system

Abstract

We provide the system. [Solution] A means of receiving user input, A means for searching a database based on the aforementioned input, A means of displaying the searched data to the user, A means for converting the displayed data into audio and playing it back, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, the method including: receiving a user utterance; adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] Regarding a site investigation report that requires an understanding of technical terms and how to view drawings, there is a problem that the customer's understanding level does not increase sufficiently with the conventional method. In addition, due to a lack of detailed knowledge about on-site work and incidental construction work, there is a problem that explanations to customers and presentation of work schedules cannot be effectively carried out. As a result, risks such as work delays and miscommunications may increase.

Means for Solving the Problems

[0005] This invention provides a means for receiving user input, searching a database, and displaying the retrieved data to the user. It also provides a system that includes means for converting the displayed data into speech and playing it back. Furthermore, it includes means for applying an artificial intelligence model to select the most suitable information from the retrieved data, means for verifying the user's authentication information in the database and generating authentication results, and means for generating and playing back speech data. In this way, it realizes a system that can effectively explain technical terms and drawings, thereby improving the customer's understanding of ancillary construction work and on-site work.

[0006] A "user" refers to anyone who uses the system to input, search, view, and receive voice guidance for information.

[0007] "Input" refers to the act of a user providing search keywords or authentication information to the system.

[0008] A "database" refers to an information aggregation system that stores information related to technical terms and drawings, and allows users to search for it as needed.

[0009] "Searching" refers to the act of finding relevant information within a database based on user input.

[0010] "Display" refers to the visual presentation of searched information on the user interface.

[0011] "Speech conversion" refers to the process of converting text data into speech data.

[0012] "Playback" refers to the act of making audio data playable for the user as audio.

[0013] An "artificial intelligence model" refers to a model that uses technologies such as machine learning and natural language processing to select the most relevant information from search results.

[0014] "Authentication information" refers to information such as IDs and passwords used to identify users and confirm their authorities.

[0015] "Authentication result" refers to the result of determining a user's access authority based on the confirmation of authentication information.

[0016] "Voice data" refers to the digital data of voices generated by voice conversion means.

[0017] As a result, important words within the scope of the claims are specifically defined, thus clarifying the technical scope of the invention.

Brief Description of the Drawings

[0018] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0019] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0022] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0023] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0024] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0031] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0038] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0039] The system according to the present invention comprises means for receiving user input, means for searching a database, means for displaying the retrieved data, means for converting the displayed data into speech and playing it back, and means for applying an artificial intelligence model to select the most suitable information for the retrieved data. It also includes means for verifying user authentication information and means for generating and playing back speech data.

[0040] System Overview

[0041] 1. User actions

[0042] Users log in to the system and enter keywords related to the technical terms or drawings they wish to search for. This allows users to obtain information tailored to their needs.

[0043] 2. Database Search

[0044] The terminal receives a request from the user and sends that request to the server. The server searches the database and extracts the relevant information.

[0045] 3. Displaying search results

[0046] The retrieved information is sent from the server to the terminal, which then displays it in the user interface.

[0047] 4. Voice guidance

[0048] If a user selects specific information and requests voice guidance, the device resends the request to the server. The server converts the information into audio data and sends it to the device. The device plays the audio data, and the user can obtain the necessary information through voice guidance.

[0049] Specific example

[0050] Login process

[0051] The user enters their ID and password into the system from their device and clicks the login button. The device sends this information to the server, which verifies the user's authentication information in its database. If authentication is successful, the server generates a login token and sends it back to the device. The device receives this token, and the user can begin using the system.

[0052] Search and display of technical terms

[0053] The user enters "earthquake-resistant design" into the search bar and clicks the search button. The device sends this request to the server. The server searches the database and extracts information related to "earthquake-resistant design." It then sends the results back to the device. The device displays this information in a list on its user interface.

[0054] Audio guidance for information

[0055] The user selects the item they want to know about from the search results list and clicks the voice guidance button. The device sends this request back to the server. The server converts the relevant information into audio data and sends it to the device. The device plays the audio data, and the user can acquire knowledge through the voice guidance.

[0056] Other features

[0057] This system includes an artificial intelligence model for selecting the most relevant information from the searched data. Specifically, the server uses the AI ​​model to analyze the search results and select the information most relevant to the user. This process allows the user to obtain the necessary information in a short amount of time.

[0058] Furthermore, a specific algorithm is used for generating and playing back audio data. The server is equipped with speech synthesis technology to convert text information into speech, enabling it to respond quickly to user requests for voice guidance. The terminal appropriately plays back the audio data, providing users with real-time voice guidance.

[0059] This system allows users to quickly obtain explanations of technical terms and diagrams, deepening their understanding of on-site survey reports. It also improves their understanding of ancillary work and on-site tasks, leading to overall improved work efficiency.

[0060] The following describes the processing flow.

[0061] Login process

[0062] Step 1:

[0063] The user starts up their device and opens the login screen. The user enters their ID and password and clicks the login button.

[0064] Step 2:

[0065] The device sends the authentication information entered by the user to the server.

[0066] Step 3:

[0067] The server checks the received authentication information in the database and performs user authentication.

[0068] Step 4:

[0069] The server generates an authentication result (success or failure), and if successful, generates a login token.

[0070] Step 5:

[0071] The server sends the login token back to the device.

[0072] Step 6:

[0073] The device receives the login token and enables the user to begin using the system.

[0074] Search and display of technical terms

[0075] Step 1:

[0076] The user enters a search keyword (e.g., "earthquake-resistant design") into the device's search bar and clicks the search button.

[0077] Step 2:

[0078] The device sends a search request and search keywords to the server.

[0079] Step 3:

[0080] The server searches the database using the search keywords it received.

[0081] Step 4:

[0082] The server extracts relevant information from the database and generates results.

[0083] Step 5:

[0084] The server sends the search results to the terminal.

[0085] Step 6:

[0086] The search results received by the device are displayed to the user in a list.

[0087] Audio guidance for information

[0088] Step 1:

[0089] The user selects the item they want to know about from the list of search results and clicks the voice guidance button.

[0090] Step 2:

[0091] The device sends a voice guidance request to the server.

[0092] Step 3:

[0093] The server begins processing the information to convert it into audio data.

[0094] Step 4:

[0095] The server generates audio data and sends it to the terminal.

[0096] Step 5:

[0097] The device plays back the received audio data and provides voice guidance to the user.

[0098] Information optimization (application of artificial intelligence models)

[0099] Step 1:

[0100] The server inputs the search results extracted from the database into an artificial intelligence model.

[0101] Step 2:

[0102] The server uses an artificial intelligence model to analyze the search results and identify the most relevant information.

[0103] Step 3:

[0104] The server selects optimized information and generates data to provide to the user.

[0105] Verification of authentication information

[0106] Step 1:

[0107] The user enters and submits authentication information (ID and password) via their device.

[0108] Step 2:

[0109] The server checks the received authentication information in the database.

[0110] Step 3:

[0111] The server generates an authentication result, and if authentication is successful, it issues a login token.

[0112] Step 4:

[0113] The server sends the authentication result or login token to the device.

[0114] Audio data generation and playback

[0115] Step 1:

[0116] The server receives the user's voice guidance request.

[0117] Step 2:

[0118] The server generates audio data based on the corresponding text information.

[0119] Step 3:

[0120] The server generates audio data and sends it to the terminal.

[0121] Step 4:

[0122] The device plays back the audio data it receives and provides it to the user.

[0123] These processing steps enable the system to efficiently provide information to users and support explanations of technical terms and on-site work procedures.

[0124] (Example 1)

[0125] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0126] In today's world, it is crucial for users to obtain necessary information quickly and accurately. However, traditional systems require users to search for information from vast databases and expend considerable time and effort to understand it. Furthermore, systems that can receive information not only in text format but also through voice guidance are limited. In addition, many systems lack sufficient user authentication security and the ability to provide the most optimal information for the user's needs. A new system is needed to address these challenges.

[0127] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0128] In this invention, the server includes means for receiving user input, means for searching a database based on the input, means for displaying the retrieved data to the user, means for converting the displayed data into speech and playing it back, means for verifying the user's authentication information in the database and generating an authentication result, and means for applying an artificial intelligence model to select the optimal information for the retrieved data. This enables the user to efficiently obtain the necessary information and understand it through voice guidance. Furthermore, highly secure user authentication and the selection of optimal information by the artificial intelligence model enable the provision of highly accurate information.

[0129] "Means for receiving user input" refers to an interface for users to provide specific information, and includes devices such as keyboards and touch panels.

[0130] "Means of searching a database" refers to a function that allows a server to query information based on input information obtained from a user and extract relevant information from within the database.

[0131] "Means of displaying searched data to the user" refers to displays and user interfaces that visually provide the extracted information to the user.

[0132] "A means of converting displayed data into audio and playing it back" refers to a system that converts text-based information into audio data and provides that audio data to the user through speakers or earphones.

[0133] "Means for verifying user authentication information in a database and generating authentication results" refers to a function that compares the authentication information provided by the user with the information stored in the database, and determines and generates whether authentication was successful or not.

[0134] "Means of applying artificial intelligence models" refers to a function in which a server uses AI technology to analyze and select the most relevant information from the retrieved data.

[0135] The system according to this invention comprises means for receiving user input, means for searching a database, means for displaying the retrieved data, means for converting the displayed data into speech and playing it back, and means for applying an artificial intelligence model to select the most suitable information for the retrieved data. It also includes means for verifying user authentication information and means for generating and playing back speech data.

[0136] System Overview

[0137] 1. User actions

[0138] Users log in to the system and enter keywords related to the technical terms or drawings they wish to search for. This allows users to obtain information tailored to their needs.

[0139] 2. Database Search

[0140] The terminal receives a request from the user and sends that request to the server. The server searches the database (e.g., MySQL® or PostgreSQL) and extracts the relevant information.

[0141] 3. Displaying search results

[0142] Information sent from the server to the terminal is displayed in the terminal's user interface (e.g., built with React or Vue.js).

[0143] 4. Voice guidance

[0144] If the user selects specific information and requests voice guidance, the device resends the request to the server. The server uses speech synthesis technology (e.g., Google® Text-to-Speech API or Amazon Polly) to convert the information into voice data and sends it to the device. The device then plays the voice data and provides voice guidance to the user.

[0145] Specific example

[0146] Login process

[0147] The user enters their ID and password into the system from their device and clicks the login button. The device sends this information to the server, which verifies the authentication information in its database. If authentication is successful, the server generates a login token and sends it back to the device. The device receives this token, and the user can begin using the system.

[0148] Search and display of technical terms

[0149] The user enters "earthquake-resistant design" into the search bar and clicks the search button. The device sends this request to the server. The server searches the database and extracts information related to "earthquake-resistant design." It then sends the results back to the device. The device displays this information in a list on its user interface.

[0150] Audio guidance for information

[0151] The user selects the item they want to know about from the search results list and clicks the voice guidance button. The device sends this request back to the server. The server converts the relevant information into audio data and sends it to the device. The device plays the audio data, and the user can acquire knowledge through the voice guidance.

[0152] Hardware and software to be used

[0153] 1. Hardware

[0154] Devices: Computers, tablets, smartphones, etc.

[0155] Server: A high-performance server machine installed in a data center.

[0156] 2. Software

[0157] Database software: MySQL, PostgreSQL

[0158] Server-side programs: Python, Node.js

[0159] Client-side programming: React, Vue.js

[0160] Text-to-Speech APIs: Google Text-to-Speech API, Amazon Polly

[0161] Artificial intelligence models: TENSORFLOW®, PyTorch

[0162] Example of a prompt

[0163] "Please provide the latest technical information regarding earthquake-resistant design."

[0164] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0165] Program processing steps

[0166] Step 1: System startup and display of login screen

[0167] 1. The terminal starts up the system.

[0168] 2. The terminal displays a login screen to the user.

[0169] Input: System startup command

[0170] Output: Login screen

[0171] Step 2: User Login

[0172] 1. The user enters their ID and password and clicks the "Login" button.

[0173] 2. The terminal receives the entered ID and password and sends them to the server.

[0174] Enter: ID and password

[0175] Output: Sending an authentication request

[0176] Step 3: Perform user authentication

[0177] 1. The server checks the received ID and password in the database.

[0178] 2. The server generates an authentication result (success or failure) and sends it back to the terminal.

[0179] Enter: ID and password

[0180] Output: Authentication result (login token or error message)

[0181] Step 4: Processing authentication results

[0182] 1. If authentication is successful, the device will receive a login token and display the main menu.

[0183] 2. If authentication fails, the device will display an error message.

[0184] Input: Authentication result

[0185] Output: Main menu or error message

[0186] Step 5: Search for technical terms

[0187] 1. The user selects the "Search" option from the main menu and enters "earthquake-resistant design" in the search bar.

[0188] 2. The user clicks the "Search" button.

[0189] 3. The device receives this request and sends it to the server.

[0190] Input: Search keyword (earthquake-resistant design)

[0191] Output: Sending a search request

[0192] Step 6: Search the database

[0193] 1. The server searches the database and extracts information related to "earthquake-resistant design".

[0194] 2. The server sends the search results to the terminal in JSON format.

[0195] Input: Search keyword

[0196] Output: Search results (JSON format)

[0197] Step 7: Displaying search results

[0198] 1. The device renders the received search results into HTML and displays them to the user as a list.

[0199] Input: Search results (JSON format)

[0200] Output: Display of search results list

[0201] Step 8: Selecting detailed information and audio guidance

[0202] 1. The user selects a specific item from the search results list and clicks the "Voice Guidance" button.

[0203] 2. The device receives this request and sends an HTTP POST request to the server containing the ID of the relevant information.

[0204] Input: ID of the selected item

[0205] Output: Sending a voice guidance request

[0206] Step 9: Generate audio data

[0207] 1. The server uses a speech synthesis API to convert the relevant information into speech data.

[0208] 2. The server sends the generated audio data to the terminal.

[0209] Input: Text information of the selected item

[0210] Output: Audio data (MP3 format)

[0211] Step 10: Play the voice guidance

[0212] 1. The device plays the acquired audio data using an audio player.

[0213] 2. Users obtain information through voice guidance.

[0214] Input: Audio data (MP3 format)

[0215] Output: Playback of voice guidance

[0216] Step 11: Optimal information selection using an AI model

[0217] 1. The server uses an AI model to analyze the search results.

[0218] 2. The AI ​​model selects the most relevant information, and the server sends the result to the terminal.

[0219] Input: Search results (text data)

[0220] Output: Selected optimal information (JSON format)

[0221] Step 12: Displaying Optimal Information

[0222] 1. The device highlights the most relevant information it receives on the user interface.

[0223] Input: Selected optimal information (JSON format)

[0224] Output: Highlighting of optimal information

[0225] (Application Example 1)

[0226] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0227] In factory production lines, there is a lack of means for workers to quickly and efficiently obtain the necessary information when setting up or maintaining robots. Conventional technologies require manual verification of search results, which is time-consuming and labor-intensive, especially for complex procedures and troubleshooting. Therefore, new methods are needed to improve work efficiency and reduce the burden on workers.

[0228] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0229] In this invention, the server includes means for receiving user input, means for searching a database based on the input, means for displaying the retrieved data to the user, means for converting the displayed data into audio and playing it back, and means for outputting the retrieved data as an audio guide. This enables workers on a factory production line to quickly obtain the necessary information and proceed with their work efficiently.

[0230] "Means of receiving user input" refers to devices and interfaces used to obtain instructions and information from users. Examples include tablets, smart glasses, and keyboards.

[0231] "Means of searching a database" refers to algorithms and programs used to extract data from storage based on predetermined keywords or conditions.

[0232] "Means of displaying searched data to the user" refers to displays or screens that visually present the retrieved information to the user. Examples include tablet screens and smart glasses displays.

[0233] "Means of converting displayed data into audio and playing it back" refers to technology that converts visual information into audio using synthesized speech and plays that audio information back through speakers or headphones.

[0234] "Means of outputting as audio guidance" refers to programs or devices that provide audio guidance for specific information or instructions. For example, a system that provides audio guidance for work procedures within a factory would fall into this category.

[0235] An "artificial intelligence model" refers to a machine learning or deep learning model used to perform inference and prediction based on given data. Examples include neural networks using TensorFlow or PyTorch.

[0236] "A means of verifying user authentication information in a database and generating authentication results" refers to technology that checks the authentication information of a user when they access a system and determines whether the user has legitimate access rights.

[0237] One embodiment of this invention is a system for enabling workers to efficiently set up and maintain robots on a factory production line. This system is realized through the following configuration and process.

[0238] Basic System Configuration

[0239] The system includes means for receiving user input, means for searching a database, means for displaying the retrieved data to the user, means for converting the displayed data into audio and playing it back, and means for outputting it as an audio guide. Furthermore, it also includes means for applying an artificial intelligence model to select the most appropriate information from the retrieved data, and means for verifying the user's authentication information.

[0240] Hardware and software

[0241] hardware

[0242] This system utilizes interface devices such as tablets, smart glasses, and head-mounted displays installed on the factory's production line. These devices function as terminals operated by workers. A server is also required for overall system control and data processing.

[0243] software

[0244] The software includes the following elements:

[0245] Languages: Python, JavaScript (registered trademark)

[0246] Frameworks: Flask (backend), React (frontend)

[0247] Libraries: TensorFlow (AI model), SpeechRecognition, Pygame (speech management)

[0248] Processing flow

[0249] User operation and interface

[0250] Users access the system using tablets or smart glasses within the factory. When a user enters keywords such as "Please tell me how to deal with a specific equipment problem" on the tablet screen, the input is sent to the server.

[0251] Database Search

[0252] The server searches the database based on the received request and extracts the relevant information. The extracted information is then preprocessed and sent to the user's terminal.

[0253] Display of search results and audio guide

[0254] The terminal displays search results on the screen and simultaneously prepares an audio guide. When the user reviews the search results and accesses specific procedures or settings changes as needed, the information is played back as audio. For example, to learn about equipment maintenance procedures, the user can enter a prompt such as, "Please tell me the maintenance procedure for the cooling system."

[0255] AI optimization feature

[0256] The server uses an AI model to select the most relevant information from the search results. This process allows the user to obtain the necessary information in the shortest possible time. Specifically, this involves neural networks using TensorFlow or PyTorch.

[0257] Audio guide generation and playback

[0258] The server uses speech synthesis technology to convert the relevant information into audio data. This technology includes gTTS (Google Text-to-Speech), among others. The converted audio data is sent to the terminal, allowing the user to receive voice guidance in real time.

[0259] This allows workers on the factory production line to quickly and efficiently acquire information and proceed with their work. At the same time, it reduces the burden on workers and improves overall productivity.

[0260] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0261] Step 1:

[0262] Users log in to the system via a tablet, smart glasses, or head-mounted display.

[0263] Input: Enter your User ID and password.

[0264] Processing: The terminal sends the entered authentication information to the server, and the server searches the database to verify the user's authentication information.

[0265] Output: An authentication result is generated, and a login token is sent back to the device.

[0266] Specific operation: Once authentication is successful, the user will be able to access the system's main screen.

[0267] Step 2:

[0268] Users enter keywords and send search requests through the interface of a tablet or smart glasses.

[0269] Input: The user enters keywords into the search bar and clicks the search button.

[0270] Processing: The terminal receives user input and sends it to the server.

[0271] Output: Requests containing the keyword reach the server.

[0272] Specific action: The server prepares to retrieve relevant information from the database.

[0273] Step 3:

[0274] The server searches the database and retrieves relevant information.

[0275] Input: Keyword search request based on user input.

[0276] Processing: The server searches the database and extracts relevant information. It then uses an AI model (such as TensorFlow) to select the optimal data.

[0277] Output: Extracted relevant information.

[0278] Specific operation: The AI model analyzes the search results and selects the most relevant information.

[0279] Step 4:

[0280] The server sends the extracted information to the user's terminal.

[0281] Input: The extracted relevant information.

[0282] Process: The server transfers the detected information to the user's terminal.

[0283] Output: The relevant information is displayed on the user terminal.

[0284] Specific operation: The results are displayed on the user's terminal, and the user can visually confirm the information.

[0285] Step 5:

[0286] The user requests a voice guide based on the displayed information.

[0287] Input: A request from the user for a voice guide for the displayed information.

[0288] Process: The terminal resends this request to the server.

[0289] Output: The request for the voice guide is sent to the server.

[0290] Specific operation: The server prepares to convert the specified information into voice data.

