Step 1:

[1262] User: Say "Tell me the latest news." The user speaks into a tablet or smart device.

[1263] Step 2:

[1264] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[1265] Step 3:

[1266] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[1267] Step 4:

[1268] Server: Receives the voice data. The server confirms that the data has been received.

[1269] Step 5:

[1270] Server: Converts the voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data, such as "Tell me about the latest news."

[1271] Step 6:

[1272] Server: A natural language processing engine analyzes the text data and determines whether the user is looking for the latest news.

[1273] Step 7:

[1274] Server: Accesses the news information API to obtain the latest news data, makes an API request, and receives response data.

[1275] Step 8:

[1276] Server: Converts the acquired news data into a text format. For example, it creates text in the format "Today's main news is..."

[1277] Step 9:

[1278] Server: Converts text data into voice data using a speech synthesis engine. The synthesized voice data is generated as "Today's main news is..."

[1279] Step 10:

[1280] Server: Sends the generated voice data to the terminal. Confirms the data transmission.

[1281] Step 11:

[1282] Terminal: Receives audio data. Checks the received data and encodes it.

[1283] Step 12:

[1284] Device: Play audio data through the speaker. Output so that the user can hear "Today's main news is..."

[1285] Health status record example

[1286] Step 1:

[1287] User: Say "Record my health status today." The user speaks into a tablet or smart device.

[1288] Step 2:

[1289] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[1290] Step 3:

[1291] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[1292] Step 4:

[1293] Server: Receives the voice data. The server confirms that the data has been received.

[1294] Step 5:

[1295] Server: Converts voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data such as "Please record today's health condition."

[1296] Step 6:

[1297] Server: Analyzes the text data using a natural language processing engine and determines that the user wants to record their health status.

[1298] Step 7:

[1299] Server: Save the text data in a database. Save the message "Record your health condition today" as the user's health record.

[1300] Step 8:

[1301] Server: Based on the stored health data, it sends notifications to medical staff and family members as needed. For example, it sends a notification that "the user's health status has been updated."

[1302] In this way, specific operations are performed at each processing step, from user voice input to information acquisition and recording of health information.

[1303] Example 1

[1304] 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."

[1305] Currently, there are many systems that use voice to input, process, and output information, but most of them have limited functionality and are difficult to meet the diverse needs of users.In addition, there is a problem that a single system cannot meet the various needs, such as fast and accurate processing of voice data, management of health information, and acquisition of information from external sources.

[1306] 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.

[1307] In this invention, the server includes means for converting voice data into text data, means for analyzing the text data and acquiring information in response to a user request, and means for converting the acquired information into voice data, thereby enabling acquisition of a variety of information using voice input.

[1308] "Voice input" is a method in which a user inputs information using their voice.

[1309] "Voice data" means data that is a digital representation of a user's voice.

[1310] A "terminal" is a device that acquires voice data and transmits it to a server.

[1311] "Encoding" is the process of converting audio data into a format that is easier to process.

[1312] A "server" is a computer system that processes voice data and provides information in response to user requests.

[1313] "Text data" is data obtained by converting voice data into a character string format.

[1314] "Natural language processing" is a technology that analyzes text data and understands human language.

[1315] "Speech synthesis" is the process of converting text data into speech data.

[1316] "Notification information" is data used to notify other users or systems of important information.

[1317] "Health Information" is data relating to a user's health condition.

[1318] "External sources" are external databases or APIs that provide weather or news information.

[1319] "User" means a person who uses this system to input and obtain information.

[1320] MODE FOR CARRYING OUT THE INVENTION

[1321] The present invention provides a system that includes a means for users to input information by voice input, converts the acquired voice data into text data, analyzes it to acquire information, and then converts it back into voice data to provide.

[1322] Acquiring voice input

[1323] For example, a user might say, "Tell me the weather today." The device captures the user's voice through a microphone and converts it into digital audio data. This audio data is encoded in real time and sent to a server. Capturing and encoding uses commonly available hardware and software.

[1324] Audio data processing

[1325] The server receives the voice data sent from the device. It converts the voice data into text data using a speech recognition engine (for example, the Google Speech-to-Text API is generally available). The generated text data is then analyzed by a natural language processing engine (for example, OpenAI's GPT language model is generally used) to understand the user's request. This analysis may result in a decision to, for example, "provide weather information."

[1326] Acquiring information and converting it into audio data

[1327] Based on the request received from the user, the server accesses an external information source (e.g., a weather information API, typically the OpenWeatherMap API) to obtain the latest weather information. The obtained weather information is converted into voice data using a speech synthesis engine (e.g., typically Amazon Polly). Text data (e.g., "Today's weather is sunny") is converted into natural-sounding speech by a voice collection engine.

[1328] Providing audio data

[1329] The server sends the generated voice data to the device. The device receives the voice data and plays it back to the user through the built-in speaker. This allows the user to hear the information aloud, such as "Today's weather is sunny."

