system

Abstract

We provide the system. [Solution] A means of receiving technical terms entered by the user, A means of sending the received technical terms to the server, A server searches a database for technical terms and generates easy-to-understand explanations. A means for sending the generated explanatory text to the user's terminal, A means for the user terminal to display the generated explanatory text, 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 method for controlling a persona chatbot, which is performed by at least one processor and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance 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] For senior users, there is a problem that it is difficult to understand the technical terms of smartphones and computers. In particular, technical terms with a lot of technical content are very difficult for senior users to understand, which has become an obstacle to the use of devices. The purpose of the present invention is to eliminate the difficulty of such technical terms and support senior users to use smartphones and computers more easily.

Means for Solving the Problems

[0005] The present invention is a system that includes the following means: means for receiving technical terms entered by a user; means for transmitting the received technical terms to a server; means for the server to search for the technical terms in a database and generate an easy-to-understand explanation; means for transmitting the generated explanation to a user terminal; and means for the user terminal to display the generated explanation. Furthermore, by including a natural language processing engine that analyzes the difficult parts of the technical terms and replaces them with simpler words, the explanation becomes even easier for the user to understand. In addition, if the search results do not exist in the database, the system also includes means for collecting related information from the internet, thereby enabling it to handle a wide range of technical terms.

[0006] "User" refers to anyone who uses a smartphone or computer. In particular, this invention focuses primarily on senior citizens.

[0007] "Technical terms" refer to technical or specialized terms related to the operation and functions of smartphones and computers. Examples include Wi-Fi and browser.

[0008] "Means of receiving" refers to the hardware and software configuration for collecting technical terms entered by the user on a terminal and sending them to a server.

[0009] "Means of transmission" refers to the communication modules or software used to send received technical terms to the server.

[0010] A "server" refers to a remote computer that receives data sent by a user and processes or analyzes it.

[0011] A "database" refers to an electronic storage system used to store and manage technical terms, their definitions, and explanations.

[0012] "Searching" refers to the process of finding a specific technical term within a database.

[0013] "Means of generation" refers to algorithms and software used to create easily understandable explanations for technical terms.

[0014] An "explanatory text" refers to a document that explains technical terms in a way that is easier to understand.

[0015] A "natural language processing engine" refers to a computer program that analyzes complex technical terms and replaces them with simpler language.

[0016] "Means of collection" refers to the process of gathering relevant information from the internet for specialized terms that do not exist in the database. [Brief explanation of the drawing]

[0017] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple 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.

Modes for Carrying Out the Invention

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

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

[0020] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

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

[0022] 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.

[0023] 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).

[0024] 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."

[0025] [First Embodiment]

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

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0032] 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.

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

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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".

[0038] This invention is a system designed to help senior users understand technical terms when using smartphones and computers. To achieve this objective, the system includes multiple means for explaining technical terms entered by the user in an easy-to-understand manner.

[0039] System Configuration

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

[0041] User terminal: A computer device such as a smartphone or tablet that provides an interface for users to input technical terms.

[0042] Server: Receives technical terms sent from the user terminal, searches the database to generate an easy-to-understand explanation, and sends it back to the user terminal.

[0043] Database: A storage system that stores technical terms and their definitions.

[0044] Natural Language Processing Engine: A software module used to replace complex technical terms with simpler language.

[0045] Program processing

[0046] 1. Enter and submit technical terms.

[0047] The user launches an app on their smartphone or tablet and enters technical terms they find difficult to understand into an input field. For example, they might enter "Wi-Fi". Once this input is complete, the device sends the technical terms to the server. Specifically, the device sends the entered data as a POST request to a particular API endpoint.

[0048] 2. Analysis of technical terms on the server

[0049] The server receives requests sent from user terminals and matches the technical terms against the database. For example, the server searches the database for the keyword "Wi-Fi". If this search finds a matching entry, the server retrieves the information for that entry. The entry includes a definition such as "Wi-Fi is a wireless LAN technical standard, a technology that enables wireless internet connectivity."

[0050] 3. Generating explanatory text

[0051] The definition obtained from the database is then passed to the natural language processing engine on the server. This engine generates an easy-to-understand explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0052] 4. Sending and displaying the description

[0053] The server generates an explanatory text and sends it back to the user's device. Specifically, the server sends data containing the explanatory text as an HTTP response. Finally, the device receives this response data and displays an easy-to-understand explanatory text on the app's screen. For example, it might say, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables," which the user then reads.

[0054] Specific example

[0055] Example 1: "Wi-Fi"

[0056] 1. The user types "What is Wi-Fi?".

[0057] 2. The device sends the keyword "Wi-Fi" to the server.

[0058] 3. The server searches the database for "Wi-Fi" and retrieves the definition: "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[0059] 4. The server uses a natural language processing engine to generate an easy-to-understand explanation: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0060] 5. The server sends an explanatory message to the terminal.

[0061] 6. The device displays an explanatory text to the user.

[0062] Example 2: "Browser"

[0063] 1. The user types "What is a browser?".

[0064] 2. The device sends the keyword "browser" to the server.

[0065] 3. The server searches the database for "browser" and retrieves the definition: "A browser is software used to display HTML documents, such as Chrome or Firefox."

[0066] 4. The server uses a natural language processing engine to generate an easy-to-understand explanation: "A browser is an application for viewing various pages on the internet."

[0067] 5. The server sends an explanatory message to the terminal.

[0068] 6. The device displays an explanatory text to the user.

[0069] In this way, the present invention can help senior users understand technical terms more easily and promote the use of smartphones and computers.

[0070] The following describes the processing flow.

[0071] Step 1:

[0072] The user launches a smartphone app and enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field. When the user taps the "Send" button, the app retrieves this technical term.

[0073] Step 2:

[0074] The terminal retrieves the entered technical term and sends an HTTP POST request to the server. The request contains the technical term.

[0075] Step 3:

[0076] The server receives an HTTP request and parses the technical terms data. Specifically, the server extracts technical terms (e.g., "Wi-Fi") from the request body.

[0077] Step 4:

[0078] The server executes an SQL query against the database to retrieve the definition of a technical term. For example, the server might retrieve the definition of the technical term "Wi-Fi" as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[0079] Step 5:

[0080] The server passes the acquired definitions to the natural language processing engine. The natural language processing engine identifies complex terms such as "wireless LAN" and "technical standards" and converts them into easily understandable language.

[0081] Step 6:

[0082] The server uses the output of a natural language processing engine to generate explanatory text that is easy for the user to understand. For example, it might generate an explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0083] Step 7:

[0084] The server generates an explanatory text which is then sent to the user's terminal as an HTTP response.

[0085] Step 8:

[0086] The terminal receives an HTTP response and extracts the generated explanatory text from the response body.

[0087] Step 9:

[0088] The device displays easy-to-understand explanatory text on the app screen. Users will be able to view explanations such as, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables."

[0089] This series of steps will make it easier for senior users to understand technical terms and to use smartphones and computers more effectively.

[0090] (Example 1)

[0091] 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."

[0092] With the advancement of modern information technology, many users, including seniors, often find it difficult to understand technical jargon when using smartphones and computers. This problem is particularly pronounced when using the internet or new software, potentially widening the digital divide. Therefore, there is a need for systems that make this technical jargon easy to understand.

[0093] 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.

[0094] In this invention, the server includes means for receiving technical terms entered by the user, means for transmitting the received technical terms to a central processing unit, means for the central processing unit to retrieve the technical terms from a storage device and generate an easy-to-understand explanation, means for transmitting the generated explanation to a user device, and means for the user device to display the generated explanation. This makes it possible for a diverse range of users, including senior citizens, to easily understand technical terms.

[0095] "User" refers to a general user of the system.

[0096] "Technical jargon" refers to terms related to a specific field or technology that are difficult for the average user to understand.

[0097] "Means of receiving" refers to devices or modules that have the function of taking in data and information entered by the user into the system.

[0098] "Means of transmission" refers to devices or modules that have the function of sending received data or information to another device or module.

[0099] A "central processing unit" refers to the main device or module that handles information processing for the entire system and processes data based on instructions.

[0100] A "storage device" refers to a storage system used to store data and information.

[0101] A "natural language processing module" refers to a software module that converts natural language into an easily understandable format through the analysis and generation of input text.

[0102] "User device" refers to a device used by a user to access the system, and includes smartphones, tablets, and computers.

[0103] "Public information sources" refer to information sources that are generally accessible, such as websites and public databases on the internet.

[0104] Modes for carrying out the invention

[0105] This invention is a system designed to support users, including senior citizens, who may have difficulty understanding technical terms. This system consists of the following main components:

[0106] Components

[0107] 1. User device: A device such as a smartphone, tablet, or computer that provides an interface for the user to input technical terms.

[0108] 2. Central Processing Unit: This is the main computer system responsible for searching, analyzing, and generating explanatory texts for technical terms.

[0109] 3. Storage device: A database that stores technical terms and their explanations.

[0110] 4. Natural Language Processing Module: This is a software module for replacing technical jargon with easily understandable language.

[0111] 5. Public Information Sources: This is a system for collecting information on specialized terminology not found in databases from the internet.

[0112] Explanation of the program's processing

[0113] To generate the program for this system, follow these steps:

[0114] Entering and sending technical terms

[0115] First, the user launches an app on their smartphone or tablet and enters technical terms they find difficult to understand into the input field. For example, the user might enter "Wi-Fi". Once this input is complete, the device sends the technical terms to the server (central processing unit). Specifically, the device sends the entered data as a POST request to a particular API endpoint.

[0116] Analysis of technical terms on servers

[0117] The server receives requests sent from user terminals and matches the technical terms against its storage. For example, the server searches the database for the keyword "Wi-Fi". If this search finds a matching entry, the server retrieves the information for that entry. The entry includes a definition such as "Wi-Fi is a wireless LAN technical standard, a technology that enables wireless internet connectivity."

[0118] Generating an explanatory text

[0119] Next, the acquired definition is passed to a natural language processing module. The server uses this module to generate an easy-to-understand explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0120] Sending and displaying the description

[0121] Finally, the generated explanation is sent to the user's device, and the terminal displays the explanation on the app's screen. For example, it might say, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables," which the user can then view.

[0122] Specific example

[0123] Example 1: "Wi-Fi"

[0124] 1. The user types "What is Wi-Fi?".

[0125] 2. The device sends the keyword "Wi-Fi" to the central processing unit.

[0126] 3. The central processing unit searches for "Wi-Fi" in the memory and obtains the definition that "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[0127] 4. The central processing unit uses a natural language processing module to generate an easy-to-understand explanation: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0128] 5. The central processing unit transmits the explanatory text to the user device.

[0129] 6. The user device displays an explanatory text to the user.

[0130] Example 2: "Browser"

[0131] 1. The user types "What is a browser?".

[0132] 2. The terminal sends the keyword "browser" to the central processing unit.

[0133] 3. The central processing unit searches for "browser" in its memory and retrieves the definition that "a browser is software for displaying HTML documents, such as Chrome or Firefox."

[0134] 4. The central processing unit uses a natural language processing module to generate an easy-to-understand explanation: "A browser is an application for viewing various pages on the internet."

[0135] 5. The central processing unit transmits the explanatory text to the user device.

[0136] 6. The user device displays an explanatory text to the user.

[0137] Example of a prompt

[0138] Examples of prompt statements to input into a generative AI model are as follows:

[0139] If a user types "What is Wi-Fi?", the system will perform the following steps:

[0140] 1. The device sends the keyword "Wi-Fi" to the central processing unit.

[0141] 2. The central processing unit searches for "Wi-Fi" in the memory and retrieves the corresponding definition.

[0142] 3. The definition obtained by the central processing unit is converted into simple words using a natural language processing module.

[0143] 4. The central processing unit sends the easy-to-understand explanatory text it has generated back to the terminal.

[0144] 5. The device displays the explanatory text on the user's screen.

[0145] As a concrete example, we will display an explanation such as, "Wi-Fi is a method that allows smartphones and computers to connect to the internet without using cables." This makes it easier for users to understand technical terms.

[0146]

[0147] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0148] Detailed explanation of the program's processing

[0149] Step 1: User input reception and submission

[0150] Input: Technical term Example: "Wi-Fi"

[0151] Operation:

[0152] The user launches the app on their smartphone or tablet and enters technical terms that are difficult to understand into the input field.

[0153] Once input is complete, the terminal sends the technical terms to the central processing unit (server).

[0154] Specifically, the device sends the entered data as a POST request to a specific API endpoint.

[0155] Output: Technical terminology data sent to the server

[0156] Step 2: The server receives the request.

[0157] Input: POST request sent from the terminal

[0158] Operation:

[0159] The server receives a POST request sent from the user's terminal.

[0160] The request includes technical terms entered by the user.

[0161] Output: Terminology data received.

[0162] Step 3: Database matching of technical terms

[0163] Input: Technical terminology data

[0164] Operation:

[0165] The server compares the received technical terms with its storage device (database).

[0166] For example, the server searches for the keyword "Wi-Fi" in the database.

[0167] If this search finds a matching entry, the server retrieves the information for that entry.

[0168] Output: Definitions of technical terms retrieved from the database. Example: "Wi-Fi is a wireless LAN technical standard, a technology that enables wireless internet connectivity."

[0169] Step 4: Analysis and conversion using a natural language processing engine

[0170] Input: Definitions of technical terms obtained from a database

[0171] Operation:

[0172] The server passes the retrieved definition to the natural language processing module.

[0173] The natural language processing module replaces complex parts with easily understandable language.

[0174] For example, it can generate an explanatory text such as, "Wi-Fi is a method that allows smartphones and computers to connect to the internet without using cables."

[0175] Output: Easy-to-understand explanation. Example: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0176] Step 5: Send and display the description.

[0177] Input: Description generated by the natural language processing module

[0178] Operation:

[0179] The server then sends the generated explanation back to the user's terminal.

[0180] Send data including a description as an HTTP response.

[0181] The device processes the HTTP response received from the server and displays an easy-to-understand explanation on the app's screen.

[0182] The user reads the displayed description.

[0183] Output: Explanation displayed on the app screen. Example: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0184] A concrete example of the entire sequence of steps

[0185] 1. In Step 1, the user types "What is Wi-Fi?".

[0186] 2. In step 2, "the device sends that data to the server."

[0187] 3. In step 3, "the server searches for 'Wi-Fi' in the database and returns the definition."

[0188] 4. In step 4, "the server passes the definition to the natural language processing module, which generates an easy-to-understand explanation."

[0189] 5. In step 5, "the server sends the generated explanation to the terminal, and the terminal displays the explanation to the user."

[0190] By following the steps outlined above, this system assists in understanding technical terms and makes it easier for users, including senior citizens, to grasp technical jargon.

[0191] (Application Example 1)

[0192] 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."

[0193] In recent years, senior citizens have increasingly used smartphones and computers, but the problem of difficulty in understanding technical jargon has become more pronounced. Security terminology, in particular, is complex, and many users struggle to understand it properly. Therefore, there is a need for support systems that enable senior citizens to easily understand technical terms and enhance their security awareness.

[0194] 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.

[0195] In this invention, the server includes means for receiving technical terms entered by the user, means for sending the received technical terms to the server, means for the server to search for the technical terms in a database and generate an easy-to-understand explanation, means for sending the generated explanation to the user terminal, means for the user terminal to display the generated explanation, means for the user to enter technical terms that are difficult to understand into an input field in the application, means for sending the entered technical terms as a POST request using an API, means for the server to compare the received technical terms with a database and convert the obtained definition into simple words using a natural language processing model, and means for sending the generated explanation as an HTTP response. This makes it possible for senior users to easily understand security terms and immediately check their explanations.

[0196] A "user terminal" is a device used by users to input technical terms and receive and display explanatory text.

[0197] "Technical jargon" refers to complex terms used in technical or specialized fields.

[0198] A "server" is a device that receives technical terms sent from a user terminal, searches a database to generate an explanation, and then sends it back to the user terminal.

[0199] A "database" is a storage system that stores technical terms and their explanations.

[0200] A "natural language processing engine" is a software module that analyzes the complex parts of technical terms and replaces them with simpler language.

[0201] "API" stands for Application Programming Interface, which is an interface for using software functions from an external source.

[0202] A "POST request" is a request method used in the HTTP protocol to send data to a server.

[0203] An "HTTP response" is the response data sent from a server to a client in the HTTP protocol.

[0204] "Hugging Face" is a popular tool that provides libraries and APIs for natural language processing.

[0205] "Simple language" refers to more general and easily understandable terms used to generate explanatory texts that are easier to understand than technical jargon.

[0206] An "input field" is an area within an application where the user enters technical terms.

[0207] "Security terminology" refers to specialized terms related to information security and network security.

[0208] This invention is a system designed to help senior users easily understand technical terms. The system consists of a user terminal, a server, a database, a natural language processing engine, and an API.

[0209] Program processing

[0210] 1. User input and data transmission

[0211] The user enters technical terms that are difficult to understand into an input field within the application. This input field is displayed on the user's device, such as a smartphone or tablet. Once the user has finished entering the terms, the device sends the entered technical terms to the server as a POST request using an API.

[0212] 2. Analysis of technical terms and acquisition of definitions

[0213] The server receives the incoming request and matches it against the database. The database stores a wide range of technical terms and their definitions; for example, if the word "firewall" is received, it retrieves a definition such as "a network security system."

[0214] 3. Generating explanatory text

[0215] The definitions of technical terms obtained are passed to a natural language processing engine on the server (e.g., Hugging Face). This engine analyzes the complex parts of the technical terms, replaces them with simpler words, and generates easy-to-understand explanations. For example, it might generate an explanation such as, "A firewall is a mechanism to protect computers and smartphones from malicious actors."

[0216] 4. Sending and displaying the description

[0217] The server sends the generated explanation as an HTTP response to the user's terminal. The user's terminal receives this response and displays the explanation within the application. This allows the user to instantly see a simple explanation of technical terms.

[0218] Specific example

[0219] Specifically, when a user types "What is a firewall?" into the app's input field, the following prompt is sent to the server:

[0220] "What is a firewall? Please explain it in simple terms."

[0221] Hardware and software to use

[0222] User devices: Smartphones, tablets

[0223] Server: A computer device that receives, analyzes, and transmits data (e.g., a cloud server).

[0224] Database: A storage system that stores technical terms and their definitions (e.g., Amazon RDS).

[0225] Natural language processing engine: Software for analyzing and simplifying technical terms (e.g., Hugging Face API)

[0226] API: An interface for sending and receiving technical terms.

[0227] This will allow senior users to more easily understand technical terms and access information that will be useful in their daily lives and to improve their security awareness.

[0228] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0229] Step 1:

[0230] The user enters technical terms into an input field within the application.

[0231] The entered data consists of technical terms such as "firewall," and this will be used as input data in Step 2.

[0232] Step 2:

[0233] The terminal sends the entered technical terms to the server using the API. The data is sent as a POST request.

[0234] Specifically, the device converts the input data into JSON format and sends it as a POST request to the API endpoint. This request is received by the server.

[0235] Step 3:

[0236] The server analyzes the received request and matches it against technical terms in the database.

[0237] The system searches a database using input data (technical terms) as keys and retrieves the corresponding definitions. For example, for the term "firewall," it retrieves the definition "network security system."

[0238] Step 4:

[0239] The server retrieves definitions of technical terms, passes them to a natural language processing engine, and converts them into simpler words.

[0240] Using a natural language processing engine (e.g., Hugging Face), the system analyzes complex technical terms and generates easy-to-understand explanations. For example, it might generate an explanation such as, "A firewall is a mechanism to protect computers and smartphones from malicious actors."

[0241] Step 5:

[0242] The server sends the generated description to the user's terminal as an HTTP response.

[0243] The generated description is converted to JSON format and sent to the terminal as an HTTP response. A success code, such as status code 200, is also sent at this time.

[0244] Step 6:

[0245] The application displays the explanatory text received by the device.

[0246] The device analyzes the received data and displays it on the application screen. This allows the user to see easy-to-understand explanations of technical terms.

[0247] Through these steps, users can input technical terms and obtain concise explanations, thereby gaining a deeper understanding.

[0248] 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.

[0249] This invention is a system designed to help senior users understand technical terms when using smartphones and computers, and further aims to recognize the user's emotions and provide appropriate explanations. This will reduce user stress and improve engagement.

[0250] System Configuration

[0251] This system consists of the following main components:

[0252] User terminal: A computer device such as a smartphone or tablet that provides an interface for users to input technical terms.

[0253] Server: Receives technical terms sent from the user terminal, searches the database to generate an easy-to-understand explanation, and sends it back to the user terminal.

[0254] Database: A storage system that stores technical terms and their definitions.

[0255] Natural Language Processing Engine: A software module used to replace complex technical terms with simpler language.

[0256] Emotion engine: A software module that recognizes the emotions of the user during input and sends that information to the server.

[0257] Program processing

[0258] 1. Enter and submit technical terms.

[0259] The user launches the app on their smartphone or tablet and enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field. When the user taps the "Send" button, the app retrieves this technical term.

[0260] 2. User emotion recognition

[0261] As the device inputs technical terms, it simultaneously analyzes the user's emotions using an emotion engine. The emotion engine performs facial recognition and voice tone analysis to identify the emotions the user is feeling at the time of input (e.g., doubt, anxiety, frustration, etc.).