[0291] Step 6:

[0292] The server converts the target information into voice and generates voice data.

[0293] Input: Text information based on the request for the voice guide.

[0294] Processing: The server uses speech synthesis technology (such as gTTS) to convert text information into speech data.

[0295] Output: Generated audio data.

[0296] Specific action: Audio data is generated and ready to be sent to the device.

[0297] Step 7:

[0298] The device plays the generated audio data to the user.

[0299] Input: Generated audio data.

[0300] Processing: The device receives the audio data and plays it through the speaker or headphones.

[0301] Output: Audio guide.

[0302] Specific operation: Users can obtain the necessary information through audio guidance and proceed with their tasks.

[0303] This allows users to quickly and efficiently obtain the necessary information within the factory and perform appropriate tasks.

[0304] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0305] The system according to the present invention includes means for receiving user input, searching a database, and displaying the retrieved data; means for converting the displayed data into speech and playing it back; and means for applying an artificial intelligence model to select the most suitable information from the retrieved data. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, the system provides optimal information tailored to the user's emotions.

[0306] Overview of the System

[0307] 1. User Operations

[0308] The user logs in to the system using a terminal and enters keywords related to the technical terms or drawings to be searched. Thereby, the user can obtain information according to their own needs.

[0309] 2. Database Search

[0310] The terminal receives the request from the user and sends the request to the server. The server searches the database and extracts relevant information.

[0311] 3. Display of Search Results

[0312] The server sends the search results to the terminal, and the terminal displays them on the user interface.

[0313] 4. Voice Guidance

[0314] When the user selects specific information and desires voice guidance, the terminal resends the request to the server again. The server converts the corresponding information into voice data and sends it to the terminal. The terminal plays the voice data, and the user can obtain the necessary information through voice guidance.

[0315] 5. Emotion Recognition

[0316] The emotion engine recognizes the user's emotion in real time. It judges the emotion from the tone of the user's voice and expression.

[0317] 6. Information Optimization

[0318] The server utilizes the emotion information obtained from the emotion engine and selects the most appropriate information using an artificial intelligence model.

[0319] 7. Voice Guidance According to Emotion

[0320] The server adjusts the content and tone of the voice guidance according to the recognized emotion and sends it to the terminal. The user can then receive voice guidance that matches their emotions.

[0321] Specific example

[0322] Login process

[0323] The user enters their ID and password into the system from their device and clicks the login button. The device sends this information to the server, which verifies the user's authentication information in its database. If authentication is successful, the server generates a login token and sends it back to the device. The device receives this token, and the user can begin using the system.

[0324] Search and display of technical terms

[0325] The user enters "earthquake-resistant design" into the search bar and clicks the search button. The device sends this request to the server. The server searches the database and extracts information related to "earthquake-resistant design." It then sends the results back to the device. The device displays this information in a list on its user interface.

[0326] Audio guidance for information

[0327] The user selects the item they want to know about from the search results list and clicks the voice guidance button. The device sends this request back to the server. The server converts the relevant information into audio data and sends it to the device. The device plays the audio data, and the user can acquire knowledge through the voice guidance.

[0328] Emotion recognition and customization

[0329] While the user is operating the system, the emotion engine recognizes their emotions from their voice tone and facial expressions. For example, if the system determines that the user is stressed, it simplifies the voice guidance and softens the tone. The server receives the output from the emotion engine and sends back the information and voice data with appropriate adjustments. The terminal plays the adjusted voice data, and the user receives emotionally sensitive guidance.

[0330] Other features

[0331] This system incorporates a mechanism for utilizing accumulated emotional information in subsequent interactions. The server stores the user's emotional history and optimizes future interactions based on this history. Furthermore, the emotional information recognized by the emotion engine is fed back to an artificial intelligence model for more accurate information selection. For example, by avoiding information that the user found unpleasant based on past history, the system can be made more user-friendly.

[0332] This system allows users to quickly obtain explanations of technical terms and diagrams, deepening their understanding of on-site survey reports. Furthermore, appropriate voice guidance tailored to the user's emotions improves their understanding of related construction work and on-site tasks. As a result, overall work efficiency is significantly improved.

[0333] The following describes the processing flow.

[0334] Login process

[0335] Step 1:

[0336] The user starts up their device and opens the login screen. The user enters their ID and password and clicks the login button.

[0337] Step 2:

[0338] The device sends the authentication information entered by the user to the server.

[0339] Step 3:

[0340] The server checks the received authentication information in the database and performs user authentication.

[0341] Step 4:

[0342] The server generates an authentication result (success or failure), and if successful, generates a login token.

[0343] Step 5:

[0344] The server sends the login token back to the device.

[0345] Step 6:

[0346] The device receives the login token and enables the user to begin using the system.

[0347] Search and display of technical terms

[0348] Step 1:

[0349] The user enters a search keyword (e.g., "earthquake-resistant design") into the device's search bar and clicks the search button.

[0350] Step 2:

[0351] The device sends a search request and search keywords to the server.

[0352] Step 3:

[0353] The server searches the database using the search keywords it received.

[0354] Step 4:

[0355] The server extracts relevant information from the database and generates results.

[0356] Step 5:

[0357] The server sends the search results to the terminal.

[0358] Step 6:

[0359] The search results received by the device are displayed to the user in a list.

[0360] Audio guidance for information

[0361] Step 1:

[0362] The user selects the item they want to know about from the list of search results and clicks the voice guidance button.

[0363] Step 2:

[0364] The device sends a voice guidance request to the server.

[0365] Step 3:

[0366] The server begins processing the information to convert it into audio data.

[0367] Step 4:

[0368] The server generates audio data and sends it to the terminal.

[0369] Step 5:

[0370] The device plays back the received audio data and provides voice guidance to the user.

[0371] Emotion recognition and customization

[0372] Step 1:

[0373] While the user is operating the system, an emotion engine built into the device recognizes the user's emotions in real time.

[0374] Step 2:

[0375] The emotion engine analyzes the user's emotions from their voice tone and facial expressions, and generates the results.

[0376] Step 3:

[0377] The device sends the output of the emotion engine to the server.

[0378] Step 4:

[0379] The server receives emotional information from the emotion engine and uses it to customize the information and voice guidance it provides.

[0380] Step 5:

[0381] The server sends the adjusted information and audio data to the terminal.

[0382] Step 6:

[0383] The device plays updated audio data, providing users with emotionally sensitive guidance.

[0384] Information optimization (application of artificial intelligence models)

[0385] Step 1:

[0386] The server inputs the search results extracted from the database into an artificial intelligence model.

[0387] Step 2:

[0388] The server uses an artificial intelligence model to analyze the search results and identify the most relevant information.

[0389] Step 3:

[0390] The server selects optimized information and generates data to provide to the user.

[0391] These processing steps enable the system to efficiently provide information to users, supporting explanations of technical terms and descriptions of on-site work. Furthermore, the introduction of an emotion engine allows for optimal voice guidance tailored to the user's emotions, thereby improving the user experience.

[0392] (Example 2)

[0393] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0394] Conventional information retrieval systems primarily focus on searching databases based on user input and displaying results, without considering the user's emotions or circumstances. Similarly, voice guidance simply converts text data into speech, failing to provide content and tone that consider the user's psychological state. This can lead to users experiencing stress when obtaining necessary information, resulting in decreased usability and satisfaction. Furthermore, the selection of optimal information using artificial intelligence models and enhanced authentication security remain insufficient.

[0395] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0396] In this invention, the server is

[0397] An emotion recognition engine that recognizes the user's emotions in real time,

[0398] A means for adjusting the content and tone of voice guidance based on the information obtained by the emotion recognition engine,

[0399] A means of applying an artificial intelligence model to select the most suitable information for the retrieved data,

[0400] This includes providing optimal information tailored to the user's emotions, and the content and tone of the voice guidance are adjusted according to the user's psychological state, resulting in a more comfortable and effective information acquisition experience.

[0401] "Means for receiving user input" refers to input interfaces for users to enter information, including devices such as keyboards and touch panels.

[0402] "Means of searching a database" refers to algorithms and systems used to retrieve relevant information from a pre-built database based on user input.

[0403] "Means of displaying searched data to the user" refers to displays or graphical user interfaces that show search results in a format that is visually accessible to the user.

[0404] "Means of converting to audio and playing it back" refers to speech synthesis programs and hardware that convert text data into audio data and play it back through speakers.

[0405] An "emotion recognition engine" refers to a software system that analyzes data such as the user's voice tone and facial expressions to recognize their emotions in real time.

[0406] "Means for adjusting the content and tone of voice guidance" refers to a program that adjusts the content and tone of voice guidance to match the user's psychological state, based on the output of the emotion recognition engine.

[0407] "Means of applying artificial intelligence models" refers to algorithms and systems that utilize machine learning and deep learning to select the most relevant information from retrieved data.

[0408] "Means for verifying user authentication information in a database and generating authentication results" refers to a program and system that compares the authentication information entered by the user with existing data in the database and determines the success or failure of authentication based on the results.

[0409] The system according to the present invention includes means for receiving user input, searching a database based on that input, and displaying the retrieved data; means for converting the displayed data into speech and playing it back; and means for applying an artificial intelligence model to select the most suitable information from the retrieved data. It also incorporates an emotion recognition engine that recognizes the user's emotions in real time and provides optimal voice guidance according to the user's emotions.

[0410] Hardware and software to be used

[0411] Device: A device including a personal computer, tablet, and smartphone.

[0412] Server: Use a high-performance server (e.g., an Amazon Web Services EC2 instance).

[0413] Database: Use a Relational Database Management System (e.g., MySQL, PostgreSQL).

[0414] Emotion recognition engine: Uses facial recognition software (e.g., OpenCV) and speech analysis software.

[0415] Artificial intelligence model: Machine learning models using TensorFlow or PyTorch are used.

[0416] Text-to-speech engine: Uses text-to-speech software (e.g., Google Text-to-Speech).

[0417] Search process

[0418] The user enters search keywords on their device and sends the request to the server. The server searches the database and retrieves the relevant information. The retrieved information is sent back to the device and displayed on the user interface. This allows the user to quickly obtain the information they need.

[0419] As a concrete example, when a user enters "earthquake-resistant design" into the search bar of their device and clicks the search button, the device sends this request to the server. The server searches the database and sends back information related to "earthquake-resistant design" to the device, which then displays this information in a list.

[0420] Voice guidance process

[0421] When a user selects specific information from the search results and wishes to receive voice guidance, they click the voice guidance button. This request is sent from the device to the server, which converts the relevant information into audio data and sends it back to the device. The device then plays this audio data, allowing the user to obtain the necessary information by voice.

[0422] As a concrete example, when a user selects the item "Fundamentals of Earthquake-Resistant Design" and clicks the voice guidance button, the device resends this request to the server. The server converts the information into audio data, and the device plays that audio.

[0423] Emotion recognition and information optimization

[0424] The emotion recognition engine recognizes the user's voice tone and facial expressions in real time and sends the obtained emotion information to the server. Based on this emotion information, the server uses an artificial intelligence model to select the most appropriate information and adjust the content and tone of the voice guidance. As a result, the user receives information guidance that is best suited to their emotions.

[0425] As a concrete example, when a user is listening to voice guidance, the emotion recognition engine detects stress. This information is sent to a server, which uses an AI model to simplify the content of the voice guidance, soften the tone, and regenerate the voice data, which is then sent to the terminal. The terminal plays the adjusted voice guidance, and the user receives information guidance with reduced stress.

[0426] Examples of input prompts for a generative AI model

[0427] "I want to search for information on earthquake-resistant design."

[0428] System: "Please enter 'earthquake-resistant design' in the search bar and click the search button."

[0429] User: Type "earthquake-resistant design" and click the search button.

[0430] System: "Information regarding earthquake-resistant design is displayed. If you would like audio guidance, please select an item and click the audio guidance button."

[0431] These features enable the system to quickly and effectively retrieve the information users need and provide optimal guidance tailored to their emotions.

[0432] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0433] Step 1:

[0434] The steps a user takes to enter their ID and password and attempt to log in.

[0435] The user enters their ID and password on the device's login interface and clicks the login button. The device sends this authentication information to the server. The server searches its database and verifies that the entered ID and password match. If authentication is successful, the server generates a login token and sends it back to the device. The device stores this token, and the user can then access the system.

[0436] Specific actions:

[0437] The user enters "ID: user123, Password: password123" and clicks the "Login" button.

[0438] The terminal sends the entered authentication information to the server in JSON format.

[0439] The server retrieves the corresponding user information from the database and verifies that it matches.

[0440] The server generates a "login token ABC123" and sends it back to the terminal.

[0441] The device stores the token it receives, allowing the user to access the system.

[0442] Input: User ID and password

[0443] Output: Login token

[0444] Step 2:

[0445] Steps for a user to enter search keywords and start a search.

[0446] The user enters the keyword they want to search for in the device's search bar and clicks the search button. The device sends the request to the server. The server searches its database based on the received keyword and retrieves the relevant information. This retrieved information is sent from the server to the device and displayed to the user.

[0447] Specific actions:

[0448] The user enters "earthquake-resistant design" and clicks the search button.

[0449] The device sends the search keyword "earthquake-resistant design" to the server as a POST request.

[0450] The server executes a database query to extract information related to "earthquake-resistant design."

[0451] The server returns the acquired information to the terminal in JSON format.

[0452] The device parses the information it receives and displays it in a user-friendly list format.

[0453] Input: Search keywords

[0454] Output: List of search results

[0455] Step 3:

[0456] Steps for users to request voice guidance

[0457] The user selects specific information from the displayed search results and clicks the voice guidance button. This request is resent from the device to the server. The server converts the relevant information into audio data and sends it to the device. The device plays this audio data, allowing the user to obtain the necessary information by voice.

[0458] Specific actions:

[0459] The user clicks the voice guidance button next to the item "Fundamentals of Earthquake-Resistant Design".

[0460] The device sends a "voice guidance request" to the server.

[0461] The server uses a text-to-speech engine (e.g., Google Text-to-Speech) to convert text related to "Fundamentals of Earthquake-Resistant Design" into speech.

[0462] The server sends the generated audio file back to the terminal.

[0463] The device plays audio data, and the user receives voice guidance.

[0464] Input: Voice guidance request (specific information)

[0465] Output: Audio data

[0466] Step 4:

[0467] The procedure by which the emotion recognition engine detects the user's emotions

[0468] While the user is operating the system, the emotion recognition engine analyzes the user's voice tone and facial expressions in real time to acquire emotional information. This emotional information is then sent to the server.

[0469] Specific actions:

[0470] While the user is operating the system, the emotion recognition engine uses the camera and microphone to capture the user's face and voice.

[0471] The device analyzes the captured data in real time to obtain "emotional information."

[0472] The device sends the emotional information it has acquired to the server.

[0473] Input: User's voice tone and facial expression

[0474] Output: Emotional information

[0475] Step 5:

[0476] Steps to optimize information based on emotional information

[0477] The server uses an artificial intelligence model to select the most appropriate information for the user based on the emotional information transmitted by the emotion recognition engine. It adjusts the content and tone of the voice guidance according to the user's emotions.

[0478] Specific actions:

[0479] The server receives emotional information and uses an artificial intelligence model (e.g., TensorFlow) to determine the optimal response.

[0480] The server makes adjustments such as simplifying the content of the voice guidance and softening the tone.

[0481] The server converts the adjusted text back into audio data.

[0482] Input: Sentiment information

[0483] Output: Adjusted audio data

[0484] Step 6:

[0485] Instructions for playing the adjusted voice guidance

[0486] The server sends the adjusted audio data to the terminal. The terminal plays this audio data and provides the user with the most suitable voice guidance.

[0487] Specific actions:

[0488] The server sends the adjusted audio data to the terminal.

[0489] The device plays the audio data it received.

[0490] Users obtain information by listening to pre-arranged voice guidance.

[0491] Input: Adjusted audio data

[0492] Output: Played audio guidance

[0493] (Application Example 2)

[0494] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0495] In factory work support, there is a need to provide workers with the information they require quickly and accurately, while also providing optimal support that takes into account their emotions. However, conventional systems have been unable to recognize workers' emotions and optimize information accordingly, resulting in problems such as a decrease in user experience and work efficiency.

[0496] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user input, means for searching a database based on the input, means for displaying the retrieved data to the user, means for converting the displayed data into speech and playing it back, means for recognizing the user's emotions, and means for adjusting the presentation of information based on the recognized emotions. This makes it possible to provide necessary information quickly and appropriately while taking into account the worker's emotions, thereby improving work efficiency and user experience.

[0497] "Means for receiving user input" refers to means of receiving user input such as voice input or touch operations, and recognizing them within the system.

[0498] "Means of searching a database" refers to means of extracting relevant information from a database based on user input.

[0499] "Means of displaying searched data to the user" refers to means of providing search results to the user visually. This includes displays and head-mounted displays.

[0500] "Means of converting data into audio and playing it back" refers to methods of converting text data into audio data and providing it to the user via voice.

[0501] "Means of recognizing user emotions" refers to methods of detecting emotions from the user's tone of voice, facial expressions, etc., and making the system recognize them.

[0502] "Means of adjusting information presentation based on recognized emotions" refers to means of optimizing the content and presentation of information presented according to the user's emotional state.

[0503] An "artificial intelligence model" is an algorithm or learning model used to process and analyze data and derive the optimal result.

[0504] A "login token" is data that represents temporary authentication information that authenticated users use to access the system.

[0505] The system that realizes this application example is a factory work support robot system. The robot provides information to workers and improves work efficiency by accepting user input, searching a database, displaying search results and providing voice guidance, and recognizing the user's emotions to provide optimal support.

[0506] The server has means to recognize user input, such as voice input or touch operations. Based on user input, the server searches the database and extracts relevant information. Database search tools such as SQL or Elasticsearch® are used for this database search.

[0507] The extracted information is sent to a terminal and displayed visually to the user. Smart glasses or head-mounted displays are used for this visual display. Furthermore, Text-to-Speech (TTS) technology is used to convert the extracted data into speech and play it back.

[0508] The robot employs an Emotion Engine to recognize emotions from the tone of the worker's voice and facial expressions. This emotion recognition engine detects the user's emotional state in real time, and that information is sent to the server.

[0509] The server uses emotional information to present optimal information through a generative AI model. The AI ​​model is designed to optimize the content and presentation of information according to emotions, providing appropriate support to the user.

[0510] As a concrete example, a user enters "earthquake-resistant design" into the search bar and clicks the search button. This request is sent to the server, which searches the database and extracts relevant information. The results are sent back to the terminal and displayed on the user interface. Furthermore, the displayed information is converted into speech and played back to the user using TTS (Text-to-Speech) technology.

[0511] Next, if the server detects that the user is experiencing stress, it uses that information to adjust the tone of its information delivery. For example, it might translate the information into simpler language and deliver it in a gentler tone.

[0512] This system will enable users to quickly obtain the information they need and receive emotionally sensitive support. Based on the following example prompts, the system will search for and provide the necessary information to the user.

[0513] Example of a prompt:

[0514] Details of a system where a user enters the keyword "earthquake-resistant design," and a factory work support robot searches a database to display information and provide voice guidance. The system also includes a feature to simplify information and soften the tone if the user is experiencing stress.

[0515] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0516] Step 1:

[0517] The user gives instructions to the device via voice input or touch operation. The user enters a keyword, such as "earthquake-resistant design." This input data (keyword) is sent to the system.

[0518] Step 2:

[0519] The terminal sends the received user input data to the server. The server searches the database based on this input data. The server retrieves relevant information using search tools such as SQL or Elasticsearch. The output is search results containing the relevant information.

[0520] Step 3:

[0521] The server sends the search results to the terminal. The terminal receives this data and displays the searched data visually to the user. Smart glasses or head-mounted displays are used for this visual display. The displayed information is the output.

[0522] Step 4:

[0523] If the user selects specific information and requests voice guidance, the device sends the selected information back to the server. The server uses Text-to-Speech (TTS) technology to convert that information into voice data.

[0524] Step 5:

[0525] The server sends the converted audio data to the terminal. The terminal plays this audio data, and the user obtains information through the voice guidance. The played voice guidance is the output.

[0526] Step 6:

[0527] When a user operates the system, the terminal captures the user's voice tone and facial expressions in real time for emotion recognition. An Emotion Engine is used for emotion recognition. This input data is then sent to the server.

[0528] Step 7:

[0529] The server retrieves emotional data from the Emotion Engine and provides this information to a generating AI model. The AI ​​model analyzes the emotional data and adjusts the optimal way to present the information. The adjusted information is then sent from the server to the terminal.

