System

Abstract

A system is provided.SOLUTION: A system, comprising: means for receiving a learning request for a specific form of English from a user; means for converting the request into a predetermined format; means for parsing the request according to the predetermined format; means for extracting relevant data from an English database based on the parsing result; means for generating customized learning materials based on the extracted data; and means for providing the learning materials to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In the past, it has been difficult to effectively learn English, which has different pronunciations and accents in different countries and regions. Furthermore, conventional learning systems have the problem of being unable to quickly and efficiently provide customized learning materials tailored to specific situations and purposes. In particular, when learning English for specific purposes, such as business or travel, preparing appropriate content can be a significant effort. Therefore, an object of the present invention is to provide an environment in which users can efficiently learn the specific form of English they require, and to provide a learning system that can accommodate different pronunciations and accents. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for receiving a specific English language learning request from a user and a means for converting the request into a predetermined format. It also includes a means for analyzing the request according to the predetermined format, a means for extracting relevant data from an English language database based on the analysis results, a means for generating customized learning materials based on the extracted data, and a means for providing the learning materials to the user. This allows users to quickly and efficiently receive customized learning materials tailored to their specific needs. Furthermore, the system can accommodate a wide range of learning needs by receiving requests via an interactive user interface and adjusting text, audio, and video data according to the user's learning style.

[0006] A "user" is an individual who uses the system to learn a particular form of English.

[0007] A "request" is information a user sends to the system asking for a particular learning objective or form of English.

[0008] A "format" is a prescribed form or structure for appropriately representing requests or other data.

[0009] A "server" is a central computer system that receives requests and processes and generates data based on them.

[0010] A "database" is a structured data storage system for centrally managing various data related to English (vocabulary, pronunciation, example sentences, etc.) for use in learning.

[0011] "Parsing" is the process by which the server understands the content of the request it receives and extracts the necessary information.

[0012] "Extraction" is the operation of retrieving necessary data from a database based on specific conditions.

[0013] "Customization" is the process of adapting data and content to a user's specific learning needs and style.

[0014] "Learning Materials" are educational content, such as text, audio, and video, provided to help users learn a particular form of English.

[0015] An "interactive user interface" is a user interface that allows a user to interact with a system to enter requests, receive learnings, provide feedback, etc. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] The present invention provides a system that allows users to efficiently learn a specific form of English. A specific embodiment of this system will be described below.

[0038] System Overview

[0039] The system consists of a user terminal, a server, and a communication network. The terminal is operated by the user and provides an interface for sending specific requests. The server generates relevant learning materials based on the received requests and provides them to the user terminal.

[0040] Program processing flow

[0041] User submits request

[0042] User: Enters their learning interest, such as a request like "I want to learn American English business terms," ​​into the device.

[0043] Request Format by Device

[0044] Terminal: Converts the request received from the user into a predetermined format and prepares it for sending to the server, for example, converting it into JSON format.

[0045] Sending a request from the device to the server

[0046] Terminal: Sends formatted request data to the server via a secure communication protocol (e.g., HTTPS).

[0047] Server parsing of the request

[0048] Server: Analyzes the received request and understands its content (e.g., "American English," "business terms").

[0049] Server-based extraction of relevant data

[0050] Server: Extracts the necessary English data from the internal database based on the request. The data used includes audio guides, vocabulary lists, and sample business conversations.

[0051] Server-based generation of learning materials

[0052] Server: Based on the extracted data, it generates customized learning materials tailored to the user's needs. These materials are provided in the form of text, audio, video, etc.

[0053] Sending learning materials from the server to the device

[0054] Server: Sends the generated learning materials to the device.

[0055] Receiving and analyzing learning materials via terminal

[0056] Terminal: Analyzes the learning materials received from the server and displays them in a user-friendly format. An interactive user interface is used to help users study effectively.

[0057] User learning

[0058] Users: Study specific forms of English using provided learning materials, such as audio files for pronunciation practice and conversation scripts based on specific scenarios.

[0059] Specific examples

[0060] Example 1: Learning business vocabulary

[0061] User: Type "I want to learn American English business vocabulary" into the device.

[0062] Terminal: Converts the request into JSON format and sends it to the server.

[0063] Server: Analyzes the request and extracts relevant business terms from the database.

[0064] Server: Generates dialogue scripts based on business scenarios and audio for pronunciation practice.

[0065] Server: Sends the generated materials to the terminal.

[0066] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[0067] Users: Learn and practice business vocabulary with the learning materials.

[0068] Example 2: Learning Travel English

[0069] User: Type into the device, "I want to learn everyday conversation that I can use while traveling in the UK."

[0070] Terminal: Converts the request into a specific format and sends it to the server.

[0071] Server: Analyzes the request and extracts British English conversation data.

[0072] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[0073] Server: Sends the generated materials to the terminal.

[0074] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[0075] Users: Learn and practice everyday conversations using the materials provided.

[0076] This system allows users to efficiently receive English learning materials customized for specific purposes and situations, enabling learning that accommodates different pronunciations and accents and is expected to be immediately usable in real-life communication situations.

[0077] The processing flow will be explained below.

[0078] Step 1:

[0079] User: Enters a request to learn a particular form of English into an interactive user interface on a device. For example, the user might enter the text "I would like to learn American English business terms."

[0080] Step 2:

[0081] Terminal: Converts the request received from the user into a predetermined format (e.g., JSON). The converted request includes the type of English (American English) and the learning category (business term).

[0082] Step 3:

[0083] Terminal: Sends a formatted request to the server via the HTTPS protocol, along with a destination URL and an authentication token.

[0084] Step 4:

[0085] Server: Analyzes requests received from devices and parses JSON data to understand the request content. Extracts "type of English" and "learning category" from the parsed data.

[0086] Step 5:

[0087] Server: Runs SQL queries against an internal database to extract relevant data based on the request, for example filtering data for "Type of English: American English" and "Study Category: Business Terms."