[0262] 3. Sending data

[0263] The device sends the acquired technical terms and sentiment data to the server as an HTTPS POST request. The request includes technical terms and user sentiment information.

[0264] 4. Analysis of technical terms and sentiment data on servers

[0265] The server receives an HTTP request and analyzes technical terms and sentiment data. Specifically, the server extracts technical terms and sentiment data (e.g., "Wi-Fi", "anxiety") from the request body.

[0266] 5. Generating the explanatory text

[0267] The server retrieves definitions for technical terms by executing SQL queries against the database. For example, the server might retrieve the definition for the technical term "Wi-Fi" as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless internet connection."

[0268] 6. Use of Natural Language Processing Engines

[0269] The acquired definitions are passed to a natural language processing engine, which identifies complex terms such as "wireless LAN" and "technical standards" and converts them into easily understandable language. Furthermore, sentiment data is taken into consideration, and the tone and content of the explanatory text are appropriately adjusted.

[0270] 7. Sending and displaying the description

[0271] The server sends the generated explanatory text to the user's terminal as an HTTP response. For example, it might be adjusted to say, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[0272] The device receives an HTTP response and extracts a descriptive text generated from the response body. Finally, the device displays a user-friendly and easy-to-understand descriptive text on the app screen, making it accessible to the user.

[0273] Specific example

[0274] Example 1: "Wi-Fi"

[0275] 1. The user typed "What is Wi-Fi?" and seems a little unsure.

[0276] 2. The device sends the keyword "Wi-Fi" and the emotion data "anxiety" to the server.

[0277] 3. The server searches the database for "Wi-Fi" and retrieves the definition: "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[0278] 4. The server uses a natural language processing engine to generate an easy-to-understand explanation: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[0279] 5. The server sends the explanatory text to the terminal.

[0280] 6. The terminal displays the explanatory text to the user.

[0281] Example 2: "Browser"

[0282] 1. The user inputs "What is a browser?" and is a bit impatient.

[0283] 2. The terminal sends the keyword "browser" and the emotion data "impatience" to the server.

[0284] 3. The server searches for "browser" in the database and obtains the definition "Browser is software for displaying HTML documents, such as Chrome or Firefox".

[0285] 4. The server uses a natural language processing engine to generate an easy-to-understand explanatory text: "A browser is an application for viewing Internet pages. We support you to solve it quickly."

[0286] 5. The server sends the explanatory text to the terminal.

[0287] 6. The terminal displays the explanatory text to the user.

[0288] In this way, the present invention supports senior users to easily understand technical terms, and by further considering the user's emotions, it can reduce stress and promote the use of smartphones and computers.

[0289] The following describes the processing flow.

[0290] Step 1:

[0291] The user launches a smartphone app and enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field. When the user taps the "Send" button, the device retrieves this technical term.

[0292] Step 2:

[0293] As the device receives input of technical terms, it simultaneously analyzes the user's emotions using an emotion engine. The emotion engine analyzes the user's facial expressions and voice to identify the user's emotions (e.g., anxiety, doubt, frustration, etc.).

[0294] Step 3:

[0295] The device structures the acquired technical terms and sentiment data and sends it to the server as an HTTP POST request. The request includes "Wi-Fi" and the user's sentiment.

[0296] Step 4:

[0297] The server receives the HTTP request and parses its contents. Specifically, the server extracts the technical term "Wi-Fi" and emotional data (e.g., "anxiety") from the request body.

[0298] Step 5:

[0299] The server executes an SQL query against the database to retrieve the definition of a technical term. For example, the server might retrieve the definition of the technical term "Wi-Fi" as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[0300] Step 6:

[0301] The server passes the acquired definitions to a natural language processing engine, which converts complex parts into easily understandable language. The natural language processing engine replaces complex terms such as "wireless LAN" and "technical standards" with simpler words.

[0302] Step 7:

[0303] Based on the analyzed emotion data of the server, adjust the content and tone of the explanatory text. For example, if the emotion data is "uneasy", adjust the explanatory text to include phrases such as "Please rest assured".

[0304] Step 8:

[0305] The server generates the final explanatory text (e.g., "Wi-Fi is a way for smartphones and computers to connect to the Internet without using cables. Please rest assured, this method is easy to use.") and sends it to the user terminal as an HTTP response.

[0306] Step 9:

[0307] The terminal receives the HTTP response and extracts the explanatory text generated from the response body.

[0308] Step 10:

[0309] The terminal displays an easy-to-understand explanatory text that takes into account the user's emotions on the app screen so that the user can view it. For example, display an explanation such as "Wi-Fi is a way for smartphones and computers to connect to the Internet without using cables. Please rest assured, this method is easy to use."

[0310] Through the above series of processing steps, senior users can more easily understand technical terms, and by further considering their emotions, they can use smartphones and computers while reducing stress.

[0311] (Example 2)

[0312] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0313] In today's technological society, many users, including the elderly, struggle to understand technical and jargon. Seniors, in particular, often experience emotional stress and frustration due to the difficulty of technical terms, which acts as a barrier to technological adoption. These challenges reduce the convenience and engagement with technology, ultimately preventing them from fully benefiting from evolving technological services.

[0314] 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.

[0315] In this invention, the server includes means for recognizing the user's emotions and generating emotion data, means for adjusting the content and tone of the explanatory text based on the emotion data, and a natural language processing engine that analyzes difficult parts of technical terms and replaces them with simpler words. This not only helps the user understand but also reduces user stress and improves engagement by providing emotionally sensitive explanations.

[0316] A "user" refers to an individual who uses a service or system.

[0317] "Technical jargon" refers to specialized or technical terms used in a particular field or industry.

[0318] A "server" refers to a computer system that receives requests from users and processes and provides data.

[0319] A "database" refers to a system that systematically stores data and allows for the retrieval and searching of that data as needed.

[0320] An "explanatory text" refers to text generated to clearly explain the meaning and usage of technical terms and jargon.

[0321] "User terminal" refers to devices used by a user, such as smartphones, tablets, and personal computers.

[0322] "Emotional data" refers to information that represents a user's emotional state (for example, anxiety, doubt, frustration, etc.).

[0323] A "natural language processing engine" refers to a software module that analyzes text data and converts it into a form that is easy for humans to understand.

[0324] An "HTTPS POST request" is a type of protocol used to send data to a server over the internet.

[0325] An "SQL query" refers to a set of commands used to manipulate or retrieve data from a database.

[0326] This invention is a system designed to assist senior users in understanding technical terms when using smartphones and computers. Furthermore, it aims to recognize the user's emotions and provide appropriate explanations. This system can reduce user stress and improve engagement.

[0327] System Configuration

[0328] This system consists of the following main components:

[0329] User terminal: A device such as a smartphone, tablet, or personal computer that provides an interface for users to input technical terms.

[0330] Server: Receives technical terms and sentiment data sent from the user terminal, searches the database to generate an easy-to-understand explanation, and sends it back to the user terminal.

[0331] Database: A storage system that stores technical terms and their definitions.

[0332] Natural Language Processing Engine: A software module used to replace complex technical terms with simpler language.

[0333] Emotion engine: A software module that recognizes the emotions of the user during input and sends that information to the server.

[0334] Explanation of the program's processing

[0335] 1. Enter and submit technical terms.

[0336] The user launches an app on their smartphone or tablet and enters a technical term they find difficult to understand into the input field. For example, they might enter "Wi-Fi". When the user taps the "Send" button, the device receives the user's input and prepares to proceed to the next step.

[0337] 2. User emotion recognition

[0338] The device activates its emotion engine simultaneously with the input of technical terms. The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice in real time. For example, the camera captures the user's facial expression, and the emotion analysis algorithm detects "anxiety." This information is then used in the following processes.

[0339] 3. Sending data

[0340] The device compiles the acquired technical terms and sentiment data and sends an HTTPS POST request to the server. The request body includes data such as "Technical Terms: Wi-Fi" and "Sentiment: Anxiety." Once the server receives this request, it proceeds to the next step.

[0341] 4. Analysis of technical terms and sentiment data on servers

[0342] The server parses the received HTTP request and extracts technical terms and sentiment data from the request body. For example, the data might be extracted in the form of "technical term = Wi-Fi" and "sentiment = anxiety." Based on this data, the server prepares to query the database and look up the definitions of the technical terms.

[0343] 5. Generating the explanatory text

[0344] The server executes SQL queries against the database to search for definitions corresponding to technical terms. For example, for the technical term "Wi-Fi," it retrieves the definition from the database as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet." Based on this retrieved definition, it generates an explanatory text.

[0345] 6. Use of Natural Language Processing Engines

[0346] The server passes the acquired definitions to a natural language processing engine. The natural language processing engine identifies complex terms such as "wireless LAN" and "technical standards" and converts them into easily understandable language. It also adjusts the tone of the explanation to be reassuring based on the emotion data "anxiety." For example, it might generate an explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[0347] 7. Sending and displaying the description

[0348] The server generates an explanatory text and sends it to the user's terminal as an HTTP response. For example, the response body might include a message like, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use." The terminal receives this HTTP response and extracts the generated explanatory text from the response body. The terminal then displays the user-friendly and emotionally reassuring explanatory text on the app screen. By viewing this explanation, the user gains a deeper understanding of technical terms and a sense of emotional reassurance.

[0349] Specific example

[0350] Example 1: "Wi-Fi"

[0351] 1. The user opens a smartphone app and types "What is Wi-Fi?". They feel a little unsure.

[0352] 2. The device acquires the keyword "Wi-Fi," analyzes the emotion data "anxiety" using the emotion engine, and sends it to the server.

[0353] 3. The server receives the HTTP request, analyzes the "Wi-Fi" and "anxiety" data, and queries the database.

[0354] 4. The server obtains the definition that "Wi-Fi is a wireless LAN technology standard that allows wireless internet connection" and uses a natural language processing engine to generate the following explanation: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[0355] 5. The server sends an explanatory message to the terminal.

[0356] 6. The device receives the explanation and displays the following message on the app screen: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[0357] Example 2: "Browser"

[0358] 1. The user opens a smartphone app, types "What's a browser?", and becomes slightly frustrated.

[0359] 2. The device acquires the keyword "browser," analyzes the emotion data "frustration" using the emotion engine, and sends it to the server.

[0360] 3. The server receives the HTTP request, analyzes the "browser" and "frustration" data, and queries the database.

[0361] 4. The server obtains the definition that "a browser is software for displaying HTML documents, such as Chrome or Firefox," and uses a natural language processing engine to generate the explanation, "A browser is an application for viewing internet pages. We will support you so that you can resolve the issue quickly."

[0362] 5. The server sends an explanatory message to the terminal.

[0363] 6. The device receives the explanation and displays the following message on the app screen: "The browser is an app for viewing internet pages. We will help you resolve the issue quickly."

[0364] Examples of prompts for generative AI models

[0365] Q: If you type "What is Wi-Fi?"

[0366] A: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, it's easy to use."

[0367] Q: What is a browser?

[0368] A: "A browser is an application for viewing internet pages. I'll help you resolve this quickly."

[0369] Thus, the present invention can help senior users understand technical terms more easily, and by taking into consideration the user's feelings, it can reduce stress and promote the use of smartphones and computers.

[0370] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0371] Step 1:

[0372] The user launches the app on their smartphone or tablet, enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field, and taps the "Send" button.

[0373] Input: Technical terms (e.g., "Wi-Fi")

[0374] Output: Technical terms (e.g., "Wi-Fi")

[0375] Specific action: The terminal receives user input and prepares to proceed to the next process.

[0376] Step 2:

[0377] The device activates its emotion engine simultaneously with the input of technical terms. The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice in real time.

[0378] Input: User's facial expressions and voice

[0379] Output: Emotional data (e.g., "anxiety")

[0380] Specific operation: The camera captures the user's facial expressions, and an emotion analysis algorithm reads the user's "anxiety."

[0381] Step 3:

[0382] The device compiles the acquired technical terms and sentiment data and sends an HTTPS POST request to the server.

[0383] Input: Technical terms (e.g., "Wi-Fi"), emotional data (e.g., "anxiety")

[0384] Output: HTTP request sent to the server

[0385] Specific action: Include technical terms and sentiment data in the request body.

[0386] Step 4:

[0387] The server analyzes the received HTTP request and extracts technical terms and sentiment data from the request body.

[0388] Input: HTTP Request

[0389] Output: Technical terms (e.g., "Wi-Fi"), emotional data (e.g., "anxiety")

[0390] Specific operation: The server parses the request body and extracts technical terms and sentiment data.

[0391] Step 5:

[0392] The server executes an SQL query against the database to retrieve definitions corresponding to technical terms.

[0393] Input: Technical terms (e.g., "Wi-Fi")

[0394] Output: Definitions of technical terms (e.g., "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless internet connection")

[0395] Specific operation: The server executes an SQL query and retrieves the corresponding definition from the database.

[0396] Step 6:

[0397] The server passes the acquired definitions to a natural language processing engine, which converts complex parts into simpler language. It also adjusts the tone of the explanatory text based on sentiment data.

[0398] Input: Definitions of technical terms (e.g., "Wi-Fi is a wireless LAN technology that allows wireless internet connection"), emotional data (e.g., "anxiety")

[0399] Output: Easy-to-understand explanation (Example: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use.")

[0400] Specific operation: The natural language processing engine converts complex parts into simpler words and adjusts the tone based on sentiment data.

[0401] Step 7:

[0402] The server generates an explanatory text which is then sent to the user's terminal as an HTTP response.

[0403] Input: A clear and easy-to-understand explanation (Example: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, it's easy to use.")

[0404] Output: HTTP response sent to the user's terminal

[0405] Specific action: Include a descriptive text in the HTTP response body.

[0406] Step 8:

[0407] The device receives an HTTP response and extracts a description generated from the response body. Finally, the device displays a user-friendly and emotionally resonant description on the app's screen.

[0408] Input: HTTP response

[0409] Output: Explanatory text displayed on the screen (Example: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use.")

[0410] Specific operation: The device extracts the explanatory text from the response body and displays it on the app's screen.

[0411] (Application Example 2)

[0412] 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".

[0413] Senior users face challenges when using electronic payment services, such as difficulty understanding technical terms and procedures, leading to anxiety and frustration. This is particularly true in the field of electronic payments, where technical jargon is prevalent, creating barriers to use and significantly detracting from the user experience. Furthermore, errors and security risks arising from a lack of understanding of technical terms must also be considered. Therefore, there is a need for electronic payment services that are easy for seniors to understand and use with confidence.

[0414] 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.

[0415] In this invention, the server includes means for receiving technical terms entered by the user, means for recognizing and analyzing emotions, means for transmitting the received technical terms and emotion data to the server, means for the server to search for technical terms in a database and generate an easy-to-understand explanation, means for adjusting the generated explanation with consideration for the user's emotions, means for transmitting the generated explanation to the user terminal, and means for the user terminal to display the generated explanation. As a result, users can easily understand and use electronic payment services with peace of mind without feeling anxious or frustrated with technical terms or procedures.

[0416] "User-input technical terms" refer to technical terms that users find difficult to understand and enter into the device's interface.

[0417] "Means for recognizing and analyzing emotions" refers to software modules used to analyze a user's emotional state, employing techniques such as facial recognition and voice tone analysis.

[0418] "Means for sending received technical terms and emotion data to the server" refers to communication means for sending technical terms and emotion recognition data acquired from the user terminal to the server.

[0419] "A means by which a server searches a database for technical terms and generates easy-to-understand explanations" refers to a process in which a server retrieves definitions corresponding to technical terms from a database and converts them into easy-to-understand explanations.

[0420] "Means for adjusting generated descriptions with consideration for user emotions" refers to a natural language processing engine that adjusts the tone and expression of generated descriptions according to the user's emotional state.

[0421] "Means for sending the generated explanatory text to the user terminal" refers to communication means for sending the explanatory text generated and adjusted by the server to the user terminal.

[0422] "Means for displaying the generated explanatory text on the user terminal" refers to screen display means for displaying the explanatory text received by the user terminal so that the user can view it.

[0423] This invention is a system designed to help senior users understand technical terms and procedures when using electronic payment services, thereby reducing stress. The system uses a combination of a natural language processing engine that converts technical terms into easy-to-understand explanations and an emotion engine that recognizes the user's emotions.

[0424] The system consists of the following elements:

[0425] 1. User terminal: A device such as a smartphone or tablet that provides an interface for users to input technical terms they find difficult to understand and for acquiring sentiment data.

[0426] 2. Emotion Recognition: Operates on the user's device and recognizes the user's emotions using facial recognition APIs (e.g., AWS® Rekognition) and voice tone analysis.

[0427] 3. Data transmission: Includes means of communication for sending user-entered technical terms and sentiment data to the server.

[0428] 4. Server: Utilizes a database and a natural language processing engine (e.g., SpaCy, BERT) to search for definitions of technical terms and generate easy-to-understand explanations.

[0429] 5. Description Adjustment: The description generated by the server is adjusted to take user emotions into consideration, and the tone and content are fine-tuned.

[0430] 6. Sending to the user terminal: The generated explanation is sent to the user terminal and displayed to the user.

[0431] Process Description

[0432] Hardware and software

[0433] Hardware: User devices (smartphones, tablets)

[0434] software:

[0435] Emotion recognition software (e.g., AWS Rekognition)

[0436] Natural language processing engines (e.g., SpaCy, BERT)

[0437] Server-side applications (e.g., Node.js, Express)

[0438] Database (e.g., MySQL (registered trademark))

[0439] Data processing and data calculation

[0440] When a user inputs a technical term, the system simultaneously acquires the term and the user's emotional data. This emotional data is obtained through facial recognition and voice tone analysis.

[0441] Next, the device sends this data to the server. The server searches its database based on the received technical terms and generates an easy-to-understand explanation. The generated explanation then goes through a natural language processing engine to adjust its tone and content according to the user's sentiment. The adjusted explanation is then sent to the user's device and finally displayed to the user on the device.

[0442] Specific examples

[0443] For example, if a user types "What is a security code?" and is feeling anxious, the device sends the keyword "security code" and the emotion data "anxiety" to the server. The server searches its database for "security code" and retrieves its definition. Then, using a natural language processing engine, it generates an explanation such as "A security code is a 3- or 4-digit number printed on the back of your card that ensures secure online transactions. There's no need to be anxious. Please check it out," and displays it to the user.

[0444] Example of a prompt

[0445] A prompt message to use when a user is feeling unsure and asks, "What is a security code?":

[0446] "The security code is a three- or four-digit number printed on the back of your card, and it guarantees secure online transactions. There's no need to worry. Please take a look."

[0447] This system will make it easy for senior users to understand technical terms and procedures, allowing them to use electronic payment services with peace of mind.

[0448] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0449] Step 1:

[0450] Users enter technical terms they don't understand into the input field of their smartphone or tablet. The keywords entered by the user might be something like "security code."

[0451] Input: Technical terms (e.g., "security code")

[0452] Output: Input technical term data

[0453] Specific operation: The user launches the application, enters a technical term into the input field, and presses the "Submit" button.

[0454] Step 2:

[0455] The device uses a camera and microphone to recognize the user's emotions. The emotion recognition engine uses facial recognition APIs and voice tone analysis.

[0456] Input: User's face image, voice data

[0457] Output: Emotional data (e.g., "anxiety")

[0458] Specific operation: The emotion recognition engine analyzes the user's facial expressions and voice tone to identify their emotional state (e.g., "anxiety").

[0459] Step 3:

[0460] The terminal receives technical terms and sentiment data and sends it to the server as an HTTPS POST request.

[0461] Input: Technical terminology data, sentiment data

[0462] Output: Data sent to the server

[0463] Specific operation: The device packages technical terminology data and sentiment data in JSON format, creates an HTTPS POST request, and sends it to the server.

[0464] Step 4:

[0465] The server receives an HTTP request and analyzes the technical terms and sentiment data.

[0466] Input: Technical terminology data, sentiment data

[0467] Output: Analysis result data

[0468] Specific operation: The server extracts technical terminology data and sentiment data from the request body and analyzes each type of data.

[0469] Step 5:

[0470] The server retrieves definitions of technical terms by executing SQL queries against the database.

[0471] Input: Technical terminology data

[0472] Output: Definition data (Example: "The security code is a 3- or 4-digit number printed on the back of the card that ensures secure online transactions.")

[0473] Specific operation: The server executes an SQL query against the database to retrieve definitions of technical terms.

[0474] Step 6:

[0475] The server retrieves definitions from the database and passes them to a natural language processing engine to generate easy-to-understand explanatory text. It also adjusts the tone and content, taking sentiment data into consideration.

[0476] Input: Definition data, sentiment data

[0477] Output: Adjusted explanation (Example: "The security code is a 3- or 4-digit number printed on the back of your card, ensuring secure online transactions. There's no need to worry. Please check it out.")

[0478] Specific operation: The natural language processing engine converts complex parts of the definition data into simpler words and adjusts the explanatory text based on sentiment data.

[0479] Step 7:

[0480] The server generates an explanatory text which is then sent to the user's terminal as an HTTP response.

[0481] Input: Adjusted description

[0482] Output: Descriptive data sent to the user terminal

[0483] Specific operation: The server generates an HTTP response containing an explanation and sends it to the user's terminal.