[1330] Health information management and notification

[1331] As another example, if a user says, "Record my health condition today," this voice data is also captured and sent to the server. The server uses a voice recognition engine to convert the voice data into text data, which is then analyzed and recorded as health information. The recorded health information is stored in a database, and notifications are sent to medical staff and family members as needed. These notifications include content such as, "Your health condition has been recorded. Please refer to the database for details."

[1332] Example prompt

[1333] Examples of generated AI prompts to parse user input:

[1334] Convert the following speech data into text and parse the request: 'What's the weather like today?'

[1335] Example of a generative AI prompt for recording health status:

[1336] Convert the following audio data into text and record the health information in a database: 'Record my health status today.'

[1337] This invention allows users to obtain various information by voice input and manage health information efficiently. In addition, the information can be promptly provided to users through fast and accurate information processing via the server.

[1338] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1339] Step 1:

[1340] The user says, "What's the weather today?" This initiates voice input. The device captures the user's voice through the built-in microphone and converts it into digital audio data. The input of this step is an audio signal, and the output is digital audio data. Specifically, the microphone device collects audio waveforms and encodes them into a digital format (e.g., PCM format).

[1341] Step 2:

[1342] The device encodes the captured digital audio data into an appropriate format in real time and sends it to the server. The input of this step is the digital audio data, and the output is the audio data sent to the server. The specific operation is a process of using the device's network interface to send the data to the server via the TCP / IP protocol, etc.

[1343] Step 3:

[1344] The server receives the voice data sent from the terminal. The received data is stored in temporary storage. The input of this step is the voice data sent to the server, and the output is the voice data stored in the temporary storage. The specific operation is the process of receiving data via the server's network interface and storing it in the storage system.

[1345] Step 4:

[1346] The server converts the voice data into text data using a voice recognition engine. A common voice recognition API (e.g., Google Speech-to-Text) can be used as the engine. The input for this step is the voice data stored in temporary storage, and the output is text data. The conversion process analyzes the voice waveform data and generates a corresponding string.

[1347] Step 5:

[1348] The server uses a natural language processing engine to analyze the text data and identify the user's request. Typically, an engine like OpenAI GPT can be used. The input for this step is the text data, and the output is the user's request. Specifically, this involves the process in which a natural language analysis algorithm analyzes the text and recognizes requests such as "provide weather information."

[1349] Step 6:

[1350] In response to a user request, the server accesses an external information source (e.g., a weather information API) to obtain the latest information. The input to this step is the user's request, and the output is the obtained information (e.g., a weather forecast). The specific operation is the process of sending an HTTP request to an API endpoint and receiving information as a response.

[1351] Step 7:

[1352] The server uses a speech synthesis engine (e.g., Amazon Polly) to convert the acquired information into speech data. The input of this step is the acquired text information, and the output is the generated speech data. Specifically, the synthesis engine analyzes the text and generates it as a speech waveform.

[1353] Step 8:

[1354] The server sends the generated voice data to the terminal. The input of this step is the generated voice data, and the output is the voice data sent to the terminal. The specific operation is the process of sending the voice data through the network interface of the server.

[1355] Step 9:

[1356] The terminal receives the audio data sent from the server and plays it using the built-in speaker. The input of this step is the received audio data, and the output is playing audio information to the user. Specifically, it includes an operation of outputting an audio waveform using the audio playback system of the terminal.

[1357] (Application example 1)

[1358] 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."

[1359] In traditional factories, production management and inventory status checks are often done manually, which can reduce work efficiency. It can also be difficult for workers to quickly obtain the information they need, resulting in communication delays. Efficiently managing and obtaining health and other daily information is also a challenge, and a system to address these issues is needed.

[1360] 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.

[1361] In this invention, the server includes a means for converting voice data into text data, a means for analyzing the text data and acquiring information in response to a user's request, and a means for converting the acquired information into voice data. This allows users to efficiently manage production and check inventory status within a factory through voice input. It also allows for the rapid acquisition and management of health information and other daily information, improving work efficiency and accelerating information sharing.

[1362] "User" means a person who uses the system to obtain information by voice input.

[1363] "Voice input" is a method of inputting information using voice data uttered by the user.

[1364] "Terminal means" is a device that captures audio data and transmits it to a server.

[1365] The "server means" is a device that processes data sent from a terminal and acquires information.

[1366] "Text data" is character information converted from voice data.

[1367] The "means for obtaining information" is a function for obtaining the information required by the user based on the analyzed text data.

[1368] The "means for converting into audio data" is a function for converting acquired information into audio format.

[1369] "A means for checking production management and inventory status within a factory by voice input" is a means for a user to check production management and inventory status within a factory by voice input.

[1370] "Health Information" is data relating to a user's health condition.

[1371] "Means for saving on a server" is a function for saving acquired information.

[1372] "Means of notification" is a function that sends information to users and related persons.

[1373] "News" refers to current events and information.

[1374] "Weather information" is data about the current weather and weather forecast.

[1375] This invention is a system that allows users to obtain information through voice input, and specific embodiments thereof are described below. The system converts voice data into text data and obtains and provides information in response to user requests. In particular, the present invention has a means for efficiently managing production and checking inventory status within a factory.