[0530] Step 8:

[0531] The device then presents the adjusted information to the user again. For example, if the server detects that the user is experiencing stress, it plays a simplified voice guidance with a softer tone. Through this process, the user receives appropriate support that is sensitive to their emotions.

[0532] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0533] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0534] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0535] [Second Embodiment]

[0536] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0537] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0538] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0539] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0540] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0541] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0542] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0543] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0544] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0545] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0546] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0547] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0548] The system according to the present invention comprises means for receiving user input, means for searching a database, means for displaying the retrieved data, means for converting the displayed data into speech and playing it back, and means for applying an artificial intelligence model to select the most suitable information for the retrieved data. It also includes means for verifying user authentication information and means for generating and playing back speech data.

[0549] System Overview

[0550] 1. User actions

[0551] Users log in to the system and enter keywords related to the technical terms or drawings they wish to search for. This allows users to obtain information tailored to their needs.

[0552] 2. Database Search

[0553] The terminal receives a request from the user and sends that request to the server. The server searches the database and extracts the relevant information.

[0554] 3. Displaying search results

[0555] The retrieved information is sent from the server to the terminal, which then displays it in the user interface.

[0556] 4. Voice guidance

[0557] If a user selects specific information and requests voice guidance, the device resends the request to the server. The server converts the information into audio data and sends it to the device. The device plays the audio data, and the user can obtain the necessary information through voice guidance.

[0558] Specific example

[0559] Login process

[0560] The user enters their ID and password into the system from their device and clicks the login button. The device sends this information to the server, which verifies the user's authentication information in its database. If authentication is successful, the server generates a login token and sends it back to the device. The device receives this token, and the user can begin using the system.

[0561] Search and display of technical terms

[0562] The user enters "earthquake-resistant design" into the search bar and clicks the search button. The device sends this request to the server. The server searches the database and extracts information related to "earthquake-resistant design." It then sends the results back to the device. The device displays this information in a list on its user interface.

[0563] Audio guidance for information

[0564] The user selects the item they want to know about from the search results list and clicks the voice guidance button. The device sends this request back to the server. The server converts the relevant information into audio data and sends it to the device. The device plays the audio data, and the user can acquire knowledge through the voice guidance.

[0565] Other features

[0566] This system includes an artificial intelligence model for selecting the most relevant information from the searched data. Specifically, the server uses the AI ​​model to analyze the search results and select the information most relevant to the user. This process allows the user to obtain the necessary information in a short amount of time.

[0567] Furthermore, a specific algorithm is used for generating and playing back audio data. The server is equipped with speech synthesis technology to convert text information into speech, enabling it to respond quickly to user requests for voice guidance. The terminal appropriately plays back the audio data, providing users with real-time voice guidance.

[0568] This system allows users to quickly obtain explanations of technical terms and diagrams, deepening their understanding of on-site survey reports. It also improves their understanding of ancillary work and on-site tasks, leading to overall improved work efficiency.

[0569] The following describes the processing flow.

[0570] Login process

[0571] Step 1:

[0572] The user starts up their device and opens the login screen. The user enters their ID and password and clicks the login button.

[0573] Step 2:

[0574] The device sends the authentication information entered by the user to the server.

[0575] Step 3:

[0576] The server checks the received authentication information in the database and performs user authentication.

[0577] Step 4:

[0578] The server generates an authentication result (success or failure), and if successful, generates a login token.

[0579] Step 5:

[0580] The server sends the login token back to the device.

[0581] Step 6:

[0582] The device receives the login token and enables the user to begin using the system.

[0583] Search and display of technical terms

[0584] Step 1:

[0585] The user enters a search keyword (e.g., "earthquake-resistant design") into the device's search bar and clicks the search button.

[0586] Step 2:

[0587] The device sends a search request and search keywords to the server.

[0588] Step 3:

[0589] The server searches the database using the search keywords it received.

[0590] Step 4:

[0591] The server extracts relevant information from the database and generates results.

[0592] Step 5:

[0593] The server sends the search results to the terminal.

[0594] Step 6:

[0595] The search results received by the device are displayed to the user in a list.

[0596] Audio guidance for information

[0597] Step 1:

[0598] The user selects the item they want to know about from the list of search results and clicks the voice guidance button.

[0599] Step 2:

[0600] The device sends a voice guidance request to the server.

[0601] Step 3:

[0602] The server begins processing the information to convert it into audio data.

[0603] Step 4:

[0604] The server generates audio data and sends it to the terminal.

[0605] Step 5:

[0606] The device plays back the received audio data and provides voice guidance to the user.

[0607] Information optimization (application of artificial intelligence models)

[0608] Step 1:

[0609] The server inputs the search results extracted from the database into an artificial intelligence model.

[0610] Step 2:

[0611] The server uses an artificial intelligence model to analyze the search results and identify the most relevant information.

[0612] Step 3:

[0613] The server selects optimized information and generates data to provide to the user.

[0614] Verification of authentication information

[0615] Step 1:

[0616] The user enters and submits authentication information (ID and password) via their device.

[0617] Step 2:

[0618] The server checks the received authentication information in the database.

[0619] Step 3:

[0620] The server generates an authentication result, and if authentication is successful, it issues a login token.

[0621] Step 4:

[0622] The server sends the authentication result or login token to the device.

[0623] Audio data generation and playback

[0624] Step 1:

[0625] The server receives the user's voice guidance request.

[0626] Step 2:

[0627] The server generates audio data based on the corresponding text information.

[0628] Step 3:

[0629] The server generates audio data and sends it to the terminal.

[0630] Step 4:

[0631] The device plays back the audio data it receives and provides it to the user.

[0632] These processing steps enable the system to efficiently provide information to users and support explanations of technical terms and on-site work procedures.

[0633] (Example 1)

[0634] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0635] In today's world, it is crucial for users to obtain necessary information quickly and accurately. However, traditional systems require users to search for information from vast databases and expend considerable time and effort to understand it. Furthermore, systems that can receive information not only in text format but also through voice guidance are limited. In addition, many systems lack sufficient user authentication security and the ability to provide the most optimal information for the user's needs. A new system is needed to address these challenges.

[0636] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0637] In this invention, the server includes means for receiving user input, means for searching a database based on the input, means for displaying the retrieved data to the user, means for converting the displayed data into speech and playing it back, means for verifying the user's authentication information in the database and generating an authentication result, and means for applying an artificial intelligence model to select the optimal information for the retrieved data. This enables the user to efficiently obtain the necessary information and understand it through voice guidance. Furthermore, highly secure user authentication and the selection of optimal information by the artificial intelligence model enable the provision of highly accurate information.

[0638] "Means for receiving user input" refers to an interface for users to provide specific information, and includes devices such as keyboards and touch panels.

[0639] "Means of searching a database" refers to a function that allows a server to query information based on input information obtained from a user and extract relevant information from within the database.

[0640] "Means of displaying searched data to the user" refers to displays and user interfaces that visually provide the extracted information to the user.

[0641] "A means of converting displayed data into audio and playing it back" refers to a system that converts text-based information into audio data and provides that audio data to the user through speakers or earphones.

[0642] "Means for verifying user authentication information in a database and generating authentication results" refers to a function that compares the authentication information provided by the user with the information stored in the database, and determines and generates whether authentication was successful or not.

[0643] "Means of applying artificial intelligence models" refers to a function in which a server uses AI technology to analyze and select the most relevant information from the retrieved data.

[0644] The system according to this invention comprises means for receiving user input, means for searching a database, means for displaying the retrieved data, means for converting the displayed data into speech and playing it back, and means for applying an artificial intelligence model to select the most suitable information for the retrieved data. It also includes means for verifying user authentication information and means for generating and playing back speech data.

[0645] System Overview

[0646] 1. User actions

[0647] Users log in to the system and enter keywords related to the technical terms or drawings they wish to search for. This allows users to obtain information tailored to their needs.

[0648] 2. Database Search

[0649] The terminal receives a request from the user and sends that request to the server. The server searches the database (e.g., MySQL or PostgreSQL) and extracts the relevant information.

[0650] 3. Displaying search results

[0651] Information sent from the server to the terminal is displayed in the terminal's user interface (e.g., built with React or Vue.js).

[0652] 4. Voice guidance

[0653] If a user selects specific information and requests voice guidance, the device resends the request to the server. The server uses speech synthesis technology (e.g., Google Text-to-Speech API or Amazon Polly) to convert the information into voice data and sends it to the device. The device then plays the voice data and provides voice guidance to the user.

[0654] Specific example

[0655] Login process

[0656] The user enters their ID and password into the system from their device and clicks the login button. The device sends this information to the server, which verifies the authentication information in its database. If authentication is successful, the server generates a login token and sends it back to the device. The device receives this token, and the user can begin using the system.

[0657] Search and display of technical terms

[0658] The user enters "earthquake-resistant design" into the search bar and clicks the search button. The device sends this request to the server. The server searches the database and extracts information related to "earthquake-resistant design." It then sends the results back to the device. The device displays this information in a list on its user interface.

[0659] Audio guidance for information

[0660] The user selects the item they want to know about from the search results list and clicks the voice guidance button. The device sends this request back to the server. The server converts the relevant information into audio data and sends it to the device. The device plays the audio data, and the user can acquire knowledge through the voice guidance.

[0661] Hardware and software to be used

[0662] 1. Hardware

[0663] Devices: Computers, tablets, smartphones, etc.

[0664] Server: A high-performance server machine installed in a data center.

[0665] 2. Software

[0666] Database software: MySQL, PostgreSQL

[0667] Server-side programs: Python, Node.js

[0668] Client-side programming: React, Vue.js

[0669] Text-to-Speech APIs: Google Text-to-Speech API, Amazon Polly

[0670] Artificial intelligence models: TensorFlow, PyTorch

[0671] Example of a prompt

[0672] "Please provide the latest technical information regarding earthquake-resistant design."

[0673] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0674] Program processing steps

[0675] Step 1: System startup and display of login screen

[0676] 1. The terminal starts up the system.

[0677] 2. The terminal displays a login screen to the user.

[0678] Input: System startup command

[0679] Output: Login screen

[0680] Step 2: User Login

[0681] 1. The user enters their ID and password and clicks the "Login" button.

[0682] 2. The terminal receives the entered ID and password and sends them to the server.

[0683] Enter: ID and password

[0684] Output: Sending an authentication request

[0685] Step 3: Perform user authentication

[0686] 1. The server checks the received ID and password in the database.

[0687] 2. The server generates an authentication result (success or failure) and sends it back to the terminal.

[0688] Enter: ID and password

[0689] Output: Authentication result (login token or error message)

[0690] Step 4: Processing authentication results

[0691] 1. If authentication is successful, the device will receive a login token and display the main menu.

[0692] 2. If authentication fails, the device will display an error message.

[0693] Input: Authentication result

[0694] Output: Main menu or error message

[0695] Step 5: Search for technical terms

[0696] 1. The user selects the "Search" option from the main menu and enters "earthquake-resistant design" in the search bar.

[0697] 2. The user clicks the "Search" button.

[0698] 3. The device receives this request and sends it to the server.

[0699] Input: Search keyword (earthquake-resistant design)

[0700] Output: Sending a search request

[0701] Step 6: Search the database

[0702] 1. The server searches the database and extracts information related to "earthquake-resistant design".

[0703] 2. The server sends the search results to the terminal in JSON format.

[0704] Input: Search keyword

[0705] Output: Search results (JSON format)

[0706] Step 7: Displaying search results

[0707] 1. The device renders the received search results into HTML and displays them to the user as a list.

[0708] Input: Search results (JSON format)

[0709] Output: Display of search results list

[0710] Step 8: Selecting detailed information and audio guidance

[0711] 1. The user selects a specific item from the search results list and clicks the "Voice Guidance" button.

[0712] 2. The device receives this request and sends an HTTP POST request to the server containing the ID of the relevant information.

[0713] Input: ID of the selected item

[0714] Output: Sending a voice guidance request

[0715] Step 9: Generate audio data

[0716] 1. The server uses a speech synthesis API to convert the relevant information into speech data.

[0717] 2. The server sends the generated audio data to the terminal.

[0718] Input: Text information of the selected item

[0719] Output: Audio data (MP3 format)

[0720] Step 10: Play the voice guidance

[0721] 1. The device plays the acquired audio data using an audio player.

[0722] 2. Users obtain information through voice guidance.

[0723] Input: Audio data (MP3 format)

[0724] Output: Playback of voice guidance

[0725] Step 11: Optimal information selection using an AI model

[0726] 1. The server uses an AI model to analyze the search results.

[0727] 2. The AI ​​model selects the most relevant information, and the server sends the result to the terminal.

[0728] Input: Search results (text data)

[0729] Output: Selected optimal information (JSON format)

[0730] Step 12: Displaying Optimal Information

[0731] 1. The device highlights the most relevant information it receives on the user interface.

[0732] Input: Selected optimal information (JSON format)

[0733] Output: Highlighting of optimal information

[0734] (Application Example 1)

[0735] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0736] In factory production lines, there is a lack of means for workers to quickly and efficiently obtain the necessary information when setting up or maintaining robots. Conventional technologies require manual verification of search results, which is time-consuming and labor-intensive, especially for complex procedures and troubleshooting. Therefore, new methods are needed to improve work efficiency and reduce the burden on workers.

[0737] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0738] In this invention, the server includes means for receiving user input, means for searching a database based on the input, means for displaying the retrieved data to the user, means for converting the displayed data into audio and playing it back, and means for outputting the retrieved data as an audio guide. This enables workers on a factory production line to quickly obtain the necessary information and proceed with their work efficiently.

[0739] "Means of receiving user input" refers to devices and interfaces used to obtain instructions and information from users. Examples include tablets, smart glasses, and keyboards.

[0740] "Means of searching a database" refers to algorithms and programs used to extract data from storage based on predetermined keywords or conditions.

[0741] "Means of displaying searched data to the user" refers to displays or screens that visually present the retrieved information to the user. Examples include tablet screens and smart glasses displays.

[0742] "Means of converting displayed data into audio and playing it back" refers to technology that converts visual information into audio using synthesized speech and plays that audio information back through speakers or headphones.

[0743] "Means of outputting as audio guidance" refers to programs or devices that provide audio guidance for specific information or instructions. For example, a system that provides audio guidance for work procedures within a factory would fall into this category.

[0744] An "artificial intelligence model" refers to a machine learning or deep learning model used to perform inference and prediction based on given data. Examples include neural networks using TensorFlow or PyTorch.

[0745] "A means of verifying user authentication information in a database and generating authentication results" refers to technology that checks the authentication information of a user when they access a system and determines whether the user has legitimate access rights.

[0746] One embodiment of this invention is a system for enabling workers to efficiently set up and maintain robots on a factory production line. This system is realized through the following configuration and process.

[0747] Basic System Configuration

[0748] The system includes means for receiving user input, means for searching a database, means for displaying the retrieved data to the user, means for converting the displayed data into audio and playing it back, and means for outputting it as an audio guide. Furthermore, it also includes means for applying an artificial intelligence model to select the most appropriate information from the retrieved data, and means for verifying the user's authentication information.

[0749] Hardware and software

[0750] hardware

[0751] This system utilizes interface devices such as tablets, smart glasses, and head-mounted displays installed on the factory's production line. These devices function as terminals operated by workers. A server is also required for overall system control and data processing.

[0752] software

[0753] The software includes the following elements:

[0754] Languages: Python, JavaScript

[0755] Frameworks: Flask (backend), React (frontend)

[0756] Libraries: TensorFlow (AI model), SpeechRecognition, Pygame (speech management)

[0757] Processing flow

[0758] User operation and interface

[0759] Users access the system using tablets or smart glasses within the factory. When a user enters keywords such as "Please tell me how to deal with a specific equipment problem" on the tablet screen, the input is sent to the server.

[0760] Database Search

[0761] The server searches the database based on the received request and extracts the relevant information. The extracted information is then preprocessed and sent to the user's terminal.

[0762] Display of search results and audio guide

[0763] The terminal displays search results on the screen and simultaneously prepares an audio guide. When the user reviews the search results and accesses specific procedures or settings changes as needed, the information is played back as audio. For example, to learn about equipment maintenance procedures, the user can enter a prompt such as, "Please tell me the maintenance procedure for the cooling system."

[0764] AI optimization feature

[0765] The server uses an AI model to select the most relevant information from the search results. This process allows the user to obtain the necessary information in the shortest possible time. Specifically, this involves neural networks using TensorFlow or PyTorch.

[0766] Audio guide generation and playback

[0767] The server uses speech synthesis technology to convert the relevant information into audio data. This technology includes gTTS (Google Text-to-Speech), among others. The converted audio data is sent to the terminal, allowing the user to receive voice guidance in real time.

[0768] This allows workers on the factory production line to quickly and efficiently acquire information and proceed with their work. At the same time, it reduces the burden on workers and improves overall productivity.

[0769] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0770] Step 1:

[0771] Users log in to the system via a tablet, smart glasses, or head-mounted display.

[0772] Input: Enter your User ID and password.

[0773] Processing: The terminal sends the entered authentication information to the server, and the server searches the database to verify the user's authentication information.

[0774] Output: An authentication result is generated, and a login token is sent back to the device.

[0775] Specific operation: Once authentication is successful, the user will be able to access the system's main screen.

[0776] Step 2:

[0777] Users enter keywords and send search requests through the interface of a tablet or smart glasses.

[0778] Input: The user enters keywords into the search bar and clicks the search button.

[0779] Processing: The terminal receives user input and sends it to the server.

[0780] Output: Requests containing the keyword reach the server.

[0781] Specific action: The server prepares to retrieve relevant information from the database.

[0782] Step 3:

[0783] The server searches the database and retrieves relevant information.

[0784] Input: Keyword search request based on user input.

[0785] Processing: The server searches the database and extracts relevant information. It then uses an AI model (such as TensorFlow) to select the optimal data.

[0786] Output: Extracted relevant information.

[0787] Specific operation: The AI ​​model analyzes the search results and selects the most relevant information.

[0788] Step 4:

[0789] The server sends the extracted information to the user's terminal.

[0790] Input: Extracted relevant information.

[0791] Processing: The server transfers the detected information to the user's terminal.

[0792] Output: Related information is displayed on the user's terminal.

[0793] Specific operation: The results are displayed on the user's device, allowing the user to visually confirm the information.

[0794] Step 5:

[0795] The user requests an audio guide based on the information displayed.

[0796] Input: A request from the user for audio guidance regarding the displayed information.

[0797] Processing: The terminal resends this request to the server.

[0798] Output: A request for audio guidance is sent to the server.

[0799] Specific action: The server prepares to convert the specified information into audio data.

[0800] Step 6:

[0801] The server converts the target information into speech and generates audio data.

[0802] Input: Text information based on requests for audio guides.

[0803] Processing: The server uses speech synthesis technology (such as gTTS) to convert text information into speech data.

[0804] Output: Generated audio data.

[0805] Specific action: Audio data is generated and ready to be sent to the device.

[0806] Step 7:

[0807] The device plays the generated audio data to the user.

[0808] Input: Generated audio data.

[0809] Processing: The device receives the audio data and plays it through the speaker or headphones.

[0810] Output: Audio guide.

[0811] Specific operation: Users can obtain the necessary information through audio guidance and proceed with their tasks.

[0812] This allows users to quickly and efficiently obtain the necessary information within the factory and perform appropriate tasks.

[0813] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0814] The system according to the present invention includes means for receiving user input, searching a database, and displaying the retrieved data; means for converting the displayed data into speech and playing it back; and means for applying an artificial intelligence model to select the most suitable information from the retrieved data. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, the system provides optimal information tailored to the user's emotions.

[0815] System Overview

[0816] 1. User actions

[0817] Users log in to the system using a terminal and enter keywords related to the technical terms or drawings they wish to search for. This allows users to obtain information tailored to their needs.

[0818] 2. Database Search

[0819] The terminal receives a request from the user and sends that request to the server. The server searches the database and extracts the relevant information.

[0820] 3. Displaying search results

[0821] The server sends the search results to the terminal, and the terminal displays them in the user interface.

[0822] 4. Voice guidance

[0823] If a user selects specific information and requests voice guidance, the device resends the request to the server. The server converts the information into audio data and sends it to the device. The device plays the audio data, and the user can obtain the necessary information through voice guidance.

[0824] 5. Recognition of emotions

[0825] The emotion engine recognizes the user's emotions in real time. It determines emotions from the user's tone of voice and facial expressions.