[0088] Step 6:

[0089] Server: Based on the extracted data, it generates customized learning materials tailored to the user's learning style. Specifically, it generates dialogue scripts based on a business meeting scenario, audio files for pronunciation practice, and related video materials.

[0090] Step 7:

[0091] Server: Sends the generated learning materials to the device. The materials are sent securely via HTTPS in JSON or binary format.

[0092] Step 8:

[0093] Terminal: Analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[0094] Step 9:

[0095] Terminal: Provides learning materials to users through an interactive user interface, including interactive exercises, pronunciation practice, and feedback.

[0096] Step 10:

[0097] User: Study the assigned English form using the provided study materials, which may include pronunciation practice, reading dialogue scripts, and watching related videos.

[0098] Example 1

[0099] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0100] Conventional English learning systems have had difficulty efficiently processing learning requests for specific forms of English and providing users with appropriate learning materials. As a result, they have been unable to provide customized learning support tailored to individual users' needs, resulting in ineffective English learning.

[0101] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0102] In this invention, the server includes means for receiving a specific form of English learning request from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from a database based on the analysis result, means for generating customized learning materials based on the extracted data, means for providing the learning materials to the user, means for transmitting the request from the terminal to the server via a secure communication protocol, and means for transmitting the learning materials from the server to the terminal, thereby enabling efficient provision of customized learning materials tailored to the individual needs of the user.

[0103] "User" refers to a person who uses the system to learn English.

[0104] "Study Request" means a desire or request for a particular form of English that a User wishes to learn through the System.

[0105] "Means" refers to a method or apparatus designed to perform a particular function or operation.

[0106] "Predetermined format" refers to a format in which data is structured according to a particular format or standard.

[0107] "Analyzing" refers to the operation of interpreting received data and extracting necessary information from it.

[0108] A "database" refers to a system for efficiently storing, managing, and retrieving structured information.

[0109] "Related data" refers to information useful for learning that is extracted based on the user's learning request.

[0110] "Study materials" refers to learning materials provided to users to help them learn English, and includes text data, audio data, video data, and the like.

[0111] "Customized" means adapted or modified to meet the needs and requirements of a particular user.

[0112] A "communication protocol" refers to a set of rules and procedures for data communication, and in this case refers to HTTPS.

[0113] "Server" refers to a computer system that receives and analyzes user requests and generates and provides study materials.

[0114] "Terminal" refers to a device operated by a user that provides an interface for sending study requests and receiving study materials.

[0115] The present invention is a system that allows users to efficiently learn a specific form of English, and is composed of a user terminal, a server, and a communication network. A specific embodiment of this system will be described below.

[0116] System Overview

[0117] The user's terminal is operated by the user and provides an interface for sending specific requests. The server is responsible for generating relevant learning materials based on the received requests and providing them to the user's terminal.

[0118] Hardware and software used

[0119] Hardware:

[0120] User's device (e.g., smartphone, tablet, PC)

[0121] Server (a computer server capable of high-performance calculations and data processing)

[0122] software:

[0123] User Interface (Web Browser, Mobile Application)

[0124] Server-side programs (Python, JavaScript, Node.js)

[0125] Database (MySQL, PostgreSQL)

[0126] Communication protocol (HTTPS)

[0127] Process Overview

[0128] 1. User submits a request

[0129] Users input their learning interests into the device, for example, requesting to learn business English or travel English.

[0130] 2. Request Format by Device

[0131] The terminal converts the request received from the user into a specified format (such as JSON format).

[0132] 3. Sending a request from the device to the server

[0133] The device sends the formatted request to the server over HTTPS.

[0134] 4. Server Parsing of the Request

[0135] The server analyzes the received request and understands its contents.

[0136] 5. Server Extraction of Relevant Data

[0137] The server extracts the necessary data from its internal database based on the request.

[0138] 6. Server-based generation of learning materials

[0139] The server generates customized learning materials based on the extracted data.

[0140] 7. Sending learning materials from the server to the device

[0141] The server transmits the generated study materials to the terminal.

[0142] 8. Receiving and analyzing learning materials by device

[0143] The terminal analyzes the learning materials received from the server and displays them in an easy-to-understand manner for the user.

[0144] 9. User Learning

[0145] The user studies using the provided study materials.

[0146] Specific examples

[0147] Example 1: Learning business vocabulary

[0148] User: Type "I want to learn American English business vocabulary" into the device.

[0149] Terminal: Converts the request into JSON format and sends it to the server.

[0150] Server: Analyzes the request and extracts relevant business terms from the database.

[0151] Server: Generates dialogue scripts based on business scenarios and audio for pronunciation practice.

[0152] Server: Sends the generated materials to the terminal.

[0153] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[0154] Users: Learn and practice business vocabulary with the learning materials.

[0155] Example prompt: "Please generate learning materials for American English business terminology."

[0156] Example 2: Learning Travel English

[0157] User: Type into the device, "I want to learn everyday conversation that I can use while traveling in the UK."

[0158] Terminal: Converts the request into a specific format and sends it to the server.

[0159] Server: Analyzes the request and extracts British English conversation data.

[0160] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[0161] Server: Sends the generated materials to the terminal.

[0162] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[0163] Users: Learn and practice everyday conversations using the materials provided.

[0164] This system allows users to efficiently receive English learning materials customized for specific purposes and situations, enabling learning that accommodates different pronunciations and accents, and is expected to be immediately usable in real-life communication situations.

[0165] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0166] Step 1: User submits request

[0167] The user inputs what they want to learn into the device. Specifically, they write the type of English they want to learn and its purpose (for example, "I want to learn American English business terms") in the input field and click the "Submit" button.

[0168] Input: Learning motivation and request details

[0169] Output: Request data entered on the terminal

[0170] Step 2: Formatting the request via the terminal

[0171] The terminal converts the request received from the user into a specific format (e.g., JSON format), which allows the server to accurately interpret the request content.