[0484] Step 8:

[0485] The application displays the explanatory text received by the user's terminal on its screen.

[0486] Input: Received explanatory data

[0487] Output: Description displayed on the screen

[0488] Specific operation: The device displays an explanatory text on the screen, which the user can view. At this time, the explanatory text will be considerate of the user's feelings, such as, "The security code is a 3-digit or 4-digit number printed on the back of the card, and it guarantees secure online transactions. There is no need to worry. Please take a look."

[0489] 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.

[0490] 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.

[0491] 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.

[0492] [Second Embodiment]

[0493] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0494] 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.

[0495] 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).

[0496] 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.

[0497] 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.

[0498] 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).

[0499] 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.

[0500] 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.

[0501] 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.

[0502] 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.

[0503] 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.

[0504] 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".

[0505] This invention is a system designed to help senior users understand technical terms when using smartphones and computers. To achieve this objective, the system includes multiple means for explaining technical terms entered by the user in an easy-to-understand manner.

[0506] System Configuration

[0507] This system consists of the following main components:

[0508] User terminal: A computer device such as a smartphone or tablet that provides an interface for users to input technical terms.

[0509] Server: Receives technical terms sent from the user terminal, searches the database to generate an easy-to-understand explanation, and sends it back to the user terminal.

[0510] Database: A storage system that stores technical terms and their definitions.

[0511] Natural Language Processing Engine: A software module used to replace complex technical terms with simpler language.

[0512] Program processing

[0513] 1. Enter and submit technical terms.

[0514] The user launches an app on their smartphone or tablet and enters technical terms they find difficult to understand into an input field. For example, they might enter "Wi-Fi". Once this input is complete, the device sends the technical terms to the server. Specifically, the device sends the entered data as a POST request to a particular API endpoint.

[0515] 2. Analysis of technical terms on the server

[0516] The server receives requests sent from user terminals and matches the technical terms against the database. For example, the server searches the database for the keyword "Wi-Fi". If this search finds a matching entry, the server retrieves the information for that entry. The entry includes a definition such as "Wi-Fi is a wireless LAN technical standard, a technology that enables wireless internet connectivity."

[0517] 3. Generating explanatory text

[0518] The definition obtained from the database is then passed to the natural language processing engine on the server. This engine generates an easy-to-understand explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0519] 4. Sending and displaying the description

[0520] The server generates an explanatory text and sends it back to the user's device. Specifically, the server sends data containing the explanatory text as an HTTP response. Finally, the device receives this response data and displays an easy-to-understand explanatory text on the app's screen. For example, it might say, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables," which the user then reads.

[0521] Specific example

[0522] Example 1: "Wi-Fi"

[0523] 1. The user types "What is Wi-Fi?".

[0524] 2. The device sends the keyword "Wi-Fi" to the server.

[0525] 3. The server searches the database for "Wi-Fi" and retrieves the definition: "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[0526] 4. The server uses a natural language processing engine to generate an easy-to-understand explanation: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0527] 5. The server sends an explanatory message to the terminal.

[0528] 6. The device displays an explanatory text to the user.

[0529] Example 2: "Browser"

[0530] 1. The user types "What is a browser?".

[0531] 2. The device sends the keyword "browser" to the server.

[0532] 3. The server searches the database for "browser" and retrieves the definition: "A browser is software used to display HTML documents, such as Chrome or Firefox."

[0533] 4. The server uses a natural language processing engine to generate an easy-to-understand explanation: "A browser is an application for viewing various pages on the internet."

[0534] 5. The server sends an explanatory message to the terminal.

[0535] 6. The device displays an explanatory text to the user.

[0536] In this way, the present invention can help senior users understand technical terms more easily and promote the use of smartphones and computers.

[0537] The following describes the processing flow.

[0538] Step 1:

[0539] The user launches a smartphone app and enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field. When the user taps the "Send" button, the app retrieves this technical term.

[0540] Step 2:

[0541] The terminal retrieves the entered technical term and sends an HTTP POST request to the server. The request contains the technical term.

[0542] Step 3:

[0543] The server receives an HTTP request and parses the technical terms data. Specifically, the server extracts technical terms (e.g., "Wi-Fi") from the request body.

[0544] Step 4:

[0545] The server executes an SQL query against the database to retrieve the definition of a technical term. For example, the server might retrieve the definition of the technical term "Wi-Fi" as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[0546] Step 5:

[0547] The server passes the acquired definitions to the natural language processing engine. The natural language processing engine identifies complex terms such as "wireless LAN" and "technical standards" and converts them into easily understandable language.

[0548] Step 6:

[0549] The server uses the output of a natural language processing engine to generate explanatory text that is easy for the user to understand. For example, it might generate an explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0550] Step 7:

[0551] The server generates an explanatory text which is then sent to the user's terminal as an HTTP response.

[0552] Step 8:

[0553] The terminal receives an HTTP response and extracts the generated explanatory text from the response body.

[0554] Step 9:

[0555] The device displays easy-to-understand explanatory text on the app screen. Users will be able to view explanations such as, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables."

[0556] This series of steps will make it easier for senior users to understand technical terms and to use smartphones and computers more effectively.

[0557] (Example 1)

[0558] 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."

[0559] With the advancement of modern information technology, many users, including seniors, often find it difficult to understand technical jargon when using smartphones and computers. This problem is particularly pronounced when using the internet or new software, potentially widening the digital divide. Therefore, there is a need for systems that make this technical jargon easy to understand.

[0560] 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.

[0561] In this invention, the server includes means for receiving technical terms entered by the user, means for transmitting the received technical terms to a central processing unit, means for the central processing unit to retrieve the technical terms from a storage device and generate an easy-to-understand explanation, means for transmitting the generated explanation to a user device, and means for the user device to display the generated explanation. This makes it possible for a diverse range of users, including senior citizens, to easily understand technical terms.

[0562] "User" refers to a general user of the system.

[0563] "Technical jargon" refers to terms related to a specific field or technology that are difficult for the average user to understand.

[0564] "Means of receiving" refers to devices or modules that have the function of taking in data and information entered by the user into the system.

[0565] "Means of transmission" refers to devices or modules that have the function of sending received data or information to another device or module.

[0566] A "central processing unit" refers to the main device or module that handles information processing for the entire system and processes data based on instructions.

[0567] A "storage device" refers to a storage system used to store data and information.

[0568] A "natural language processing module" refers to a software module that converts natural language into an easily understandable format through the analysis and generation of input text.

[0569] "User device" refers to a device used by a user to access the system, and includes smartphones, tablets, and computers.

[0570] "Public information sources" refer to information sources that are generally accessible, such as websites and public databases on the internet.

[0571] Modes for carrying out the invention

[0572] This invention is a system designed to support users, including senior citizens, who may have difficulty understanding technical terms. This system consists of the following main components:

[0573] Components

[0574] 1. User device: A device such as a smartphone, tablet, or computer that provides an interface for the user to input technical terms.

[0575] 2. Central Processing Unit: This is the main computer system responsible for searching, analyzing, and generating explanatory texts for technical terms.

[0576] 3. Storage device: A database that stores technical terms and their explanations.

[0577] 4. Natural Language Processing Module: This is a software module for replacing technical jargon with easily understandable language.

[0578] 5. Public Information Sources: This is a system for collecting information on specialized terminology not found in databases from the internet.

[0579] Explanation of the program's processing

[0580] To generate the program for this system, follow these steps:

[0581] Entering and sending technical terms

[0582] First, the user launches an app on their smartphone or tablet and enters technical terms they find difficult to understand into the input field. For example, the user might enter "Wi-Fi". Once this input is complete, the device sends the technical terms to the server (central processing unit). Specifically, the device sends the entered data as a POST request to a particular API endpoint.

[0583] Analysis of technical terms on servers

[0584] The server receives requests sent from user terminals and matches the technical terms against its storage. For example, the server searches the database for the keyword "Wi-Fi". If this search finds a matching entry, the server retrieves the information for that entry. The entry includes a definition such as "Wi-Fi is a wireless LAN technical standard, a technology that enables wireless internet connectivity."

[0585] Generating an explanatory text

[0586] Next, the acquired definition is passed to a natural language processing module. The server uses this module to generate an easy-to-understand explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0587] Sending and displaying the description

[0588] Finally, the generated explanation is sent to the user's device, and the terminal displays the explanation on the app's screen. For example, it might say, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables," which the user can then view.

[0589] Specific example

[0590] Example 1: "Wi-Fi"

[0591] 1. The user types "What is Wi-Fi?".

[0592] 2. The device sends the keyword "Wi-Fi" to the central processing unit.

[0593] 3. The central processing unit searches for "Wi-Fi" in the memory and obtains the definition that "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[0594] 4. The central processing unit uses a natural language processing module to generate an easy-to-understand explanation: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0595] 5. The central processing unit transmits the explanatory text to the user device.

[0596] 6. The user device displays an explanatory text to the user.

[0597] Example 2: "Browser"

[0598] 1. The user types "What is a browser?".

[0599] 2. The terminal sends the keyword "browser" to the central processing unit.

[0600] 3. The central processing unit searches for "browser" in its memory and retrieves the definition that "a browser is software for displaying HTML documents, such as Chrome or Firefox."

[0601] 4. The central processing unit uses a natural language processing module to generate an easy-to-understand explanation: "A browser is an application for viewing various pages on the internet."

[0602] 5. The central processing unit transmits the explanatory text to the user device.

[0603] 6. The user device displays an explanatory text to the user.

[0604] Example of a prompt

[0605] Examples of prompt statements to input into a generative AI model are as follows:

[0606] If a user types "What is Wi-Fi?", the system will perform the following steps:

[0607] 1. The device sends the keyword "Wi-Fi" to the central processing unit.

[0608] 2. The central processing unit searches for "Wi-Fi" in the memory and retrieves the corresponding definition.

[0609] 3. The definition obtained by the central processing unit is converted into simple words using a natural language processing module.

[0610] 4. The central processing unit sends the easy-to-understand explanatory text it has generated back to the terminal.

[0611] 5. The device displays the explanatory text on the user's screen.

[0612] As a concrete example, we will display an explanation such as, "Wi-Fi is a method that allows smartphones and computers to connect to the internet without using cables." This makes it easier for users to understand technical terms.

[0613]

[0614] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0615] Detailed explanation of the program's processing

[0616] Step 1: User input reception and submission

[0617] Input: Technical term Example: "Wi-Fi"

[0618] Operation:

[0619] The user launches the app on their smartphone or tablet and enters technical terms that are difficult to understand into the input field.

[0620] Once input is complete, the terminal sends the technical terms to the central processing unit (server).

[0621] Specifically, the device sends the entered data as a POST request to a specific API endpoint.

[0622] Output: Technical terminology data sent to the server

[0623] Step 2: The server receives the request.

[0624] Input: POST request sent from the terminal

[0625] Operation:

[0626] The server receives a POST request sent from the user's terminal.

[0627] The request includes technical terms entered by the user.

[0628] Output: Terminology data received.

[0629] Step 3: Database matching of technical terms

[0630] Input: Technical terminology data

[0631] Operation:

[0632] The server compares the received technical terms with its storage device (database).

[0633] For example, the server searches for the keyword "Wi-Fi" in the database.

[0634] If this search finds a matching entry, the server retrieves the information for that entry.

[0635] Output: Definitions of technical terms retrieved from the database. Example: "Wi-Fi is a wireless LAN technical standard, a technology that enables wireless internet connectivity."

[0636] Step 4: Analysis and conversion using a natural language processing engine

[0637] Input: Definitions of technical terms obtained from a database

[0638] Operation:

[0639] The server passes the retrieved definition to the natural language processing module.

[0640] The natural language processing module replaces complex parts with easily understandable language.

[0641] For example, it can generate an explanatory text such as, "Wi-Fi is a method that allows smartphones and computers to connect to the internet without using cables."

[0642] Output: Easy-to-understand explanation. Example: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0643] Step 5: Send and display the description.

[0644] Input: Description generated by the natural language processing module

[0645] Operation:

[0646] The server then sends the generated explanation back to the user's terminal.

[0647] Send data including a description as an HTTP response.

[0648] The device processes the HTTP response received from the server and displays an easy-to-understand explanation on the app's screen.

[0649] The user reads the displayed description.

[0650] Output: Explanation displayed on the app screen. Example: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0651] A concrete example of the entire sequence of steps

[0652] 1. In Step 1, the user types "What is Wi-Fi?".

[0653] 2. In step 2, "the device sends that data to the server."

[0654] 3. In step 3, "the server searches for 'Wi-Fi' in the database and returns the definition."

[0655] 4. In step 4, "the server passes the definition to the natural language processing module, which generates an easy-to-understand explanation."

[0656] 5. In step 5, "the server sends the generated explanation to the terminal, and the terminal displays the explanation to the user."

[0657] By following the steps outlined above, this system assists in understanding technical terms and makes it easier for users, including senior citizens, to grasp technical jargon.

[0658] (Application Example 1)

[0659] 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."

[0660] In recent years, senior citizens have increasingly used smartphones and computers, but the problem of difficulty in understanding technical jargon has become more pronounced. Security terminology, in particular, is complex, and many users struggle to understand it properly. Therefore, there is a need for support systems that enable senior citizens to easily understand technical terms and enhance their security awareness.

[0661] 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.

[0662] In this invention, the server includes means for receiving technical terms entered by the user, means for sending the received technical terms to the server, means for the server to search for the technical terms in a database and generate an easy-to-understand explanation, means for sending the generated explanation to the user terminal, means for the user terminal to display the generated explanation, means for the user to enter technical terms that are difficult to understand into an input field in the application, means for sending the entered technical terms as a POST request using an API, means for the server to compare the received technical terms with a database and convert the obtained definition into simple words using a natural language processing model, and means for sending the generated explanation as an HTTP response. This makes it possible for senior users to easily understand security terms and immediately check their explanations.

[0663] A "user terminal" is a device used by users to input technical terms and receive and display explanatory text.

[0664] "Technical jargon" refers to complex terms used in technical or specialized fields.

[0665] A "server" is a device that receives technical terms sent from a user terminal, searches a database to generate an explanation, and then sends it back to the user terminal.

[0666] A "database" is a storage system that stores technical terms and their explanations.

[0667] A "natural language processing engine" is a software module that analyzes the complex parts of technical terms and replaces them with simpler language.

[0668] "API" stands for Application Programming Interface, which is an interface for using software functions from an external source.

[0669] A "POST request" is a request method used in the HTTP protocol to send data to a server.

[0670] An "HTTP response" is the response data sent from a server to a client in the HTTP protocol.

[0671] "Hugging Face" is a popular tool that provides libraries and APIs for natural language processing.

[0672] "Simple language" refers to more general and easily understandable terms used to generate explanatory texts that are easier to understand than technical jargon.

[0673] An "input field" is an area within an application where the user enters technical terms.

[0674] "Security terminology" refers to specialized terms related to information security and network security.

[0675] This invention is a system designed to help senior users easily understand technical terms. The system consists of a user terminal, a server, a database, a natural language processing engine, and an API.

[0676] Program processing

[0677] 1. User input and data transmission

[0678] The user enters technical terms that are difficult to understand into an input field within the application. This input field is displayed on the user's device, such as a smartphone or tablet. Once the user has finished entering the terms, the device sends the entered technical terms to the server as a POST request using an API.

[0679] 2. Analysis of technical terms and acquisition of definitions

[0680] The server receives the incoming request and matches it against the database. The database stores a wide range of technical terms and their definitions; for example, if the word "firewall" is received, it retrieves a definition such as "a network security system."

[0681] 3. Generating explanatory text

[0682] The definitions of technical terms obtained are passed to a natural language processing engine on the server (e.g., Hugging Face). This engine analyzes the complex parts of the technical terms, replaces them with simpler words, and generates easy-to-understand explanations. For example, it might generate an explanation such as, "A firewall is a mechanism to protect computers and smartphones from malicious actors."

[0683] 4. Sending and displaying the description

[0684] The server sends the generated explanation as an HTTP response to the user's terminal. The user's terminal receives this response and displays the explanation within the application. This allows the user to instantly see a simple explanation of technical terms.

[0685] Specific example

[0686] Specifically, when a user types "What is a firewall?" into the app's input field, the following prompt is sent to the server:

[0687] "What is a firewall? Please explain it in simple terms."

[0688] Hardware and software to use

[0689] User devices: Smartphones, tablets

[0690] Server: A computer device that receives, analyzes, and transmits data (e.g., a cloud server).

[0691] Database: A storage system that stores technical terms and their definitions (e.g., Amazon RDS).

[0692] Natural language processing engine: Software for analyzing and simplifying technical terms (e.g., Hugging Face API)

[0693] API: An interface for sending and receiving technical terms.

[0694] This will allow senior users to more easily understand technical terms and access information that will be useful in their daily lives and to improve their security awareness.

[0695] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0696] Step 1:

[0697] The user enters technical terms into an input field within the application.

[0698] The entered data consists of technical terms such as "firewall," and this will be used as input data in Step 2.

[0699] Step 2:

[0700] The terminal sends the entered technical terms to the server using the API. The data is sent as a POST request.

[0701] Specifically, the device converts the input data into JSON format and sends it as a POST request to the API endpoint. This request is received by the server.

[0702] Step 3:

[0703] The server analyzes the received request and matches it against technical terms in the database.

[0704] The system searches a database using input data (technical terms) as keys and retrieves the corresponding definitions. For example, for the term "firewall," it retrieves the definition "network security system."

[0705] Step 4:

[0706] The server retrieves definitions of technical terms, passes them to a natural language processing engine, and converts them into simpler words.

[0707] Using a natural language processing engine (e.g., Hugging Face), the system analyzes complex technical terms and generates easy-to-understand explanations. For example, it might generate an explanation such as, "A firewall is a mechanism to protect computers and smartphones from malicious actors."

[0708] Step 5:

[0709] The server sends the generated description to the user's terminal as an HTTP response.

[0710] The generated description is converted to JSON format and sent to the terminal as an HTTP response. A success code, such as status code 200, is also sent at this time.

[0711] Step 6:

[0712] The application displays the explanatory text received by the device.

[0713] The device analyzes the received data and displays it on the application screen. This allows the user to see easy-to-understand explanations of technical terms.

[0714] Through these steps, users can input technical terms and obtain concise explanations, thereby gaining a deeper understanding.

[0715] 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.

[0716] This invention is a system designed to help senior users understand technical terms when using smartphones and computers, and further aims to recognize the user's emotions and provide appropriate explanations. This will reduce user stress and improve engagement.

[0717] System Configuration

[0718] This system consists of the following main components:

[0719] User terminal: A computer device such as a smartphone or tablet that provides an interface for users to input technical terms.

[0720] Server: Receives technical terms sent from the user terminal, searches the database to generate an easy-to-understand explanation, and sends it back to the user terminal.

[0721] Database: A storage system that stores technical terms and their definitions.

[0722] Natural Language Processing Engine: A software module used to replace complex technical terms with simpler language.

[0723] Emotion engine: A software module that recognizes the emotions of the user during input and sends that information to the server.

[0724] Program processing

[0725] 1. Enter and submit technical terms.

[0726] The user launches the app on their smartphone or tablet and enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field. When the user taps the "Send" button, the app retrieves this technical term.

[0727] 2. User emotion recognition

[0728] As the device inputs technical terms, it simultaneously analyzes the user's emotions using an emotion engine. The emotion engine performs facial recognition and voice tone analysis to identify the emotions the user is feeling at the time of input (e.g., doubt, anxiety, frustration, etc.).

[0729] 3. Sending data

[0730] The device sends the acquired technical terms and sentiment data to the server as an HTTPS POST request. The request includes technical terms and user sentiment information.

[0731] 4. Analysis of technical terms and sentiment data on servers

[0732] The server receives an HTTP request and analyzes technical terms and sentiment data. Specifically, the server extracts technical terms and sentiment data (e.g., "Wi-Fi", "anxiety") from the request body.

[0733] 5. Generating the explanatory text

[0734] The server retrieves definitions for technical terms by executing SQL queries against the database. For example, the server might retrieve the definition for the technical term "Wi-Fi" as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless internet connection."

[0735] 6. Use of Natural Language Processing Engines

[0736] The acquired definitions are passed to a natural language processing engine, which identifies complex terms such as "wireless LAN" and "technical standards" and converts them into easily understandable language. Furthermore, sentiment data is taken into consideration, and the tone and content of the explanatory text are appropriately adjusted.

[0737] 7. Sending and displaying the description

[0738] The server sends the generated explanatory text to the user's terminal as an HTTP response. For example, it might be adjusted to say, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[0739] The device receives an HTTP response and extracts a descriptive text generated from the response body. Finally, the device displays a user-friendly and easy-to-understand descriptive text on the app screen, making it accessible to the user.

[0740] Specific example

[0741] Example 1: "Wi-Fi"

[0742] 1. The user typed "What is Wi-Fi?" and seems a little unsure.

[0743] 2. The device sends the keyword "Wi-Fi" and the emotion data "anxiety" to the server.

[0744] 3. The server searches the database for "Wi-Fi" and retrieves the definition: "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[0745] 4. The server uses a natural language processing engine to generate an easy-to-understand explanation: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[0746] 5. The server sends an explanatory message to the terminal.