[0826] 6. Information Optimization

[0827] The server utilizes emotional information obtained from the emotion engine and uses an artificial intelligence model to select the most appropriate information.

[0828] 7. Voice guidance that responds to emotions

[0829] The server adjusts the content and tone of the voice guidance according to the recognized emotion and sends it to the terminal. The user can then receive voice guidance that matches their emotions.

[0830] Specific example

[0831] Login process

[0832] The user enters their ID and password into the system from their device and clicks the login button. The device sends this information to the server, which verifies the user's authentication information in its database. If authentication is successful, the server generates a login token and sends it back to the device. The device receives this token, and the user can begin using the system.

[0833] Search and display of technical terms

[0834] The user enters "earthquake-resistant design" into the search bar and clicks the search button. The device sends this request to the server. The server searches the database and extracts information related to "earthquake-resistant design." It then sends the results back to the device. The device displays this information in a list on its user interface.

[0835] Audio guidance for information

[0836] The user selects the item they want to know about from the search results list and clicks the voice guidance button. The device sends this request back to the server. The server converts the relevant information into audio data and sends it to the device. The device plays the audio data, and the user can acquire knowledge through the voice guidance.

[0837] Emotion recognition and customization

[0838] While the user is operating the system, the emotion engine recognizes their emotions from their voice tone and facial expressions. For example, if the system determines that the user is stressed, it simplifies the voice guidance and softens the tone. The server receives the output from the emotion engine and sends back the information and voice data with appropriate adjustments. The terminal plays the adjusted voice data, and the user receives emotionally sensitive guidance.

[0839] Other features

[0840] This system incorporates a mechanism for utilizing accumulated emotional information in subsequent interactions. The server stores the user's emotional history and optimizes future interactions based on this history. Furthermore, the emotional information recognized by the emotion engine is fed back to an artificial intelligence model for more accurate information selection. For example, by avoiding information that the user found unpleasant based on past history, the system can be made more user-friendly.

[0841] This system allows users to quickly obtain explanations of technical terms and diagrams, deepening their understanding of on-site survey reports. Furthermore, appropriate voice guidance tailored to the user's emotions improves their understanding of related construction work and on-site tasks. As a result, overall work efficiency is significantly improved.

[0842] The following describes the processing flow.

[0843] Login process

[0844] Step 1:

[0845] The user starts up their device and opens the login screen. The user enters their ID and password and clicks the login button.

[0846] Step 2:

[0847] The device sends the authentication information entered by the user to the server.

[0848] Step 3:

[0849] The server checks the received authentication information in the database and performs user authentication.

[0850] Step 4:

[0851] The server generates an authentication result (success or failure), and if successful, generates a login token.

[0852] Step 5:

[0853] The server sends the login token back to the device.

[0854] Step 6:

[0855] The device receives the login token and enables the user to begin using the system.

[0856] Search and display of technical terms

[0857] Step 1:

[0858] The user enters a search keyword (e.g., "earthquake-resistant design") into the device's search bar and clicks the search button.

[0859] Step 2:

[0860] The device sends a search request and search keywords to the server.

[0861] Step 3:

[0862] The server searches the database using the search keywords it received.

[0863] Step 4:

[0864] The server extracts relevant information from the database and generates results.

[0865] Step 5:

[0866] The server sends the search results to the terminal.

[0867] Step 6:

[0868] The search results received by the device are displayed to the user in a list.

[0869] Audio guidance for information

[0870] Step 1:

[0871] The user selects the item they want to know about from the list of search results and clicks the voice guidance button.

[0872] Step 2:

[0873] The device sends a voice guidance request to the server.

[0874] Step 3:

[0875] The server begins processing the information to convert it into audio data.

[0876] Step 4:

[0877] The server generates audio data and sends it to the terminal.

[0878] Step 5:

[0879] The device plays back the received audio data and provides voice guidance to the user.

[0880] Emotion recognition and customization

[0881] Step 1:

[0882] While the user is operating the system, an emotion engine built into the device recognizes the user's emotions in real time.

[0883] Step 2:

[0884] The emotion engine analyzes the user's emotions from their voice tone and facial expressions, and generates the results.

[0885] Step 3:

[0886] The device sends the output of the emotion engine to the server.

[0887] Step 4:

[0888] The server receives emotional information from the emotion engine and uses it to customize the information and voice guidance it provides.

[0889] Step 5:

[0890] The server sends the adjusted information and audio data to the terminal.

[0891] Step 6:

[0892] The device plays updated audio data, providing users with emotionally sensitive guidance.

[0893] Information optimization (application of artificial intelligence models)

[0894] Step 1:

[0895] The server inputs the search results extracted from the database into an artificial intelligence model.

[0896] Step 2:

[0897] The server uses an artificial intelligence model to analyze the search results and identify the most relevant information.

[0898] Step 3:

[0899] The server selects optimized information and generates data to provide to the user.

[0900] These processing steps enable the system to efficiently provide information to users, supporting explanations of technical terms and descriptions of on-site work. Furthermore, the introduction of an emotion engine allows for optimal voice guidance tailored to the user's emotions, thereby improving the user experience.

[0901] (Example 2)

[0902] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0903] Conventional information retrieval systems primarily focus on searching databases based on user input and displaying results, without considering the user's emotions or circumstances. Similarly, voice guidance simply converts text data into speech, failing to provide content and tone that consider the user's psychological state. This can lead to users experiencing stress when obtaining necessary information, resulting in decreased usability and satisfaction. Furthermore, the selection of optimal information using artificial intelligence models and enhanced authentication security remain insufficient.

[0904] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0905] In this invention, the server is

[0906] An emotion recognition engine that recognizes the user's emotions in real time,

[0907] A means for adjusting the content and tone of voice guidance based on the information obtained by the emotion recognition engine,

[0908] A means of applying an artificial intelligence model to select the most suitable information for the retrieved data,

[0909] This includes providing optimal information tailored to the user's emotions, and the content and tone of the voice guidance are adjusted according to the user's psychological state, resulting in a more comfortable and effective information acquisition experience.

[0910] "Means for receiving user input" refers to input interfaces for users to enter information, including devices such as keyboards and touch panels.

[0911] "Means of searching a database" refers to algorithms and systems used to retrieve relevant information from a pre-built database based on user input.

[0912] "Means of displaying searched data to the user" refers to displays or graphical user interfaces that show search results in a format that is visually accessible to the user.

[0913] "Means of converting to audio and playing it back" refers to speech synthesis programs and hardware that convert text data into audio data and play it back through speakers.

[0914] An "emotion recognition engine" refers to a software system that analyzes data such as the user's voice tone and facial expressions to recognize their emotions in real time.

[0915] "Means for adjusting the content and tone of voice guidance" refers to a program that adjusts the content and tone of voice guidance to match the user's psychological state, based on the output of the emotion recognition engine.

[0916] "Means of applying artificial intelligence models" refers to algorithms and systems that utilize machine learning and deep learning to select the most relevant information from retrieved data.

[0917] "Means for verifying user authentication information in a database and generating authentication results" refers to a program and system that compares the authentication information entered by the user with existing data in the database and determines the success or failure of authentication based on the results.

[0918] The system according to the present invention includes means for receiving user input, searching a database based on that input, and displaying the retrieved data; means for converting the displayed data into speech and playing it back; and means for applying an artificial intelligence model to select the most suitable information from the retrieved data. It also incorporates an emotion recognition engine that recognizes the user's emotions in real time and provides optimal voice guidance according to the user's emotions.

[0919] Hardware and software to be used

[0920] Device: A device including a personal computer, tablet, and smartphone.

[0921] Server: Use a high-performance server (e.g., an Amazon Web Services EC2 instance).

[0922] Database: Use a Relational Database Management System (e.g., MySQL, PostgreSQL).

[0923] Emotion recognition engine: Uses facial recognition software (e.g., OpenCV) and speech analysis software.

[0924] Artificial intelligence model: Machine learning models using TensorFlow or PyTorch are used.

[0925] Text-to-speech engine: Uses text-to-speech software (e.g., Google Text-to-Speech).

[0926] Search process

[0927] The user enters search keywords on their device and sends the request to the server. The server searches the database and retrieves the relevant information. The retrieved information is sent back to the device and displayed on the user interface. This allows the user to quickly obtain the information they need.

[0928] As a concrete example, when a user enters "earthquake-resistant design" into the search bar of their device and clicks the search button, the device sends this request to the server. The server searches the database and sends back information related to "earthquake-resistant design" to the device, which then displays this information in a list.

[0929] Voice guidance process

[0930] When a user selects specific information from the search results and wishes to receive voice guidance, they click the voice guidance button. This request is sent from the device to the server, which converts the relevant information into audio data and sends it back to the device. The device then plays this audio data, allowing the user to obtain the necessary information by voice.

[0931] As a concrete example, when a user selects the item "Fundamentals of Earthquake-Resistant Design" and clicks the voice guidance button, the device resends this request to the server. The server converts the information into audio data, and the device plays that audio.

[0932] Emotion recognition and information optimization

[0933] The emotion recognition engine recognizes the user's voice tone and facial expressions in real time and sends the obtained emotion information to the server. Based on this emotion information, the server uses an artificial intelligence model to select the most appropriate information and adjust the content and tone of the voice guidance. As a result, the user receives information guidance that is best suited to their emotions.

[0934] As a concrete example, when a user is listening to voice guidance, the emotion recognition engine detects stress. This information is sent to a server, which uses an AI model to simplify the content of the voice guidance, soften the tone, and regenerate the voice data, which is then sent to the terminal. The terminal plays the adjusted voice guidance, and the user receives information guidance with reduced stress.

[0935] Examples of input prompts for a generative AI model

[0936] "I want to search for information on earthquake-resistant design."

[0937] System: "Please enter 'earthquake-resistant design' in the search bar and click the search button."

[0938] User: Type "earthquake-resistant design" and click the search button.

[0939] System: "Information regarding earthquake-resistant design is displayed. If you would like audio guidance, please select an item and click the audio guidance button."

[0940] These features enable the system to quickly and effectively retrieve the information users need and provide optimal guidance tailored to their emotions.

[0941] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0942] Step 1:

[0943] The steps a user takes to enter their ID and password and attempt to log in.

[0944] The user enters their ID and password on the device's login interface and clicks the login button. The device sends this authentication information to the server. The server searches its database and verifies that the entered ID and password match. If authentication is successful, the server generates a login token and sends it back to the device. The device stores this token, and the user can then access the system.

[0945] Specific actions:

[0946] The user enters "ID: user123, Password: password123" and clicks the "Login" button.

[0947] The terminal sends the entered authentication information to the server in JSON format.

[0948] The server retrieves the corresponding user information from the database and verifies that it matches.

[0949] The server generates a "login token ABC123" and sends it back to the terminal.

[0950] The device stores the token it receives, allowing the user to access the system.

[0951] Input: User ID and password

[0952] Output: Login token

[0953] Step 2:

[0954] Steps for a user to enter search keywords and start a search.

[0955] The user enters the keyword they want to search for in the device's search bar and clicks the search button. The device sends the request to the server. The server searches its database based on the received keyword and retrieves the relevant information. This retrieved information is sent from the server to the device and displayed to the user.

[0956] Specific actions:

[0957] The user enters "earthquake-resistant design" and clicks the search button.

[0958] The device sends the search keyword "earthquake-resistant design" to the server as a POST request.

[0959] The server executes a database query to extract information related to "earthquake-resistant design."

[0960] The server returns the acquired information to the terminal in JSON format.

[0961] The device parses the information it receives and displays it in a user-friendly list format.

[0962] Input: Search keywords

[0963] Output: List of search results

[0964] Step 3:

[0965] Steps for users to request voice guidance

[0966] The user selects specific information from the displayed search results and clicks the voice guidance button. This request is resent from the device to the server. The server converts the relevant information into audio data and sends it to the device. The device plays this audio data, allowing the user to obtain the necessary information by voice.

[0967] Specific actions:

[0968] The user clicks the voice guidance button next to the item "Fundamentals of Earthquake-Resistant Design".

[0969] The device sends a "voice guidance request" to the server.

[0970] The server uses a text-to-speech engine (e.g., Google Text-to-Speech) to convert text related to "Fundamentals of Earthquake-Resistant Design" into speech.

[0971] The server sends the generated audio file back to the terminal.

[0972] The device plays audio data, and the user receives voice guidance.

[0973] Input: Voice guidance request (specific information)

[0974] Output: Audio data

[0975] Step 4:

[0976] The procedure by which the emotion recognition engine detects the user's emotions

[0977] While the user is operating the system, the emotion recognition engine analyzes the user's voice tone and facial expressions in real time to acquire emotional information. This emotional information is then sent to the server.

[0978] Specific actions:

[0979] While the user is operating the system, the emotion recognition engine uses the camera and microphone to capture the user's face and voice.

[0980] The device analyzes the captured data in real time to obtain "emotional information."

[0981] The device sends the emotional information it has acquired to the server.

[0982] Input: User's voice tone and facial expression

[0983] Output: Emotional information

[0984] Step 5:

[0985] Steps to optimize information based on emotional information

[0986] The server uses an artificial intelligence model to select the most appropriate information for the user based on the emotional information transmitted by the emotion recognition engine. It adjusts the content and tone of the voice guidance according to the user's emotions.

[0987] Specific actions:

[0988] The server receives emotional information and uses an artificial intelligence model (e.g., TensorFlow) to determine the optimal response.

[0989] The server makes adjustments such as simplifying the content of the voice guidance and softening the tone.

[0990] The server converts the adjusted text back into audio data.

[0991] Input: Sentiment information

[0992] Output: Adjusted audio data

[0993] Step 6:

[0994] Instructions for playing the adjusted voice guidance

[0995] The server sends the adjusted audio data to the terminal. The terminal plays this audio data and provides the user with the most suitable voice guidance.

[0996] Specific actions:

[0997] The server sends the adjusted audio data to the terminal.

[0998] The device plays the audio data it received.

[0999] Users obtain information by listening to pre-arranged voice guidance.

[1000] Input: Adjusted audio data

[1001] Output: Played audio guidance

[1002] (Application Example 2)

[1003] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1004] In factory work support, there is a need to provide workers with the information they require quickly and accurately, while also providing optimal support that takes into account their emotions. However, conventional systems have been unable to recognize workers' emotions and optimize information accordingly, resulting in problems such as a decrease in user experience and work efficiency.

[1005] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user input, means for searching a database based on the input, means for displaying the retrieved data to the user, means for converting the displayed data into speech and playing it back, means for recognizing the user's emotions, and means for adjusting the presentation of information based on the recognized emotions. This makes it possible to provide necessary information quickly and appropriately while taking into account the worker's emotions, thereby improving work efficiency and user experience.

[1006] "Means for receiving user input" refers to means of receiving user input such as voice input or touch operations, and recognizing them within the system.

[1007] "Means of searching a database" refers to means of extracting relevant information from a database based on user input.

[1008] "Means of displaying searched data to the user" refers to means of providing search results to the user visually. This includes displays and head-mounted displays.

[1009] "Means of converting data into audio and playing it back" refers to methods of converting text data into audio data and providing it to the user via voice.

[1010] "Means of recognizing user emotions" refers to methods of detecting emotions from the user's tone of voice, facial expressions, etc., and making the system recognize them.

[1011] "Means of adjusting information presentation based on recognized emotions" refers to means of optimizing the content and presentation of information presented according to the user's emotional state.

[1012] An "artificial intelligence model" is an algorithm or learning model used to process and analyze data and derive the optimal result.

[1013] A "login token" is data that represents temporary authentication information that authenticated users use to access the system.

[1014] The system that realizes this application example is a factory work support robot system. The robot provides information to workers and improves work efficiency by accepting user input, searching a database, displaying search results and providing voice guidance, and recognizing the user's emotions to provide optimal support.

[1015] The server has means to recognize user input, such as voice input or touch gestures. Based on user input, the server searches the database and extracts relevant information. Database search tools such as SQL or Elasticsearch are used for this database search.

[1016] The extracted information is sent to a terminal and displayed visually to the user. Smart glasses or head-mounted displays are used for this visual display. Furthermore, Text-to-Speech (TTS) technology is used to convert the extracted data into speech and play it back.

[1017] The robot employs an Emotion Engine to recognize emotions from the tone of the worker's voice and facial expressions. This emotion recognition engine detects the user's emotional state in real time, and that information is sent to the server.

[1018] The server uses emotional information to present optimal information through a generative AI model. The AI ​​model is designed to optimize the content and presentation of information according to emotions, providing appropriate support to the user.

[1019] As a concrete example, a user enters "earthquake-resistant design" into the search bar and clicks the search button. This request is sent to the server, which searches the database and extracts relevant information. The results are sent back to the terminal and displayed on the user interface. Furthermore, the displayed information is converted into speech and played back to the user using TTS (Text-to-Speech) technology.

[1020] Next, if the server detects that the user is experiencing stress, it uses that information to adjust the tone of its information delivery. For example, it might translate the information into simpler language and deliver it in a gentler tone.

[1021] This system will enable users to quickly obtain the information they need and receive emotionally sensitive support. Based on the following example prompts, the system will search for and provide the necessary information to the user.

[1022] Example of a prompt:

[1023] Details of a system where a user enters the keyword "earthquake-resistant design," and a factory work support robot searches a database to display information and provide voice guidance. The system also includes a feature to simplify information and soften the tone if the user is experiencing stress.

[1024] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1025] Step 1:

[1026] The user gives instructions to the device via voice input or touch operation. The user enters a keyword, such as "earthquake-resistant design." This input data (keyword) is sent to the system.

[1027] Step 2:

[1028] The terminal sends the received user input data to the server. The server searches the database based on this input data. The server retrieves relevant information using search tools such as SQL or Elasticsearch. The output is search results containing the relevant information.

[1029] Step 3:

[1030] The server sends the search results to the terminal. The terminal receives this data and displays the searched data visually to the user. Smart glasses or head-mounted displays are used for this visual display. The displayed information is the output.

[1031] Step 4:

[1032] If the user selects specific information and requests voice guidance, the device sends the selected information back to the server. The server uses Text-to-Speech (TTS) technology to convert that information into voice data.

[1033] Step 5:

[1034] The server sends the converted audio data to the terminal. The terminal plays this audio data, and the user obtains information through the voice guidance. The played voice guidance is the output.

[1035] Step 6:

[1036] When a user operates the system, the terminal captures the user's voice tone and facial expressions in real time for emotion recognition. An Emotion Engine is used for emotion recognition. This input data is then sent to the server.

[1037] Step 7:

[1038] The server retrieves emotional data from the Emotion Engine and provides this information to a generating AI model. The AI ​​model analyzes the emotional data and adjusts the optimal way to present the information. The adjusted information is then sent from the server to the terminal.

[1039] Step 8:

[1040] The device then presents the adjusted information to the user again. For example, if the server detects that the user is experiencing stress, it plays a simplified voice guidance with a softer tone. Through this process, the user receives appropriate support that is sensitive to their emotions.

[1041] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1042] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1043] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1044] [Third Embodiment]

[1045] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1046] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1047] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1048] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1049] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1050] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1051] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1052] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1053] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1054] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1055] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1056] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1057] The system according to the present invention comprises means for receiving user input, means for searching a database, means for displaying the retrieved data, means for converting the displayed data into speech and playing it back, and means for applying an artificial intelligence model to select the most suitable information for the retrieved data. It also includes means for verifying user authentication information and means for generating and playing back speech data.

[1058] System Overview

[1059] 1. User actions

[1060] Users log in to the system and enter keywords related to the technical terms or drawings they wish to search for. This allows users to obtain information tailored to their needs.

[1061] 2. Database Search

[1062] The terminal receives a request from the user and sends that request to the server. The server searches the database and extracts the relevant information.

[1063] 3. Displaying search results

[1064] The retrieved information is sent from the server to the terminal, which then displays it in the user interface.

[1065] 4. Voice guidance

[1066] If a user selects specific information and requests voice guidance, the device resends the request to the server. The server converts the information into audio data and sends it to the device. The device plays the audio data, and the user can obtain the necessary information through voice guidance.

[1067] Specific example

[1068] Login process

[1069] The user enters their ID and password into the system from their device and clicks the login button. The device sends this information to the server, which verifies the user's authentication information in its database. If authentication is successful, the server generates a login token and sends it back to the device. The device receives this token, and the user can begin using the system.