[0172] Input: The raw request data entered by the user

[0173] Output: Request data in JSON format

[0174] Specific operation: Structures request data using JavaScript or Python and converts it to JSON format.

[0175] Step 3: Sending a request from the device to the server

[0176] The terminal sends the formatted request data to the server via HTTPS, which allows the request data to be transmitted securely to the server.

[0177] Input: Request data in JSON format

[0178] Output: Request data sent to the server

[0179] Specific behavior: Sends a request to the server using the HTTPS protocol.

[0180] Step 4: Server Parses the Request

[0181] The server analyzes the received request data and understands its contents. For example, from a request such as "I want to learn American English business terms," ​​it extracts "Type of English: American English" and "Use: Business terms."

[0182] Input: JSON data sent to the server

[0183] Output: Extracted elements of the request content (type of English, purpose, etc.)

[0184] Specific operation: Parse the JSON data using a program such as Python and extract the necessary information.

[0185] Step 5: Server Extraction of Relevant Data

[0186] The server extracts relevant data from its internal database based on the request content. For example, based on the information "American English" and "business terminology," it retrieves a list of related business terms and audio guides.

[0187] Input: Extracted request content

[0188] Output: Relevant data extracted from the database

[0189] What it does: Retrieves relevant information from a database using SQL queries.

[0190] Step 6: Server generates learning materials

[0191] The server then generates customized learning materials based on the extracted data, which are tailored to the user's needs. These materials consist of text, audio, and video data.

[0192] Input: Extracted relevant data

[0193] Output: Learning materials suitable for the user

[0194] What it does: Consolidates and formats data using text and speech generation engines.

[0195] Step 7: Sending learning materials from the server to the device

[0196] The server packages the generated learning materials in JSON format and sends them back to the terminal via HTTPS.

[0197] Input: Generated learning materials

[0198] Output: Learning materials in JSON format sent to the device

[0199] Specific operation: Sends data to the device using HTTPS.

[0200] Step 8: Receiving and analyzing the learning materials on the device

[0201] The terminal parses the JSON data received from the server and displays the contents in an interactive user interface, allowing users to easily view the materials.

[0202] Input: JSON data sent from the server

[0203] Output: Learning materials displayed in a user interface

[0204] What it does: It parses the data using JavaScript and displays it in the interface using HTML and CSS.

[0205] Step 9: User Training

[0206] Users study using learning materials displayed on their devices, including audio files for pronunciation practice and conversation scripts based on specific scenarios. They can also get feedback on their pronunciation using audio playback and recording functions.

[0207] Input: Study materials

[0208] Output: Learning outcomes (improvement of knowledge and skills)

[0209] Specific actions: Playing audio files, displaying text, and conducting interactive practice sessions.

[0210] In this way, the system can efficiently provide users with English learning materials that are customized to their individual needs.

[0211] (Application example 1)

[0212] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0213] In food delivery, delivery workers often have difficulty communicating smoothly with English-speaking customers, which can lead to lower customer satisfaction and delivery delays, making it a major challenge for businesses.

[0214] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0215] In this invention, the server includes means for receiving a learning request for a specific form of English from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from an English database based on the analysis results, means for generating customized learning materials based on the extracted data, means for including English phrases used in delivery situations in the generated learning materials, means for adding audio guidance to the learning materials using speech synthesis technology, and means for providing the learning materials to the user. This enables delivery personnel to learn English phrases required for specific delivery situations and use them in actual delivery situations.

[0216] The "means for receiving a learning request from a user regarding a specific form of English" is a mechanism including an interface through which a user inputs a request to learn a specific form of English and the system receives the request.

[0217] The "means for converting the request into a predetermined format" refers to a process for converting a request entered by a user into a standardized data format within the system (e.g., JSON).

[0218] The "means for analyzing a request according to a predetermined format" refers to an algorithm or software for analyzing and understanding the request content based on the converted format.

[0219] "Means for extracting relevant data from an English database based on the analysis results" refers to the process of searching and extracting data related to English learning from a database based on the request analysis results.

[0220] "Means for generating customized learning materials based on extracted data" refers to a method for using extracted English data to create specific learning materials (text, audio, video, etc.) tailored to the user's learning goals and situation.

[0221] "Means for including English phrases used in delivery situations in the generated learning materials" refers to the process of incorporating English phrases required in specific delivery situations, such as food delivery, into the learning materials.

[0222] "Means for adding audio guidance to study materials using speech synthesis technology" refers to a method for adding audio guidance corresponding to the generated study materials using speech synthesis technology.

[0223] The "means for providing the learning materials to the user" refers to a mechanism for transmitting the finalized learning materials to the user's device so that the user can use them.

[0224] The system of this invention is designed to enable users to efficiently learn and use English in food delivery situations. The system is primarily composed of terminals, including smartphones, a server, and a communication network.

[0225] Hardware and Software

[0226] Hardware: Smartphone

[0227] software:

[0228] Development environment: Android Studio, Xcode

[0229] Backend: Node.js, Express.js

[0230] Database: MongoDB

[0231] Communication: HTTPS, REST API

[0232] Speech synthesis: Google Text-to-Speech API

[0233] Program processing overview

[0234] User submits request

[0235] Users use their smartphones to submit learning requests for specific English phrases, such as "I want to learn English phrases that can be used in delivery situations," to the application.

[0236] Request format conversion

[0237] The device converts this request into a predetermined format such as JSON and prepares it to be sent to the server.

[0238] Submitting a Request

[0239] The formatted request data is sent securely to the server over HTTPS.

[0240] Server parsing of the request

[0241] The server analyzes the received request and understands its contents, using a natural language processing engine such as the Google Cloud Natural Language API.

[0242] Extracting relevant data

[0243] Based on the analysis results, the server searches and extracts relevant English phrases and learning data from its internal MongoDB database.