[1376] System Overview

[1377] 1. Acquiring voice input

[1378] The device is equipped with a microphone to capture user voice input: when a user says something like, "What is the current production line status?" or "What is the inventory status of part number 123?", the voice data is captured in real time.

[1379] 2. Audio data conversion

[1380] The acquired voice data is sent to the server, where it is converted into text data using a voice recognition engine called speech_recognition.

[1381] 3. Text data analysis and information acquisition

[1382] The server then uses a natural language processing engine to analyze the converted text data, understand the user's request, and executes API access or database queries to obtain information on the status of a production line or inventory, for example.

[1383] 4. Converting information into audio data

[1384] The acquired information is converted into voice data using the gtts (Google Text-to-Speech) library. In this process, text data (e.g., "The current production line is operating normally") is converted into natural-sounding speech.

[1385] 5. Playing audio data

[1386] The terminal receives the voice data sent from the server and plays it back to the user using the built-in speaker, allowing the user to obtain the necessary information by voice.

[1387] Specific examples

[1388] Factory production management

[1389] Imagine the following instructions being given in a factory:

[1390] Example instruction 1: "What is the status of the production line?"

[1391] → Robot replies: "The current production line is operating normally."

[1392] Example instruction 2: "What is the stock status of part number 123?"

[1393] → The robot responds: "We only have 20 units of part number 123 left in stock."

[1394] Prompt Sentence Examples

[1395] By inputting the following prompt sentence into the generative AI model, an appropriate response will be generated:

[1396] Example prompt: "Create a program that uses a voice interface to instruct a robot to check production management status and inventory status at the factory."

[1397] Hardware and software used

[1398] Hardware: Microphone, speaker, or robot with built-in microphone and speaker

[1399] Software: speech_recognition (speech recognition library), gtts (Google Text-to-Speech library), mpg321 (audio playback software)

[1400] In this way, the present invention provides a system that realizes efficient production management and inventory status confirmation within a factory, and quickly acquires and provides information through user voice input.

[1401] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1402] Step 1:

[1403] The device receives the user's voice input.

[1404] Input: User speech (e.g., "What's the status of the production line?").

[1405] What it does: Captures audio data using the device's microphone and encodes it in real time into a processable format.

[1406] Output: The encoded audio data.

[1407] Step 2:

[1408] The terminal transmits the acquired voice data to the server.

[1409] Input: Encoded audio data.

[1410] What it does: Sends encoded audio data over the network to a server.

[1411] Output: Audio data transferred to the server.

[1412] Step 3:

[1413] The server converts the voice data into text data.

[1414] Input: The transmitted audio data.

[1415] How it works: Converts audio data into text using the speech_recognition library.

[1416] Output: The converted text data (e.g., "What is the status of the production line?").

[1417] Step 4:

[1418] The server parses the text data and understands the request.

[1419] Input: Text data.

[1420] How it works: It uses a natural language processing engine to parse what the user is asking.

[1421] Output: The request (e.g., "Get the status of the production line").

[1422] Step 5:

[1423] The server retrieves information based on the user's request.

[1424] Input: Request content.

[1425] What it does: Accesses databases and APIs to get production line status and inventory status.

[1426] Output: The information obtained (e.g., "The current production line is operating normally.").

[1427] Step 6:

[1428] The server converts the acquired information into audio data.

[1429] Input: The information obtained.

[1430] Operation: Converts text data into audio data using the gtts library.

[1431] Output: The generated audio data.

[1432] Step 7:

[1433] The terminal receives and plays back the audio data transmitted from the server.

[1434] Input: The generated audio data.

[1435] What it does: Receives audio data over the network and plays it back to the user using the built-in speaker.

[1436] Output: A spoken response to the user (e.g., "The current production line is operating normally.").

[1437] 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.

[1438] The present invention is a system that includes a means for a user to input information by voice input, a terminal means for acquiring voice data from the user, a server means for converting the acquired voice data into text data, a means for analyzing the text data and acquiring information in response to a user request, a server means for converting the acquired information into voice data, and a terminal means for playing the voice data back to the user. Furthermore, it is combined with an emotion engine that recognizes emotions from the user's voice data. The detailed operation of this system is described below.

[1439] User voice input

[1440] For example, a user might say, "Tell me today's news." This speech is captured through the microphone of the device (e.g., a tablet or smart device). The device encodes the captured voice data in real time, converts it into a binary format, and sends it to the server.

[1441] Analyzing voice data and obtaining information

[1442] The server receives the voice data sent from the device. It uses a voice recognition engine to convert the received voice data into text data. It then uses a natural language processing engine to analyze the text data and understand the user's request. In this example, it determines that the user is requesting "news delivery."

[1443] Next, the server accesses the news information API to obtain the latest news data, makes an API request, and receives response data.

[1444] Converting acquired information into audio data and playing it back

[1445] The server converts the acquired news data into text format, then uses a speech synthesis engine to convert this text data into voice data, which is then sent to the terminal in voice data format.