[1070] Search and display of technical terms

[1071] The user enters "earthquake-resistant design" into the search bar and clicks the search button. The device sends this request to the server. The server searches the database and extracts information related to "earthquake-resistant design." It then sends the results back to the device. The device displays this information in a list on its user interface.

[1072] Audio guidance for information

[1073] The user selects the item they want to know about from the search results list and clicks the voice guidance button. The device sends this request back to the server. The server converts the relevant information into audio data and sends it to the device. The device plays the audio data, and the user can acquire knowledge through the voice guidance.

[1074] Other features

[1075] This system includes an artificial intelligence model for selecting the most relevant information from the searched data. Specifically, the server uses the AI ​​model to analyze the search results and select the information most relevant to the user. This process allows the user to obtain the necessary information in a short amount of time.

[1076] Furthermore, a specific algorithm is used for generating and playing back audio data. The server is equipped with speech synthesis technology to convert text information into speech, enabling it to respond quickly to user requests for voice guidance. The terminal appropriately plays back the audio data, providing users with real-time voice guidance.

[1077] This system allows users to quickly obtain explanations of technical terms and diagrams, deepening their understanding of on-site survey reports. It also improves their understanding of ancillary work and on-site tasks, leading to overall improved work efficiency.

[1078] The following describes the processing flow.

[1079] Login process

[1080] Step 1:

[1081] The user starts up their device and opens the login screen. The user enters their ID and password and clicks the login button.

[1082] Step 2:

[1083] The device sends the authentication information entered by the user to the server.

[1084] Step 3:

[1085] The server checks the received authentication information in the database and performs user authentication.

[1086] Step 4:

[1087] The server generates an authentication result (success or failure), and if successful, generates a login token.

[1088] Step 5:

[1089] The server sends the login token back to the device.

[1090] Step 6:

[1091] The device receives the login token and enables the user to begin using the system.

[1092] Search and display of technical terms

[1093] Step 1:

[1094] The user enters a search keyword (e.g., "earthquake-resistant design") into the device's search bar and clicks the search button.

[1095] Step 2:

[1096] The device sends a search request and search keywords to the server.

[1097] Step 3:

[1098] The server searches the database using the search keywords it received.

[1099] Step 4:

[1100] The server extracts relevant information from the database and generates results.

[1101] Step 5:

[1102] The server sends the search results to the terminal.

[1103] Step 6:

[1104] The search results received by the device are displayed to the user in a list.

[1105] Audio guidance for information

[1106] Step 1:

[1107] The user selects the item they want to know about from the list of search results and clicks the voice guidance button.

[1108] Step 2:

[1109] The device sends a voice guidance request to the server.

[1110] Step 3:

[1111] The server begins processing the information to convert it into audio data.

[1112] Step 4:

[1113] The server generates audio data and sends it to the terminal.

[1114] Step 5:

[1115] The device plays back the received audio data and provides voice guidance to the user.

[1116] Information optimization (application of artificial intelligence models)

[1117] Step 1:

[1118] The server inputs the search results extracted from the database into an artificial intelligence model.

[1119] Step 2:

[1120] The server uses an artificial intelligence model to analyze the search results and identify the most relevant information.

[1121] Step 3:

[1122] The server selects optimized information and generates data to provide to the user.

[1123] Verification of authentication information

[1124] Step 1:

[1125] The user enters and submits authentication information (ID and password) via their device.

[1126] Step 2:

[1127] The server checks the received authentication information in the database.

[1128] Step 3:

[1129] The server generates an authentication result, and if authentication is successful, it issues a login token.

[1130] Step 4:

[1131] The server sends the authentication result or login token to the device.

[1132] Audio data generation and playback

[1133] Step 1:

[1134] The server receives the user's voice guidance request.

[1135] Step 2:

[1136] The server generates audio data based on the corresponding text information.

[1137] Step 3:

[1138] The server generates audio data and sends it to the terminal.

[1139] Step 4:

[1140] The device plays back the audio data it receives and provides it to the user.

[1141] These processing steps enable the system to efficiently provide information to users and support explanations of technical terms and on-site work procedures.

[1142] (Example 1)

[1143] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1144] In today's world, it is crucial for users to obtain necessary information quickly and accurately. However, traditional systems require users to search for information from vast databases and expend considerable time and effort to understand it. Furthermore, systems that can receive information not only in text format but also through voice guidance are limited. In addition, many systems lack sufficient user authentication security and the ability to provide the most optimal information for the user's needs. A new system is needed to address these challenges.

[1145] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1146] In this invention, the server includes means for receiving user input, means for searching a database based on the input, means for displaying the retrieved data to the user, means for converting the displayed data into speech and playing it back, means for verifying the user's authentication information in the database and generating an authentication result, and means for applying an artificial intelligence model to select the optimal information for the retrieved data. This enables the user to efficiently obtain the necessary information and understand it through voice guidance. Furthermore, highly secure user authentication and the selection of optimal information by the artificial intelligence model enable the provision of highly accurate information.

[1147] "Means for receiving user input" refers to an interface for users to provide specific information, and includes devices such as keyboards and touch panels.

[1148] "Means of searching a database" refers to a function that allows a server to query information based on input information obtained from a user and extract relevant information from within the database.

[1149] "Means of displaying searched data to the user" refers to displays and user interfaces that visually provide the extracted information to the user.

[1150] "A means of converting displayed data into audio and playing it back" refers to a system that converts text-based information into audio data and provides that audio data to the user through speakers or earphones.

[1151] "Means for verifying user authentication information in a database and generating authentication results" refers to a function that compares the authentication information provided by the user with the information stored in the database, and determines and generates whether authentication was successful or not.

[1152] "Means of applying artificial intelligence models" refers to a function in which a server uses AI technology to analyze and select the most relevant information from the retrieved data.

[1153] The system according to this invention comprises means for receiving user input, means for searching a database, means for displaying the retrieved data, means for converting the displayed data into speech and playing it back, and means for applying an artificial intelligence model to select the most suitable information for the retrieved data. It also includes means for verifying user authentication information and means for generating and playing back speech data.

[1154] System Overview

[1155] 1. User actions

[1156] Users log in to the system and enter keywords related to the technical terms or drawings they wish to search for. This allows users to obtain information tailored to their needs.

[1157] 2. Database Search

[1158] The terminal receives a request from the user and sends that request to the server. The server searches the database (e.g., MySQL or PostgreSQL) and extracts the relevant information.

[1159] 3. Displaying search results

[1160] Information sent from the server to the terminal is displayed in the terminal's user interface (e.g., built with React or Vue.js).

[1161] 4. Voice guidance

[1162] If a user selects specific information and requests voice guidance, the device resends the request to the server. The server uses speech synthesis technology (e.g., Google Text-to-Speech API or Amazon Polly) to convert the information into voice data and sends it to the device. The device then plays the voice data and provides voice guidance to the user.

[1163] Specific example

[1164] Login process

[1165] The user enters their ID and password into the system from their device and clicks the login button. The device sends this information to the server, which verifies the authentication information in its database. If authentication is successful, the server generates a login token and sends it back to the device. The device receives this token, and the user can begin using the system.

[1166] Search and display of technical terms

[1167] The user enters "earthquake-resistant design" into the search bar and clicks the search button. The device sends this request to the server. The server searches the database and extracts information related to "earthquake-resistant design." It then sends the results back to the device. The device displays this information in a list on its user interface.

[1168] Audio guidance for information

[1169] The user selects the item they want to know about from the search results list and clicks the voice guidance button. The device sends this request back to the server. The server converts the relevant information into audio data and sends it to the device. The device plays the audio data, and the user can acquire knowledge through the voice guidance.

[1170] Hardware and software to be used

[1171] 1. Hardware

[1172] Devices: Computers, tablets, smartphones, etc.

[1173] Server: A high-performance server machine installed in a data center.

[1174] 2. Software

[1175] Database software: MySQL, PostgreSQL

[1176] Server-side programs: Python, Node.js

[1177] Client-side programming: React, Vue.js

[1178] Text-to-Speech APIs: Google Text-to-Speech API, Amazon Polly

[1179] Artificial intelligence models: TensorFlow, PyTorch

[1180] Example of a prompt

[1181] "Please provide the latest technical information regarding earthquake-resistant design."

[1182] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1183] Program processing steps

[1184] Step 1: System startup and display of login screen

[1185] 1. The terminal starts up the system.

[1186] 2. The terminal displays a login screen to the user.

[1187] Input: System startup command

[1188] Output: Login screen

[1189] Step 2: User Login

[1190] 1. The user enters their ID and password and clicks the "Login" button.

[1191] 2. The terminal receives the entered ID and password and sends them to the server.

[1192] Enter: ID and password

[1193] Output: Sending an authentication request

[1194] Step 3: Perform user authentication

[1195] 1. The server checks the received ID and password in the database.

[1196] 2. The server generates an authentication result (success or failure) and sends it back to the terminal.

[1197] Enter: ID and password

[1198] Output: Authentication result (login token or error message)

[1199] Step 4: Processing authentication results

[1200] 1. If authentication is successful, the device will receive a login token and display the main menu.

[1201] 2. If authentication fails, the device will display an error message.

[1202] Input: Authentication result

[1203] Output: Main menu or error message

[1204] Step 5: Search for technical terms

[1205] 1. The user selects the "Search" option from the main menu and enters "earthquake-resistant design" in the search bar.

[1206] 2. The user clicks the "Search" button.

[1207] 3. The device receives this request and sends it to the server.

[1208] Input: Search keyword (earthquake-resistant design)

[1209] Output: Sending a search request

[1210] Step 6: Search the database

[1211] 1. The server searches the database and extracts information related to "earthquake-resistant design".

[1212] 2. The server sends the search results to the terminal in JSON format.

[1213] Input: Search keyword

[1214] Output: Search results (JSON format)

[1215] Step 7: Displaying search results

[1216] 1. The device renders the received search results into HTML and displays them to the user as a list.

[1217] Input: Search results (JSON format)

[1218] Output: Display of search results list

[1219] Step 8: Selecting detailed information and audio guidance

[1220] 1. The user selects a specific item from the search results list and clicks the "Voice Guidance" button.

[1221] 2. The device receives this request and sends an HTTP POST request to the server containing the ID of the relevant information.

[1222] Input: ID of the selected item

[1223] Output: Sending a voice guidance request

[1224] Step 9: Generate audio data

[1225] 1. The server uses a speech synthesis API to convert the relevant information into speech data.

[1226] 2. The server sends the generated audio data to the terminal.

[1227] Input: Text information of the selected item

[1228] Output: Audio data (MP3 format)

[1229] Step 10: Play the voice guidance

[1230] 1. The device plays the acquired audio data using an audio player.

[1231] 2. Users obtain information through voice guidance.

[1232] Input: Audio data (MP3 format)

[1233] Output: Playback of voice guidance

[1234] Step 11: Optimal information selection using an AI model

[1235] 1. The server uses an AI model to analyze the search results.

[1236] 2. The AI ​​model selects the most relevant information, and the server sends the result to the terminal.

[1237] Input: Search results (text data)

[1238] Output: Selected optimal information (JSON format)

[1239] Step 12: Displaying Optimal Information

[1240] 1. The device highlights the most relevant information it receives on the user interface.

[1241] Input: Selected optimal information (JSON format)

[1242] Output: Highlighting of optimal information

[1243] (Application Example 1)

[1244] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1245] In factory production lines, there is a lack of means for workers to quickly and efficiently obtain the necessary information when setting up or maintaining robots. Conventional technologies require manual verification of search results, which is time-consuming and labor-intensive, especially for complex procedures and troubleshooting. Therefore, new methods are needed to improve work efficiency and reduce the burden on workers.

[1246] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1247] In this invention, the server includes means for receiving user input, means for searching a database based on the input, means for displaying the retrieved data to the user, means for converting the displayed data into audio and playing it back, and means for outputting the retrieved data as an audio guide. This enables workers on a factory production line to quickly obtain the necessary information and proceed with their work efficiently.

[1248] "Means of receiving user input" refers to devices and interfaces used to obtain instructions and information from users. Examples include tablets, smart glasses, and keyboards.

[1249] "Means of searching a database" refers to algorithms and programs used to extract data from storage based on predetermined keywords or conditions.

[1250] "Means of displaying searched data to the user" refers to displays or screens that visually present the retrieved information to the user. Examples include tablet screens and smart glasses displays.

[1251] "Means of converting displayed data into audio and playing it back" refers to technology that converts visual information into audio using synthesized speech and plays that audio information back through speakers or headphones.

[1252] "Means of outputting as audio guidance" refers to programs or devices that provide audio guidance for specific information or instructions. For example, a system that provides audio guidance for work procedures within a factory would fall into this category.

[1253] An "artificial intelligence model" refers to a machine learning or deep learning model used to perform inference and prediction based on given data. Examples include neural networks using TensorFlow or PyTorch.

[1254] "A means of verifying user authentication information in a database and generating authentication results" refers to technology that checks the authentication information of a user when they access a system and determines whether the user has legitimate access rights.

[1255] One embodiment of this invention is a system for enabling workers to efficiently set up and maintain robots on a factory production line. This system is realized through the following configuration and process.

[1256] Basic System Configuration

[1257] The system includes means for receiving user input, means for searching a database, means for displaying the retrieved data to the user, means for converting the displayed data into audio and playing it back, and means for outputting it as an audio guide. Furthermore, it also includes means for applying an artificial intelligence model to select the most appropriate information from the retrieved data, and means for verifying the user's authentication information.

[1258] Hardware and software

[1259] hardware

[1260] This system utilizes interface devices such as tablets, smart glasses, and head-mounted displays installed on the factory's production line. These devices function as terminals operated by workers. A server is also required for overall system control and data processing.

[1261] software

[1262] The software includes the following elements:

[1263] Languages: Python, JavaScript

[1264] Frameworks: Flask (backend), React (frontend)

[1265] Libraries: TensorFlow (AI model), SpeechRecognition, Pygame (speech management)

[1266] Processing flow

[1267] User operation and interface

[1268] Users access the system using tablets or smart glasses within the factory. When a user enters keywords such as "Please tell me how to deal with a specific equipment problem" on the tablet screen, the input is sent to the server.

[1269] Database Search

[1270] The server searches the database based on the received request and extracts the relevant information. The extracted information is then preprocessed and sent to the user's terminal.

[1271] Display of search results and audio guide

[1272] The terminal displays search results on the screen and simultaneously prepares an audio guide. When the user reviews the search results and accesses specific procedures or settings changes as needed, the information is played back as audio. For example, to learn about equipment maintenance procedures, the user can enter a prompt such as, "Please tell me the maintenance procedure for the cooling system."

[1273] AI optimization feature

[1274] The server uses an AI model to select the most relevant information from the search results. This process allows the user to obtain the necessary information in the shortest possible time. Specifically, this involves neural networks using TensorFlow or PyTorch.

[1275] Audio guide generation and playback

[1276] The server uses speech synthesis technology to convert the relevant information into audio data. This technology includes gTTS (Google Text-to-Speech), among others. The converted audio data is sent to the terminal, allowing the user to receive voice guidance in real time.

[1277] This allows workers on the factory production line to quickly and efficiently acquire information and proceed with their work. At the same time, it reduces the burden on workers and improves overall productivity.

[1278] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1279] Step 1:

[1280] Users log in to the system via a tablet, smart glasses, or head-mounted display.

[1281] Input: Enter your User ID and password.

[1282] Processing: The terminal sends the entered authentication information to the server, and the server searches the database to verify the user's authentication information.

[1283] Output: An authentication result is generated, and a login token is sent back to the device.

[1284] Specific operation: Once authentication is successful, the user will be able to access the system's main screen.

[1285] Step 2:

[1286] Users enter keywords and send search requests through the interface of a tablet or smart glasses.

[1287] Input: The user enters keywords into the search bar and clicks the search button.

[1288] Processing: The terminal receives user input and sends it to the server.

[1289] Output: Requests containing the keyword reach the server.

[1290] Specific action: The server prepares to retrieve relevant information from the database.

[1291] Step 3:

[1292] The server searches the database and retrieves relevant information.

[1293] Input: Keyword search request based on user input.

[1294] Processing: The server searches the database and extracts relevant information. It then uses an AI model (such as TensorFlow) to select the optimal data.

[1295] Output: Extracted relevant information.

[1296] Specific operation: The AI ​​model analyzes the search results and selects the most relevant information.

[1297] Step 4:

[1298] The server sends the extracted information to the user's terminal.

[1299] Input: Extracted relevant information.

[1300] Processing: The server transfers the detected information to the user's terminal.

[1301] Output: Related information is displayed on the user's terminal.

[1302] Specific operation: The results are displayed on the user's device, allowing the user to visually confirm the information.

[1303] Step 5:

[1304] The user requests an audio guide based on the information displayed.

[1305] Input: A request from the user for audio guidance regarding the displayed information.

[1306] Processing: The terminal resends this request to the server.

[1307] Output: A request for audio guidance is sent to the server.

[1308] Specific action: The server prepares to convert the specified information into audio data.

[1309] Step 6:

[1310] The server converts the target information into speech and generates audio data.

[1311] Input: Text information based on requests for audio guides.

[1312] Processing: The server uses speech synthesis technology (such as gTTS) to convert text information into speech data.

[1313] Output: Generated audio data.

[1314] Specific action: Audio data is generated and ready to be sent to the device.

[1315] Step 7:

[1316] The device plays the generated audio data to the user.

[1317] Input: Generated audio data.

[1318] Processing: The device receives the audio data and plays it through the speaker or headphones.

[1319] Output: Audio guide.

[1320] Specific operation: Users can obtain the necessary information through audio guidance and proceed with their tasks.

[1321] This allows users to quickly and efficiently obtain the necessary information within the factory and perform appropriate tasks.

[1322] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1323] The system according to the present invention includes means for receiving user input, searching a database, and displaying the retrieved data; means for converting the displayed data into speech and playing it back; and means for applying an artificial intelligence model to select the most suitable information from the retrieved data. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, the system provides optimal information tailored to the user's emotions.

[1324] System Overview

[1325] 1. User actions

[1326] Users log in to the system using a terminal and enter keywords related to the technical terms or drawings they wish to search for. This allows users to obtain information tailored to their needs.

[1327] 2. Database Search

[1328] The terminal receives a request from the user and sends that request to the server. The server searches the database and extracts the relevant information.

[1329] 3. Displaying search results

[1330] The server sends the search results to the terminal, and the terminal displays them in the user interface.

[1331] 4. Voice guidance

[1332] If a user selects specific information and requests voice guidance, the device resends the request to the server. The server converts the information into audio data and sends it to the device. The device plays the audio data, and the user can obtain the necessary information through voice guidance.

[1333] 5. Recognition of emotions

[1334] The emotion engine recognizes the user's emotions in real time. It determines emotions from the user's tone of voice and facial expressions.

[1335] 6. Information Optimization

[1336] The server utilizes emotional information obtained from the emotion engine and uses an artificial intelligence model to select the most appropriate information.

[1337] 7. Voice guidance that responds to emotions

[1338] The server adjusts the content and tone of the voice guidance according to the recognized emotion and sends it to the terminal. The user can then receive voice guidance that matches their emotions.

[1339] Specific example

[1340] Login process

[1341] The user enters their ID and password into the system from their device and clicks the login button. The device sends this information to the server, which verifies the user's authentication information in its database. If authentication is successful, the server generates a login token and sends it back to the device. The device receives this token, and the user can begin using the system.

[1342] Search and display of technical terms

[1343] The user enters "earthquake-resistant design" into the search bar and clicks the search button. The device sends this request to the server. The server searches the database and extracts information related to "earthquake-resistant design." It then sends the results back to the device. The device displays this information in a list on its user interface.

[1344] Audio guidance for information

[1345] The user selects the item they want to know about from the search results list and clicks the voice guidance button. The device sends this request back to the server. The server converts the relevant information into audio data and sends it to the device. The device plays the audio data, and the user can acquire knowledge through the voice guidance.

[1346] Emotion recognition and customization

[1347] While the user is operating the system, the emotion engine recognizes their emotions from their voice tone and facial expressions. For example, if the system determines that the user is stressed, it simplifies the voice guidance and softens the tone. The server receives the output from the emotion engine and sends back the information and voice data with appropriate adjustments. The terminal plays the adjusted voice data, and the user receives emotionally sensitive guidance.

[1348] Other features

[1349] This system incorporates a mechanism for utilizing accumulated emotional information in subsequent interactions. The server stores the user's emotional history and optimizes future interactions based on this history. Furthermore, the emotional information recognized by the emotion engine is fed back to an artificial intelligence model for more accurate information selection. For example, by avoiding information that the user found unpleasant based on past history, the system can be made more user-friendly.