[0747] 6. The device displays an explanatory text to the user.

[0748] Example 2: "Browser"

[0749] 1. The user types "What is a browser?" and seems a little frustrated.

[0750] 2. The device sends the keyword "browser" and emotion data "frustration" to the server.

[0751] 3. The server searches the database for "browser" and retrieves the definition: "A browser is software used to display HTML documents, such as Chrome or Firefox."

[0752] 4. The server uses a natural language processing engine to generate an easy-to-understand explanation: "A browser is an application for viewing internet pages. We will support you so that you can resolve your issue quickly."

[0753] 5. The server sends an explanatory message to the terminal.

[0754] 6. The device displays an explanatory text to the user.

[0755] In this way, the present invention can help senior users understand technical terms more easily, and by taking into consideration the user's feelings, it can reduce stress and promote the use of smartphones and computers.

[0756] The following describes the processing flow.

[0757] Step 1:

[0758] The user launches a smartphone app and enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field. When the user taps the "Send" button, the device retrieves this technical term.

[0759] Step 2:

[0760] As the device receives input of technical terms, it simultaneously analyzes the user's emotions using an emotion engine. The emotion engine analyzes the user's facial expressions and voice to identify the user's emotions (e.g., anxiety, doubt, frustration, etc.).

[0761] Step 3:

[0762] The device structures the acquired technical terms and sentiment data and sends it to the server as an HTTP POST request. The request includes "Wi-Fi" and the user's sentiment.

[0763] Step 4:

[0764] The server receives the HTTP request and parses its contents. Specifically, the server extracts the technical term "Wi-Fi" and emotional data (e.g., "anxiety") from the request body.

[0765] Step 5:

[0766] The server executes an SQL query against the database to retrieve the definition of a technical term. For example, the server might retrieve the definition of the technical term "Wi-Fi" as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[0767] Step 6:

[0768] The server passes the acquired definitions to a natural language processing engine, which converts complex parts into easily understandable language. The natural language processing engine replaces complex terms such as "wireless LAN" and "technical standards" with simpler words.

[0769] Step 7:

[0770] The server adjusts the content and tone of the explanatory text based on the analyzed sentiment data. For example, if the sentiment data indicates "anxiety," the explanatory text will be adjusted to include phrases such as "Please rest assured."

[0771] Step 8:

[0772] The server generates a final explanation (e.g., "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use.") and sends it to the user's terminal as an HTTP response.

[0773] Step 9:

[0774] The terminal receives an HTTP response and extracts the generated explanatory text from the response body.

[0775] Step 10:

[0776] The device will display easy-to-understand explanations on the app screen that are considerate of the user's feelings, and allow the user to view them. For example, it might display an explanation such as, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[0777] Through these processing steps, senior users will find it easier to understand technical terms, and by taking their feelings into consideration, they will be able to use smartphones and computers with reduced stress.

[0778] (Example 2)

[0779] 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".

[0780] In today's technological society, many users, including the elderly, struggle to understand technical and jargon. Seniors, in particular, often experience emotional stress and frustration due to the difficulty of technical terms, which acts as a barrier to technological adoption. These challenges reduce the convenience and engagement with technology, ultimately preventing them from fully benefiting from evolving technological services.

[0781] 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.

[0782] In this invention, the server includes means for recognizing the user's emotions and generating emotion data, means for adjusting the content and tone of the explanatory text based on the emotion data, and a natural language processing engine that analyzes difficult parts of technical terms and replaces them with simpler words. This not only helps the user understand but also reduces user stress and improves engagement by providing emotionally sensitive explanations.

[0783] A "user" refers to an individual who uses a service or system.

[0784] "Technical jargon" refers to specialized or technical terms used in a particular field or industry.

[0785] A "server" refers to a computer system that receives requests from users and processes and provides data.

[0786] A "database" refers to a system that systematically stores data and allows for the retrieval and searching of that data as needed.

[0787] An "explanatory text" refers to text generated to clearly explain the meaning and usage of technical terms and jargon.

[0788] "User terminal" refers to devices used by a user, such as smartphones, tablets, and personal computers.

[0789] "Emotional data" refers to information that represents a user's emotional state (for example, anxiety, doubt, frustration, etc.).

[0790] A "natural language processing engine" refers to a software module that analyzes text data and converts it into a form that is easy for humans to understand.

[0791] An "HTTPS POST request" is a type of protocol used to send data to a server over the internet.

[0792] An "SQL query" refers to a set of commands used to manipulate or retrieve data from a database.

[0793] This invention is a system designed to assist senior users in understanding technical terms when using smartphones and computers. Furthermore, it aims to recognize the user's emotions and provide appropriate explanations. This system can reduce user stress and improve engagement.

[0794] System Configuration

[0795] This system consists of the following main components:

[0796] User terminal: A device such as a smartphone, tablet, or personal computer that provides an interface for users to input technical terms.

[0797] Server: Receives technical terms and sentiment data sent from the user terminal, searches the database to generate an easy-to-understand explanation, and sends it back to the user terminal.

[0798] Database: A storage system that stores technical terms and their definitions.

[0799] Natural Language Processing Engine: A software module used to replace complex technical terms with simpler language.

[0800] Emotion engine: A software module that recognizes the emotions of the user during input and sends that information to the server.

[0801] Explanation of the program's processing

[0802] 1. Enter and submit technical terms.

[0803] The user launches an app on their smartphone or tablet and enters a technical term they find difficult to understand into the input field. For example, they might enter "Wi-Fi". When the user taps the "Send" button, the device receives the user's input and prepares to proceed to the next step.

[0804] 2. User emotion recognition

[0805] The device activates its emotion engine simultaneously with the input of technical terms. The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice in real time. For example, the camera captures the user's facial expression, and the emotion analysis algorithm detects "anxiety." This information is then used in the following processes.

[0806] 3. Sending data

[0807] The device compiles the acquired technical terms and sentiment data and sends an HTTPS POST request to the server. The request body includes data such as "Technical Terms: Wi-Fi" and "Sentiment: Anxiety." Once the server receives this request, it proceeds to the next step.

[0808] 4. Analysis of technical terms and sentiment data on servers

[0809] The server parses the received HTTP request and extracts technical terms and sentiment data from the request body. For example, the data might be extracted in the form of "technical term = Wi-Fi" and "sentiment = anxiety." Based on this data, the server prepares to query the database and look up the definitions of the technical terms.

[0810] 5. Generating the explanatory text

[0811] The server executes SQL queries against the database to search for definitions corresponding to technical terms. For example, for the technical term "Wi-Fi," it retrieves the definition from the database as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet." Based on this retrieved definition, it generates an explanatory text.

[0812] 6. Use of Natural Language Processing Engines

[0813] The server passes the acquired definitions to a natural language processing engine. The natural language processing engine identifies complex terms such as "wireless LAN" and "technical standards" and converts them into easily understandable language. It also adjusts the tone of the explanation to be reassuring based on the emotion data "anxiety." For example, it might generate an explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[0814] 7. Sending and displaying the description

[0815] The server generates an explanatory text and sends it to the user's terminal as an HTTP response. For example, the response body might include a message like, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use." The terminal receives this HTTP response and extracts the generated explanatory text from the response body. The terminal then displays the user-friendly and emotionally reassuring explanatory text on the app screen. By viewing this explanation, the user gains a deeper understanding of technical terms and a sense of emotional reassurance.

[0816] Specific example

[0817] Example 1: "Wi-Fi"

[0818] 1. The user opens a smartphone app and types "What is Wi-Fi?". They feel a little unsure.

[0819] 2. The device acquires the keyword "Wi-Fi," analyzes the emotion data "anxiety" using the emotion engine, and sends it to the server.

[0820] 3. The server receives the HTTP request, analyzes the "Wi-Fi" and "anxiety" data, and queries the database.

[0821] 4. The server obtains the definition that "Wi-Fi is a wireless LAN technology standard that allows wireless internet connection" and uses a natural language processing engine to generate the following explanation: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[0822] 5. The server sends an explanatory message to the terminal.

[0823] 6. The device receives the explanation and displays the following message on the app screen: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[0824] Example 2: "Browser"

[0825] 1. The user opens a smartphone app, types "What's a browser?", and becomes slightly frustrated.

[0826] 2. The device acquires the keyword "browser," analyzes the emotion data "frustration" using the emotion engine, and sends it to the server.

[0827] 3. The server receives the HTTP request, analyzes the "browser" and "frustration" data, and queries the database.

[0828] 4. The server obtains the definition that "a browser is software for displaying HTML documents, such as Chrome or Firefox," and uses a natural language processing engine to generate the explanation, "A browser is an application for viewing internet pages. We will support you so that you can resolve the issue quickly."

[0829] 5. The server sends an explanatory message to the terminal.

[0830] 6. The device receives the explanation and displays the following message on the app screen: "The browser is an app for viewing internet pages. We will help you resolve the issue quickly."

[0831] Examples of prompts for generative AI models

[0832] Q: If you type "What is Wi-Fi?"

[0833] A: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, it's easy to use."

[0834] Q: What is a browser?

[0835] A: "A browser is an application for viewing internet pages. I'll help you resolve this quickly."

[0836] Thus, the present invention can help senior users understand technical terms more easily, and by taking into consideration the user's feelings, it can reduce stress and promote the use of smartphones and computers.

[0837] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0838] Step 1:

[0839] The user launches the app on their smartphone or tablet, enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field, and taps the "Send" button.

[0840] Input: Technical terms (e.g., "Wi-Fi")

[0841] Output: Technical terms (e.g., "Wi-Fi")

[0842] Specific action: The terminal receives user input and prepares to proceed to the next process.

[0843] Step 2:

[0844] The device activates its emotion engine simultaneously with the input of technical terms. The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice in real time.

[0845] Input: User's facial expressions and voice

[0846] Output: Emotional data (e.g., "anxiety")

[0847] Specific operation: The camera captures the user's facial expressions, and an emotion analysis algorithm reads the user's "anxiety."

[0848] Step 3:

[0849] The device compiles the acquired technical terms and sentiment data and sends an HTTPS POST request to the server.

[0850] Input: Technical terms (e.g., "Wi-Fi"), emotional data (e.g., "anxiety")

[0851] Output: HTTP request sent to the server

[0852] Specific action: Include technical terms and sentiment data in the request body.

[0853] Step 4:

[0854] The server analyzes the received HTTP request and extracts technical terms and sentiment data from the request body.

[0855] Input: HTTP Request

[0856] Output: Technical terms (e.g., "Wi-Fi"), emotional data (e.g., "anxiety")

[0857] Specific operation: The server parses the request body and extracts technical terms and sentiment data.

[0858] Step 5:

[0859] The server executes an SQL query against the database to retrieve definitions corresponding to technical terms.

[0860] Input: Technical terms (e.g., "Wi-Fi")

[0861] Output: Definitions of technical terms (e.g., "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless internet connection")

[0862] Specific operation: The server executes an SQL query and retrieves the corresponding definition from the database.

[0863] Step 6:

[0864] The server passes the acquired definitions to a natural language processing engine, which converts complex parts into simpler language. It also adjusts the tone of the explanatory text based on sentiment data.

[0865] Input: Definitions of technical terms (e.g., "Wi-Fi is a wireless LAN technology that allows wireless internet connection"), emotional data (e.g., "anxiety")

[0866] Output: Easy-to-understand explanation (Example: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use.")

[0867] Specific operation: The natural language processing engine converts complex parts into simpler words and adjusts the tone based on sentiment data.

[0868] Step 7:

[0869] The server generates an explanatory text which is then sent to the user's terminal as an HTTP response.

[0870] Input: A clear and easy-to-understand explanation (Example: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, it's easy to use.")

[0871] Output: HTTP response sent to the user's terminal

[0872] Specific action: Include a descriptive text in the HTTP response body.

[0873] Step 8:

[0874] The device receives an HTTP response and extracts a description generated from the response body. Finally, the device displays a user-friendly and emotionally resonant description on the app's screen.

[0875] Input: HTTP response

[0876] Output: Explanatory text displayed on the screen (Example: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use.")

[0877] Specific operation: The device extracts the explanatory text from the response body and displays it on the app's screen.

[0878] (Application Example 2)

[0879] 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."

[0880] Senior users face challenges when using electronic payment services, such as difficulty understanding technical terms and procedures, leading to anxiety and frustration. This is particularly true in the field of electronic payments, where technical jargon is prevalent, creating barriers to use and significantly detracting from the user experience. Furthermore, errors and security risks arising from a lack of understanding of technical terms must also be considered. Therefore, there is a need for electronic payment services that are easy for seniors to understand and use with confidence.

[0881] 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.

[0882] In this invention, the server includes means for receiving technical terms entered by the user, means for recognizing and analyzing emotions, means for transmitting the received technical terms and emotion data to the server, means for the server to search for technical terms in a database and generate an easy-to-understand explanation, means for adjusting the generated explanation with consideration for the user's emotions, means for transmitting the generated explanation to the user terminal, and means for the user terminal to display the generated explanation. As a result, users can easily understand and use electronic payment services with peace of mind without feeling anxious or frustrated with technical terms or procedures.

[0883] "User-input technical terms" refer to technical terms that users find difficult to understand and enter into the device's interface.

[0884] "Means for recognizing and analyzing emotions" refers to software modules used to analyze a user's emotional state, employing techniques such as facial recognition and voice tone analysis.

[0885] "Means for sending received technical terms and emotion data to the server" refers to communication means for sending technical terms and emotion recognition data acquired from the user terminal to the server.

[0886] "A means by which a server searches a database for technical terms and generates easy-to-understand explanations" refers to a process in which a server retrieves definitions corresponding to technical terms from a database and converts them into easy-to-understand explanations.

[0887] "Means for adjusting generated descriptions with consideration for user emotions" refers to a natural language processing engine that adjusts the tone and expression of generated descriptions according to the user's emotional state.

[0888] "Means for sending the generated explanatory text to the user terminal" refers to communication means for sending the explanatory text generated and adjusted by the server to the user terminal.

[0889] "Means for displaying the generated explanatory text on the user terminal" refers to screen display means for displaying the explanatory text received by the user terminal so that the user can view it.

[0890] This invention is a system designed to help senior users understand technical terms and procedures when using electronic payment services, thereby reducing stress. The system uses a combination of a natural language processing engine that converts technical terms into easy-to-understand explanations and an emotion engine that recognizes the user's emotions.

[0891] The system consists of the following elements:

[0892] 1. User terminal: A device such as a smartphone or tablet that provides an interface for users to input technical terms they find difficult to understand and for acquiring sentiment data.

[0893] 2. Emotion Recognition: This function operates on the user's device and recognizes the user's emotions using facial recognition APIs (e.g., AWS Rekognition) and voice tone analysis.

[0894] 3. Data transmission: Includes means of communication for sending user-entered technical terms and sentiment data to the server.

[0895] 4. Server: Utilizes a database and a natural language processing engine (e.g., SpaCy, BERT) to search for definitions of technical terms and generate easy-to-understand explanations.

[0896] 5. Description Adjustment: The description generated by the server is adjusted to take user emotions into consideration, and the tone and content are fine-tuned.

[0897] 6. Sending to the user terminal: The generated explanation is sent to the user terminal and displayed to the user.

[0898] Process Description

[0899] Hardware and software

[0900] Hardware: User devices (smartphones, tablets)

[0901] software:

[0902] Emotion recognition software (e.g., AWS Rekognition)

[0903] Natural language processing engines (e.g., SpaCy, BERT)

[0904] Server-side applications (e.g., Node.js, Express)

[0905] Database (e.g., MySQL)

[0906] Data processing and data calculation

[0907] When a user inputs a technical term, the system simultaneously acquires the term and the user's emotional data. This emotional data is obtained through facial recognition and voice tone analysis.

[0908] Next, the device sends this data to the server. The server searches its database based on the received technical terms and generates an easy-to-understand explanation. The generated explanation then goes through a natural language processing engine to adjust its tone and content according to the user's sentiment. The adjusted explanation is then sent to the user's device and finally displayed to the user on the device.

[0909] Specific examples

[0910] For example, if a user types "What is a security code?" and is feeling anxious, the device sends the keyword "security code" and the emotion data "anxiety" to the server. The server searches its database for "security code" and retrieves its definition. Then, using a natural language processing engine, it generates an explanation such as "A security code is a 3- or 4-digit number printed on the back of your card that ensures secure online transactions. There's no need to be anxious. Please check it out," and displays it to the user.

[0911] Example of a prompt

[0912] A prompt message to use when a user is feeling unsure and asks, "What is a security code?":

[0913] "The security code is a three- or four-digit number printed on the back of your card, and it guarantees secure online transactions. There's no need to worry. Please take a look."

[0914] This system will make it easy for senior users to understand technical terms and procedures, allowing them to use electronic payment services with peace of mind.

[0915] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0916] Step 1:

[0917] Users enter technical terms they don't understand into the input field of their smartphone or tablet. The keywords entered by the user might be something like "security code."

[0918] Input: Technical terms (e.g., "security code")

[0919] Output: Input technical term data

[0920] Specific operation: The user launches the application, enters a technical term into the input field, and presses the "Submit" button.

[0921] Step 2:

[0922] The device uses a camera and microphone to recognize the user's emotions. The emotion recognition engine uses facial recognition APIs and voice tone analysis.

[0923] Input: User's face image, voice data

[0924] Output: Emotional data (e.g., "anxiety")

[0925] Specific operation: The emotion recognition engine analyzes the user's facial expressions and voice tone to identify their emotional state (e.g., "anxiety").

[0926] Step 3:

[0927] The terminal receives technical terms and sentiment data and sends it to the server as an HTTPS POST request.

[0928] Input: Technical terminology data, sentiment data

[0929] Output: Data sent to the server

[0930] Specific operation: The device packages technical terminology data and sentiment data in JSON format, creates an HTTPS POST request, and sends it to the server.

[0931] Step 4:

[0932] The server receives an HTTP request and analyzes the technical terms and sentiment data.

[0933] Input: Technical terminology data, sentiment data

[0934] Output: Analysis result data

[0935] Specific operation: The server extracts technical terminology data and sentiment data from the request body and analyzes each type of data.

[0936] Step 5:

[0937] The server retrieves definitions of technical terms by executing SQL queries against the database.

[0938] Input: Technical terminology data

[0939] Output: Definition data (Example: "The security code is a 3- or 4-digit number printed on the back of the card that ensures secure online transactions.")

[0940] Specific operation: The server executes an SQL query against the database to retrieve definitions of technical terms.

[0941] Step 6:

[0942] The server retrieves definitions from the database and passes them to a natural language processing engine to generate easy-to-understand explanatory text. It also adjusts the tone and content, taking sentiment data into consideration.

[0943] Input: Definition data, sentiment data

[0944] Output: Adjusted explanation (Example: "The security code is a 3- or 4-digit number printed on the back of your card, ensuring secure online transactions. There's no need to worry. Please check it out.")

[0945] Specific operation: The natural language processing engine converts complex parts of the definition data into simpler words and adjusts the explanatory text based on sentiment data.

[0946] Step 7:

[0947] The server generates an explanatory text which is then sent to the user's terminal as an HTTP response.

[0948] Input: Adjusted description

[0949] Output: Descriptive data sent to the user terminal

[0950] Specific operation: The server generates an HTTP response containing an explanation and sends it to the user's terminal.

[0951] Step 8:

[0952] The application displays the explanatory text received by the user's terminal on its screen.

[0953] Input: Received explanatory data

[0954] Output: Description displayed on the screen

[0955] Specific operation: The device displays an explanatory text on the screen, which the user can view. At this time, the explanatory text will be considerate of the user's feelings, such as, "The security code is a 3-digit or 4-digit number printed on the back of the card, and it guarantees secure online transactions. There is no need to worry. Please take a look."

[0956] 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.

[0957] 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.

[0958] 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.

[0959] [Third Embodiment]

[0960] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0961] 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.

[0962] 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).

[0963] 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.

[0964] 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.

[0965] 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).

[0966] 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.

[0967] 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.

[0968] 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.

[0969] 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.

[0970] 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.

[0971] 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".

[0972] This invention is a system designed to help senior users understand technical terms when using smartphones and computers. To achieve this objective, the system includes multiple means for explaining technical terms entered by the user in an easy-to-understand manner.

[0973] System Configuration

[0974] This system consists of the following main components:

[0975] User terminal: A computer device such as a smartphone or tablet that provides an interface for users to input technical terms.

[0976] Server: Receives technical terms sent from the user terminal, searches the database to generate an easy-to-understand explanation, and sends it back to the user terminal.

[0977] Database: A storage system that stores technical terms and their definitions.

[0978] Natural Language Processing Engine: A software module used to replace complex technical terms with simpler language.

[0979] Program processing

[0980] 1. Enter and submit technical terms.

[0981] The user launches an app on their smartphone or tablet and enters technical terms they find difficult to understand into an input field. For example, they might enter "Wi-Fi". Once this input is complete, the device sends the technical terms to the server. Specifically, the device sends the entered data as a POST request to a particular API endpoint.

[0982] 2. Analysis of technical terms on the server

[0983] The server receives requests sent from user terminals and matches the technical terms against the database. For example, the server searches the database for the keyword "Wi-Fi". If this search finds a matching entry, the server retrieves the information for that entry. The entry includes a definition such as "Wi-Fi is a wireless LAN technical standard, a technology that enables wireless internet connectivity."