[1446] The device receives the audio data sent from the server and plays it back to the user using the built-in speaker. The user can hear information such as "Today's news is..."

[1447] Recognizing and responding to user emotions

[1448] The server simultaneously analyzes the user's emotions using an emotion engine while recognizing the voice. For example, if the user speaks in a "tired voice," the emotion engine will recognize this as "fatigue."

[1449] Based on the results of emotion recognition, the server will adjust its response, for example, if the user is tired, it will add a thoughtful comment such as "Here's the latest news. Please take it easy today."

[1450] If necessary, the recognized emotional information can be notified to medical staff or family members. In this case, the server can send an alert saying, "The user seems tired."

[1451] Recording and Notification of Health Information

[1452] Similarly, if the user says, "Record my health condition today," the device captures the voice and sends it to the server. The server then converts the text data using a speech recognition engine, analyzes it, and records it as health information. It also uses an emotion engine to recognize the user's emotions and notify medical staff or family members as necessary.

[1453] Specific examples

[1454] For example, if a user says, "I'm very tired right now," the device captures this speech and sends the data to the server. The server then converts it into text data using a speech recognition engine and analyzes the meaning of "tired." At the same time, the emotion engine recognizes the "feeling of fatigue" and generates voice data in a gentle tone saying, "Please take a rest," which is then sent to the user via the device. The server then sends notifications to medical staff and family members depending on the situation.

[1455] In this way, this system enables two-way communication using voice and emotions, and can better understand and respond to the user's needs, providing comprehensive support for the elderly and those requiring care to live their daily lives with peace of mind.

[1456] The processing flow will be explained below.

[1457] News confirmation and emotion recognition processing flow

[1458] Step 1:

[1459] User: Say "Tell me the latest news." The user speaks into a tablet or smart device.

[1460] Step 2:

[1461] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[1462] Step 3:

[1463] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[1464] Step 4:

[1465] Server: Receives the voice data. The server confirms that the data has been received.

[1466] Step 5:

[1467] Server: Converts the voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data, such as "Tell me about the latest news."

[1468] Step 6:

[1469] Server: A natural language processing engine analyzes the text data and determines whether the user is looking for the latest news.

[1470] Step 7:

[1471] Server: Accesses the news information API to obtain the latest news data, makes an API request, and receives response data.

[1472] Step 8:

[1473] Server: Converts the acquired news data into a text format. For example, it creates text in the format "Today's main news is..."

[1474] Step 9:

[1475] Server: Converts text data into voice data using a speech synthesis engine. The synthesized voice data is generated as "Today's main news is..."

[1476] Step 10:

[1477] Server: Sends the generated voice data to the terminal. Confirms the data transmission.

[1478] Step 11:

[1479] Terminal: Receives audio data. Checks the received data and encodes it.

[1480] Step 12:

[1481] Device: Play audio data through the speaker. Output so that the user can hear "Today's main news is..."

[1482] Health status recording and emotion recognition process

[1483] Step 1:

[1484] User: Say "Record my health status today." The user speaks into a tablet or smart device.

[1485] Step 2:

[1486] Device: Captures the user's voice using a microphone, encodes the captured voice data in real time, and converts the voice data into a binary format.

[1487] Step 3:

[1488] Terminal: The converted voice data is sent to the server. The terminal establishes communication with the server via the Internet and transmits the data.

[1489] Step 4:

[1490] Server: Receives the voice data. The server confirms that the data has been received.

[1491] Step 5:

[1492] Server: Converts voice data into text data using a voice recognition engine. The voice recognition engine analyzes the voice and converts it into text data such as "Please record today's health condition."

[1493] Step 6:

[1494] Server: Analyzes the text data using a natural language processing engine and determines that the user wants to record their health status.

[1495] Step 7:

[1496] Server: Save the text data in a database. Save the message "Record your health condition today" as the user's health record.

[1497] Step 8:

[1498] Server: Analyzes the user's emotions using an emotion engine based on the stored health information. For example, if the user says "I'm tired," the emotion engine will recognize this as "fatigue."

[1499] Step 9:

[1500] Server: Adjust the response based on the emotion engine's recognition results. For example, if the user is tired, add a message saying "Take a good rest."

[1501] Step 10:

[1502] Server: Convert the response message into voice data. Using a voice synthesis engine, generate the voice data "Please take a good rest."

[1503] Step 11:

[1504] Server: Sends the generated voice data to the terminal. Confirms the data transmission.

[1505] Step 12:

[1506] Terminal: Receives and encodes audio data.

[1507] Step 13:

[1508] Device: Plays audio data through the speaker, outputting "Please take a good rest" so that the user can hear it.

[1509] Step 14:

[1510] Server: Notifies medical staff or family members of the recognized emotion information, for example, by sending an alert saying, "The user seems tired."

[1511] In this way, a system that combines an emotion engine can perform a series of processes, from acquiring information from the user's voice input to responding while taking into account the user's emotional state.

[1512] Example 2

[1513] 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."

[1514] Conventional voice assistant systems mainly respond simply to the user's voice input, and lack the ability to appropriately recognize the user's emotions and health status and adjust responses accordingly. In particular, there is a lack of comprehensive support for the elderly and those requiring care to live their daily lives with peace of mind.