[1350] This system allows users to quickly obtain explanations of technical terms and diagrams, deepening their understanding of on-site survey reports. Furthermore, appropriate voice guidance tailored to the user's emotions improves their understanding of related construction work and on-site tasks. As a result, overall work efficiency is significantly improved.

[1351] The following describes the processing flow.

[1352] Login process

[1353] Step 1:

[1354] The user starts up their device and opens the login screen. The user enters their ID and password and clicks the login button.

[1355] Step 2:

[1356] The device sends the authentication information entered by the user to the server.

[1357] Step 3:

[1358] The server checks the received authentication information in the database and performs user authentication.

[1359] Step 4:

[1360] The server generates an authentication result (success or failure), and if successful, generates a login token.

[1361] Step 5:

[1362] The server sends the login token back to the device.

[1363] Step 6:

[1364] The device receives the login token and enables the user to begin using the system.

[1365] Search and display of technical terms

[1366] Step 1:

[1367] The user enters a search keyword (e.g., "earthquake-resistant design") into the device's search bar and clicks the search button.

[1368] Step 2:

[1369] The device sends a search request and search keywords to the server.

[1370] Step 3:

[1371] The server searches the database using the search keywords it received.

[1372] Step 4:

[1373] The server extracts relevant information from the database and generates results.

[1374] Step 5:

[1375] The server sends the search results to the terminal.

[1376] Step 6:

[1377] The search results received by the device are displayed to the user in a list.

[1378] Audio guidance for information

[1379] Step 1:

[1380] The user selects the item they want to know about from the list of search results and clicks the voice guidance button.

[1381] Step 2:

[1382] The device sends a voice guidance request to the server.

[1383] Step 3:

[1384] The server begins processing the information to convert it into audio data.

[1385] Step 4:

[1386] The server generates audio data and sends it to the terminal.

[1387] Step 5:

[1388] The device plays back the received audio data and provides voice guidance to the user.

[1389] Emotion recognition and customization

[1390] Step 1:

[1391] While the user is operating the system, an emotion engine built into the device recognizes the user's emotions in real time.

[1392] Step 2:

[1393] The emotion engine analyzes the user's emotions from their voice tone and facial expressions, and generates the results.

[1394] Step 3:

[1395] The device sends the output of the emotion engine to the server.

[1396] Step 4:

[1397] The server receives emotional information from the emotion engine and uses it to customize the information and voice guidance it provides.

[1398] Step 5:

[1399] The server sends the adjusted information and audio data to the terminal.

[1400] Step 6:

[1401] The device plays updated audio data, providing users with emotionally sensitive guidance.

[1402] Information optimization (application of artificial intelligence models)

[1403] Step 1:

[1404] The server inputs the search results extracted from the database into an artificial intelligence model.

[1405] Step 2:

[1406] The server uses an artificial intelligence model to analyze the search results and identify the most relevant information.

[1407] Step 3:

[1408] The server selects optimized information and generates data to provide to the user.

[1409] These processing steps enable the system to efficiently provide information to users, supporting explanations of technical terms and descriptions of on-site work. Furthermore, the introduction of an emotion engine allows for optimal voice guidance tailored to the user's emotions, thereby improving the user experience.

[1410] (Example 2)

[1411] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1412] Conventional information retrieval systems primarily focus on searching databases based on user input and displaying results, without considering the user's emotions or circumstances. Similarly, voice guidance simply converts text data into speech, failing to provide content and tone that consider the user's psychological state. This can lead to users experiencing stress when obtaining necessary information, resulting in decreased usability and satisfaction. Furthermore, the selection of optimal information using artificial intelligence models and enhanced authentication security remain insufficient.

[1413] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1414] In this invention, the server is

[1415] An emotion recognition engine that recognizes the user's emotions in real time,

[1416] A means for adjusting the content and tone of voice guidance based on the information obtained by the emotion recognition engine,

[1417] A means of applying an artificial intelligence model to select the most suitable information for the retrieved data,

[1418] This includes providing optimal information tailored to the user's emotions, and the content and tone of the voice guidance are adjusted according to the user's psychological state, resulting in a more comfortable and effective information acquisition experience.

[1419] "Means for receiving user input" refers to input interfaces for users to enter information, including devices such as keyboards and touch panels.

[1420] "Means of searching a database" refers to algorithms and systems used to retrieve relevant information from a pre-built database based on user input.

[1421] "Means of displaying searched data to the user" refers to displays or graphical user interfaces that show search results in a format that is visually accessible to the user.

[1422] "Means of converting to audio and playing it back" refers to speech synthesis programs and hardware that convert text data into audio data and play it back through speakers.

[1423] An "emotion recognition engine" refers to a software system that analyzes data such as the user's voice tone and facial expressions to recognize their emotions in real time.

[1424] "Means for adjusting the content and tone of voice guidance" refers to a program that adjusts the content and tone of voice guidance to match the user's psychological state, based on the output of the emotion recognition engine.

[1425] "Means of applying artificial intelligence models" refers to algorithms and systems that utilize machine learning and deep learning to select the most relevant information from retrieved data.

[1426] "Means for verifying user authentication information in a database and generating authentication results" refers to a program and system that compares the authentication information entered by the user with existing data in the database and determines the success or failure of authentication based on the results.

[1427] The system according to the present invention includes means for receiving user input, searching a database based on that input, and displaying the retrieved data; means for converting the displayed data into speech and playing it back; and means for applying an artificial intelligence model to select the most suitable information from the retrieved data. It also incorporates an emotion recognition engine that recognizes the user's emotions in real time and provides optimal voice guidance according to the user's emotions.

[1428] Hardware and software to be used

[1429] Device: A device including a personal computer, tablet, and smartphone.

[1430] Server: Use a high-performance server (e.g., an Amazon Web Services EC2 instance).

[1431] Database: Use a Relational Database Management System (e.g., MySQL, PostgreSQL).

[1432] Emotion recognition engine: Uses facial recognition software (e.g., OpenCV) and speech analysis software.

[1433] Artificial intelligence model: Machine learning models using TensorFlow or PyTorch are used.

[1434] Text-to-speech engine: Uses text-to-speech software (e.g., Google Text-to-Speech).

[1435] Search process

[1436] The user enters search keywords on their device and sends the request to the server. The server searches the database and retrieves the relevant information. The retrieved information is sent back to the device and displayed on the user interface. This allows the user to quickly obtain the information they need.

[1437] As a concrete example, when a user enters "earthquake-resistant design" into the search bar of their device and clicks the search button, the device sends this request to the server. The server searches the database and sends back information related to "earthquake-resistant design" to the device, which then displays this information in a list.

[1438] Voice guidance process

[1439] When a user selects specific information from the search results and wishes to receive voice guidance, they click the voice guidance button. This request is sent from the device to the server, which converts the relevant information into audio data and sends it back to the device. The device then plays this audio data, allowing the user to obtain the necessary information by voice.

[1440] As a concrete example, when a user selects the item "Fundamentals of Earthquake-Resistant Design" and clicks the voice guidance button, the device resends this request to the server. The server converts the information into audio data, and the device plays that audio.

[1441] Emotion recognition and information optimization

[1442] The emotion recognition engine recognizes the user's voice tone and facial expressions in real time and sends the obtained emotion information to the server. Based on this emotion information, the server uses an artificial intelligence model to select the most appropriate information and adjust the content and tone of the voice guidance. As a result, the user receives information guidance that is best suited to their emotions.

[1443] As a concrete example, when a user is listening to voice guidance, the emotion recognition engine detects stress. This information is sent to a server, which uses an AI model to simplify the content of the voice guidance, soften the tone, and regenerate the voice data, which is then sent to the terminal. The terminal plays the adjusted voice guidance, and the user receives information guidance with reduced stress.

[1444] Examples of input prompts for a generative AI model

[1445] "I want to search for information on earthquake-resistant design."

[1446] System: "Please enter 'earthquake-resistant design' in the search bar and click the search button."

[1447] User: Type "earthquake-resistant design" and click the search button.

[1448] System: "Information regarding earthquake-resistant design is displayed. If you would like audio guidance, please select an item and click the audio guidance button."

[1449] These features enable the system to quickly and effectively retrieve the information users need and provide optimal guidance tailored to their emotions.

[1450] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1451] Step 1:

[1452] The steps a user takes to enter their ID and password and attempt to log in.

[1453] The user enters their ID and password on the device's login interface and clicks the login button. The device sends this authentication information to the server. The server searches its database and verifies that the entered ID and password match. If authentication is successful, the server generates a login token and sends it back to the device. The device stores this token, and the user can then access the system.

[1454] Specific actions:

[1455] The user enters "ID: user123, Password: password123" and clicks the "Login" button.

[1456] The terminal sends the entered authentication information to the server in JSON format.

[1457] The server retrieves the corresponding user information from the database and verifies that it matches.

[1458] The server generates a "login token ABC123" and sends it back to the terminal.

[1459] The device stores the token it receives, allowing the user to access the system.

[1460] Input: User ID and password

[1461] Output: Login token

[1462] Step 2:

[1463] Steps for a user to enter search keywords and start a search.

[1464] The user enters the keyword they want to search for in the device's search bar and clicks the search button. The device sends the request to the server. The server searches its database based on the received keyword and retrieves the relevant information. This retrieved information is sent from the server to the device and displayed to the user.

[1465] Specific actions:

[1466] The user enters "earthquake-resistant design" and clicks the search button.

[1467] The device sends the search keyword "earthquake-resistant design" to the server as a POST request.

[1468] The server executes a database query to extract information related to "earthquake-resistant design."

[1469] The server returns the acquired information to the terminal in JSON format.

[1470] The device parses the information it receives and displays it in a user-friendly list format.

[1471] Input: Search keywords

[1472] Output: List of search results

[1473] Step 3:

[1474] Steps for users to request voice guidance

[1475] The user selects specific information from the displayed search results and clicks the voice guidance button. This request is resent from the device to the server. The server converts the relevant information into audio data and sends it to the device. The device plays this audio data, allowing the user to obtain the necessary information by voice.

[1476] Specific actions:

[1477] The user clicks the voice guidance button next to the item "Fundamentals of Earthquake-Resistant Design".

[1478] The device sends a "voice guidance request" to the server.

[1479] The server uses a text-to-speech engine (e.g., Google Text-to-Speech) to convert text related to "Fundamentals of Earthquake-Resistant Design" into speech.

[1480] The server sends the generated audio file back to the terminal.

[1481] The device plays audio data, and the user receives voice guidance.

[1482] Input: Voice guidance request (specific information)

[1483] Output: Audio data

[1484] Step 4:

[1485] The procedure by which the emotion recognition engine detects the user's emotions

[1486] While the user is operating the system, the emotion recognition engine analyzes the user's voice tone and facial expressions in real time to acquire emotional information. This emotional information is then sent to the server.

[1487] Specific actions:

[1488] While the user is operating the system, the emotion recognition engine uses the camera and microphone to capture the user's face and voice.

[1489] The device analyzes the captured data in real time to obtain "emotional information."

[1490] The device sends the emotional information it has acquired to the server.

[1491] Input: User's voice tone and facial expression

[1492] Output: Emotional information

[1493] Step 5:

[1494] Steps to optimize information based on emotional information

[1495] The server uses an artificial intelligence model to select the most appropriate information for the user based on the emotional information transmitted by the emotion recognition engine. It adjusts the content and tone of the voice guidance according to the user's emotions.

[1496] Specific actions:

[1497] The server receives emotional information and uses an artificial intelligence model (e.g., TensorFlow) to determine the optimal response.

[1498] The server makes adjustments such as simplifying the content of the voice guidance and softening the tone.

[1499] The server converts the adjusted text back into audio data.

[1500] Input: Sentiment information

[1501] Output: Adjusted audio data

[1502] Step 6:

[1503] Instructions for playing the adjusted voice guidance

[1504] The server sends the adjusted audio data to the terminal. The terminal plays this audio data and provides the user with the most suitable voice guidance.

[1505] Specific actions:

[1506] The server sends the adjusted audio data to the terminal.

[1507] The device plays the audio data it received.

[1508] Users obtain information by listening to pre-arranged voice guidance.

[1509] Input: Adjusted audio data

[1510] Output: Played audio guidance

[1511] (Application Example 2)

[1512] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1513] In factory work support, there is a need to provide workers with the information they require quickly and accurately, while also providing optimal support that takes into account their emotions. However, conventional systems have been unable to recognize workers' emotions and optimize information accordingly, resulting in problems such as a decrease in user experience and work efficiency.

[1514] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user input, means for searching a database based on the input, means for displaying the retrieved data to the user, means for converting the displayed data into speech and playing it back, means for recognizing the user's emotions, and means for adjusting the presentation of information based on the recognized emotions. This makes it possible to provide necessary information quickly and appropriately while taking into account the worker's emotions, thereby improving work efficiency and user experience.

[1515] "Means for receiving user input" refers to means of receiving user input such as voice input or touch operations, and recognizing them within the system.

[1516] "Means of searching a database" refers to means of extracting relevant information from a database based on user input.

[1517] "Means of displaying searched data to the user" refers to means of providing search results to the user visually. This includes displays and head-mounted displays.

[1518] "Means of converting data into audio and playing it back" refers to methods of converting text data into audio data and providing it to the user via voice.

[1519] "Means of recognizing user emotions" refers to methods of detecting emotions from the user's tone of voice, facial expressions, etc., and making the system recognize them.

[1520] "Means of adjusting information presentation based on recognized emotions" refers to means of optimizing the content and presentation of information presented according to the user's emotional state.

[1521] An "artificial intelligence model" is an algorithm or learning model used to process and analyze data and derive the optimal result.

[1522] A "login token" is data that represents temporary authentication information that authenticated users use to access the system.

[1523] The system that realizes this application example is a factory work support robot system. The robot provides information to workers and improves work efficiency by accepting user input, searching a database, displaying search results and providing voice guidance, and recognizing the user's emotions to provide optimal support.

[1524] The server has means to recognize user input, such as voice input or touch gestures. Based on user input, the server searches the database and extracts relevant information. Database search tools such as SQL or Elasticsearch are used for this database search.

[1525] The extracted information is sent to a terminal and displayed visually to the user. Smart glasses or head-mounted displays are used for this visual display. Furthermore, Text-to-Speech (TTS) technology is used to convert the extracted data into speech and play it back.

[1526] The robot employs an Emotion Engine to recognize emotions from the tone of the worker's voice and facial expressions. This emotion recognition engine detects the user's emotional state in real time, and that information is sent to the server.

[1527] The server uses emotional information to present optimal information through a generative AI model. The AI ​​model is designed to optimize the content and presentation of information according to emotions, providing appropriate support to the user.

[1528] As a concrete example, a user enters "earthquake-resistant design" into the search bar and clicks the search button. This request is sent to the server, which searches the database and extracts relevant information. The results are sent back to the terminal and displayed on the user interface. Furthermore, the displayed information is converted into speech and played back to the user using TTS (Text-to-Speech) technology.

[1529] Next, if the server detects that the user is experiencing stress, it uses that information to adjust the tone of its information delivery. For example, it might translate the information into simpler language and deliver it in a gentler tone.

[1530] This system will enable users to quickly obtain the information they need and receive emotionally sensitive support. Based on the following example prompts, the system will search for and provide the necessary information to the user.

[1531] Example of a prompt:

[1532] Details of a system where a user enters the keyword "earthquake-resistant design," and a factory work support robot searches a database to display information and provide voice guidance. The system also includes a feature to simplify information and soften the tone if the user is experiencing stress.

[1533] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1534] Step 1:

[1535] The user gives instructions to the device via voice input or touch operation. The user enters a keyword, such as "earthquake-resistant design." This input data (keyword) is sent to the system.

[1536] Step 2:

[1537] The terminal sends the received user input data to the server. The server searches the database based on this input data. The server retrieves relevant information using search tools such as SQL or Elasticsearch. The output is search results containing the relevant information.

[1538] Step 3:

[1539] The server sends the search results to the terminal. The terminal receives this data and displays the searched data visually to the user. Smart glasses or head-mounted displays are used for this visual display. The displayed information is the output.

[1540] Step 4:

[1541] If the user selects specific information and requests voice guidance, the device sends the selected information back to the server. The server uses Text-to-Speech (TTS) technology to convert that information into voice data.

[1542] Step 5:

[1543] The server sends the converted audio data to the terminal. The terminal plays this audio data, and the user obtains information through the voice guidance. The played voice guidance is the output.

[1544] Step 6:

[1545] When a user operates the system, the terminal captures the user's voice tone and facial expressions in real time for emotion recognition. An Emotion Engine is used for emotion recognition. This input data is then sent to the server.

[1546] Step 7:

[1547] The server retrieves emotional data from the Emotion Engine and provides this information to a generating AI model. The AI ​​model analyzes the emotional data and adjusts the optimal way to present the information. The adjusted information is then sent from the server to the terminal.

[1548] Step 8:

[1549] The device then presents the adjusted information to the user again. For example, if the server detects that the user is experiencing stress, it plays a simplified voice guidance with a softer tone. Through this process, the user receives appropriate support that is sensitive to their emotions.

[1550] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1551] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1552] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1553] [Fourth Embodiment]

[1554] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1555] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1556] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1557] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1558] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1559] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1560] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1561] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1562] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1563] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1564] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1565] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1566] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1567] The system according to the present invention comprises means for receiving user input, means for searching a database, means for displaying the retrieved data, means for converting the displayed data into speech and playing it back, and means for applying an artificial intelligence model to select the most suitable information for the retrieved data. It also includes means for verifying user authentication information and means for generating and playing back speech data.

[1568] System Overview

[1569] 1. User actions

[1570] Users log in to the system and enter keywords related to the technical terms or drawings they wish to search for. This allows users to obtain information tailored to their needs.

[1571] 2. Database Search

[1572] The terminal receives a request from the user and sends that request to the server. The server searches the database and extracts the relevant information.

[1573] 3. Displaying search results

[1574] The retrieved information is sent from the server to the terminal, which then displays it in the user interface.

[1575] 4. Voice guidance

[1576] If a user selects specific information and requests voice guidance, the device resends the request to the server. The server converts the information into audio data and sends it to the device. The device plays the audio data, and the user can obtain the necessary information through voice guidance.

[1577] Specific example

[1578] Login process

[1579] The user enters their ID and password into the system from their device and clicks the login button. The device sends this information to the server, which verifies the user's authentication information in its database. If authentication is successful, the server generates a login token and sends it back to the device. The device receives this token, and the user can begin using the system.

[1580] Search and display of technical terms

[1581] The user enters "earthquake-resistant design" into the search bar and clicks the search button. The device sends this request to the server. The server searches the database and extracts information related to "earthquake-resistant design." It then sends the results back to the device. The device displays this information in a list on its user interface.

[1582] Audio guidance for information

[1583] The user selects the item they want to know about from the search results list and clicks the voice guidance button. The device sends this request back to the server. The server converts the relevant information into audio data and sends it to the device. The device plays the audio data, and the user can acquire knowledge through the voice guidance.

[1584] Other features

[1585] This system includes an artificial intelligence model for selecting the most relevant information from the searched data. Specifically, the server uses the AI ​​model to analyze the search results and select the information most relevant to the user. This process allows the user to obtain the necessary information in a short amount of time.

[1586] Furthermore, a specific algorithm is used for generating and playing back audio data. The server is equipped with speech synthesis technology to convert text information into speech, enabling it to respond quickly to user requests for voice guidance. The terminal appropriately plays back the audio data, providing users with real-time voice guidance.

[1587] This system allows users to quickly obtain explanations of technical terms and diagrams, deepening their understanding of on-site survey reports. It also improves their understanding of ancillary work and on-site tasks, leading to overall improved work efficiency.

[1588] The following describes the processing flow.

[1589] Login process

[1590] Step 1:

[1591] The user starts up their device and opens the login screen. The user enters their ID and password and clicks the login button.

[1592] Step 2:

[1593] The device sends the authentication information entered by the user to the server.

[1594] Step 3:

[1595] The server checks the received authentication information in the database and performs user authentication.

[1596] Step 4:

[1597] The server generates an authentication result (success or failure), and if successful, generates a login token.

[1598] Step 5:

[1599] The server sends the login token back to the device.

[1600] Step 6:

[1601] The device receives the login token and enables the user to begin using the system.