[0244] Generating learning materials

[0245] Based on the extracted data, the server generates customized learning materials tailored to the user's needs, including English phrases and audio guides for delivery situations. The audio guides are generated using the Google Text-to-Speech API.

[0246] Providing learning materials

[0247] The generated learning materials are sent to the device in JSON format and provided through a user interface, allowing users to study text, audio, and video data through a smartphone app.

[0248] Specific examples

[0249] Prompt Sentence Examples

[0250] "What phrases should I use when delivering a package to a customer?"

[0251] "English to explain delivery delays"

[0252] This allows users to learn English phrases needed for specific delivery situations and use them in actual delivery situations. This system solves the problem of communicating smoothly with English-speaking customers and contributes to improving customer satisfaction.

[0253] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0254] Step 1:

[0255] A user launches the app on their smartphone and enters a specific learning request, such as "I want to learn English phrases that can be used in delivery situations." This request is received through the user interface.

[0256] Step 2:

[0257] Converts the request received by the terminal into a specified format (e.g. JSON). The input is a text request from the user, and the output is the formatted request data.

[0258] Step 3:

[0259] The terminal sends formatted request data to the server using a secure communication protocol (HTTPS). The input is the formatted request data, and the output is the request sent to the server.

[0260] Step 4:

[0261] The server analyzes the request it receives and understands its content. This analysis is performed using a natural language processing engine such as Google Cloud Natural Language API. The input is formatted request data, and the output obtained from the analysis is an understanding of the content: "English phrases that can be used in delivery situations."

[0262] Step 5:

[0263] The server searches and extracts related English phrase data from an internal MongoDB database based on the analysis results. The input is the analysis results, and the output is related English phrase data.

[0264] Step 6:

[0265] The server generates customized learning materials based on the extracted data, tailored to the user's needs. These materials include English phrases used in delivery situations and audio guides. The audio guides are generated using the Google Text-to-Speech API. The input is the extracted English phrase data and analysis results, and the output is customized learning materials.

[0266] Step 7:

[0267] The server sends the generated learning materials to the terminal. The input is the generated learning materials, and the output is the transmission of the materials to the terminal.

[0268] Step 8:

[0269] The terminal displays the received learning materials to the user. Through an interactive user interface, the user can view and study text, audio guides, and video data. The input is the received learning materials, and the output is the learning content provided to the user.

[0270] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0271] The present invention provides a system that allows users to efficiently learn a specific form of English, combined with an emotional engine that dynamically adjusts the learning content according to the user's emotional state.

[0272] System Overview

[0273] The system consists of a user's device, a server, and a communication network. The device is operated by the user and provides an interface for sending specific requests. The server generates relevant learning materials based on the received requests and provides them to the user's device. Furthermore, the system incorporates an emotion engine that recognizes the user's emotional state and dynamically adjusts the learning materials accordingly.

[0274] Program processing flow

[0275] User submits request

[0276] User: Inputs a request for learning, such as "I want to learn American English business terms," ​​into the terminal via the terminal's interactive user interface.

[0277] Request Format by Device

[0278] Terminal: Converts the request received from the user into a predetermined format (e.g., JSON). The converted request includes the type of English (American English) and the learning category (business term).

[0279] Sending a request from the device to the server

[0280] Terminal: Sends a formatted request to the server via the HTTPS protocol, along with a destination URL and an authentication token.

[0281] Server parsing of the request

[0282] Server: Analyzes requests received from devices and understands their content (e.g., "American English," "business terms").

[0283] Server-based extraction of relevant data

[0284] Server: Runs SQL queries against an internal database to extract relevant data based on the request, for example filtering data for "Type of English: American English" and "Study Category: Business Terms."

[0285] Emotion recognition by emotion engine

[0286] Emotion engine: Determines the user's emotional state by analyzing facial expressions, voice tone, and language patterns. Data is collected from sensors such as the device's camera and microphone.

[0287] Server-based generation of learning materials

[0288] Server: Based on the extracted data and the analysis results of the emotion engine, the server generates customized learning materials according to the user's emotional state. Specifically, it adjusts the learning content and approach depending on whether the user is relaxed or stressed.

[0289] Sending learning materials from the server to the device

[0290] Server: Sends the generated learning materials to the device. The materials are sent securely via HTTPS in JSON or binary format.

[0291] Receiving and analyzing learning materials via terminal

[0292] Terminal: Analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[0293] Providing data to users via terminals

[0294] Terminal: Provides learning materials to users through an interactive user interface, including interactive exercises, pronunciation practice, and feedback.

[0295] User learning

[0296] Users: Study a given form of English using the provided study materials, which may include audio files for pronunciation practice and conversation scripts based on specific scenarios.

[0297] Specific examples

[0298] Example 1: Learning business vocabulary

[0299] User: Type "I want to learn American English business vocabulary" into the device.

[0300] Terminal: Converts the request into JSON format and sends it to the server.

[0301] Server: Analyzes the request and extracts relevant business terms from the database.

[0302] Emotion engine: Recognizes the user's emotional state and determines the appropriate learning approach.

[0303] Server: Generates dialogue scripts and pronunciation practice audio based on business scenarios, and adopts an approach that is tailored to the user's emotional state.

[0304] Server: Sends the generated materials to the terminal.

[0305] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[0306] Users: Learn and practice business vocabulary with the learning materials.

[0307] Example 2: Learning Travel English

[0308] User: Type into the device, "I want to learn everyday conversation that I can use while traveling in the UK."

[0309] Terminal: Converts the request into a specific format and sends it to the server.

[0310] Server: Analyzes the request and extracts British English conversation data.

[0311] Emotion engine: Recognizes the user's emotional state and provides relaxing content as needed.

[0312] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[0313] Server: Sends the generated materials to the terminal.

[0314] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[0315] Users: Learn and practice everyday conversations using the materials provided.