[0984] 3. Generating explanatory text

[0985] The definition obtained from the database is then passed to the natural language processing engine on the server. This engine generates an easy-to-understand explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0986] 4. Sending and displaying the description

[0987] The server generates an explanatory text and sends it back to the user's device. Specifically, the server sends data containing the explanatory text as an HTTP response. Finally, the device receives this response data and displays an easy-to-understand explanatory text on the app's screen. For example, it might say, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables," which the user then reads.

[0988] Specific example

[0989] Example 1: "Wi-Fi"

[0990] 1. The user types "What is Wi-Fi?".

[0991] 2. The device sends the keyword "Wi-Fi" to the server.

[0992] 3. The server searches the database for "Wi-Fi" and retrieves the definition: "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[0993] 4. The server uses a natural language processing engine to generate an easy-to-understand explanation: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[0994] 5. The server sends an explanatory message to the terminal.

[0995] 6. The device displays an explanatory text to the user.

[0996] Example 2: "Browser"

[0997] 1. The user types "What is a browser?".

[0998] 2. The device sends the keyword "browser" to the server.

[0999] 3. The server searches the database for "browser" and retrieves the definition: "A browser is software used to display HTML documents, such as Chrome or Firefox."

[1000] 4. The server uses a natural language processing engine to generate an easy-to-understand explanation: "A browser is an application for viewing various pages on the internet."

[1001] 5. The server sends an explanatory message to the terminal.

[1002] 6. The device displays an explanatory text to the user.

[1003] In this way, the present invention can help senior users understand technical terms more easily and promote the use of smartphones and computers.

[1004] The following describes the processing flow.

[1005] Step 1:

[1006] The user launches a smartphone app and enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field. When the user taps the "Send" button, the app retrieves this technical term.

[1007] Step 2:

[1008] The terminal retrieves the entered technical term and sends an HTTP POST request to the server. The request contains the technical term.

[1009] Step 3:

[1010] The server receives an HTTP request and parses the technical terms data. Specifically, the server extracts technical terms (e.g., "Wi-Fi") from the request body.

[1011] Step 4:

[1012] The server executes an SQL query against the database to retrieve the definition of a technical term. For example, the server might retrieve the definition of the technical term "Wi-Fi" as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[1013] Step 5:

[1014] The server passes the acquired definitions to the natural language processing engine. The natural language processing engine identifies complex terms such as "wireless LAN" and "technical standards" and converts them into easily understandable language.

[1015] Step 6:

[1016] The server uses the output of a natural language processing engine to generate explanatory text that is easy for the user to understand. For example, it might generate an explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[1017] Step 7:

[1018] The server generates an explanatory text which is then sent to the user's terminal as an HTTP response.

[1019] Step 8:

[1020] The terminal receives an HTTP response and extracts the generated explanatory text from the response body.

[1021] Step 9:

[1022] The device displays easy-to-understand explanatory text on the app screen. Users will be able to view explanations such as, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables."

[1023] This series of steps will make it easier for senior users to understand technical terms and to use smartphones and computers more effectively.

[1024] (Example 1)

[1025] 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."

[1026] With the advancement of modern information technology, many users, including seniors, often find it difficult to understand technical jargon when using smartphones and computers. This problem is particularly pronounced when using the internet or new software, potentially widening the digital divide. Therefore, there is a need for systems that make this technical jargon easy to understand.

[1027] 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.

[1028] In this invention, the server includes means for receiving technical terms entered by the user, means for transmitting the received technical terms to a central processing unit, means for the central processing unit to retrieve the technical terms from a storage device and generate an easy-to-understand explanation, means for transmitting the generated explanation to a user device, and means for the user device to display the generated explanation. This makes it possible for a diverse range of users, including senior citizens, to easily understand technical terms.

[1029] "User" refers to a general user of the system.

[1030] "Technical jargon" refers to terms related to a specific field or technology that are difficult for the average user to understand.

[1031] "Means of receiving" refers to devices or modules that have the function of taking in data and information entered by the user into the system.

[1032] "Means of transmission" refers to devices or modules that have the function of sending received data or information to another device or module.

[1033] A "central processing unit" refers to the main device or module that handles information processing for the entire system and processes data based on instructions.

[1034] A "storage device" refers to a storage system used to store data and information.

[1035] A "natural language processing module" refers to a software module that converts natural language into an easily understandable format through the analysis and generation of input text.

[1036] "User device" refers to a device used by a user to access the system, and includes smartphones, tablets, and computers.

[1037] "Public information sources" refer to information sources that are generally accessible, such as websites and public databases on the internet.

[1038] Modes for carrying out the invention

[1039] This invention is a system designed to support users, including senior citizens, who may have difficulty understanding technical terms. This system consists of the following main components:

[1040] Components

[1041] 1. User device: A device such as a smartphone, tablet, or computer that provides an interface for the user to input technical terms.

[1042] 2. Central Processing Unit: This is the main computer system responsible for searching, analyzing, and generating explanatory texts for technical terms.

[1043] 3. Storage device: A database that stores technical terms and their explanations.

[1044] 4. Natural Language Processing Module: This is a software module for replacing technical jargon with easily understandable language.

[1045] 5. Public Information Sources: This is a system for collecting information on specialized terminology not found in databases from the internet.

[1046] Explanation of the program's processing

[1047] To generate the program for this system, follow these steps:

[1048] Entering and sending technical terms

[1049] First, the user launches an app on their smartphone or tablet and enters technical terms they find difficult to understand into the input field. For example, the user might enter "Wi-Fi". Once this input is complete, the device sends the technical terms to the server (central processing unit). Specifically, the device sends the entered data as a POST request to a particular API endpoint.

[1050] Analysis of technical terms on servers

[1051] The server receives requests sent from user terminals and matches the technical terms against its storage. For example, the server searches the database for the keyword "Wi-Fi". If this search finds a matching entry, the server retrieves the information for that entry. The entry includes a definition such as "Wi-Fi is a wireless LAN technical standard, a technology that enables wireless internet connectivity."

[1052] Generating an explanatory text

[1053] Next, the acquired definition is passed to a natural language processing module. The server uses this module to generate an easy-to-understand explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[1054] Sending and displaying the description

[1055] Finally, the generated explanation is sent to the user's device, and the terminal displays the explanation on the app's screen. For example, it might say, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables," which the user can then view.

[1056] Specific example

[1057] Example 1: "Wi-Fi"

[1058] 1. The user types "What is Wi-Fi?".

[1059] 2. The device sends the keyword "Wi-Fi" to the central processing unit.

[1060] 3. The central processing unit searches for "Wi-Fi" in the memory and obtains the definition that "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[1061] 4. The central processing unit uses a natural language processing module to generate an easy-to-understand explanation: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[1062] 5. The central processing unit transmits the explanatory text to the user device.

[1063] 6. The user device displays an explanatory text to the user.

[1064] Example 2: "Browser"

[1065] 1. The user types "What is a browser?".

[1066] 2. The terminal sends the keyword "browser" to the central processing unit.

[1067] 3. The central processing unit searches for "browser" in its memory and retrieves the definition that "a browser is software for displaying HTML documents, such as Chrome or Firefox."

[1068] 4. The central processing unit uses a natural language processing module to generate an easy-to-understand explanation: "A browser is an application for viewing various pages on the internet."

[1069] 5. The central processing unit transmits the explanatory text to the user device.

[1070] 6. The user device displays an explanatory text to the user.

[1071] Example of a prompt

[1072] Examples of prompt statements to input into a generative AI model are as follows:

[1073] If a user types "What is Wi-Fi?", the system will perform the following steps:

[1074] 1. The device sends the keyword "Wi-Fi" to the central processing unit.

[1075] 2. The central processing unit searches for "Wi-Fi" in the memory and retrieves the corresponding definition.

[1076] 3. The definition obtained by the central processing unit is converted into simple words using a natural language processing module.

[1077] 4. The central processing unit sends the easy-to-understand explanatory text it has generated back to the terminal.

[1078] 5. The device displays the explanatory text on the user's screen.

[1079] As a concrete example, we will display an explanation such as, "Wi-Fi is a method that allows smartphones and computers to connect to the internet without using cables." This makes it easier for users to understand technical terms.

[1080]

[1081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1082] Detailed explanation of the program's processing

[1083] Step 1: User input reception and submission

[1084] Input: Technical term Example: "Wi-Fi"

[1085] Operation:

[1086] The user launches the app on their smartphone or tablet and enters technical terms that are difficult to understand into the input field.

[1087] Once input is complete, the terminal sends the technical terms to the central processing unit (server).

[1088] Specifically, the device sends the entered data as a POST request to a specific API endpoint.

[1089] Output: Technical terminology data sent to the server

[1090] Step 2: The server receives the request.

[1091] Input: POST request sent from the terminal

[1092] Operation:

[1093] The server receives a POST request sent from the user's terminal.

[1094] The request includes technical terms entered by the user.

[1095] Output: Terminology data received.

[1096] Step 3: Database matching of technical terms

[1097] Input: Technical terminology data

[1098] Operation:

[1099] The server compares the received technical terms with its storage device (database).

[1100] For example, the server searches for the keyword "Wi-Fi" in the database.

[1101] If this search finds a matching entry, the server retrieves the information for that entry.

[1102] Output: Definitions of technical terms retrieved from the database. Example: "Wi-Fi is a wireless LAN technical standard, a technology that enables wireless internet connectivity."

[1103] Step 4: Analysis and conversion using a natural language processing engine

[1104] Input: Definitions of technical terms obtained from a database

[1105] Operation:

[1106] The server passes the retrieved definition to the natural language processing module.

[1107] The natural language processing module replaces complex parts with easily understandable language.

[1108] For example, it can generate an explanatory text such as, "Wi-Fi is a method that allows smartphones and computers to connect to the internet without using cables."

[1109] Output: Easy-to-understand explanation. Example: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[1110] Step 5: Send and display the description.

[1111] Input: Description generated by the natural language processing module

[1112] Operation:

[1113] The server then sends the generated explanation back to the user's terminal.

[1114] Send data including a description as an HTTP response.

[1115] The device processes the HTTP response received from the server and displays an easy-to-understand explanation on the app's screen.

[1116] The user reads the displayed description.

[1117] Output: Explanation displayed on the app screen. Example: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[1118] A concrete example of the entire sequence of steps

[1119] 1. In Step 1, the user types "What is Wi-Fi?".

[1120] 2. In step 2, "the device sends that data to the server."

[1121] 3. In step 3, "the server searches for 'Wi-Fi' in the database and returns the definition."

[1122] 4. In step 4, "the server passes the definition to the natural language processing module, which generates an easy-to-understand explanation."

[1123] 5. In step 5, "the server sends the generated explanation to the terminal, and the terminal displays the explanation to the user."

[1124] By following the steps outlined above, this system assists in understanding technical terms and makes it easier for users, including senior citizens, to grasp technical jargon.

[1125] (Application Example 1)

[1126] 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."

[1127] In recent years, senior citizens have increasingly used smartphones and computers, but the problem of difficulty in understanding technical jargon has become more pronounced. Security terminology, in particular, is complex, and many users struggle to understand it properly. Therefore, there is a need for support systems that enable senior citizens to easily understand technical terms and enhance their security awareness.

[1128] 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.

[1129] In this invention, the server includes means for receiving technical terms entered by the user, means for sending the received technical terms to the server, means for the server to search for the technical terms in a database and generate an easy-to-understand explanation, means for sending the generated explanation to the user terminal, means for the user terminal to display the generated explanation, means for the user to enter technical terms that are difficult to understand into an input field in the application, means for sending the entered technical terms as a POST request using an API, means for the server to compare the received technical terms with a database and convert the obtained definition into simple words using a natural language processing model, and means for sending the generated explanation as an HTTP response. This makes it possible for senior users to easily understand security terms and immediately check their explanations.

[1130] A "user terminal" is a device used by users to input technical terms and receive and display explanatory text.

[1131] "Technical jargon" refers to complex terms used in technical or specialized fields.

[1132] A "server" is a device that receives technical terms sent from a user terminal, searches a database to generate an explanation, and then sends it back to the user terminal.

[1133] A "database" is a storage system that stores technical terms and their explanations.

[1134] A "natural language processing engine" is a software module that analyzes the complex parts of technical terms and replaces them with simpler language.

[1135] "API" stands for Application Programming Interface, which is an interface for using software functions from an external source.

[1136] A "POST request" is a request method used in the HTTP protocol to send data to a server.

[1137] An "HTTP response" is the response data sent from a server to a client in the HTTP protocol.

[1138] "Hugging Face" is a popular tool that provides libraries and APIs for natural language processing.

[1139] "Simple language" refers to more general and easily understandable terms used to generate explanatory texts that are easier to understand than technical jargon.

[1140] An "input field" is an area within an application where the user enters technical terms.

[1141] "Security terminology" refers to specialized terms related to information security and network security.

[1142] This invention is a system designed to help senior users easily understand technical terms. The system consists of a user terminal, a server, a database, a natural language processing engine, and an API.

[1143] Program processing

[1144] 1. User input and data transmission

[1145] The user enters technical terms that are difficult to understand into an input field within the application. This input field is displayed on the user's device, such as a smartphone or tablet. Once the user has finished entering the terms, the device sends the entered technical terms to the server as a POST request using an API.

[1146] 2. Analysis of technical terms and acquisition of definitions

[1147] The server receives the incoming request and matches it against the database. The database stores a wide range of technical terms and their definitions; for example, if the word "firewall" is received, it retrieves a definition such as "a network security system."

[1148] 3. Generating explanatory text

[1149] The definitions of technical terms obtained are passed to a natural language processing engine on the server (e.g., Hugging Face). This engine analyzes the complex parts of the technical terms, replaces them with simpler words, and generates easy-to-understand explanations. For example, it might generate an explanation such as, "A firewall is a mechanism to protect computers and smartphones from malicious actors."

[1150] 4. Sending and displaying the description

[1151] The server sends the generated explanation as an HTTP response to the user's terminal. The user's terminal receives this response and displays the explanation within the application. This allows the user to instantly see a simple explanation of technical terms.

[1152] Specific example

[1153] Specifically, when a user types "What is a firewall?" into the app's input field, the following prompt is sent to the server:

[1154] "What is a firewall? Please explain it in simple terms."

[1155] Hardware and software to use

[1156] User devices: Smartphones, tablets

[1157] Server: A computer device that receives, analyzes, and transmits data (e.g., a cloud server).

[1158] Database: A storage system that stores technical terms and their definitions (e.g., Amazon RDS).

[1159] Natural language processing engine: Software for analyzing and simplifying technical terms (e.g., Hugging Face API)

[1160] API: An interface for sending and receiving technical terms.

[1161] This will allow senior users to more easily understand technical terms and access information that will be useful in their daily lives and to improve their security awareness.

[1162] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1163] Step 1:

[1164] The user enters technical terms into an input field within the application.

[1165] The entered data consists of technical terms such as "firewall," and this will be used as input data in Step 2.

[1166] Step 2:

[1167] The terminal sends the entered technical terms to the server using the API. The data is sent as a POST request.

[1168] Specifically, the device converts the input data into JSON format and sends it as a POST request to the API endpoint. This request is received by the server.

[1169] Step 3:

[1170] The server analyzes the received request and matches it against technical terms in the database.

[1171] The system searches a database using input data (technical terms) as keys and retrieves the corresponding definitions. For example, for the term "firewall," it retrieves the definition "network security system."

[1172] Step 4:

[1173] The server retrieves definitions of technical terms, passes them to a natural language processing engine, and converts them into simpler words.

[1174] Using a natural language processing engine (e.g., Hugging Face), the system analyzes complex technical terms and generates easy-to-understand explanations. For example, it might generate an explanation such as, "A firewall is a mechanism to protect computers and smartphones from malicious actors."

[1175] Step 5:

[1176] The server sends the generated description to the user's terminal as an HTTP response.

[1177] The generated description is converted to JSON format and sent to the terminal as an HTTP response. A success code, such as status code 200, is also sent at this time.

[1178] Step 6:

[1179] The application displays the explanatory text received by the device.

[1180] The device analyzes the received data and displays it on the application screen. This allows the user to see easy-to-understand explanations of technical terms.

[1181] Through these steps, users can input technical terms and obtain concise explanations, thereby gaining a deeper understanding.

[1182] 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.

[1183] This invention is a system designed to help senior users understand technical terms when using smartphones and computers, and further aims to recognize the user's emotions and provide appropriate explanations. This will reduce user stress and improve engagement.

[1184] System Configuration

[1185] This system consists of the following main components:

[1186] User terminal: A computer device such as a smartphone or tablet that provides an interface for users to input technical terms.

[1187] Server: Receives technical terms sent from the user terminal, searches the database to generate an easy-to-understand explanation, and sends it back to the user terminal.

[1188] Database: A storage system that stores technical terms and their definitions.

[1189] Natural Language Processing Engine: A software module used to replace complex technical terms with simpler language.

[1190] Emotion engine: A software module that recognizes the emotions of the user during input and sends that information to the server.

[1191] Program processing

[1192] 1. Enter and submit technical terms.

[1193] The user launches the app on their smartphone or tablet and enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field. When the user taps the "Send" button, the app retrieves this technical term.

[1194] 2. User emotion recognition

[1195] As the device inputs technical terms, it simultaneously analyzes the user's emotions using an emotion engine. The emotion engine performs facial recognition and voice tone analysis to identify the emotions the user is feeling at the time of input (e.g., doubt, anxiety, frustration, etc.).

[1196] 3. Sending data

[1197] The device sends the acquired technical terms and sentiment data to the server as an HTTPS POST request. The request includes technical terms and user sentiment information.

[1198] 4. Analysis of technical terms and sentiment data on servers

[1199] The server receives an HTTP request and analyzes technical terms and sentiment data. Specifically, the server extracts technical terms and sentiment data (e.g., "Wi-Fi", "anxiety") from the request body.

[1200] 5. Generating the explanatory text

[1201] The server retrieves definitions for technical terms by executing SQL queries against the database. For example, the server might retrieve the definition for the technical term "Wi-Fi" as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless internet connection."

[1202] 6. Use of Natural Language Processing Engines

[1203] The acquired definitions are passed to a natural language processing engine, which identifies complex terms such as "wireless LAN" and "technical standards" and converts them into easily understandable language. Furthermore, sentiment data is taken into consideration, and the tone and content of the explanatory text are appropriately adjusted.

[1204] 7. Sending and displaying the description

[1205] The server sends the generated explanatory text to the user's terminal as an HTTP response. For example, it might be adjusted to say, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[1206] The device receives an HTTP response and extracts a descriptive text generated from the response body. Finally, the device displays a user-friendly and easy-to-understand descriptive text on the app screen, making it accessible to the user.

[1207] Specific example

[1208] Example 1: "Wi-Fi"

[1209] 1. The user typed "What is Wi-Fi?" and seems a little unsure.

[1210] 2. The device sends the keyword "Wi-Fi" and the emotion data "anxiety" to the server.

[1211] 3. The server searches the database for "Wi-Fi" and retrieves the definition: "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[1212] 4. The server uses a natural language processing engine to generate an easy-to-understand explanation: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[1213] 5. The server sends an explanatory message to the terminal.

[1214] 6. The device displays an explanatory text to the user.

[1215] Example 2: "Browser"

[1216] 1. The user types "What is a browser?" and seems a little frustrated.

[1217] 2. The device sends the keyword "browser" and emotion data "frustration" to the server.

[1218] 3. The server searches the database for "browser" and retrieves the definition: "A browser is software used to display HTML documents, such as Chrome or Firefox."

[1219] 4. The server uses a natural language processing engine to generate an easy-to-understand explanation: "A browser is an application for viewing internet pages. We will support you so that you can resolve your issue quickly."

[1220] 5. The server sends an explanatory message to the terminal.

[1221] 6. The device displays an explanatory text to the user.

[1222] In this way, the present invention can help senior users understand technical terms more easily, and by taking into consideration the user's feelings, it can reduce stress and promote the use of smartphones and computers.

[1223] The following describes the processing flow.

[1224] Step 1:

[1225] The user launches a smartphone app and enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field. When the user taps the "Send" button, the device retrieves this technical term.

[1226] Step 2:

[1227] As the device receives input of technical terms, it simultaneously analyzes the user's emotions using an emotion engine. The emotion engine analyzes the user's facial expressions and voice to identify the user's emotions (e.g., anxiety, doubt, frustration, etc.).

[1228] Step 3:

[1229] The device structures the acquired technical terms and sentiment data and sends it to the server as an HTTP POST request. The request includes "Wi-Fi" and the user's sentiment.

[1230] Step 4:

[1231] The server receives the HTTP request and parses its contents. Specifically, the server extracts the technical term "Wi-Fi" and emotional data (e.g., "anxiety") from the request body.

[1232] Step 5:

[1233] The server executes an SQL query against the database to retrieve the definition of a technical term. For example, the server might retrieve the definition of the technical term "Wi-Fi" as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[1234] Step 6:

[1235] The server passes the acquired definitions to a natural language processing engine, which converts complex parts into easily understandable language. The natural language processing engine replaces complex terms such as "wireless LAN" and "technical standards" with simpler words.