[1515] 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.

[1516] In this invention, the server includes: means for a user to input information by voice input; terminal means for acquiring voice data from the user; server means for converting the acquired voice data into text data; means for analyzing the text data and acquiring information according to the user's request; server means for converting the acquired information into voice data; terminal means for playing the voice data back to the user; server means including an emotion engine for recognizing emotions from the user's voice data; and means for adjusting response content based on the results of emotion recognition. This makes it possible to provide appropriate responses that take into account the user's emotions and health condition, enabling comprehensive support to enable the elderly and those requiring care to live their daily lives with peace of mind.

[1517] "Voice input" is a means by which a user inputs information as voice.

[1518] A "terminal" is a device that acquires voice data from a user and transmits it to a server.

[1519] A "server" is a device that converts acquired voice data into text data, analyzes and acquires information, and responds to the user.

[1520] A "voice recognition engine" is software for converting voice data into text data.

[1521] A "natural language processing engine" is software that analyzes text data and understands user requests.

[1522] "Information acquisition means" refers to a means for acquiring information from an external information source in response to a user request.

[1523] A "speech synthesis engine" is software for converting text data into voice data.

[1524] The "emotion engine" is software that recognizes emotions from the user's voice data.

[1525] The "response content adjustment means" is a means for adjusting the response content based on the result of emotion recognition.

[1526] "Health Information" means information relating to a user's health condition.

[1527] "Means of notification" refers to the means of notifying medical staff and family members of information as necessary.

[1528] "News Information API" is an external API that obtains the latest news information.

[1529] "Voice data" refers to data in which the user's voice is encoded as a digital signal.

[1530] "Text data" refers to character data obtained by converting voice data.

[1531] The present invention is a system in which a user inputs information by voice, and includes the following components: Through this system, the user is supported in obtaining daily information and managing their health.

[1532] User voice input

[1533] For example, a user may say, "Tell me today's news." The user's voice input is captured through the microphone of the device (e.g., tablet or smart device). The device converts the captured voice into a digital signal, encodes the voice data into a binary format, and then sends it to the server.

[1534] Receiving and converting audio data

[1535] The server receives the voice data sent from the device and converts it into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text API).The server then analyzes the text using a natural language processing engine (e.g., IBM Watson NLU) to understand the user's request.

[1536] Obtaining information

[1537] In response to a user request, the server accesses a news information API (e.g., NewsAPI) to obtain the latest news data. If the user wishes to record their health status, the server similarly converts the voice to text and records and saves it as health information.

[1538] Converting acquired information into audio data

[1539] The server uses a speech synthesis engine (e.g., Amazon Polly) to convert the acquired news data into audio data, which is then sent to the device and played back to the user.

[1540] Recognizing and responding to user emotions

[1541] The server uses an emotion engine (e.g., Affectiva) to simultaneously recognize the voice and analyze the user's emotions. For example, if the server determines that the user sounds tired, it adjusts the response and provides a thoughtful comment such as "Please take a rest" in a gentle tone. In some cases, it may also notify medical staff or family members.

[1542] Specific examples

[1543] For example, if a user says, "I'm very tired right now," the device captures this voice, converts it into a digital signal, and sends it to the server. The server then uses a speech recognition engine to convert the voice data into text data and analyzes the meaning of "tired." At the same time, the emotion engine recognizes the "feeling of fatigue." The server then generates voice data in a gentle tone saying, "Please take a rest," and sends it to the device. The device then plays this voice data to the user. Additionally, it may send notifications to medical staff or family members depending on the situation.

[1544] Examples of prompt statements

[1545] "A user says they want to know today's news. How does the system respond?"

[1546] “If a user says they are tired, what sentiment analysis does the system perform and how does it respond?”

[1547] "Please explain the process your system goes through to record the user's health status."

[1548] In this way, the present invention uses a system that combines voice recognition, natural language processing, and emotion analysis, enabling responses that are adapted to the diverse needs of users and providing comprehensive support, particularly for the elderly and those requiring care.

[1549] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1550] Step 1:

[1551] For example, a user might say, "Tell me today's news." This speech is captured through the device's microphone. The device converts the speech into a digital signal and encodes the speech data into a binary format. The input is the user's speech, and the output is the encoded speech data. The device then sends the encoded speech data to the server.

[1552] Step 2:

[1553] The server receives the voice data sent from the terminal. The input is encoded voice data. The server uses a voice recognition engine to convert the received voice data into text data. The output at this stage is text data. General voice recognition software is used as the voice recognition engine.

[1554] Step 3:

[1555] The server uses a natural language processing engine to analyze the text data and understand the user's request. The input is text data, and the output is the analyzed user request. Specifically, the server determines that the text data requests "provision of news." This allows the server to proceed to the next information acquisition step.

[1556] Step 4:

[1557] The server queries external information sources in response to user requests. The input is the parsed request content. The server accesses the news information API and sends an API request. As a result, it receives the latest news data. The output is the news data.