[0316] This system allows users to efficiently receive English learning materials customized to their specific goals and situations. Furthermore, the system's emotional engine reflects the user's emotional state in real time and provides optimal learning approaches, enabling an effective and flexible learning experience.

[0317] The processing flow will be explained below.

[0318] Step 1:

[0319] User: Enters a request to learn a particular form of English into an interactive user interface on a device. For example, the user might enter the text "I would like to learn American English business terms."

[0320] Step 2:

[0321] Terminal: Converts the request received from the user into a predetermined format (e.g., JSON). The converted request includes the type of English (American English) and the learning category (business term).

[0322] Step 3:

[0323] Terminal: Sends a formatted request to the server via the HTTPS protocol, along with a destination URL and an authentication token.

[0324] Step 4:

[0325] Server: Analyzes requests received from devices and parses JSON data to understand their contents. Extracts "type of English" and "learning category" from the parsed data.

[0326] Step 5:

[0327] Server: Runs SQL queries against an internal database to extract relevant data based on the request, for example filtering data for "Type of English: American English" and "Study Category: Business Terms."

[0328] Step 6:

[0329] Emotion engine: Recognizes the user's emotional state. It determines the user's emotional state by analyzing their facial expressions, voice tone, and language patterns. Data is collected from sensors such as the device's camera and microphone.

[0330] Step 7:

[0331] Server: Based on the extracted data and the analysis results of the emotion engine, it generates customized learning materials according to the user's emotional state. For example, if the user is relaxed, it provides regular learning materials, but if the user is stressed, it adds relaxing content or encouraging messages.

[0332] Step 8:

[0333] Server: Sends the generated learning materials to the device. The materials are sent securely via HTTPS in JSON or binary format.

[0334] Step 9:

[0335] Terminal: Analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[0336] Step 10:

[0337] Terminal: Provides learning materials to users through an interactive user interface, including interactive exercises, pronunciation practice, and feedback.

[0338] Step 11:

[0339] Users: Study a given form of English using the provided study materials, which may include audio files for pronunciation practice and conversation scripts based on specific scenarios.

[0340] Example 2

[0341] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0342] Conventional English learning systems provide uniform learning materials without considering the user's emotional state, making it difficult to provide an effective learning experience. Furthermore, they often lack the flexibility to respond to specific user needs, resulting in reduced learning efficiency.

[0343] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0344] In this invention, the server includes means for receiving a specific English learning request from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from an English database based on the analysis results, means for generating customized learning materials based on the extracted data, an emotion engine for recognizing the user's emotional state and dynamically adjusting the learning materials according to that state, and means for providing the learning materials to the user. This enables effective and flexible English learning by reflecting the user's emotional state in real time and providing an optimal learning approach.

[0345] "User" refers to a person or group of people who intend to use the System to learn a particular form of English.

[0346] A "request" refers to input data that indicates a user's request or desire regarding learning content to the system.

[0347] "Predetermined format" refers to the standardized data format required to parse and process a request.

[0348] "Analysis" refers to the process of interpreting the contents of a received request and performing the necessary processing within the system based on that information.

[0349] An "English database" refers to a collection of data that stores various data related to English (word lists, example sentences, conversation scripts, etc.).

[0350] "Related data" refers to data that is extracted from the English database based on the analysis results and is suitable for the user's learning objectives.

[0351] "Customization" refers to the process of individually tailoring learning materials to a user's specific needs and circumstances.

[0352] "Study materials" refers to various materials such as text data, audio data, and video data provided by the system for users to study English.

[0353] "Emotional state" refers to the emotions and psychological state (relaxed, stressed, etc.) that a user feels while using the system.

[0354] "Emotion engine" refers to a module within the system that recognizes the user's emotional state and dynamically adjusts learning materials accordingly.

[0355] "Dynamic adjustment" refers to the process of adaptively changing learning materials and methods in real time.

[0356] This invention provides a system that allows users to efficiently learn a specific form of English, and further combines it with an emotional engine that dynamically adjusts the learning content according to the user's emotional state. This system consists of a user terminal, a server, and a communication network. The specific configuration and operation procedure are described below.

[0357] System Overview

[0358] Hardware and Software

[0359] 1. User Device

[0360] Hardware: Personal computers, tablets, smartphones, etc.

[0361] Software: Web browser, dedicated application.

[0362] 2. Server

[0363] Hardware: High-performance cloud or on-premise servers.

[0364] Software: Web server software, database management systems (e.g., MySQL, PostgreSQL), emotion recognition engines (e.g., Microsoft Azure Emotion API, IBM Watson).

[0365] 3. Communication Network

[0366] Internet connection (e.g. Wi-Fi, 4G / 5G network)

[0367] Program processing flow

[0368] User operations

[0369] The user utilizes the device's interactive user interface to input a specific learning request, for example, "I want to learn American English business terms," ​​either by text or voice.

[0370] Terminal handling

[0371] The device receives requests entered by the user and converts them into a specific format (e.g., JSON format). The converted request includes the type of English (e.g., American English) and the learning category (e.g., business terminology).

[0372] The device sends a request to the server via the HTTPS protocol, along with the destination URL and an authentication token.

[0373] Server Processing

[0374] The server parses the request received from the device and understands its contents, which includes deserializing the JSON data.

[0375] The server runs SQL queries against an internal database to extract relevant data based on the request, such as word lists and example sentences for "American English" and "business terms."

[0376] The emotion engine determines a user's emotional state by analyzing facial expression data, voice tone, and language patterns, data collected from sensors such as the device's camera and microphone.

[0377] The server uses the extracted data and the analysis results of the emotion engine to generate customized learning materials according to the user's emotional state: for example, if the user is relaxed, it provides review materials on basic concepts, and if the user is stressed, it provides interactive exercises.

[0378] The server sends the generated learning materials to the device in JSON or binary format, securely transmitted via the HTTPS protocol.

[0379] Terminal handling

[0380] The device analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[0381] The device uses an interactive user interface to provide learning materials to the user, including interactive exercises, pronunciation practice, and feedback features.