[1236] Step 7:

[1237] The server adjusts the content and tone of the explanatory text based on the analyzed sentiment data. For example, if the sentiment data indicates "anxiety," the explanatory text will be adjusted to include phrases such as "Please rest assured."

[1238] Step 8:

[1239] The server generates a final explanation (e.g., "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use.") and sends it to the user's terminal as an HTTP response.

[1240] Step 9:

[1241] The terminal receives an HTTP response and extracts the generated explanatory text from the response body.

[1242] Step 10:

[1243] The device will display easy-to-understand explanations on the app screen that are considerate of the user's feelings, and allow the user to view them. For example, it might display an explanation such as, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[1244] Through these processing steps, senior users will find it easier to understand technical terms, and by taking their feelings into consideration, they will be able to use smartphones and computers with reduced stress.

[1245] (Example 2)

[1246] 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."

[1247] In today's technological society, many users, including the elderly, struggle to understand technical and jargon. Seniors, in particular, often experience emotional stress and frustration due to the difficulty of technical terms, which acts as a barrier to technological adoption. These challenges reduce the convenience and engagement with technology, ultimately preventing them from fully benefiting from evolving technological services.

[1248] 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.

[1249] In this invention, the server includes means for recognizing the user's emotions and generating emotion data, means for adjusting the content and tone of the explanatory text based on the emotion data, and a natural language processing engine that analyzes difficult parts of technical terms and replaces them with simpler words. This not only helps the user understand but also reduces user stress and improves engagement by providing emotionally sensitive explanations.

[1250] A "user" refers to an individual who uses a service or system.

[1251] "Technical jargon" refers to specialized or technical terms used in a particular field or industry.

[1252] A "server" refers to a computer system that receives requests from users and processes and provides data.

[1253] A "database" refers to a system that systematically stores data and allows for the retrieval and searching of that data as needed.

[1254] An "explanatory text" refers to text generated to clearly explain the meaning and usage of technical terms and jargon.

[1255] "User terminal" refers to devices used by a user, such as smartphones, tablets, and personal computers.

[1256] "Emotional data" refers to information that represents a user's emotional state (for example, anxiety, doubt, frustration, etc.).

[1257] A "natural language processing engine" refers to a software module that analyzes text data and converts it into a form that is easy for humans to understand.

[1258] An "HTTPS POST request" is a type of protocol used to send data to a server over the internet.

[1259] An "SQL query" refers to a set of commands used to manipulate or retrieve data from a database.

[1260] This invention is a system designed to assist senior users in understanding technical terms when using smartphones and computers. Furthermore, it aims to recognize the user's emotions and provide appropriate explanations. This system can reduce user stress and improve engagement.

[1261] System Configuration

[1262] This system consists of the following main components:

[1263] User terminal: A device such as a smartphone, tablet, or personal computer that provides an interface for users to input technical terms.

[1264] Server: Receives technical terms and sentiment data sent from the user terminal, searches the database to generate an easy-to-understand explanation, and sends it back to the user terminal.

[1265] Database: A storage system that stores technical terms and their definitions.

[1266] Natural Language Processing Engine: A software module used to replace complex technical terms with simpler language.

[1267] Emotion engine: A software module that recognizes the emotions of the user during input and sends that information to the server.

[1268] Explanation of the program's processing

[1269] 1. Enter and submit technical terms.

[1270] The user launches an app on their smartphone or tablet and enters a technical term they find difficult to understand into the input field. For example, they might enter "Wi-Fi". When the user taps the "Send" button, the device receives the user's input and prepares to proceed to the next step.

[1271] 2. User emotion recognition

[1272] The device activates its emotion engine simultaneously with the input of technical terms. The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice in real time. For example, the camera captures the user's facial expression, and the emotion analysis algorithm detects "anxiety." This information is then used in the following processes.

[1273] 3. Sending data

[1274] The device compiles the acquired technical terms and sentiment data and sends an HTTPS POST request to the server. The request body includes data such as "Technical Terms: Wi-Fi" and "Sentiment: Anxiety." Once the server receives this request, it proceeds to the next step.

[1275] 4. Analysis of technical terms and sentiment data on servers

[1276] The server parses the received HTTP request and extracts technical terms and sentiment data from the request body. For example, the data might be extracted in the form of "technical term = Wi-Fi" and "sentiment = anxiety." Based on this data, the server prepares to query the database and look up the definitions of the technical terms.

[1277] 5. Generating the explanatory text

[1278] The server executes SQL queries against the database to search for definitions corresponding to technical terms. For example, for the technical term "Wi-Fi," it retrieves the definition from the database as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet." Based on this retrieved definition, it generates an explanatory text.

[1279] 6. Use of Natural Language Processing Engines

[1280] The server passes the acquired definitions to a natural language processing engine. The natural language processing engine identifies complex terms such as "wireless LAN" and "technical standards" and converts them into easily understandable language. It also adjusts the tone of the explanation to be reassuring based on the emotion data "anxiety." For example, it might generate an explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[1281] 7. Sending and displaying the description

[1282] The server generates an explanatory text and sends it to the user's terminal as an HTTP response. For example, the response body might include a message like, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use." The terminal receives this HTTP response and extracts the generated explanatory text from the response body. The terminal then displays the user-friendly and emotionally reassuring explanatory text on the app screen. By viewing this explanation, the user gains a deeper understanding of technical terms and a sense of emotional reassurance.

[1283] Specific example

[1284] Example 1: "Wi-Fi"

[1285] 1. The user opens a smartphone app and types "What is Wi-Fi?". They feel a little unsure.

[1286] 2. The device acquires the keyword "Wi-Fi," analyzes the emotion data "anxiety" using the emotion engine, and sends it to the server.

[1287] 3. The server receives the HTTP request, analyzes the "Wi-Fi" and "anxiety" data, and queries the database.

[1288] 4. The server obtains the definition that "Wi-Fi is a wireless LAN technology standard that allows wireless internet connection" and uses a natural language processing engine to generate the following explanation: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[1289] 5. The server sends an explanatory message to the terminal.

[1290] 6. The device receives the explanation and displays the following message on the app screen: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[1291] Example 2: "Browser"

[1292] 1. The user opens a smartphone app, types "What's a browser?", and becomes slightly frustrated.

[1293] 2. The device acquires the keyword "browser," analyzes the emotion data "frustration" using the emotion engine, and sends it to the server.

[1294] 3. The server receives the HTTP request, analyzes the "browser" and "frustration" data, and queries the database.

[1295] 4. The server obtains the definition that "a browser is software for displaying HTML documents, such as Chrome or Firefox," and uses a natural language processing engine to generate the explanation, "A browser is an application for viewing internet pages. We will support you so that you can resolve the issue quickly."

[1296] 5. The server sends an explanatory message to the terminal.

[1297] 6. The device receives the explanation and displays the following message on the app screen: "The browser is an app for viewing internet pages. We will help you resolve the issue quickly."

[1298] Examples of prompts for generative AI models

[1299] Q: If you type "What is Wi-Fi?"

[1300] A: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, it's easy to use."

[1301] Q: What is a browser?

[1302] A: "A browser is an application for viewing internet pages. I'll help you resolve this quickly."

[1303] Thus, the present invention can help senior users understand technical terms more easily, and by taking into consideration the user's feelings, it can reduce stress and promote the use of smartphones and computers.

[1304] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1305] Step 1:

[1306] The user launches the app on their smartphone or tablet, enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field, and taps the "Send" button.

[1307] Input: Technical terms (e.g., "Wi-Fi")

[1308] Output: Technical terms (e.g., "Wi-Fi")

[1309] Specific action: The terminal receives user input and prepares to proceed to the next process.

[1310] Step 2:

[1311] The device activates its emotion engine simultaneously with the input of technical terms. The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice in real time.

[1312] Input: User's facial expressions and voice

[1313] Output: Emotional data (e.g., "anxiety")

[1314] Specific operation: The camera captures the user's facial expressions, and an emotion analysis algorithm reads the user's "anxiety."

[1315] Step 3:

[1316] The device compiles the acquired technical terms and sentiment data and sends an HTTPS POST request to the server.

[1317] Input: Technical terms (e.g., "Wi-Fi"), emotional data (e.g., "anxiety")

[1318] Output: HTTP request sent to the server

[1319] Specific action: Include technical terms and sentiment data in the request body.

[1320] Step 4:

[1321] The server analyzes the received HTTP request and extracts technical terms and sentiment data from the request body.

[1322] Input: HTTP Request

[1323] Output: Technical terms (e.g., "Wi-Fi"), emotional data (e.g., "anxiety")

[1324] Specific operation: The server parses the request body and extracts technical terms and sentiment data.

[1325] Step 5:

[1326] The server executes an SQL query against the database to retrieve definitions corresponding to technical terms.

[1327] Input: Technical terms (e.g., "Wi-Fi")

[1328] Output: Definitions of technical terms (e.g., "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless internet connection")

[1329] Specific operation: The server executes an SQL query and retrieves the corresponding definition from the database.

[1330] Step 6:

[1331] The server passes the acquired definitions to a natural language processing engine, which converts complex parts into simpler language. It also adjusts the tone of the explanatory text based on sentiment data.

[1332] Input: Definitions of technical terms (e.g., "Wi-Fi is a wireless LAN technology that allows wireless internet connection"), emotional data (e.g., "anxiety")

[1333] Output: Easy-to-understand explanation (Example: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use.")

[1334] Specific operation: The natural language processing engine converts complex parts into simpler words and adjusts the tone based on sentiment data.

[1335] Step 7:

[1336] The server generates an explanatory text which is then sent to the user's terminal as an HTTP response.

[1337] Input: A clear and easy-to-understand explanation (Example: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, it's easy to use.")

[1338] Output: HTTP response sent to the user's terminal

[1339] Specific action: Include a descriptive text in the HTTP response body.

[1340] Step 8:

[1341] The device receives an HTTP response and extracts a description generated from the response body. Finally, the device displays a user-friendly and emotionally resonant description on the app's screen.

[1342] Input: HTTP response

[1343] Output: Explanatory text displayed on the screen (Example: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use.")

[1344] Specific operation: The device extracts the explanatory text from the response body and displays it on the app's screen.

[1345] (Application Example 2)

[1346] 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."

[1347] Senior users face challenges when using electronic payment services, such as difficulty understanding technical terms and procedures, leading to anxiety and frustration. This is particularly true in the field of electronic payments, where technical jargon is prevalent, creating barriers to use and significantly detracting from the user experience. Furthermore, errors and security risks arising from a lack of understanding of technical terms must also be considered. Therefore, there is a need for electronic payment services that are easy for seniors to understand and use with confidence.

[1348] 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.

[1349] In this invention, the server includes means for receiving technical terms entered by the user, means for recognizing and analyzing emotions, means for transmitting the received technical terms and emotion data to the server, means for the server to search for technical terms in a database and generate an easy-to-understand explanation, means for adjusting the generated explanation with consideration for the user's emotions, means for transmitting the generated explanation to the user terminal, and means for the user terminal to display the generated explanation. As a result, users can easily understand and use electronic payment services with peace of mind without feeling anxious or frustrated with technical terms or procedures.

[1350] "User-input technical terms" refer to technical terms that users find difficult to understand and enter into the device's interface.

[1351] "Means for recognizing and analyzing emotions" refers to software modules used to analyze a user's emotional state, employing techniques such as facial recognition and voice tone analysis.

[1352] "Means for sending received technical terms and emotion data to the server" refers to communication means for sending technical terms and emotion recognition data acquired from the user terminal to the server.

[1353] "A means by which a server searches a database for technical terms and generates easy-to-understand explanations" refers to a process in which a server retrieves definitions corresponding to technical terms from a database and converts them into easy-to-understand explanations.

[1354] "Means for adjusting generated descriptions with consideration for user emotions" refers to a natural language processing engine that adjusts the tone and expression of generated descriptions according to the user's emotional state.

[1355] "Means for sending the generated explanatory text to the user terminal" refers to communication means for sending the explanatory text generated and adjusted by the server to the user terminal.

[1356] "Means for displaying the generated explanatory text on the user terminal" refers to screen display means for displaying the explanatory text received by the user terminal so that the user can view it.

[1357] This invention is a system designed to help senior users understand technical terms and procedures when using electronic payment services, thereby reducing stress. The system uses a combination of a natural language processing engine that converts technical terms into easy-to-understand explanations and an emotion engine that recognizes the user's emotions.

[1358] The system consists of the following elements:

[1359] 1. User terminal: A device such as a smartphone or tablet that provides an interface for users to input technical terms they find difficult to understand and for acquiring sentiment data.

[1360] 2. Emotion Recognition: This function operates on the user's device and recognizes the user's emotions using facial recognition APIs (e.g., AWS Rekognition) and voice tone analysis.

[1361] 3. Data transmission: Includes means of communication for sending user-entered technical terms and sentiment data to the server.

[1362] 4. Server: Utilizes a database and a natural language processing engine (e.g., SpaCy, BERT) to search for definitions of technical terms and generate easy-to-understand explanations.

[1363] 5. Description Adjustment: The description generated by the server is adjusted to take user emotions into consideration, and the tone and content are fine-tuned.

[1364] 6. Sending to the user terminal: The generated explanation is sent to the user terminal and displayed to the user.

[1365] Process Description

[1366] Hardware and software

[1367] Hardware: User devices (smartphones, tablets)

[1368] software:

[1369] Emotion recognition software (e.g., AWS Rekognition)

[1370] Natural language processing engines (e.g., SpaCy, BERT)

[1371] Server-side applications (e.g., Node.js, Express)

[1372] Database (e.g., MySQL)

[1373] Data processing and data calculation

[1374] When a user inputs a technical term, the system simultaneously acquires the term and the user's emotional data. This emotional data is obtained through facial recognition and voice tone analysis.

[1375] Next, the device sends this data to the server. The server searches its database based on the received technical terms and generates an easy-to-understand explanation. The generated explanation then goes through a natural language processing engine to adjust its tone and content according to the user's sentiment. The adjusted explanation is then sent to the user's device and finally displayed to the user on the device.

[1376] Specific examples

[1377] For example, if a user types "What is a security code?" and is feeling anxious, the device sends the keyword "security code" and the emotion data "anxiety" to the server. The server searches its database for "security code" and retrieves its definition. Then, using a natural language processing engine, it generates an explanation such as "A security code is a 3- or 4-digit number printed on the back of your card that ensures secure online transactions. There's no need to be anxious. Please check it out," and displays it to the user.

[1378] Example of a prompt

[1379] A prompt message to use when a user is feeling unsure and asks, "What is a security code?":

[1380] "The security code is a three- or four-digit number printed on the back of your card, and it guarantees secure online transactions. There's no need to worry. Please take a look."

[1381] This system will make it easy for senior users to understand technical terms and procedures, allowing them to use electronic payment services with peace of mind.

[1382] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1383] Step 1:

[1384] Users enter technical terms they don't understand into the input field of their smartphone or tablet. The keywords entered by the user might be something like "security code."

[1385] Input: Technical terms (e.g., "security code")

[1386] Output: Input technical term data

[1387] Specific operation: The user launches the application, enters a technical term into the input field, and presses the "Submit" button.

[1388] Step 2:

[1389] The device uses a camera and microphone to recognize the user's emotions. The emotion recognition engine uses facial recognition APIs and voice tone analysis.

[1390] Input: User's face image, voice data

[1391] Output: Emotional data (e.g., "anxiety")

[1392] Specific operation: The emotion recognition engine analyzes the user's facial expressions and voice tone to identify their emotional state (e.g., "anxiety").

[1393] Step 3:

[1394] The terminal receives technical terms and sentiment data and sends it to the server as an HTTPS POST request.

[1395] Input: Technical terminology data, sentiment data

[1396] Output: Data sent to the server

[1397] Specific operation: The device packages technical terminology data and sentiment data in JSON format, creates an HTTPS POST request, and sends it to the server.

[1398] Step 4:

[1399] The server receives an HTTP request and analyzes the technical terms and sentiment data.

[1400] Input: Technical terminology data, sentiment data

[1401] Output: Analysis result data

[1402] Specific operation: The server extracts technical terminology data and sentiment data from the request body and analyzes each type of data.

[1403] Step 5:

[1404] The server retrieves definitions of technical terms by executing SQL queries against the database.

[1405] Input: Technical terminology data

[1406] Output: Definition data (Example: "The security code is a 3- or 4-digit number printed on the back of the card that ensures secure online transactions.")

[1407] Specific operation: The server executes an SQL query against the database to retrieve definitions of technical terms.

[1408] Step 6:

[1409] The server retrieves definitions from the database and passes them to a natural language processing engine to generate easy-to-understand explanatory text. It also adjusts the tone and content, taking sentiment data into consideration.

[1410] Input: Definition data, sentiment data

[1411] Output: Adjusted explanation (Example: "The security code is a 3- or 4-digit number printed on the back of your card, ensuring secure online transactions. There's no need to worry. Please check it out.")

[1412] Specific operation: The natural language processing engine converts complex parts of the definition data into simpler words and adjusts the explanatory text based on sentiment data.

[1413] Step 7:

[1414] The server generates an explanatory text which is then sent to the user's terminal as an HTTP response.

[1415] Input: Adjusted description

[1416] Output: Descriptive data sent to the user terminal

[1417] Specific operation: The server generates an HTTP response containing an explanation and sends it to the user's terminal.

[1418] Step 8:

[1419] The application displays the explanatory text received by the user's terminal on its screen.

[1420] Input: Received explanatory data

[1421] Output: Description displayed on the screen

[1422] Specific operation: The device displays an explanatory text on the screen, which the user can view. At this time, the explanatory text will be considerate of the user's feelings, such as, "The security code is a 3-digit or 4-digit number printed on the back of the card, and it guarantees secure online transactions. There is no need to worry. Please take a look."

[1423] 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.

[1424] 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.

[1425] 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.

[1426] [Fourth Embodiment]

[1427] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1428] 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.

[1429] 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).

[1430] 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.

[1431] 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.

[1432] 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).

[1433] 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.

[1434] 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.

[1435] 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.

[1436] 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.

[1437] 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.

[1438] 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.

[1439] 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".

[1440] This invention is a system designed to help senior users understand technical terms when using smartphones and computers. To achieve this objective, the system includes multiple means for explaining technical terms entered by the user in an easy-to-understand manner.

[1441] System Configuration

[1442] This system consists of the following main components:

[1443] User terminal: A computer device such as a smartphone or tablet that provides an interface for users to input technical terms.

[1444] Server: Receives technical terms sent from the user terminal, searches the database to generate an easy-to-understand explanation, and sends it back to the user terminal.

[1445] Database: A storage system that stores technical terms and their definitions.

[1446] Natural Language Processing Engine: A software module used to replace complex technical terms with simpler language.

[1447] Program processing

[1448] 1. Enter and submit technical terms.

[1449] The user launches an app on their smartphone or tablet and enters technical terms they find difficult to understand into an input field. For example, they might enter "Wi-Fi". Once this input is complete, the device sends the technical terms to the server. Specifically, the device sends the entered data as a POST request to a particular API endpoint.

[1450] 2. Analysis of technical terms on the server

[1451] The server receives requests sent from user terminals and matches the technical terms against the database. For example, the server searches the database for the keyword "Wi-Fi". If this search finds a matching entry, the server retrieves the information for that entry. The entry includes a definition such as "Wi-Fi is a wireless LAN technical standard, a technology that enables wireless internet connectivity."

[1452] 3. Generating explanatory text

[1453] The definition obtained from the database is then passed to the natural language processing engine on the server. This engine generates an easy-to-understand explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[1454] 4. Sending and displaying the description

[1455] The server generates an explanatory text and sends it back to the user's device. Specifically, the server sends data containing the explanatory text as an HTTP response. Finally, the device receives this response data and displays an easy-to-understand explanatory text on the app's screen. For example, it might say, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables," which the user then reads.

[1456] Specific example

[1457] Example 1: "Wi-Fi"

[1458] 1. The user types "What is Wi-Fi?".

[1459] 2. The device sends the keyword "Wi-Fi" to the server.

[1460] 3. The server searches the database for "Wi-Fi" and retrieves the definition: "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[1461] 4. The server uses a natural language processing engine to generate an easy-to-understand explanation: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[1462] 5. The server sends an explanatory message to the terminal.

[1463] 6. The device displays an explanatory text to the user.

[1464] Example 2: "Browser"

[1465] 1. The user types "What is a browser?".

[1466] 2. The device sends the keyword "browser" to the server.

[1467] 3. The server searches the database for "browser" and retrieves the definition: "A browser is software used to display HTML documents, such as Chrome or Firefox."

[1468] 4. The server uses a natural language processing engine to generate an easy-to-understand explanation: "A browser is an application for viewing various pages on the internet."

[1469] 5. The server sends an explanatory message to the terminal.

[1470] 6. The device displays an explanatory text to the user.

[1471] In this way, the present invention can help senior users understand technical terms more easily and promote the use of smartphones and computers.

[1472] The following describes the processing flow.

[1473] Step 1:

[1474] The user launches a smartphone app and enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field. When the user taps the "Send" button, the app retrieves this technical term.