[1558] Step 5:

[1559] The server formats the acquired news data into text format. The input is news data, and the output is formatted text data. Furthermore, a speech synthesis engine is used to convert the formatted text data into voice data. The output is converted voice data.

[1560] Step 6:

[1561] The server sends the converted audio data to the device. The device decodes the received audio data and plays it back to the user through the built-in speaker. The input is the converted audio data, and the output is the audio playback. The user can hear information such as "Today's news is..." by voice.

[1562] Step 7:

[1563] The server simultaneously recognizes the voice and uses an emotion engine to analyze the user's emotions. The input is voice data, and the output is analyzed emotion information. For example, if the user's voice is judged to sound tired, the emotion engine will recognize "fatigue."

[1564] Step 8:

[1565] The server adjusts the response content based on the emotion recognition results. The input is the analyzed emotion information, and the output is the adjusted response content. For example, if the user is tired, a thoughtful comment such as "Here's the latest news. Please take it easy today and don't push yourself too hard" is added to the voice data.

[1566] Step 9:

[1567] If necessary, the server notifies medical staff or family members of the recognized emotion information. The input is the analyzed emotion information, and the output is the notification content. For example, it sends a message saying, "The user seems tired."

[1568] Step 10:

[1569] Similarly, when a user says, "Record my health condition today," the device captures the voice and sends it to the server. The server uses a voice recognition engine to convert the voice data into text data, analyzes it, and records it as health information. The input is voice data, and the output is the recorded health data. The emotion engine also recognizes the user's emotions.

[1570] (Application example 2)

[1571] 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."

[1572] In conventional factory robot systems, it was difficult to accurately recognize voice instructions from workers and quickly and accurately execute those instructions. Furthermore, systems that could grasp the emotional state of workers and respond accordingly were not sufficiently developed. As a result, it was not possible to improve worker stress management or work efficiency. Furthermore, if a worker was fatigued or stressed, not taking appropriate action could lead to a decrease in work safety.

[1573] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1574] In this invention, the server includes a means for acquiring voice data and converting it into text data, a means for acquiring information in response to a user request, a means for converting the acquired information into voice data, a means including an emotion engine for analyzing the voice data and recognizing the user's emotion, and a means for adjusting the response content in accordance with the recognized emotion. This enables prompt and accurate execution of voice-input instructions and appropriate responses according to the worker's emotional state, contributing to improved work efficiency and ensuring safety.

[1575] "User" refers to a person who uses the system to provide information by voice input.

[1576] "Voice input" refers to a user speaking through a voice capture device such as a microphone.

[1577] "Terminal" refers to the device that receives voice data from the user and transmits it to the server.

[1578] "Voice Data" means information that is a digital representation of the voice uttered by a User.

[1579] "Text data" refers to data in a format in which voice data has been converted into text.

[1580] The term "server" refers to a device that processes acquired voice data, converts it into text data, and further analyzes the text data to acquire information.

[1581] An "emotion engine" refers to software or a system that analyzes a user's emotions from voice data and expresses them as digital data.

[1582] "Means of obtaining information" refers to the process of obtaining the necessary information from external APIs or databases based on user requests.

[1583] "Means for adjusting response content" refers to the ability to appropriately change the information provided or the content of responses based on the user's emotional state.

[1584] "News information" refers to information about current events and important topics.

[1585] "Medical staff" refers to professionals who manage users' health information.

[1586] "Family Member" refers to individuals who have a close relationship with the User.

[1587] MODE FOR CARRYING OUT THE INVENTION

[1588] This invention is a system that utilizes voice input and emotion recognition to improve the efficiency of factory work and enable responses according to the emotional state of workers. Specific embodiments of this system are described below.

[1589] Hardware and Software Configuration

[1590] The system utilizes the following hardware and software:

[1591] Hardware: microphones, speakers, factory robots.

[1592] Software: speech_recognition, robot_controller, text_to_speech, emotion_recognition, alert_system.

[1593] Acquiring and converting audio data

[1594] The user inputs commands such as "move the part" by voice through a microphone. The device captures the voice data, encodes it in real time, and sends it to the server. The server then converts the voice data into text data using the speech_recognition engine.

[1595] Text data analysis and response

[1596] The server analyzes the received text data and understands the user's request. For example, it may obtain an instruction such as "move a part" as a result of the analysis. Then, it uses the robot_controller to send a command to the factory robot to perform the requested action.

[1597] Emotion recognition and response regulation

[1598] At the same time, the server uses emotion_recognition to analyze emotions from the user's voice data. If the user speaks in a tired voice, the emotion engine detects "fatigue." In this case, to adjust the response, it uses alert_system to generate a message such as "Please take a break," converts it into voice data, and plays it back to the user through the device. The text_to_speech engine converts the text generated by the server into voice data.

[1599] Acquisition and provision of information

[1600] When a user makes a voice request such as "Tell me today's news," the server similarly converts the voice data into text data and determines that the request is for news. Next, the server accesses the news information API to obtain the latest news data, converts it into voice data using the text_to_speech engine, and provides it to the user via the device.