[0382] Specific examples

[0383] Example 1: Learning business vocabulary

[0384] User: Type "I want to learn American English business vocabulary" into the terminal.

[0385] Terminal: Converts the request into JSON format and sends it to the server.

[0386] Server: Analyzes the request and extracts relevant business terms from the database.

[0387] Emotion engine: Recognizes the user's emotional state and determines the appropriate learning approach.

[0388] Server: Generates dialogue scripts and pronunciation practice audio based on business scenarios, and adopts an approach that is tailored to the user's emotional state.

[0389] Server: Sends the generated materials to the terminal.

[0390] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[0391] Users: Learn and practice business vocabulary with the learning materials.

[0392] Example 2: Learning Travel English

[0393] User: Type "I want to learn everyday conversations I can use while traveling in the UK" into the device.

[0394] Terminal: Converts the request into a specific format and sends it to the server.

[0395] Server: Analyzes the request and extracts British English conversation data.

[0396] Emotion engine: Recognizes the user's emotional state and provides relaxing content as needed.

[0397] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[0398] Server: Sends the generated materials to the terminal.

[0399] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[0400] Users: Learn and practice everyday conversations using the materials provided.

[0401] In this way, users can efficiently receive learning materials customized to their specific goals and situations. Furthermore, the emotional engine reflects the user's emotional state in real time and provides the optimal learning approach, enabling effective and flexible English learning.

[0402] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0403] Step 1:

[0404] The user inputs a learning request into the device, such as "I want to learn American English business terms." Text and voice input are possible through the user interface.

[0405] Input data: User learning request (e.g., American English business terms)

[0406] Output data: Request data containing the user's intent

[0407] Step 2:

[0408] The device converts the request received from the user into JSON format, which includes the type of English and the learning category.

[0409] Input data: Request data (text format)

[0410] Data processing: Converting request data to JSON format

[0411] Output data: Request data in JSON format

[0412] Step 3:

[0413] The terminal sends formatted request data to the server using the HTTPS protocol, which includes the destination URL and the authentication token.

[0414] Input data: JSON format request data, destination URL, authentication token

[0415] Data calculation: Secure data transmission (HTTPS protocol)

[0416] Output data: Sending request data to the server

[0417] Step 4:

[0418] The server analyzes the request data received from the terminal, understands its contents, deserializes the request, and checks for errors in the contents.

[0419] Input data: Request data in JSON format

[0420] Data processing: Deserializing and error checking the request data

[0421] Output data: Analysis results (type of English, learning category)

[0422] Step 5:

[0423] Based on the analysis results, the server runs SQL queries against an internal database to extract relevant English data.

[0424] Input data: Analysis results (type of English, learning category)

[0425] Data operations: executing SQL queries and database searches

[0426] Output data: Related English data (e.g., a list of business terms)

[0427] Step 6:

[0428] The emotion engine analyzes data collected from the device's camera and microphone to determine the user's emotional state.

[0429] Input data: User's facial expression data, voice tone, language patterns

[0430] Data Computation: Analysis with Emotion Recognition Algorithms

[0431] Output data: Emotional state (relaxed, stressed, etc.)

[0432] Step 7:

[0433] The server generates customized learning materials based on the extracted English data and the analysis results of the emotion engine, specifically incorporating the optimal learning approach according to the user's emotional state.

[0434] Input data: related English data, emotional state

[0435] Data calculation: Generation of learning materials (e.g., dialogue scripts, pronunciation practice audio)

[0436] Output data: customized learning materials

[0437] Step 8:

[0438] The server sends the generated learning materials to the device in JSON or binary format.

[0439] Input data: customized learning materials

[0440] Data processing: Format conversion and secure transmission of learning materials (HTTPS protocol)

[0441] Output data: Sending learning materials to the device

[0442] Step 9:

[0443] The device analyzes the learning materials received from the server and converts them into a format that can be provided to the user, including text display, audio playback, and video playback.

[0444] Input data: training materials (JSON or binary format)

[0445] Data processing: Analysis and format conversion of learning materials

[0446] Output data: learning materials provided to the user

[0447] Step 10:

[0448] The device provides learning materials to the user using an interactive user interface, including interactive exercises, pronunciation practice, and feedback features.

[0449] Input data: learning materials provided

[0450] Specific operations: text display, audio playback, video playback, recording function

[0451] Output data: User's interactive learning experience

[0452] Step 11:

[0453] Users use the provided learning materials to study designated English forms, practice pronunciation, and practice conversation scenarios.

[0454] Input data: learning materials

[0455] Specific actions: pronunciation practice (playing and recording audio files), scenario-based conversation practice

[0456] Output data: learning progress and outcomes

[0457] (Application example 2)

[0458] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0459] Conventional English learning systems provide uniform learning materials without considering the user's emotional state, which often reduces the user's concentration and motivation to learn. Furthermore, if the learning content does not match the user's emotional state, the learning effect is insufficient. Therefore, a flexible system that allows users to learn English effectively is needed.

[0460] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0461] In this invention, the server includes means for receiving a specific form of English learning request from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from an English database based on the analysis results, means for generating customized learning materials based on the extracted data, means for recognizing the user's emotional state and dynamically adjusting the learning materials according to the state, and means for providing the learning materials to the user. This makes it possible to provide optimal learning content according to the user's emotional state and maximize learning effectiveness.

[0462] "Means for receiving learning requests from users about a particular form of English" refers to an interface and communication device that allows a user to input and send learning requests about a particular form of English (e.g., American English business vocabulary, British English everyday conversation, etc.) to the system.

[0463] "Means for converting the request into a predetermined format" refers to a process or algorithm that converts a learning request received from a user into a specified data format (e.g., JSON).

[0464] The "means for parsing a request according to a predetermined format" refers to a program and logic for parsing formatted request data and extracting and understanding the content of the request.