[1602] Search and display of technical terms

[1603] Step 1:

[1604] The user enters a search keyword (e.g., "earthquake-resistant design") into the device's search bar and clicks the search button.

[1605] Step 2:

[1606] The device sends a search request and search keywords to the server.

[1607] Step 3:

[1608] The server searches the database using the search keywords it received.

[1609] Step 4:

[1610] The server extracts relevant information from the database and generates results.

[1611] Step 5:

[1612] The server sends the search results to the terminal.

[1613] Step 6:

[1614] The search results received by the device are displayed to the user in a list.

[1615] Audio guidance for information

[1616] Step 1:

[1617] The user selects the item they want to know about from the list of search results and clicks the voice guidance button.

[1618] Step 2:

[1619] The device sends a voice guidance request to the server.

[1620] Step 3:

[1621] The server begins processing the information to convert it into audio data.

[1622] Step 4:

[1623] The server generates audio data and sends it to the terminal.

[1624] Step 5:

[1625] The device plays back the received audio data and provides voice guidance to the user.

[1626] Information optimization (application of artificial intelligence models)

[1627] Step 1:

[1628] The server inputs the search results extracted from the database into an artificial intelligence model.

[1629] Step 2:

[1630] The server uses an artificial intelligence model to analyze the search results and identify the most relevant information.

[1631] Step 3:

[1632] The server selects optimized information and generates data to provide to the user.

[1633] Verification of authentication information

[1634] Step 1:

[1635] The user enters and submits authentication information (ID and password) via their device.

[1636] Step 2:

[1637] The server checks the received authentication information in the database.

[1638] Step 3:

[1639] The server generates an authentication result, and if authentication is successful, it issues a login token.

[1640] Step 4:

[1641] The server sends the authentication result or login token to the device.

[1642] Audio data generation and playback

[1643] Step 1:

[1644] The server receives the user's voice guidance request.

[1645] Step 2:

[1646] The server generates audio data based on the corresponding text information.

[1647] Step 3:

[1648] The server generates audio data and sends it to the terminal.

[1649] Step 4:

[1650] The device plays back the audio data it receives and provides it to the user.

[1651] These processing steps enable the system to efficiently provide information to users and support explanations of technical terms and on-site work procedures.

[1652] (Example 1)

[1653] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1654] In today's world, it is crucial for users to obtain necessary information quickly and accurately. However, traditional systems require users to search for information from vast databases and expend considerable time and effort to understand it. Furthermore, systems that can receive information not only in text format but also through voice guidance are limited. In addition, many systems lack sufficient user authentication security and the ability to provide the most optimal information for the user's needs. A new system is needed to address these challenges.

[1655] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1656] In this invention, the server includes means for receiving user input, means for searching a database based on the input, means for displaying the retrieved data to the user, means for converting the displayed data into speech and playing it back, means for verifying the user's authentication information in the database and generating an authentication result, and means for applying an artificial intelligence model to select the optimal information for the retrieved data. This enables the user to efficiently obtain the necessary information and understand it through voice guidance. Furthermore, highly secure user authentication and the selection of optimal information by the artificial intelligence model enable the provision of highly accurate information.

[1657] "Means for receiving user input" refers to an interface for users to provide specific information, and includes devices such as keyboards and touch panels.

[1658] "Means of searching a database" refers to a function that allows a server to query information based on input information obtained from a user and extract relevant information from within the database.

[1659] "Means of displaying searched data to the user" refers to displays and user interfaces that visually provide the extracted information to the user.

[1660] "A means of converting displayed data into audio and playing it back" refers to a system that converts text-based information into audio data and provides that audio data to the user through speakers or earphones.

[1661] "Means for verifying user authentication information in a database and generating authentication results" refers to a function that compares the authentication information provided by the user with the information stored in the database, and determines and generates whether authentication was successful or not.

[1662] "Means of applying artificial intelligence models" refers to a function in which a server uses AI technology to analyze and select the most relevant information from the retrieved data.

[1663] The system according to this invention comprises means for receiving user input, means for searching a database, means for displaying the retrieved data, means for converting the displayed data into speech and playing it back, and means for applying an artificial intelligence model to select the most suitable information for the retrieved data. It also includes means for verifying user authentication information and means for generating and playing back speech data.

[1664] System Overview

[1665] 1. User actions

[1666] Users log in to the system and enter keywords related to the technical terms or drawings they wish to search for. This allows users to obtain information tailored to their needs.

[1667] 2. Database Search

[1668] The terminal receives a request from the user and sends that request to the server. The server searches the database (e.g., MySQL or PostgreSQL) and extracts the relevant information.

[1669] 3. Displaying search results

[1670] Information sent from the server to the terminal is displayed in the terminal's user interface (e.g., built with React or Vue.js).

[1671] 4. Voice guidance

[1672] If a user selects specific information and requests voice guidance, the device resends the request to the server. The server uses speech synthesis technology (e.g., Google Text-to-Speech API or Amazon Polly) to convert the information into voice data and sends it to the device. The device then plays the voice data and provides voice guidance to the user.

[1673] Specific example

[1674] Login process

[1675] The user enters their ID and password into the system from their device and clicks the login button. The device sends this information to the server, which verifies the authentication information in its database. If authentication is successful, the server generates a login token and sends it back to the device. The device receives this token, and the user can begin using the system.

[1676] Search and display of technical terms

[1677] The user enters "earthquake-resistant design" into the search bar and clicks the search button. The device sends this request to the server. The server searches the database and extracts information related to "earthquake-resistant design." It then sends the results back to the device. The device displays this information in a list on its user interface.

[1678] Audio guidance for information

[1679] The user selects the item they want to know about from the search results list and clicks the voice guidance button. The device sends this request back to the server. The server converts the relevant information into audio data and sends it to the device. The device plays the audio data, and the user can acquire knowledge through the voice guidance.

[1680] Hardware and software to be used

[1681] 1. Hardware

[1682] Devices: Computers, tablets, smartphones, etc.

[1683] Server: A high-performance server machine installed in a data center.

[1684] 2. Software

[1685] Database software: MySQL, PostgreSQL

[1686] Server-side programs: Python, Node.js

[1687] Client-side programming: React, Vue.js

[1688] Text-to-Speech APIs: Google Text-to-Speech API, Amazon Polly

[1689] Artificial intelligence models: TensorFlow, PyTorch

[1690] Example of a prompt

[1691] "Please provide the latest technical information regarding earthquake-resistant design."

[1692] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1693] Program processing steps

[1694] Step 1: System startup and display of login screen

[1695] 1. The terminal starts up the system.

[1696] 2. The terminal displays a login screen to the user.

[1697] Input: System startup command

[1698] Output: Login screen

[1699] Step 2: User Login

[1700] 1. The user enters their ID and password and clicks the "Login" button.

[1701] 2. The terminal receives the entered ID and password and sends them to the server.

[1702] Enter: ID and password

[1703] Output: Sending an authentication request

[1704] Step 3: Perform user authentication

[1705] 1. The server checks the received ID and password in the database.

[1706] 2. The server generates an authentication result (success or failure) and sends it back to the terminal.

[1707] Enter: ID and password

[1708] Output: Authentication result (login token or error message)

[1709] Step 4: Processing authentication results

[1710] 1. If authentication is successful, the device will receive a login token and display the main menu.

[1711] 2. If authentication fails, the device will display an error message.

[1712] Input: Authentication result

[1713] Output: Main menu or error message

[1714] Step 5: Search for technical terms

[1715] 1. The user selects the "Search" option from the main menu and enters "earthquake-resistant design" in the search bar.

[1716] 2. The user clicks the "Search" button.

[1717] 3. The device receives this request and sends it to the server.

[1718] Input: Search keyword (earthquake-resistant design)

[1719] Output: Sending a search request

[1720] Step 6: Search the database

[1721] 1. The server searches the database and extracts information related to "earthquake-resistant design".

[1722] 2. The server sends the search results to the terminal in JSON format.

[1723] Input: Search keyword

[1724] Output: Search results (JSON format)

[1725] Step 7: Displaying search results

[1726] 1. The device renders the received search results into HTML and displays them to the user as a list.

[1727] Input: Search results (JSON format)

[1728] Output: Display of search results list

[1729] Step 8: Selecting detailed information and audio guidance

[1730] 1. The user selects a specific item from the search results list and clicks the "Voice Guidance" button.

[1731] 2. The device receives this request and sends an HTTP POST request to the server containing the ID of the relevant information.

[1732] Input: ID of the selected item

[1733] Output: Sending a voice guidance request

[1734] Step 9: Generate audio data

[1735] 1. The server uses a speech synthesis API to convert the relevant information into speech data.

[1736] 2. The server sends the generated audio data to the terminal.

[1737] Input: Text information of the selected item

[1738] Output: Audio data (MP3 format)

[1739] Step 10: Play the voice guidance

[1740] 1. The device plays the acquired audio data using an audio player.

[1741] 2. Users obtain information through voice guidance.

[1742] Input: Audio data (MP3 format)

[1743] Output: Playback of voice guidance

[1744] Step 11: Optimal information selection using an AI model

[1745] 1. The server uses an AI model to analyze the search results.

[1746] 2. The AI ​​model selects the most relevant information, and the server sends the result to the terminal.

[1747] Input: Search results (text data)

[1748] Output: Selected optimal information (JSON format)

[1749] Step 12: Displaying Optimal Information

[1750] 1. The device highlights the most relevant information it receives on the user interface.

[1751] Input: Selected optimal information (JSON format)

[1752] Output: Highlighting of optimal information

[1753] (Application Example 1)

[1754] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1755] In factory production lines, there is a lack of means for workers to quickly and efficiently obtain the necessary information when setting up or maintaining robots. Conventional technologies require manual verification of search results, which is time-consuming and labor-intensive, especially for complex procedures and troubleshooting. Therefore, new methods are needed to improve work efficiency and reduce the burden on workers.

[1756] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1757] In this invention, the server includes means for receiving user input, means for searching a database based on the input, means for displaying the retrieved data to the user, means for converting the displayed data into audio and playing it back, and means for outputting the retrieved data as an audio guide. This enables workers on a factory production line to quickly obtain the necessary information and proceed with their work efficiently.

[1758] "Means of receiving user input" refers to devices and interfaces used to obtain instructions and information from users. Examples include tablets, smart glasses, and keyboards.

[1759] "Means of searching a database" refers to algorithms and programs used to extract data from storage based on predetermined keywords or conditions.

[1760] "Means of displaying searched data to the user" refers to displays or screens that visually present the retrieved information to the user. Examples include tablet screens and smart glasses displays.

[1761] "Means of converting displayed data into audio and playing it back" refers to technology that converts visual information into audio using synthesized speech and plays that audio information back through speakers or headphones.

[1762] "Means of outputting as audio guidance" refers to programs or devices that provide audio guidance for specific information or instructions. For example, a system that provides audio guidance for work procedures within a factory would fall into this category.

[1763] An "artificial intelligence model" refers to a machine learning or deep learning model used to perform inference and prediction based on given data. Examples include neural networks using TensorFlow or PyTorch.

[1764] "A means of verifying user authentication information in a database and generating authentication results" refers to technology that checks the authentication information of a user when they access a system and determines whether the user has legitimate access rights.

[1765] One embodiment of this invention is a system for enabling workers to efficiently set up and maintain robots on a factory production line. This system is realized through the following configuration and process.

[1766] Basic System Configuration

[1767] The system includes means for receiving user input, means for searching a database, means for displaying the retrieved data to the user, means for converting the displayed data into audio and playing it back, and means for outputting it as an audio guide. Furthermore, it also includes means for applying an artificial intelligence model to select the most appropriate information from the retrieved data, and means for verifying the user's authentication information.

[1768] Hardware and software

[1769] hardware

[1770] This system utilizes interface devices such as tablets, smart glasses, and head-mounted displays installed on the factory's production line. These devices function as terminals operated by workers. A server is also required for overall system control and data processing.

[1771] software

[1772] The software includes the following elements:

[1773] Languages: Python, JavaScript

[1774] Frameworks: Flask (backend), React (frontend)

[1775] Libraries: TensorFlow (AI model), SpeechRecognition, Pygame (speech management)

[1776] Processing flow

[1777] User operation and interface

[1778] Users access the system using tablets or smart glasses within the factory. When a user enters keywords such as "Please tell me how to deal with a specific equipment problem" on the tablet screen, the input is sent to the server.

[1779] Database Search

[1780] The server searches the database based on the received request and extracts the relevant information. The extracted information is then preprocessed and sent to the user's terminal.

[1781] Display of search results and audio guide

[1782] The terminal displays search results on the screen and simultaneously prepares an audio guide. When the user reviews the search results and accesses specific procedures or settings changes as needed, the information is played back as audio. For example, to learn about equipment maintenance procedures, the user can enter a prompt such as, "Please tell me the maintenance procedure for the cooling system."

[1783] AI optimization feature

[1784] The server uses an AI model to select the most relevant information from the search results. This process allows the user to obtain the necessary information in the shortest possible time. Specifically, this involves neural networks using TensorFlow or PyTorch.

[1785] Audio guide generation and playback

[1786] The server uses speech synthesis technology to convert the relevant information into audio data. This technology includes gTTS (Google Text-to-Speech), among others. The converted audio data is sent to the terminal, allowing the user to receive voice guidance in real time.

[1787] This allows workers on the factory production line to quickly and efficiently acquire information and proceed with their work. At the same time, it reduces the burden on workers and improves overall productivity.

[1788] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1789] Step 1:

[1790] Users log in to the system via a tablet, smart glasses, or head-mounted display.

[1791] Input: Enter your User ID and password.

[1792] Processing: The terminal sends the entered authentication information to the server, and the server searches the database to verify the user's authentication information.

[1793] Output: An authentication result is generated, and a login token is sent back to the device.

[1794] Specific operation: Once authentication is successful, the user will be able to access the system's main screen.

[1795] Step 2:

[1796] Users enter keywords and send search requests through the interface of a tablet or smart glasses.

[1797] Input: The user enters keywords into the search bar and clicks the search button.

[1798] Processing: The terminal receives user input and sends it to the server.

[1799] Output: Requests containing the keyword reach the server.

[1800] Specific action: The server prepares to retrieve relevant information from the database.

[1801] Step 3:

[1802] The server searches the database and retrieves relevant information.

[1803] Input: Keyword search request based on user input.

[1804] Processing: The server searches the database and extracts relevant information. It then uses an AI model (such as TensorFlow) to select the optimal data.

[1805] Output: Extracted relevant information.

[1806] Specific operation: The AI ​​model analyzes the search results and selects the most relevant information.

[1807] Step 4:

[1808] The server sends the extracted information to the user's terminal.

[1809] Input: Extracted relevant information.

[1810] Processing: The server transfers the detected information to the user's terminal.

[1811] Output: Related information is displayed on the user's terminal.

[1812] Specific operation: The results are displayed on the user's device, allowing the user to visually confirm the information.

[1813] Step 5:

[1814] The user requests an audio guide based on the information displayed.

[1815] Input: A request from the user for audio guidance regarding the displayed information.

[1816] Processing: The terminal resends this request to the server.

[1817] Output: A request for audio guidance is sent to the server.

[1818] Specific action: The server prepares to convert the specified information into audio data.

[1819] Step 6:

[1820] The server converts the target information into speech and generates audio data.

[1821] Input: Text information based on requests for audio guides.

[1822] Processing: The server uses speech synthesis technology (such as gTTS) to convert text information into speech data.

[1823] Output: Generated audio data.

[1824] Specific action: Audio data is generated and ready to be sent to the device.

[1825] Step 7:

[1826] The device plays the generated audio data to the user.

[1827] Input: Generated audio data.

[1828] Processing: The device receives the audio data and plays it through the speaker or headphones.

[1829] Output: Audio guide.

[1830] Specific operation: Users can obtain the necessary information through audio guidance and proceed with their tasks.

[1831] This allows users to quickly and efficiently obtain the necessary information within the factory and perform appropriate tasks.

[1832] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1833] The system according to the present invention includes means for receiving user input, searching a database, and displaying the retrieved data; means for converting the displayed data into speech and playing it back; and means for applying an artificial intelligence model to select the most suitable information from the retrieved data. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, the system provides optimal information tailored to the user's emotions.

[1834] System Overview

[1835] 1. User actions

[1836] Users log in to the system using a terminal and enter keywords related to the technical terms or drawings they wish to search for. This allows users to obtain information tailored to their needs.

[1837] 2. Database Search

[1838] The terminal receives a request from the user and sends that request to the server. The server searches the database and extracts the relevant information.

[1839] 3. Displaying search results

[1840] The server sends the search results to the terminal, and the terminal displays them in the user interface.

[1841] 4. Voice guidance

[1842] If a user selects specific information and requests voice guidance, the device resends the request to the server. The server converts the information into audio data and sends it to the device. The device plays the audio data, and the user can obtain the necessary information through voice guidance.

[1843] 5. Recognition of emotions

[1844] The emotion engine recognizes the user's emotions in real time. It determines emotions from the user's tone of voice and facial expressions.

[1845] 6. Information Optimization

[1846] The server utilizes emotional information obtained from the emotion engine and uses an artificial intelligence model to select the most appropriate information.

[1847] 7. Voice guidance that responds to emotions

[1848] The server adjusts the content and tone of the voice guidance according to the recognized emotion and sends it to the terminal. The user can then receive voice guidance that matches their emotions.

[1849] Specific example

[1850] Login process

[1851] The user enters their ID and password into the system from their device and clicks the login button. The device sends this information to the server, which verifies the user's authentication information in its database. If authentication is successful, the server generates a login token and sends it back to the device. The device receives this token, and the user can begin using the system.

[1852] Search and display of technical terms

[1853] The user enters "earthquake-resistant design" into the search bar and clicks the search button. The device sends this request to the server. The server searches the database and extracts information related to "earthquake-resistant design." It then sends the results back to the device. The device displays this information in a list on its user interface.

[1854] Audio guidance for information

[1855] The user selects the item they want to know about from the search results list and clicks the voice guidance button. The device sends this request back to the server. The server converts the relevant information into audio data and sends it to the device. The device plays the audio data, and the user can acquire knowledge through the voice guidance.

[1856] Emotion recognition and customization

[1857] While the user is operating the system, the emotion engine recognizes their emotions from their voice tone and facial expressions. For example, if the system determines that the user is stressed, it simplifies the voice guidance and softens the tone. The server receives the output from the emotion engine and sends back the information and voice data with appropriate adjustments. The terminal plays the adjusted voice data, and the user receives emotionally sensitive guidance.

[1858] Other features

[1859] This system incorporates a mechanism for utilizing accumulated emotional information in subsequent interactions. The server stores the user's emotional history and optimizes future interactions based on this history. Furthermore, the emotional information recognized by the emotion engine is fed back to an artificial intelligence model for more accurate information selection. For example, by avoiding information that the user found unpleasant based on past history, the system can be made more user-friendly.

[1860] This system allows users to quickly obtain explanations of technical terms and diagrams, deepening their understanding of on-site survey reports. Furthermore, appropriate voice guidance tailored to the user's emotions improves their understanding of related construction work and on-site tasks. As a result, overall work efficiency is significantly improved.

[1861] The following describes the processing flow.

[1862] Login process

[1863] Step 1:

[1864] The user starts up their device and opens the login screen. The user enters their ID and password and clicks the login button.

[1865] Step 2:

[1866] The device sends the authentication information entered by the user to the server.

[1867] Step 3:

[1868] The server checks the received authentication information in the database and performs user authentication.

[1869] Step 4:

[1870] The server generates an authentication result (success or failure), and if successful, generates a login token.

[1871] Step 5:

[1872] The server sends the login token back to the device.

[1873] Step 6:

[1874] The device receives the login token and enables the user to begin using the system.

[1875] Search and display of technical terms

[1876] Step 1:

[1877] The user enters a search keyword (e.g., "earthquake-resistant design") into the device's search bar and clicks the search button.

[1878] Step 2:

[1879] The device sends a search request and search keywords to the server.

[1880] Step 3:

[1881] The server searches the database using the search keywords it received.

[1882] Step 4:

[1883] The server extracts relevant information from the database and generates results.

[1884] Step 5:

[1885] The server sends the search results to the terminal.

[1886] Step 6:

[1887] The search results received by the device are displayed to the user in a list.

[1888] Audio guidance for information

[1889] Step 1:

[1890] The user selects the item they want to know about from the list of search results and clicks the voice guidance button.

[1891] Step 2:

[1892] The device sends a voice guidance request to the server.

[1893] Step 3:

[1894] The server begins processing the information to convert it into audio data.