[1601] Specific examples

[1602] For example, if a user utters a prompt phrase such as "Please move the part," the system will analyze it and give specific movement instructions to a factory robot. If a worker says, "I'm very tired right now," the system will analyze the voice, recognize the emotion, and generate and play an alert saying, "Please take a break."

[1603] Example prompt sentence:

[1604] Please move the parts.

[1605] "Do you think you need a break?"

[1606] "Please stop what you're doing now."

[1607] The above is a specific embodiment for carrying out the present invention. This invention enables operation by voice input and realizes responses according to the emotional state. This improves work efficiency and ensures the safety of the worker.

[1608] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1609] Step 1:

[1610] The user inputs information through voice input. Input: The user gives a voice command (e.g., "move the part"). To perform a specific action, the user speaks the command into the microphone.

[1611] Step 2:

[1612] The device receives voice data from the user. Input: User's voice. Output: Digital voice data. Specifically, the microphone captures the voice and encodes the voice data.

[1613] Step 3:

[1614] The device transmits the encoded voice data to the server in real time. Input: Digital voice data. Output: Voice data transmitted to the server. Specifically, the device transmits the voice data to the server via the network.

[1615] Step 4:

[1616] The server converts the received voice data into text data using a speech recognition engine. Input: Voice data. Output: Text data (e.g., "Move the part"). Specifically, the server starts the speech_recognition engine and converts the voice data into text.

[1617] Step 5:

[1618] The server analyzes the text data to understand the user's request. Input: Text data. Output: Request content (e.g., "Move the part"). Specifically, the server uses a natural language processing engine to analyze the text data and extract the request content.

[1619] Step 6:

[1620] The server generates instructions for the factory robot based on the request and controls the robot. Input: Request. Output: Robot control command. For specific operations, the server uses robot_controller to generate commands that instruct the specific robot operations and sends them to the robot.

[1621] Step 7:

[1622] The server simultaneously recognizes the user's emotions from the voice data. Input: Voice data. Output: Emotion data (e.g., "fatigue"). Specifically, the server uses the emotion_recognition engine to analyze the voice data and detect the user's emotional state.

[1623] Step 8:

[1624] The server adjusts the response content based on the emotion recognition results. Input: Emotion data, request content. Output: Adjusted response message (e.g., "Move the parts. Please take a break."). Specifically, the server generates an additional message depending on the emotion recognition results.

[1625] Step 9:

[1626] The server converts the tailored response message from text to audio data and sends it to the device. Input: Tailored response message. Output: Audio data. Specifically, the server uses the text_to_speech engine to convert the text message into audio data and then sends it to the device.

[1627] Step 10:

[1628] The device plays the received audio data to the user. Input: Audio data. Output: Audio response to the user. Specifically, the device uses a speaker to play the audio data to the user.

[1629] Through the above steps, the factory robot operates based on the user's voice input and provides an appropriate response according to the user's emotional state.

[1630] 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.

[1631] 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.

[1632] 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.

[1633] 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.

[1634] 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.

[1635] 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.

[1636] 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).

[1637] 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.

[1638] 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."

[1639] 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.

[1640] 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).

[1641] 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.

[1642] 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.

[1643] 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.

[1644] 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.

[1645] 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.

[1646] 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.

[1647] 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.

[1648] 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.

[1649] 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.

[1650] 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.

[1651] The following is further disclosed regarding the above embodiment.

[1652] (Claim 1)

[1653] a means for a user to input information by voice input;

[1654] a terminal means for acquiring voice data from a user;

[1655] a server means for converting the acquired voice data into text data;

[1656] A means for analyzing the text data and obtaining information in response to a user request;

[1657] a server means for converting the acquired information into voice data;

[1658] terminal means for playing back audio data to a user;

[1659] A system including:

[1660] (Claim 2)

[1661] a terminal means for acquiring health information of a user by voice input;

[1662] means for converting the voice data into text data and recording the user's health information;

[1663] means for storing the recorded health information on a server;

[1664] a means of notifying medical staff or family members as necessary;

[1665] 10. The system of claim 1, comprising:

[1666] (Claim 3)

[1667] means for obtaining news and weather information in response to a user's request;

[1668] A means for converting the acquired information into audio data and providing it to the user;

[1669] 10. The system of claim 1, comprising:

[1670] (Claim 4)

[1671] means for analyzing text data, the means comprising a natural language processing engine;

[1672] means for converting the acquired information into voice data, the means including a voice synthesis engine;

[1673] 10. The system of claim 1, comprising:

[1674] (Claim 5)

[1675] A means for storing the health information input by the user via voice on a server;

[1676] means for monitoring the user's health status based on the stored health information;

[1677] 3. The system of claim 2, comprising:

[1678] "Example 1"

[1679] (Claim 1)

[1680] means for inputting information by voice input;

[1681] a terminal means for acquiring voice data;

[1682] means for encoding the acquired audio data and transmitting the encoded data to a server;

[1683] a server means for converting voice data into text data;

[1684] A means for analyzing the text data and obtaining information in response to a user request;