[1475] Step 2:

[1476] The terminal retrieves the entered technical term and sends an HTTP POST request to the server. The request contains the technical term.

[1477] Step 3:

[1478] The server receives an HTTP request and parses the technical terms data. Specifically, the server extracts technical terms (e.g., "Wi-Fi") from the request body.

[1479] Step 4:

[1480] The server executes an SQL query against the database to retrieve the definition of a technical term. For example, the server might retrieve the definition of the technical term "Wi-Fi" as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[1481] Step 5:

[1482] The server passes the acquired definitions to the natural language processing engine. The natural language processing engine identifies complex terms such as "wireless LAN" and "technical standards" and converts them into easily understandable language.

[1483] Step 6:

[1484] The server uses the output of a natural language processing engine to generate explanatory text that is easy for the user to understand. For example, it might generate an explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[1485] Step 7:

[1486] The server generates an explanatory text which is then sent to the user's terminal as an HTTP response.

[1487] Step 8:

[1488] The terminal receives an HTTP response and extracts the generated explanatory text from the response body.

[1489] Step 9:

[1490] The device displays easy-to-understand explanatory text on the app screen. Users will be able to view explanations such as, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables."

[1491] This series of steps will make it easier for senior users to understand technical terms and to use smartphones and computers more effectively.

[1492] (Example 1)

[1493] 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".

[1494] With the advancement of modern information technology, many users, including seniors, often find it difficult to understand technical jargon when using smartphones and computers. This problem is particularly pronounced when using the internet or new software, potentially widening the digital divide. Therefore, there is a need for systems that make this technical jargon easy to understand.

[1495] 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.

[1496] In this invention, the server includes means for receiving technical terms entered by the user, means for transmitting the received technical terms to a central processing unit, means for the central processing unit to retrieve the technical terms from a storage device and generate an easy-to-understand explanation, means for transmitting the generated explanation to a user device, and means for the user device to display the generated explanation. This makes it possible for a diverse range of users, including senior citizens, to easily understand technical terms.

[1497] "User" refers to a general user of the system.

[1498] "Technical jargon" refers to terms related to a specific field or technology that are difficult for the average user to understand.

[1499] "Means of receiving" refers to devices or modules that have the function of taking in data and information entered by the user into the system.

[1500] "Means of transmission" refers to devices or modules that have the function of sending received data or information to another device or module.

[1501] A "central processing unit" refers to the main device or module that handles information processing for the entire system and processes data based on instructions.

[1502] A "storage device" refers to a storage system used to store data and information.

[1503] A "natural language processing module" refers to a software module that converts natural language into an easily understandable format through the analysis and generation of input text.

[1504] "User device" refers to a device used by a user to access the system, and includes smartphones, tablets, and computers.

[1505] "Public information sources" refer to information sources that are generally accessible, such as websites and public databases on the internet.

[1506] Modes for carrying out the invention

[1507] This invention is a system designed to support users, including senior citizens, who may have difficulty understanding technical terms. This system consists of the following main components:

[1508] Components

[1509] 1. User device: A device such as a smartphone, tablet, or computer that provides an interface for the user to input technical terms.

[1510] 2. Central Processing Unit: This is the main computer system responsible for searching, analyzing, and generating explanatory texts for technical terms.

[1511] 3. Storage device: A database that stores technical terms and their explanations.

[1512] 4. Natural Language Processing Module: This is a software module for replacing technical jargon with easily understandable language.

[1513] 5. Public Information Sources: This is a system for collecting information on specialized terminology not found in databases from the internet.

[1514] Explanation of the program's processing

[1515] To generate the program for this system, follow these steps:

[1516] Entering and sending technical terms

[1517] First, the user launches an app on their smartphone or tablet and enters technical terms they find difficult to understand into the input field. For example, the user might enter "Wi-Fi". Once this input is complete, the device sends the technical terms to the server (central processing unit). Specifically, the device sends the entered data as a POST request to a particular API endpoint.

[1518] Analysis of technical terms on servers

[1519] The server receives requests sent from user terminals and matches the technical terms against its storage. For example, the server searches the database for the keyword "Wi-Fi". If this search finds a matching entry, the server retrieves the information for that entry. The entry includes a definition such as "Wi-Fi is a wireless LAN technical standard, a technology that enables wireless internet connectivity."

[1520] Generating an explanatory text

[1521] Next, the acquired definition is passed to a natural language processing module. The server uses this module to generate an easy-to-understand explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[1522] Sending and displaying the description

[1523] Finally, the generated explanation is sent to the user's device, and the terminal displays the explanation on the app's screen. For example, it might say, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables," which the user can then view.

[1524] Specific example

[1525] Example 1: "Wi-Fi"

[1526] 1. The user types "What is Wi-Fi?".

[1527] 2. The device sends the keyword "Wi-Fi" to the central processing unit.

[1528] 3. The central processing unit searches for "Wi-Fi" in the memory and obtains the definition that "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[1529] 4. The central processing unit uses a natural language processing module to generate an easy-to-understand explanation: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[1530] 5. The central processing unit transmits the explanatory text to the user device.

[1531] 6. The user device displays an explanatory text to the user.

[1532] Example 2: "Browser"

[1533] 1. The user types "What is a browser?".

[1534] 2. The terminal sends the keyword "browser" to the central processing unit.

[1535] 3. The central processing unit searches for "browser" in its memory and retrieves the definition that "a browser is software for displaying HTML documents, such as Chrome or Firefox."

[1536] 4. The central processing unit uses a natural language processing module to generate an easy-to-understand explanation: "A browser is an application for viewing various pages on the internet."

[1537] 5. The central processing unit transmits the explanatory text to the user device.

[1538] 6. The user device displays an explanatory text to the user.

[1539] Example of a prompt

[1540] Examples of prompt statements to input into a generative AI model are as follows:

[1541] If a user types "What is Wi-Fi?", the system will perform the following steps:

[1542] 1. The device sends the keyword "Wi-Fi" to the central processing unit.

[1543] 2. The central processing unit searches for "Wi-Fi" in the memory and retrieves the corresponding definition.

[1544] 3. The definition obtained by the central processing unit is converted into simple words using a natural language processing module.

[1545] 4. The central processing unit sends the easy-to-understand explanatory text it has generated back to the terminal.

[1546] 5. The device displays the explanatory text on the user's screen.

[1547] As a concrete example, we will display an explanation such as, "Wi-Fi is a method that allows smartphones and computers to connect to the internet without using cables." This makes it easier for users to understand technical terms.

[1548]

[1549] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1550] Detailed explanation of the program's processing

[1551] Step 1: User input reception and submission

[1552] Input: Technical term Example: "Wi-Fi"

[1553] Operation:

[1554] The user launches the app on their smartphone or tablet and enters technical terms that are difficult to understand into the input field.

[1555] Once input is complete, the terminal sends the technical terms to the central processing unit (server).

[1556] Specifically, the device sends the entered data as a POST request to a specific API endpoint.

[1557] Output: Technical terminology data sent to the server

[1558] Step 2: The server receives the request.

[1559] Input: POST request sent from the terminal

[1560] Operation:

[1561] The server receives a POST request sent from the user's terminal.

[1562] The request includes technical terms entered by the user.

[1563] Output: Terminology data received.

[1564] Step 3: Database matching of technical terms

[1565] Input: Technical terminology data

[1566] Operation:

[1567] The server compares the received technical terms with its storage device (database).

[1568] For example, the server searches for the keyword "Wi-Fi" in the database.

[1569] If this search finds a matching entry, the server retrieves the information for that entry.

[1570] Output: Definitions of technical terms retrieved from the database. Example: "Wi-Fi is a wireless LAN technical standard, a technology that enables wireless internet connectivity."

[1571] Step 4: Analysis and conversion using a natural language processing engine

[1572] Input: Definitions of technical terms obtained from a database

[1573] Operation:

[1574] The server passes the retrieved definition to the natural language processing module.

[1575] The natural language processing module replaces complex parts with easily understandable language.

[1576] For example, it can generate an explanatory text such as, "Wi-Fi is a method that allows smartphones and computers to connect to the internet without using cables."

[1577] Output: Easy-to-understand explanation. Example: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[1578] Step 5: Send and display the description.

[1579] Input: Description generated by the natural language processing module

[1580] Operation:

[1581] The server then sends the generated explanation back to the user's terminal.

[1582] Send data including a description as an HTTP response.

[1583] The device processes the HTTP response received from the server and displays an easy-to-understand explanation on the app's screen.

[1584] The user reads the displayed description.

[1585] Output: Explanation displayed on the app screen. Example: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables."

[1586] A concrete example of the entire sequence of steps

[1587] 1. In Step 1, the user types "What is Wi-Fi?".

[1588] 2. In step 2, "the device sends that data to the server."

[1589] 3. In step 3, "the server searches for 'Wi-Fi' in the database and returns the definition."

[1590] 4. In step 4, "the server passes the definition to the natural language processing module, which generates an easy-to-understand explanation."

[1591] 5. In step 5, "the server sends the generated explanation to the terminal, and the terminal displays the explanation to the user."

[1592] By following the steps outlined above, this system assists in understanding technical terms and makes it easier for users, including senior citizens, to grasp technical jargon.

[1593] (Application Example 1)

[1594] 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".

[1595] In recent years, senior citizens have increasingly used smartphones and computers, but the problem of difficulty in understanding technical jargon has become more pronounced. Security terminology, in particular, is complex, and many users struggle to understand it properly. Therefore, there is a need for support systems that enable senior citizens to easily understand technical terms and enhance their security awareness.

[1596] 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.

[1597] In this invention, the server includes means for receiving technical terms entered by the user, means for sending the received technical terms to the server, means for the server to search for the technical terms in a database and generate an easy-to-understand explanation, means for sending the generated explanation to the user terminal, means for the user terminal to display the generated explanation, means for the user to enter technical terms that are difficult to understand into an input field in the application, means for sending the entered technical terms as a POST request using an API, means for the server to compare the received technical terms with a database and convert the obtained definition into simple words using a natural language processing model, and means for sending the generated explanation as an HTTP response. This makes it possible for senior users to easily understand security terms and immediately check their explanations.

[1598] A "user terminal" is a device used by users to input technical terms and receive and display explanatory text.

[1599] "Technical jargon" refers to complex terms used in technical or specialized fields.

[1600] A "server" is a device that receives technical terms sent from a user terminal, searches a database to generate an explanation, and then sends it back to the user terminal.

[1601] A "database" is a storage system that stores technical terms and their explanations.

[1602] A "natural language processing engine" is a software module that analyzes the complex parts of technical terms and replaces them with simpler language.

[1603] "API" stands for Application Programming Interface, which is an interface for using software functions from an external source.

[1604] A "POST request" is a request method used in the HTTP protocol to send data to a server.

[1605] An "HTTP response" is the response data sent from a server to a client in the HTTP protocol.

[1606] "Hugging Face" is a popular tool that provides libraries and APIs for natural language processing.

[1607] "Simple language" refers to more general and easily understandable terms used to generate explanatory texts that are easier to understand than technical jargon.

[1608] An "input field" is an area within an application where the user enters technical terms.

[1609] "Security terminology" refers to specialized terms related to information security and network security.

[1610] This invention is a system designed to help senior users easily understand technical terms. The system consists of a user terminal, a server, a database, a natural language processing engine, and an API.

[1611] Program processing

[1612] 1. User input and data transmission

[1613] The user enters technical terms that are difficult to understand into an input field within the application. This input field is displayed on the user's device, such as a smartphone or tablet. Once the user has finished entering the terms, the device sends the entered technical terms to the server as a POST request using an API.

[1614] 2. Analysis of technical terms and acquisition of definitions

[1615] The server receives the incoming request and matches it against the database. The database stores a wide range of technical terms and their definitions; for example, if the word "firewall" is received, it retrieves a definition such as "a network security system."

[1616] 3. Generating explanatory text

[1617] The definitions of technical terms obtained are passed to a natural language processing engine on the server (e.g., Hugging Face). This engine analyzes the complex parts of the technical terms, replaces them with simpler words, and generates easy-to-understand explanations. For example, it might generate an explanation such as, "A firewall is a mechanism to protect computers and smartphones from malicious actors."

[1618] 4. Sending and displaying the description

[1619] The server sends the generated explanation as an HTTP response to the user's terminal. The user's terminal receives this response and displays the explanation within the application. This allows the user to instantly see a simple explanation of technical terms.

[1620] Specific example

[1621] Specifically, when a user types "What is a firewall?" into the app's input field, the following prompt is sent to the server:

[1622] "What is a firewall? Please explain it in simple terms."

[1623] Hardware and software to use

[1624] User devices: Smartphones, tablets

[1625] Server: A computer device that receives, analyzes, and transmits data (e.g., a cloud server).

[1626] Database: A storage system that stores technical terms and their definitions (e.g., Amazon RDS).

[1627] Natural language processing engine: Software for analyzing and simplifying technical terms (e.g., Hugging Face API)

[1628] API: An interface for sending and receiving technical terms.

[1629] This will allow senior users to more easily understand technical terms and access information that will be useful in their daily lives and to improve their security awareness.

[1630] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1631] Step 1:

[1632] The user enters technical terms into an input field within the application.

[1633] The entered data consists of technical terms such as "firewall," and this will be used as input data in Step 2.

[1634] Step 2:

[1635] The terminal sends the entered technical terms to the server using the API. The data is sent as a POST request.

[1636] Specifically, the device converts the input data into JSON format and sends it as a POST request to the API endpoint. This request is received by the server.

[1637] Step 3:

[1638] The server analyzes the received request and matches it against technical terms in the database.

[1639] The system searches a database using input data (technical terms) as keys and retrieves the corresponding definitions. For example, for the term "firewall," it retrieves the definition "network security system."

[1640] Step 4:

[1641] The server retrieves definitions of technical terms, passes them to a natural language processing engine, and converts them into simpler words.

[1642] Using a natural language processing engine (e.g., Hugging Face), the system analyzes complex technical terms and generates easy-to-understand explanations. For example, it might generate an explanation such as, "A firewall is a mechanism to protect computers and smartphones from malicious actors."

[1643] Step 5:

[1644] The server sends the generated description to the user's terminal as an HTTP response.

[1645] The generated description is converted to JSON format and sent to the terminal as an HTTP response. A success code, such as status code 200, is also sent at this time.

[1646] Step 6:

[1647] The application displays the explanatory text received by the device.

[1648] The device analyzes the received data and displays it on the application screen. This allows the user to see easy-to-understand explanations of technical terms.

[1649] Through these steps, users can input technical terms and obtain concise explanations, thereby gaining a deeper understanding.

[1650] 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.

[1651] This invention is a system designed to help senior users understand technical terms when using smartphones and computers, and further aims to recognize the user's emotions and provide appropriate explanations. This will reduce user stress and improve engagement.

[1652] System Configuration

[1653] This system consists of the following main components:

[1654] User terminal: A computer device such as a smartphone or tablet that provides an interface for users to input technical terms.

[1655] Server: Receives technical terms sent from the user terminal, searches the database to generate an easy-to-understand explanation, and sends it back to the user terminal.

[1656] Database: A storage system that stores technical terms and their definitions.

[1657] Natural Language Processing Engine: A software module used to replace complex technical terms with simpler language.

[1658] Emotion engine: A software module that recognizes the emotions of the user during input and sends that information to the server.

[1659] Program processing

[1660] 1. Enter and submit technical terms.

[1661] The user launches the app on their smartphone or tablet and enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field. When the user taps the "Send" button, the app retrieves this technical term.

[1662] 2. User emotion recognition

[1663] As the device inputs technical terms, it simultaneously analyzes the user's emotions using an emotion engine. The emotion engine performs facial recognition and voice tone analysis to identify the emotions the user is feeling at the time of input (e.g., doubt, anxiety, frustration, etc.).

[1664] 3. Sending data

[1665] The device sends the acquired technical terms and sentiment data to the server as an HTTPS POST request. The request includes technical terms and user sentiment information.

[1666] 4. Analysis of technical terms and sentiment data on servers

[1667] The server receives an HTTP request and analyzes technical terms and sentiment data. Specifically, the server extracts technical terms and sentiment data (e.g., "Wi-Fi", "anxiety") from the request body.

[1668] 5. Generating the explanatory text

[1669] The server retrieves definitions for technical terms by executing SQL queries against the database. For example, the server might retrieve the definition for the technical term "Wi-Fi" as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless internet connection."

[1670] 6. Use of Natural Language Processing Engines

[1671] The acquired definitions are passed to a natural language processing engine, which identifies complex terms such as "wireless LAN" and "technical standards" and converts them into easily understandable language. Furthermore, sentiment data is taken into consideration, and the tone and content of the explanatory text are appropriately adjusted.

[1672] 7. Sending and displaying the description

[1673] The server sends the generated explanatory text to the user's terminal as an HTTP response. For example, it might be adjusted to say, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[1674] The device receives an HTTP response and extracts a descriptive text generated from the response body. Finally, the device displays a user-friendly and easy-to-understand descriptive text on the app screen, making it accessible to the user.

[1675] Specific example

[1676] Example 1: "Wi-Fi"

[1677] 1. The user typed "What is Wi-Fi?" and seems a little unsure.

[1678] 2. The device sends the keyword "Wi-Fi" and the emotion data "anxiety" to the server.

[1679] 3. The server searches the database for "Wi-Fi" and retrieves the definition: "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[1680] 4. The server uses a natural language processing engine to generate an easy-to-understand explanation: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[1681] 5. The server sends an explanatory message to the terminal.

[1682] 6. The device displays an explanatory text to the user.

[1683] Example 2: "Browser"

[1684] 1. The user types "What is a browser?" and seems a little frustrated.

[1685] 2. The device sends the keyword "browser" and emotion data "frustration" to the server.

[1686] 3. The server searches the database for "browser" and retrieves the definition: "A browser is software used to display HTML documents, such as Chrome or Firefox."

[1687] 4. The server uses a natural language processing engine to generate an easy-to-understand explanation: "A browser is an application for viewing internet pages. We will support you so that you can resolve your issue quickly."

[1688] 5. The server sends an explanatory message to the terminal.

[1689] 6. The device displays an explanatory text to the user.

[1690] In this way, the present invention can help senior users understand technical terms more easily, and by taking into consideration the user's feelings, it can reduce stress and promote the use of smartphones and computers.

[1691] The following describes the processing flow.

[1692] Step 1:

[1693] The user launches a smartphone app and enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field. When the user taps the "Send" button, the device retrieves this technical term.

[1694] Step 2:

[1695] As the device receives input of technical terms, it simultaneously analyzes the user's emotions using an emotion engine. The emotion engine analyzes the user's facial expressions and voice to identify the user's emotions (e.g., anxiety, doubt, frustration, etc.).

[1696] Step 3:

[1697] The device structures the acquired technical terms and sentiment data and sends it to the server as an HTTP POST request. The request includes "Wi-Fi" and the user's sentiment.

[1698] Step 4:

[1699] The server receives the HTTP request and parses its contents. Specifically, the server extracts the technical term "Wi-Fi" and emotional data (e.g., "anxiety") from the request body.

[1700] Step 5:

[1701] The server executes an SQL query against the database to retrieve the definition of a technical term. For example, the server might retrieve the definition of the technical term "Wi-Fi" as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet."

[1702] Step 6:

[1703] The server passes the acquired definitions to a natural language processing engine, which converts complex parts into easily understandable language. The natural language processing engine replaces complex terms such as "wireless LAN" and "technical standards" with simpler words.

[1704] Step 7:

[1705] The server adjusts the content and tone of the explanatory text based on the analyzed sentiment data. For example, if the sentiment data indicates "anxiety," the explanatory text will be adjusted to include phrases such as "Please rest assured."

[1706] Step 8:

[1707] The server generates a final explanation (e.g., "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use.") and sends it to the user's terminal as an HTTP response.

[1708] Step 9:

[1709] The terminal receives an HTTP response and extracts the generated explanatory text from the response body.

[1710] Step 10:

[1711] The device will display easy-to-understand explanations on the app screen that are considerate of the user's feelings, and allow the user to view them. For example, it might display an explanation such as, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[1712] Through these processing steps, senior users will find it easier to understand technical terms, and by taking their feelings into consideration, they will be able to use smartphones and computers with reduced stress.

[1713] (Example 2)

[1714] 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".

[1715] In today's technological society, many users, including the elderly, struggle to understand technical and jargon. Seniors, in particular, often experience emotional stress and frustration due to the difficulty of technical terms, which acts as a barrier to technological adoption. These challenges reduce the convenience and engagement with technology, ultimately preventing them from fully benefiting from evolving technological services.

[1716] 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.

[1717] In this invention, the server includes means for recognizing the user's emotions and generating emotion data, means for adjusting the content and tone of the explanatory text based on the emotion data, and a natural language processing engine that analyzes difficult parts of technical terms and replaces them with simpler words. This not only helps the user understand but also reduces user stress and improves engagement by providing emotionally sensitive explanations.

[1718] A "user" refers to an individual who uses a service or system.

[1719] "Technical jargon" refers to specialized or technical terms used in a particular field or industry.

[1720] A "server" refers to a computer system that receives requests from users and processes and provides data.

[1721] A "database" refers to a system that systematically stores data and allows for the retrieval and searching of that data as needed.