[0465] The "means for extracting relevant data from an English database based on the analysis results" refers to algorithms and query execution means for searching and retrieving English data (e.g., specific words or phrases) from a database that corresponds to the analysis results of the request.

[0466] The "means for generating customized learning materials based on extracted data" refers to a program and system that creates learning materials tailored to the user based on the extracted relevant data.

[0467] "Means for recognizing the user's emotional state and dynamically adjusting learning materials according to that state" refers to an engine and algorithm that uses sensors such as cameras and microphones to analyze the user's emotional state (relaxation, stress, concentration, etc.) in real time and adjusts the learning content appropriately based on the results.

[0468] The "means for providing the learning materials to the user" refers to communication and display means for delivering the created customized learning materials to the user's terminal and enabling display and playback.

[0469] This invention is a system that allows users to efficiently learn a specific form of English, and further combines it with an emotional engine that dynamically adjusts the learning content according to the user's emotional state. The system consists of a user terminal, a server, and a communication network.

[0470] System configuration

[0471] 1. User's device

[0472] The user device can be a smartphone, VR headset, tablet, etc., and through the user interface, they can input learning requests, collect emotional data, and display learning materials. In particular, when using a VR headset, interactive English learning in a VR shop format is possible.

[0473] 2. Server

[0474] The server has the following features:

[0475] Request reception and format conversion: Receives an English learning request from the user and converts it into a specified format (e.g., JSON format).

[0476] Request analysis and data extraction: Analyze the request content and extract relevant data from the English database.

[0477] Generation of customized learning materials: Customized learning materials are generated based on the extracted data and the analysis results of the emotion engine.

[0478] Provision of learning materials: The generated learning materials are sent to the user's terminal for display and playback.

[0479] 3. Emotion Engine

[0480] The emotion engine analyzes the user's emotional state (relaxed, stressed, focused, etc.) through sensors such as cameras and microphones. This analysis data is used to dynamically adjust learning materials.

[0481] Hardware and software used

[0482] Hardware: smartphone, VR headset, camera, microphone

[0483] Software: Flask (a Python web framework), Emotion API (an emotion recognition library), database management system (e.g., MySQL or SQLite)

[0484] A concrete example of the processing flow

[0485] Example 1: Learning business vocabulary

[0486] The user uses the user interface of the terminal to input a request such as "I would like to learn American English business terms."

[0487] The terminal converts this request into JSON format and sends it to the server.

[0488] The server parses the request and extracts relevant business terms from a database.

[0489] The emotion engine recognizes the user's emotional state as "relaxed" and generates learning materials with a calm tone.

[0490] The server sends the generated learning materials to the user's terminal, and the user learns in an interactive format in a VR environment.

[0491] Example 2: Learning Travel English

[0492] The user uses the user interface of the terminal to input a request such as "I would like to learn everyday conversation that can be used while traveling in England."

[0493] The terminal converts this request into a predetermined format and sends it to the server.

[0494] The server analyzes the request content and extracts everyday conversation data from a database.

[0495] The emotion engine recognizes the user's emotional state as "stress" and generates support-oriented learning materials.

[0496] The server sends the generated learning materials to the user's terminal, and the user studies in a VR environment.

[0497] Prompt Sentence Examples

[0498] A user has submitted a request to learn "Business English." Their current emotional state is perceived as "Relaxed." Use this information to generate Business English learning materials presented in a calm tone.

[0499] This system allows users to efficiently receive English learning materials customized to their specific goals and situations. Furthermore, the system's emotional engine reflects the user's emotional state in real time and provides the optimal learning approach, resulting in an effective and flexible learning experience.

[0500] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0501] Step 1:

[0502] The user uses the device's user interface to input a request for English learning. The device receives the input request and converts it into a specified format (e.g., JSON format). Specifically, the user might input something like "I want to learn American English business terms," ​​and format it as JSON data. The input is the user's learning request, and the output is formatted JSON data.

[0503] Step 2:

[0504] The terminal sends a formatted request to the server via the HTTPS protocol. The sent data also includes the destination URL and an authentication token. In this step, the input is JSON data generated on the terminal, and the output is the data sent to the server as an HTTPS request.

[0505] Step 3:

[0506] The server analyzes the request data received from the device. The analysis includes reading the type of English and learning category (e.g., "American English," "Business Terms," ​​etc.) contained in the request. The input is the JSON data received by the server, and the output is the type of English and learning category as the analysis results.

[0507] Step 4:

[0508] The server queries the internal database based on the analysis results and extracts relevant data. Specifically, it filters data that matches "English type: American English" and "Learning category: Business terms." The input is the analysis results, and the output is the filtered relevant data.

[0509] Step 5:

[0510] The server sends data collected from the camera and microphone to the emotion engine to recognize the user's emotional state. The emotion engine performs facial expression and voice analysis to determine whether the user is relaxed or stressed. The input is sensor data from the camera and microphone, and the output is the analyzed emotional state.

[0511] Step 6:

[0512] The server generates learning materials according to the user's emotional state based on the extracted data and the analysis results of the emotion engine. For example, if the user is relaxed, it generates learning materials with a calm tone, and if the user is stressed, it generates materials with a supportive tone. The input is the filtered data and the user's emotional state, and the output is customized learning materials.

[0513] Step 7:

[0514] The server sends the generated learning materials to the terminal. The materials are sent securely via the HTTPS protocol in JSON or binary format. The input is the generated learning materials, and the output is the data sent to the terminal.

[0515] Step 8:

[0516] The terminal analyzes the learning materials received from the server and converts them into a format that can be provided to the user, such as text display, audio playback, and video playback. The input is the material received from the server, and the output is the learning materials in the interface provided to the user.

[0517] Step 9:

[0518] Users study English using the learning materials displayed on the device. Through user operation, they efficiently learn the target English form through interactive dialogue-style exercises, pronunciation practice, and feedback functions. The input is the learning materials provided by the device, and the output is the user's learning progress.