[1685] a server means for converting the acquired information into voice data;

[1686] terminal means for playing back audio data to a user;

[1687] A system including:

[1688] (Claim 2)

[1689] a means for acquiring a user's health information by voice input;

[1690] A means for converting the voice data into text data and analyzing the text data to understand the health information;

[1691] a means for recording and storing health information on a server;

[1692] A means of communicating notification information to medical staff or family members as needed;

[1693] 10. The system of claim 1, comprising:

[1694] (Claim 3)

[1695] a means for obtaining information from external sources in response to a user's request;

[1696] A means for converting the acquired information into audio data and providing it to the user;

[1697] 10. The system of claim 1, comprising:

[1698] "Application Example 1"

[1699] (Claim 1)

[1700] a means for a user to input information by voice input;

[1701] a terminal means for acquiring voice data from a user;

[1702] a server means for converting the acquired voice data into text data;

[1703] A means for analyzing the text data and obtaining information in response to a user request;

[1704] a server means for converting the acquired information into voice data;

[1705] terminal means for playing back audio data to a user;

[1706] A means to check production management and inventory status within the factory by voice input,

[1707] A system including:

[1708] (Claim 2)

[1709] a terminal means for acquiring health information of a user by voice input;

[1710] means for converting the voice data into text data and recording the user's health information;

[1711] means for storing the recorded health information on a server;

[1712] a means of notifying medical staff or family members as necessary;

[1713] 10. The system of claim 1, comprising:

[1714] (Claim 3)

[1715] means for obtaining news and weather information in response to a user's request;

[1716] A means for converting the acquired information into audio data and providing it to the user;

[1717] 10. The system of claim 1, comprising:

[1718] "Example 2: Combining Emotion Engines"

[1719] (Claim 1)

[1720] a means for a user to input information by voice input;

[1721] a terminal means for acquiring voice data from a user;

[1722] a server means for converting the acquired voice data into text data;

[1723] A means for analyzing the text data and obtaining information in response to a user request;

[1724] a server means for converting the acquired information into voice data;

[1725] terminal means for playing back audio data to a user;

[1726] a server means including an emotion engine for recognizing emotions from the user's voice data;

[1727] A means for adjusting the response content based on the result of the emotion recognition;

[1728] A system including:

[1729] (Claim 2)

[1730] a terminal means for acquiring health information of a user by voice input;

[1731] means for converting the voice data into text data and recording the user's health information;

[1732] means for storing the recorded health information on a server;

[1733] a means of notifying medical staff or family members as necessary;

[1734] 10. The system of claim 1, comprising:

[1735] (Claim 3)

[1736] means for obtaining news and weather information in response to a user's request;

[1737] A means for converting the acquired information into audio data and providing it to the user;

[1738] A means of analyzing user sentiment and adjusting response content;

[1739] 10. The system of claim 1, comprising:

[1740] "Application example 2 when combining emotion engines"

[1741] (Claim 1)

[1742] a means for a user to input information by voice input;

[1743] a terminal means for acquiring voice data from a user;

[1744] a server means for converting the acquired voice data into text data;

[1745] A means for analyzing the text data and obtaining information in response to a user request;

[1746] a server means for converting the acquired information into voice data;

[1747] terminal means for playing back audio data to a user;

[1748] means for analyzing voice data and including an emotion engine for recognizing an emotion of a user;

[1749] a means for adjusting response content in response to the perceived emotion;

[1750] A system including:

[1751] (Claim 2)

[1752] a means for acquiring a user's health information by voice input;

[1753] means for converting the voice data into text data and recording the user's health information;

[1754] means for storing the recorded health information on a server;

[1755] a means of notifying medical staff or family members as necessary;

[1756] a means for adjusting a response based on the emotion recognition results;

[1757] 10. The system of claim 1, comprising:

[1758] (Claim 3)

[1759] means for obtaining news and weather information in response to a user's request;

[1760] A means for converting the acquired information into audio data and providing it to the user;

[1761] A means to tailor appropriate news content through sentiment analysis;

[1762] 10. The system of claim 1, comprising: [Explanation of symbols]

[1763] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for a user to input information by voice input; a terminal means for acquiring voice data from a user; a server means for converting the acquired voice data into text data; A means for analyzing the text data and obtaining information in response to a user request; a server means for converting the acquired information into voice data; terminal means for playing back audio data to a user; A system including:

2. a terminal means for acquiring health information of a user by voice input; means for converting the voice data into text data and recording the user's health information; means for storing the recorded health information on a server; a means of notifying medical staff or family members as necessary; The system of claim 1 , comprising:

3. means for obtaining news and weather information in response to a user's request; A means for converting the acquired information into audio data and providing it to the user; The system of claim 1 , comprising:

4. means for analyzing text data, the means comprising a natural language processing engine; means for converting the acquired information into voice data, the means including a voice synthesis engine; The system of claim 1 , comprising:

5. A means for storing the health information input by the user via voice on a server; means for monitoring the user's health status based on the stored health information; The system of claim 2 , comprising:

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