[1722] An "explanatory text" refers to text generated to clearly explain the meaning and usage of technical terms and jargon.

[1723] "User terminal" refers to devices used by a user, such as smartphones, tablets, and personal computers.

[1724] "Emotional data" refers to information that represents a user's emotional state (for example, anxiety, doubt, frustration, etc.).

[1725] A "natural language processing engine" refers to a software module that analyzes text data and converts it into a form that is easy for humans to understand.

[1726] An "HTTPS POST request" is a type of protocol used to send data to a server over the internet.

[1727] An "SQL query" refers to a set of commands used to manipulate or retrieve data from a database.

[1728] This invention is a system designed to assist senior users in understanding technical terms when using smartphones and computers. Furthermore, it aims to recognize the user's emotions and provide appropriate explanations. This system can reduce user stress and improve engagement.

[1729] System Configuration

[1730] This system consists of the following main components:

[1731] User terminal: A device such as a smartphone, tablet, or personal computer that provides an interface for users to input technical terms.

[1732] Server: Receives technical terms and sentiment data sent from the user terminal, searches the database to generate an easy-to-understand explanation, and sends it back to the user terminal.

[1733] Database: A storage system that stores technical terms and their definitions.

[1734] Natural Language Processing Engine: A software module used to replace complex technical terms with simpler language.

[1735] Emotion engine: A software module that recognizes the emotions of the user during input and sends that information to the server.

[1736] Explanation of the program's processing

[1737] 1. Enter and submit technical terms.

[1738] The user launches an app on their smartphone or tablet and enters a technical term they find difficult to understand into the input field. For example, they might enter "Wi-Fi". When the user taps the "Send" button, the device receives the user's input and prepares to proceed to the next step.

[1739] 2. User emotion recognition

[1740] The device activates its emotion engine simultaneously with the input of technical terms. The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice in real time. For example, the camera captures the user's facial expression, and the emotion analysis algorithm detects "anxiety." This information is then used in the following processes.

[1741] 3. Sending data

[1742] The device compiles the acquired technical terms and sentiment data and sends an HTTPS POST request to the server. The request body includes data such as "Technical Terms: Wi-Fi" and "Sentiment: Anxiety." Once the server receives this request, it proceeds to the next step.

[1743] 4. Analysis of technical terms and sentiment data on servers

[1744] The server parses the received HTTP request and extracts technical terms and sentiment data from the request body. For example, the data might be extracted in the form of "technical term = Wi-Fi" and "sentiment = anxiety." Based on this data, the server prepares to query the database and look up the definitions of the technical terms.

[1745] 5. Generating the explanatory text

[1746] The server executes SQL queries against the database to search for definitions corresponding to technical terms. For example, for the technical term "Wi-Fi," it retrieves the definition from the database as "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless connection to the internet." Based on this retrieved definition, it generates an explanatory text.

[1747] 6. Use of Natural Language Processing Engines

[1748] The server passes the acquired definitions to a natural language processing engine. The natural language processing engine identifies complex terms such as "wireless LAN" and "technical standards" and converts them into easily understandable language. It also adjusts the tone of the explanation to be reassuring based on the emotion data "anxiety." For example, it might generate an explanation such as, "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[1749] 7. Sending and displaying the description

[1750] The server generates an explanatory text and sends it to the user's terminal as an HTTP response. For example, the response body might include a message like, "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use." The terminal receives this HTTP response and extracts the generated explanatory text from the response body. The terminal then displays the user-friendly and emotionally reassuring explanatory text on the app screen. By viewing this explanation, the user gains a deeper understanding of technical terms and a sense of emotional reassurance.

[1751] Specific example

[1752] Example 1: "Wi-Fi"

[1753] 1. The user opens a smartphone app and types "What is Wi-Fi?". They feel a little unsure.

[1754] 2. The device acquires the keyword "Wi-Fi," analyzes the emotion data "anxiety" using the emotion engine, and sends it to the server.

[1755] 3. The server receives the HTTP request, analyzes the "Wi-Fi" and "anxiety" data, and queries the database.

[1756] 4. The server obtains the definition that "Wi-Fi is a wireless LAN technology standard that allows wireless internet connection" and uses a natural language processing engine to generate the following explanation: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[1757] 5. The server sends an explanatory message to the terminal.

[1758] 6. The device receives the explanation and displays the following message on the app screen: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use."

[1759] Example 2: "Browser"

[1760] 1. The user opens a smartphone app, types "What's a browser?", and becomes slightly frustrated.

[1761] 2. The device acquires the keyword "browser," analyzes the emotion data "frustration" using the emotion engine, and sends it to the server.

[1762] 3. The server receives the HTTP request, analyzes the "browser" and "frustration" data, and queries the database.

[1763] 4. The server obtains the definition that "a browser is software for displaying HTML documents, such as Chrome or Firefox," and uses a natural language processing engine to generate the explanation, "A browser is an application for viewing internet pages. We will support you so that you can resolve the issue quickly."

[1764] 5. The server sends an explanatory message to the terminal.

[1765] 6. The device receives the explanation and displays the following message on the app screen: "The browser is an app for viewing internet pages. We will help you resolve the issue quickly."

[1766] Examples of prompts for generative AI models

[1767] Q: If you type "What is Wi-Fi?"

[1768] A: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, it's easy to use."

[1769] Q: What is a browser?

[1770] A: "A browser is an application for viewing internet pages. I'll help you resolve this quickly."

[1771] Thus, the present invention can help senior users understand technical terms more easily, and by taking into consideration the user's feelings, it can reduce stress and promote the use of smartphones and computers.

[1772] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1773] Step 1:

[1774] The user launches the app on their smartphone or tablet, enters a technical term they find difficult to understand (e.g., "Wi-Fi") into the input field, and taps the "Send" button.

[1775] Input: Technical terms (e.g., "Wi-Fi")

[1776] Output: Technical terms (e.g., "Wi-Fi")

[1777] Specific action: The terminal receives user input and prepares to proceed to the next process.

[1778] Step 2:

[1779] The device activates its emotion engine simultaneously with the input of technical terms. The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice in real time.

[1780] Input: User's facial expressions and voice

[1781] Output: Emotional data (e.g., "anxiety")

[1782] Specific operation: The camera captures the user's facial expressions, and an emotion analysis algorithm reads the user's "anxiety."

[1783] Step 3:

[1784] The device compiles the acquired technical terms and sentiment data and sends an HTTPS POST request to the server.

[1785] Input: Technical terms (e.g., "Wi-Fi"), emotional data (e.g., "anxiety")

[1786] Output: HTTP request sent to the server

[1787] Specific action: Include technical terms and sentiment data in the request body.

[1788] Step 4:

[1789] The server analyzes the received HTTP request and extracts technical terms and sentiment data from the request body.

[1790] Input: HTTP Request

[1791] Output: Technical terms (e.g., "Wi-Fi"), emotional data (e.g., "anxiety")

[1792] Specific operation: The server parses the request body and extracts technical terms and sentiment data.

[1793] Step 5:

[1794] The server executes an SQL query against the database to retrieve definitions corresponding to technical terms.

[1795] Input: Technical terms (e.g., "Wi-Fi")

[1796] Output: Definitions of technical terms (e.g., "Wi-Fi is a wireless LAN technical standard, a technology that allows wireless internet connection")

[1797] Specific operation: The server executes an SQL query and retrieves the corresponding definition from the database.

[1798] Step 6:

[1799] The server passes the acquired definitions to a natural language processing engine, which converts complex parts into simpler language. It also adjusts the tone of the explanatory text based on sentiment data.

[1800] Input: Definitions of technical terms (e.g., "Wi-Fi is a wireless LAN technology that allows wireless internet connection"), emotional data (e.g., "anxiety")

[1801] Output: Easy-to-understand explanation (Example: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use.")

[1802] Specific operation: The natural language processing engine converts complex parts into simpler words and adjusts the tone based on sentiment data.

[1803] Step 7:

[1804] The server generates an explanatory text which is then sent to the user's terminal as an HTTP response.

[1805] Input: A clear and easy-to-understand explanation (Example: "Wi-Fi is a way for smartphones and computers to connect to the internet without using cables. Don't worry, it's easy to use.")

[1806] Output: HTTP response sent to the user's terminal

[1807] Specific action: Include a descriptive text in the HTTP response body.

[1808] Step 8:

[1809] The device receives an HTTP response and extracts a description generated from the response body. Finally, the device displays a user-friendly and emotionally resonant description on the app's screen.

[1810] Input: HTTP response

[1811] Output: Explanatory text displayed on the screen (Example: "Wi-Fi is a method for smartphones and computers to connect to the internet without using cables. Don't worry, this method is easy to use.")

[1812] Specific operation: The device extracts the explanatory text from the response body and displays it on the app's screen.

[1813] (Application Example 2)

[1814] 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".

[1815] Senior users face challenges when using electronic payment services, such as difficulty understanding technical terms and procedures, leading to anxiety and frustration. This is particularly true in the field of electronic payments, where technical jargon is prevalent, creating barriers to use and significantly detracting from the user experience. Furthermore, errors and security risks arising from a lack of understanding of technical terms must also be considered. Therefore, there is a need for electronic payment services that are easy for seniors to understand and use with confidence.

[1816] 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.

[1817] In this invention, the server includes means for receiving technical terms entered by the user, means for recognizing and analyzing emotions, means for transmitting the received technical terms and emotion data to the server, means for the server to search for technical terms in a database and generate an easy-to-understand explanation, means for adjusting the generated explanation with consideration for the user's emotions, means for transmitting the generated explanation to the user terminal, and means for the user terminal to display the generated explanation. As a result, users can easily understand and use electronic payment services with peace of mind without feeling anxious or frustrated with technical terms or procedures.

[1818] "User-input technical terms" refer to technical terms that users find difficult to understand and enter into the device's interface.

[1819] "Means for recognizing and analyzing emotions" refers to software modules used to analyze a user's emotional state, employing techniques such as facial recognition and voice tone analysis.

[1820] "Means for sending received technical terms and emotion data to the server" refers to communication means for sending technical terms and emotion recognition data acquired from the user terminal to the server.

[1821] "A means by which a server searches a database for technical terms and generates easy-to-understand explanations" refers to a process in which a server retrieves definitions corresponding to technical terms from a database and converts them into easy-to-understand explanations.

[1822] "Means for adjusting generated descriptions with consideration for user emotions" refers to a natural language processing engine that adjusts the tone and expression of generated descriptions according to the user's emotional state.

[1823] "Means for sending the generated explanatory text to the user terminal" refers to communication means for sending the explanatory text generated and adjusted by the server to the user terminal.

[1824] "Means for displaying the generated explanatory text on the user terminal" refers to screen display means for displaying the explanatory text received by the user terminal so that the user can view it.

[1825] This invention is a system designed to help senior users understand technical terms and procedures when using electronic payment services, thereby reducing stress. The system uses a combination of a natural language processing engine that converts technical terms into easy-to-understand explanations and an emotion engine that recognizes the user's emotions.

[1826] The system consists of the following elements:

[1827] 1. User terminal: A device such as a smartphone or tablet that provides an interface for users to input technical terms they find difficult to understand and for acquiring sentiment data.

[1828] 2. Emotion Recognition: This function operates on the user's device and recognizes the user's emotions using facial recognition APIs (e.g., AWS Rekognition) and voice tone analysis.

[1829] 3. Data transmission: Includes means of communication for sending user-entered technical terms and sentiment data to the server.

[1830] 4. Server: Utilizes a database and a natural language processing engine (e.g., SpaCy, BERT) to search for definitions of technical terms and generate easy-to-understand explanations.

[1831] 5. Description Adjustment: The description generated by the server is adjusted to take user emotions into consideration, and the tone and content are fine-tuned.

[1832] 6. Sending to the user terminal: The generated explanation is sent to the user terminal and displayed to the user.

[1833] Process Description

[1834] Hardware and software

[1835] Hardware: User devices (smartphones, tablets)

[1836] software:

[1837] Emotion recognition software (e.g., AWS Rekognition)

[1838] Natural language processing engines (e.g., SpaCy, BERT)

[1839] Server-side applications (e.g., Node.js, Express)

[1840] Database (e.g., MySQL)

[1841] Data processing and data calculation

[1842] When a user inputs a technical term, the system simultaneously acquires the term and the user's emotional data. This emotional data is obtained through facial recognition and voice tone analysis.

[1843] Next, the device sends this data to the server. The server searches its database based on the received technical terms and generates an easy-to-understand explanation. The generated explanation then goes through a natural language processing engine to adjust its tone and content according to the user's sentiment. The adjusted explanation is then sent to the user's device and finally displayed to the user on the device.

[1844] Specific examples

[1845] For example, if a user types "What is a security code?" and is feeling anxious, the device sends the keyword "security code" and the emotion data "anxiety" to the server. The server searches its database for "security code" and retrieves its definition. Then, using a natural language processing engine, it generates an explanation such as "A security code is a 3- or 4-digit number printed on the back of your card that ensures secure online transactions. There's no need to be anxious. Please check it out," and displays it to the user.

[1846] Example of a prompt

[1847] A prompt message to use when a user is feeling unsure and asks, "What is a security code?":

[1848] "The security code is a three- or four-digit number printed on the back of your card, and it guarantees secure online transactions. There's no need to worry. Please take a look."

[1849] This system will make it easy for senior users to understand technical terms and procedures, allowing them to use electronic payment services with peace of mind.

[1850] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1851] Step 1:

[1852] Users enter technical terms they don't understand into the input field of their smartphone or tablet. The keywords entered by the user might be something like "security code."

[1853] Input: Technical terms (e.g., "security code")

[1854] Output: Input technical term data

[1855] Specific operation: The user launches the application, enters a technical term into the input field, and presses the "Submit" button.

[1856] Step 2:

[1857] The device uses a camera and microphone to recognize the user's emotions. The emotion recognition engine uses facial recognition APIs and voice tone analysis.

[1858] Input: User's face image, voice data

[1859] Output: Emotional data (e.g., "anxiety")

[1860] Specific operation: The emotion recognition engine analyzes the user's facial expressions and voice tone to identify their emotional state (e.g., "anxiety").

[1861] Step 3:

[1862] The terminal receives technical terms and sentiment data and sends it to the server as an HTTPS POST request.

[1863] Input: Technical terminology data, sentiment data

[1864] Output: Data sent to the server

[1865] Specific operation: The device packages technical terminology data and sentiment data in JSON format, creates an HTTPS POST request, and sends it to the server.

[1866] Step 4:

[1867] The server receives an HTTP request and analyzes the technical terms and sentiment data.

[1868] Input: Technical terminology data, sentiment data

[1869] Output: Analysis result data

[1870] Specific operation: The server extracts technical terminology data and sentiment data from the request body and analyzes each type of data.

[1871] Step 5:

[1872] The server retrieves definitions of technical terms by executing SQL queries against the database.

[1873] Input: Technical terminology data

[1874] Output: Definition data (Example: "The security code is a 3- or 4-digit number printed on the back of the card that ensures secure online transactions.")

[1875] Specific operation: The server executes an SQL query against the database to retrieve definitions of technical terms.

[1876] Step 6:

[1877] The server retrieves definitions from the database and passes them to a natural language processing engine to generate easy-to-understand explanatory text. It also adjusts the tone and content, taking sentiment data into consideration.

[1878] Input: Definition data, sentiment data

[1879] Output: Adjusted explanation (Example: "The security code is a 3- or 4-digit number printed on the back of your card, ensuring secure online transactions. There's no need to worry. Please check it out.")

[1880] Specific operation: The natural language processing engine converts complex parts of the definition data into simpler words and adjusts the explanatory text based on sentiment data.

[1881] Step 7:

[1882] The server generates an explanatory text which is then sent to the user's terminal as an HTTP response.

[1883] Input: Adjusted description

[1884] Output: Descriptive data sent to the user terminal

[1885] Specific operation: The server generates an HTTP response containing an explanation and sends it to the user's terminal.

[1886] Step 8:

[1887] The application displays the explanatory text received by the user's terminal on its screen.

[1888] Input: Received explanatory data

[1889] Output: Description displayed on the screen

[1890] Specific operation: The device displays an explanatory text on the screen, which the user can view. At this time, the explanatory text will be considerate of the user's feelings, such as, "The security code is a 3-digit or 4-digit number printed on the back of the card, and it guarantees secure online transactions. There is no need to worry. Please take a look."

[1891] 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.

[1892] 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.

[1893] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1894] 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.

[1895] 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.

[1896] 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.

[1897] 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.

[1898] 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.

[1899] 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."

[1900] 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.

[1901] 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.

[1902] 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.

[1903] 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.

[1904] 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.

[1905] 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.

[1906] 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.

[1907] 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.

[1908] 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.

[1909] 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.

[1910] 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.

[1911] 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.

[1912] The following is further disclosed regarding the embodiments described above.

[1913] (Claim 1)

[1914] A means of receiving technical terms entered by the user,

[1915] A means of sending the received technical terms to the server,

[1916] A server searches a database for technical terms and generates easy-to-understand explanations.

[1917] A means for sending the generated explanatory text to the user's terminal,

[1918] A means for the user terminal to display the generated explanatory text,

[1919] A system that includes this.

[1920] (Claim 2)

[1921] The system according to claim 1, comprising a natural language processing engine that analyzes the complex parts of technical terms and replaces them with simpler words.

[1922] (Claim 3)

[1923] The system according to claim 1, further comprising means for collecting relevant information from the internet if the search results are not found in the database.

[1924] "Example 1"

[1925] (Claim 1)

[1926] A means of receiving technical terms entered by the user,

[1927] A means for transmitting received technical terms to a central processing unit,

[1928] A means by which a central processing unit searches for technical terms in memory and generates an easy-to-understand explanation,

[1929] A means for transmitting the generated explanatory text to the user device,

[1930] A means for the user device to display the generated explanatory text,

[1931] A system that includes this.

[1932] (Claim 2)

[1933] The system according to claim 1, comprising a natural language processing module that analyzes the complex parts of technical terms and replaces them with simpler words.

[1934] (Claim 3)

[1935] The system according to claim 1, further comprising means for collecting relevant information from public sources if the search results are not present in the storage device.

[1936] "Application Example 1"

[1937] (Claim 1)

[1938] A means of receiving technical terms entered by the user,

[1939] A means of sending the received technical terms to the server,

[1940] A server searches a database for technical terms and generates easy-to-understand explanations.

[1941] A means for sending the generated explanatory text to the user's terminal,

[1942] A means for the user terminal to display the generated explanatory text,

[1943] A means for the user to enter technical terms that are difficult to understand into input fields within the application,

[1944] A means of sending technical terms entered using an API as a POST request,

[1945] A method for matching technical terms received by the server against a database, and converting the retrieved definitions into simpler words using Hugging Face's natural language processing model,

[1946] A means of sending the generated description as an HTTP response,

[1947] A system that includes this.

[1948] (Claim 2)

[1949] The system according to claim 1, comprising a natural language processing engine that analyzes the complex parts of technical terms and replaces them with simpler words.

[1950] (Claim 3)

[1951] The system according to claim 1, further comprising means for collecting relevant information from the internet if the search results are not found in the database.

[1952] "Example 2 of combining an emotion engine"

[1953] (Claim 1)

[1954] A means of receiving technical terms entered by the user,

[1955] A means of sending the received technical terms to the server,

[1956] A server searches a database for technical terms and generates easy-to-understand explanations.

[1957] A means for sending the generated explanatory text to the user's terminal,

[1958] A means for the user terminal to display the generated explanatory text,

[1959] A means of recognizing user emotions and generating emotion data,

[1960] A system that includes means for adjusting the content and tone of explanatory text based on sentiment data.

[1961] (Claim 2)

[1962] The system according to claim 1, comprising a natural language processing engine that analyzes the complex parts of technical terms and replaces them with simpler words.

[1963] (Claim 3)

[1964] The system according to claim 1, further comprising means for collecting relevant information from the internet if the search results are not found in the database.

[1965] "Application example 2 when combining with an emotional engine"

[1966] (Claim 1)

[1967] A means of receiving technical terms entered by the user,

[1968] Means for recognizing and analyzing emotions,

[1969] A means of sending received technical terms and emotional data to a server,

[1970] A server searches a database for technical terms and generates easy-to-understand explanations.

[1971] A means of adjusting the generated description text with consideration for the user's emotions,

[1972] A means for sending the generated explanatory text to the user's terminal,

[1973] A means for the user terminal to display the generated explanatory text,

[1974] A system that includes this.

[1975] (Claim 2)

[1976] The system according to claim 1, comprising a natural language processing engine that analyzes difficult parts of technical terms and replaces them with simpler words.

[1977] (Claim 3)

[1978] The system according to claim 1, further comprising means for collecting relevant information from a global network if the search results are not found in the database. [Explanation of symbols]

[1979] 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 technical terms entered by the user, A means of sending the received technical terms to the server, A server searches a database for technical terms and generates easy-to-understand explanations. A means for sending the generated explanatory text to the user's terminal, A means for the user terminal to display the generated explanatory text, A system that includes this.

2. The system according to claim 1, comprising a natural language processing engine that analyzes the difficult parts of technical terms and replaces them with simpler words.

3. The system according to claim 1, further comprising means for collecting relevant information from the internet if the search results are not found in the database.

Images