[1895] Step 4:

[1896] The server generates audio data and sends it to the terminal.

[1897] Step 5:

[1898] The device plays back the received audio data and provides voice guidance to the user.

[1899] Emotion recognition and customization

[1900] Step 1:

[1901] While the user is operating the system, an emotion engine built into the device recognizes the user's emotions in real time.

[1902] Step 2:

[1903] The emotion engine analyzes the user's emotions from their voice tone and facial expressions, and generates the results.

[1904] Step 3:

[1905] The device sends the output of the emotion engine to the server.

[1906] Step 4:

[1907] The server receives emotional information from the emotion engine and uses it to customize the information and voice guidance it provides.

[1908] Step 5:

[1909] The server sends the adjusted information and audio data to the terminal.

[1910] Step 6:

[1911] The device plays updated audio data, providing users with emotionally sensitive guidance.

[1912] Information optimization (application of artificial intelligence models)

[1913] Step 1:

[1914] The server inputs the search results extracted from the database into an artificial intelligence model.

[1915] Step 2:

[1916] The server uses an artificial intelligence model to analyze the search results and identify the most relevant information.

[1917] Step 3:

[1918] The server selects optimized information and generates data to provide to the user.

[1919] These processing steps enable the system to efficiently provide information to users, supporting explanations of technical terms and descriptions of on-site work. Furthermore, the introduction of an emotion engine allows for optimal voice guidance tailored to the user's emotions, thereby improving the user experience.

[1920] (Example 2)

[1921] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1922] Conventional information retrieval systems primarily focus on searching databases based on user input and displaying results, without considering the user's emotions or circumstances. Similarly, voice guidance simply converts text data into speech, failing to provide content and tone that consider the user's psychological state. This can lead to users experiencing stress when obtaining necessary information, resulting in decreased usability and satisfaction. Furthermore, the selection of optimal information using artificial intelligence models and enhanced authentication security remain insufficient.

[1923] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1924] In this invention, the server is

[1925] An emotion recognition engine that recognizes the user's emotions in real time,

[1926] A means for adjusting the content and tone of voice guidance based on the information obtained by the emotion recognition engine,

[1927] A means of applying an artificial intelligence model to select the most suitable information for the retrieved data,

[1928] This includes providing optimal information tailored to the user's emotions, and the content and tone of the voice guidance are adjusted according to the user's psychological state, resulting in a more comfortable and effective information acquisition experience.

[1929] "Means for receiving user input" refers to input interfaces for users to enter information, including devices such as keyboards and touch panels.

[1930] "Means of searching a database" refers to algorithms and systems used to retrieve relevant information from a pre-built database based on user input.

[1931] "Means of displaying searched data to the user" refers to displays or graphical user interfaces that show search results in a format that is visually accessible to the user.

[1932] "Means of converting to audio and playing it back" refers to speech synthesis programs and hardware that convert text data into audio data and play it back through speakers.

[1933] An "emotion recognition engine" refers to a software system that analyzes data such as the user's voice tone and facial expressions to recognize their emotions in real time.

[1934] "Means for adjusting the content and tone of voice guidance" refers to a program that adjusts the content and tone of voice guidance to match the user's psychological state, based on the output of the emotion recognition engine.

[1935] "Means of applying artificial intelligence models" refers to algorithms and systems that utilize machine learning and deep learning to select the most relevant information from retrieved data.

[1936] "Means for verifying user authentication information in a database and generating authentication results" refers to a program and system that compares the authentication information entered by the user with existing data in the database and determines the success or failure of authentication based on the results.

[1937] The system according to the present invention includes means for receiving user input, searching a database based on that input, and displaying the retrieved data; means for converting the displayed data into speech and playing it back; and means for applying an artificial intelligence model to select the most suitable information from the retrieved data. It also incorporates an emotion recognition engine that recognizes the user's emotions in real time and provides optimal voice guidance according to the user's emotions.

[1938] Hardware and software to be used

[1939] Device: A device including a personal computer, tablet, and smartphone.

[1940] Server: Use a high-performance server (e.g., an Amazon Web Services EC2 instance).

[1941] Database: Use a Relational Database Management System (e.g., MySQL, PostgreSQL).

[1942] Emotion recognition engine: Uses facial recognition software (e.g., OpenCV) and speech analysis software.

[1943] Artificial intelligence model: Machine learning models using TensorFlow or PyTorch are used.

[1944] Text-to-speech engine: Uses text-to-speech software (e.g., Google Text-to-Speech).

[1945] Search process

[1946] The user enters search keywords on their device and sends the request to the server. The server searches the database and retrieves the relevant information. The retrieved information is sent back to the device and displayed on the user interface. This allows the user to quickly obtain the information they need.

[1947] As a concrete example, when a user enters "earthquake-resistant design" into the search bar of their device and clicks the search button, the device sends this request to the server. The server searches the database and sends back information related to "earthquake-resistant design" to the device, which then displays this information in a list.

[1948] Voice guidance process

[1949] When a user selects specific information from the search results and wishes to receive voice guidance, they click the voice guidance button. This request is sent from the device to the server, which converts the relevant information into audio data and sends it back to the device. The device then plays this audio data, allowing the user to obtain the necessary information by voice.

[1950] As a concrete example, when a user selects the item "Fundamentals of Earthquake-Resistant Design" and clicks the voice guidance button, the device resends this request to the server. The server converts the information into audio data, and the device plays that audio.

[1951] Emotion recognition and information optimization

[1952] The emotion recognition engine recognizes the user's voice tone and facial expressions in real time and sends the obtained emotion information to the server. Based on this emotion information, the server uses an artificial intelligence model to select the most appropriate information and adjust the content and tone of the voice guidance. As a result, the user receives information guidance that is best suited to their emotions.

[1953] As a concrete example, when a user is listening to voice guidance, the emotion recognition engine detects stress. This information is sent to a server, which uses an AI model to simplify the content of the voice guidance, soften the tone, and regenerate the voice data, which is then sent to the terminal. The terminal plays the adjusted voice guidance, and the user receives information guidance with reduced stress.

[1954] Examples of input prompts for a generative AI model

[1955] "I want to search for information on earthquake-resistant design."

[1956] System: "Please enter 'earthquake-resistant design' in the search bar and click the search button."

[1957] User: Type "earthquake-resistant design" and click the search button.

[1958] System: "Information regarding earthquake-resistant design is displayed. If you would like audio guidance, please select an item and click the audio guidance button."

[1959] These features enable the system to quickly and effectively retrieve the information users need and provide optimal guidance tailored to their emotions.

[1960] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1961] Step 1:

[1962] The steps a user takes to enter their ID and password and attempt to log in.

[1963] The user enters their ID and password on the device's login interface and clicks the login button. The device sends this authentication information to the server. The server searches its database and verifies that the entered ID and password match. If authentication is successful, the server generates a login token and sends it back to the device. The device stores this token, and the user can then access the system.

[1964] Specific actions:

[1965] The user enters "ID: user123, Password: password123" and clicks the "Login" button.

[1966] The terminal sends the entered authentication information to the server in JSON format.

[1967] The server retrieves the corresponding user information from the database and verifies that it matches.

[1968] The server generates a "login token ABC123" and sends it back to the terminal.

[1969] The device stores the token it receives, allowing the user to access the system.

[1970] Input: User ID and password

[1971] Output: Login token

[1972] Step 2:

[1973] Steps for a user to enter search keywords and start a search.

[1974] The user enters the keyword they want to search for in the device's search bar and clicks the search button. The device sends the request to the server. The server searches its database based on the received keyword and retrieves the relevant information. This retrieved information is sent from the server to the device and displayed to the user.

[1975] Specific actions:

[1976] The user enters "earthquake-resistant design" and clicks the search button.

[1977] The device sends the search keyword "earthquake-resistant design" to the server as a POST request.

[1978] The server executes a database query to extract information related to "earthquake-resistant design."

[1979] The server returns the acquired information to the terminal in JSON format.

[1980] The device parses the information it receives and displays it in a user-friendly list format.

[1981] Input: Search keywords

[1982] Output: List of search results

[1983] Step 3:

[1984] Steps for users to request voice guidance

[1985] The user selects specific information from the displayed search results and clicks the voice guidance button. This request is resent from the device to the server. The server converts the relevant information into audio data and sends it to the device. The device plays this audio data, allowing the user to obtain the necessary information by voice.

[1986] Specific actions:

[1987] The user clicks the voice guidance button next to the item "Fundamentals of Earthquake-Resistant Design".

[1988] The device sends a "voice guidance request" to the server.

[1989] The server uses a text-to-speech engine (e.g., Google Text-to-Speech) to convert text related to "Fundamentals of Earthquake-Resistant Design" into speech.

[1990] The server sends the generated audio file back to the terminal.

[1991] The device plays audio data, and the user receives voice guidance.

[1992] Input: Voice guidance request (specific information)

[1993] Output: Audio data

[1994] Step 4:

[1995] The procedure by which the emotion recognition engine detects the user's emotions

[1996] While the user is operating the system, the emotion recognition engine analyzes the user's voice tone and facial expressions in real time to acquire emotional information. This emotional information is then sent to the server.

[1997] Specific actions:

[1998] While the user is operating the system, the emotion recognition engine uses the camera and microphone to capture the user's face and voice.

[1999] The device analyzes the captured data in real time to obtain "emotional information."

[2000] The device sends the emotional information it has acquired to the server.

[2001] Input: User's voice tone and facial expression

[2002] Output: Emotional information

[2003] Step 5:

[2004] Steps to optimize information based on emotional information

[2005] The server uses an artificial intelligence model to select the most appropriate information for the user based on the emotional information transmitted by the emotion recognition engine. It adjusts the content and tone of the voice guidance according to the user's emotions.

[2006] Specific actions:

[2007] The server receives emotional information and uses an artificial intelligence model (e.g., TensorFlow) to determine the optimal response.

[2008] The server makes adjustments such as simplifying the content of the voice guidance and softening the tone.

[2009] The server converts the adjusted text back into audio data.

[2010] Input: Sentiment information

[2011] Output: Adjusted audio data

[2012] Step 6:

[2013] Instructions for playing the adjusted voice guidance

[2014] The server sends the adjusted audio data to the terminal. The terminal plays this audio data and provides the user with the most suitable voice guidance.

[2015] Specific actions:

[2016] The server sends the adjusted audio data to the terminal.

[2017] The device plays the audio data it received.

[2018] Users obtain information by listening to pre-arranged voice guidance.

[2019] Input: Adjusted audio data

[2020] Output: Played audio guidance

[2021] (Application Example 2)

[2022] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2023] In factory work support, there is a need to provide workers with the information they require quickly and accurately, while also providing optimal support that takes into account their emotions. However, conventional systems have been unable to recognize workers' emotions and optimize information accordingly, resulting in problems such as a decrease in user experience and work efficiency.

[2024] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user input, means for searching a database based on the input, means for displaying the retrieved data to the user, means for converting the displayed data into speech and playing it back, means for recognizing the user's emotions, and means for adjusting the presentation of information based on the recognized emotions. This makes it possible to provide necessary information quickly and appropriately while taking into account the worker's emotions, thereby improving work efficiency and user experience.

[2025] "Means for receiving user input" refers to means of receiving user input such as voice input or touch operations, and recognizing them within the system.

[2026] "Means of searching a database" refers to means of extracting relevant information from a database based on user input.

[2027] "Means of displaying searched data to the user" refers to means of providing search results to the user visually. This includes displays and head-mounted displays.

[2028] "Means of converting data into audio and playing it back" refers to methods of converting text data into audio data and providing it to the user via voice.

[2029] "Means of recognizing user emotions" refers to methods of detecting emotions from the user's tone of voice, facial expressions, etc., and making the system recognize them.

[2030] "Means of adjusting information presentation based on recognized emotions" refers to means of optimizing the content and presentation of information presented according to the user's emotional state.

[2031] An "artificial intelligence model" is an algorithm or learning model used to process and analyze data and derive the optimal result.

[2032] A "login token" is data that represents temporary authentication information that authenticated users use to access the system.

[2033] The system that realizes this application example is a factory work support robot system. The robot provides information to workers and improves work efficiency by accepting user input, searching a database, displaying search results and providing voice guidance, and recognizing the user's emotions to provide optimal support.

[2034] The server has means to recognize user input, such as voice input or touch gestures. Based on user input, the server searches the database and extracts relevant information. Database search tools such as SQL or Elasticsearch are used for this database search.

[2035] The extracted information is sent to a terminal and displayed visually to the user. Smart glasses or head-mounted displays are used for this visual display. Furthermore, Text-to-Speech (TTS) technology is used to convert the extracted data into speech and play it back.

[2036] The robot employs an Emotion Engine to recognize emotions from the tone of the worker's voice and facial expressions. This emotion recognition engine detects the user's emotional state in real time, and that information is sent to the server.

[2037] The server uses emotional information to present optimal information through a generative AI model. The AI ​​model is designed to optimize the content and presentation of information according to emotions, providing appropriate support to the user.

[2038] As a concrete example, a user enters "earthquake-resistant design" into the search bar and clicks the search button. This request is sent to the server, which searches the database and extracts relevant information. The results are sent back to the terminal and displayed on the user interface. Furthermore, the displayed information is converted into speech and played back to the user using TTS (Text-to-Speech) technology.

[2039] Next, if the server detects that the user is experiencing stress, it uses that information to adjust the tone of its information delivery. For example, it might translate the information into simpler language and deliver it in a gentler tone.

[2040] This system will enable users to quickly obtain the information they need and receive emotionally sensitive support. Based on the following example prompts, the system will search for and provide the necessary information to the user.

[2041] Example of a prompt:

[2042] Details of a system where a user enters the keyword "earthquake-resistant design," and a factory work support robot searches a database to display information and provide voice guidance. The system also includes a feature to simplify information and soften the tone if the user is experiencing stress.

[2043] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2044] Step 1:

[2045] The user gives instructions to the device via voice input or touch operation. The user enters a keyword, such as "earthquake-resistant design." This input data (keyword) is sent to the system.

[2046] Step 2:

[2047] The terminal sends the received user input data to the server. The server searches the database based on this input data. The server retrieves relevant information using search tools such as SQL or Elasticsearch. The output is search results containing the relevant information.

[2048] Step 3:

[2049] The server sends the search results to the terminal. The terminal receives this data and displays the searched data visually to the user. Smart glasses or head-mounted displays are used for this visual display. The displayed information is the output.

[2050] Step 4:

[2051] If the user selects specific information and requests voice guidance, the device sends the selected information back to the server. The server uses Text-to-Speech (TTS) technology to convert that information into voice data.

[2052] Step 5:

[2053] The server sends the converted audio data to the terminal. The terminal plays this audio data, and the user obtains information through the voice guidance. The played voice guidance is the output.

[2054] Step 6:

[2055] When a user operates the system, the terminal captures the user's voice tone and facial expressions in real time for emotion recognition. An Emotion Engine is used for emotion recognition. This input data is then sent to the server.

[2056] Step 7:

[2057] The server retrieves emotional data from the Emotion Engine and provides this information to a generating AI model. The AI ​​model analyzes the emotional data and adjusts the optimal way to present the information. The adjusted information is then sent from the server to the terminal.

[2058] Step 8:

[2059] The device then presents the adjusted information to the user again. For example, if the server detects that the user is experiencing stress, it plays a simplified voice guidance with a softer tone. Through this process, the user receives appropriate support that is sensitive to their emotions.

[2060] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[2061] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2062] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[2063] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2064] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[2065] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[2066] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[2067] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[2068] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[2069] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[2070] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[2071] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[2072] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[2073] 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.

[2074] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[2075] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[2076] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[2077] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[2078] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[2079] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[2080] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[2081] The following is further disclosed regarding the embodiments described above.

[2082] (Claim 1)

[2083] A means of receiving user input,

[2084] A means for searching a database based on the aforementioned input,

[2085] A means of displaying the searched data to the user,

[2086] A means for converting the displayed data into audio and playing it back,

[2087] A system that includes this.

[2088] (Claim 2)

[2089] The system according to claim 1, further comprising means for applying an artificial intelligence model to select the most appropriate information for the retrieved data.

[2090] (Claim 3)

[2091] The system according to claim 1, further comprising means for verifying user authentication information in a database and generating an authentication result.

[2092] (Claim 4)

[2093] The system according to claim 1, further comprising means for generating and playing back audio data.

[2094] (Claim 5)

[2095] A database search method for collecting search results,

[2096] An artificial intelligence model for analyzing collected information,

[2097] means for converting the analyzed information into audio data,

[2098] The system according to claim 1, including the following:

[2099] By defining the claims in this way, the technical scope of the system can be clearly defined, and a wide range of technical features can be covered.

[2100] "Example 1"

[2101] (Claim 1)

[2102] A means of receiving user input,

[2103] A means for searching a database based on the aforementioned input,

[2104] A means of displaying the searched data to the user,

[2105] A means for converting the displayed data into audio and playing it back,

[2106] A means of checking user authentication information in a database and generating an authentication result,

[2107] A means of applying an artificial intelligence model to select the most suitable information for the retrieved data,

[2108] A system that includes this.

[2109] (Claim 2)

[2110] The system according to claim 1, which uses an artificial intelligence model to analyze the retrieved data and select the most relevant information.

[2111] (Claim 3)

[2112] The system according to claim 1, further comprising means for converting search results into audio data using speech synthesis technology and for playing back the audio data.

[2113] "Application Example 1"

[2114] (Claim 1)

[2115] A means of receiving user input,

[2116] A means for searching a database based on the aforementioned input,

[2117] A means of displaying the searched data to the user,

[2118] A means for converting the displayed data into audio and playing it back,

[2119] Means for outputting the retrieved data as an audio guide,

[2120] A system that includes this.

[2121] (Claim 2)

[2122] The system according to claim 1, further comprising means for applying an artificial intelligence model to select the most appropriate information for the retrieved data.

[2123] (Claim 3)

[2124] The system according to claim 1, further comprising means for verifying user authentication information in a database and generating an authentication result.

[2125] (Claim 4)

[2126] The system according to claim 1, further comprising means for providing the user with specific work procedures or setting changes as voice guidance.

[2127] "Example 2 of combining an emotion engine"

[2128] (Claim 1)

[2129] A means of receiving user input,

[2130] A means for searching a database based on the aforementioned input,

[2131] A means of displaying the searched data to the user,

[2132] A means of converting some or all of the retrieved data into audio and playing it back,

[2133] An emotion recognition engine that recognizes the user's emotions in real time,

[2134] A means for adjusting the content and tone of voice guidance based on the information obtained by the emotion recognition engine,

[2135] A system that includes this.

[2136] (Claim 2)

[2137] The system according to claim 1, further comprising means for applying an artificial intelligence model to select the most appropriate information for the retrieved data.

[2138] (Claim 3)

[2139] The system according to claim 1, further comprising means for verifying user authentication information in a database and generating an authentication result.

[2140] "Application example 2 when combining with an emotional engine"

[2141] (Claim 1)

[2142] A means of receiving user input,

[2143] A means for searching a database based on the aforementioned input,

[2144] A means of displaying the searched data to the user,

[2145] A means for converting the displayed data into audio and playing it back,

[2146] Means of recognizing user emotions,

[2147] Means for adjusting the presentation of information based on the recognized emotions,

[2148] A system that includes this.

[2149] (Claim 2)

[2150] It further includes means for applying an artificial intelligence model to select the most relevant information from the retrieved data.

[2151] The system according to claim 1, comprising means for optimizing information selection based on emotion recognition results.

[2152] (Claim 3)

[2153] A means of checking user authentication information in a database and generating an authentication result,

[2154] A means for generating a login token after the aforementioned authentication,

[2155] The system according to claim 1, further comprising means for a user to operate the system using the aforementioned login token. [Explanation of symbols]

[2156] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving user input, A means for searching a database based on the aforementioned input, A means of displaying the searched data to the user, A means for converting the displayed data into audio and playing it back, A system that includes this.

2. The system according to claim 1, further comprising means for applying an artificial intelligence model to select the most appropriate information for the retrieved data.

3. The system according to claim 1, further comprising means for verifying user authentication information in a database and generating an authentication result.

4. The system according to claim 1, further comprising means for generating and playing back audio data.

5. A database search method for collecting search results, An artificial intelligence model for analyzing collected information, means for converting the analyzed information into audio data, The system according to claim 1, including the following: By defining the claims in this way, the technical scope of the system can be clearly defined, and a wide range of technical features can be covered.

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