[0519] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0520] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0521] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0522] [Second embodiment]

[0523] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0524] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0525] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0526] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0527] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0528] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0529] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0530] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0531] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0532] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0533] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0534] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0535] The present invention provides a system that allows users to efficiently learn a specific form of English. A specific embodiment of this system will be described below.

[0536] System Overview

[0537] The system consists of a user terminal, a server, and a communication network. The terminal is operated by the user and provides an interface for sending specific requests. The server generates relevant learning materials based on the received requests and provides them to the user terminal.

[0538] Program processing flow

[0539] User submits request

[0540] User: Enters their learning interest, such as a request like "I want to learn American English business terms," ​​into the device.

[0541] Request Format by Device

[0542] Terminal: Converts the request received from the user into a predetermined format and prepares it for sending to the server, for example, converting it into JSON format.

[0543] Sending a request from the device to the server

[0544] Terminal: Sends formatted request data to the server via a secure communication protocol (e.g., HTTPS).

[0545] Server parsing of the request

[0546] Server: Analyzes the received request and understands its content (e.g., "American English," "business terms").

[0547] Server-based extraction of relevant data

[0548] Server: Extracts the necessary English data from the internal database based on the request. The data used includes audio guides, vocabulary lists, and sample business conversations.

[0549] Server-based generation of learning materials

[0550] Server: Based on the extracted data, it generates customized learning materials tailored to the user's needs. These materials are provided in the form of text, audio, video, etc.

[0551] Sending learning materials from the server to the device

[0552] Server: Sends the generated learning materials to the device.

[0553] Receiving and analyzing learning materials via terminal

[0554] Terminal: Analyzes the learning materials received from the server and displays them in a user-friendly format. An interactive user interface is used to help users study effectively.

[0555] User learning

[0556] Users: Study specific forms of English using provided learning materials, such as audio files for pronunciation practice and conversation scripts based on specific scenarios.

[0557] Specific examples

[0558] Example 1: Learning business vocabulary

[0559] User: Type "I want to learn American English business vocabulary" into the device.

[0560] Terminal: Converts the request into JSON format and sends it to the server.

[0561] Server: Analyzes the request and extracts relevant business terms from the database.

[0562] Server: Generates dialogue scripts based on business scenarios and audio for pronunciation practice.

[0563] Server: Sends the generated materials to the terminal.

[0564] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[0565] Users: Learn and practice business vocabulary with the learning materials.

[0566] Example 2: Learning Travel English

[0567] User: Type into the device, "I want to learn everyday conversation that I can use while traveling in the UK."

[0568] Terminal: Converts the request into a specific format and sends it to the server.

[0569] Server: Analyzes the request and extracts British English conversation data.

[0570] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[0571] Server: Sends the generated materials to the terminal.

[0572] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[0573] Users: Learn and practice everyday conversations using the materials provided.

[0574] This system allows users to efficiently receive English learning materials customized for specific purposes and situations, enabling learning that accommodates different pronunciations and accents and is expected to be immediately usable in real-life communication situations.

[0575] The processing flow will be explained below.

[0576] Step 1:

[0577] User: Enters a request to learn a particular form of English into an interactive user interface on a device. For example, the user might enter the text "I would like to learn American English business terms."

[0578] Step 2:

[0579] Terminal: Converts the request received from the user into a predetermined format (e.g., JSON). The converted request includes the type of English (American English) and the learning category (business term).

[0580] Step 3:

[0581] Terminal: Sends a formatted request to the server via the HTTPS protocol, along with a destination URL and an authentication token.

[0582] Step 4:

[0583] Server: Analyzes requests received from devices and parses JSON data to understand the request content. Extracts "type of English" and "learning category" from the parsed data.

[0584] Step 5:

[0585] Server: Runs SQL queries against an internal database to extract relevant data based on the request, for example filtering data for "Type of English: American English" and "Study Category: Business Terms."

[0586] Step 6:

[0587] Server: Based on the extracted data, it generates customized learning materials tailored to the user's learning style. Specifically, it generates dialogue scripts based on a business meeting scenario, audio files for pronunciation practice, and related video materials.

[0588] Step 7:

[0589] Server: Sends the generated learning materials to the device. The materials are sent securely via HTTPS in JSON or binary format.

[0590] Step 8:

[0591] Terminal: Analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[0592] Step 9:

[0593] Terminal: Provides learning materials to users through an interactive user interface, including interactive exercises, pronunciation practice, and feedback.

[0594] Step 10:

[0595] User: Study the assigned English form using the provided study materials, which may include pronunciation practice, reading dialogue scripts, and watching related videos.

[0596] Example 1

[0597] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0598] Conventional English learning systems have had difficulty efficiently processing learning requests for specific forms of English and providing users with appropriate learning materials. As a result, they have been unable to provide customized learning support tailored to individual users' needs, resulting in ineffective English learning.

[0599] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0600] In this invention, the server includes means for receiving a specific form of English learning request from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from a database based on the analysis result, means for generating customized learning materials based on the extracted data, means for providing the learning materials to the user, means for transmitting the request from the terminal to the server via a secure communication protocol, and means for transmitting the learning materials from the server to the terminal, thereby enabling efficient provision of customized learning materials tailored to the individual needs of the user.

[0601] "User" refers to a person who uses the system to learn English.

[0602] "Study Request" means a desire or request for a particular form of English that a User wishes to learn through the System.

[0603] "Means" refers to a method or apparatus designed to perform a particular function or operation.

[0604] "Predetermined format" refers to a format in which data is structured according to a particular format or standard.

[0605] "Analyzing" refers to the operation of interpreting received data and extracting necessary information from it.

[0606] A "database" refers to a system for efficiently storing, managing, and retrieving structured information.

[0607] "Related data" refers to information useful for learning that is extracted based on the user's learning request.

[0608] "Study materials" refers to learning materials provided to users to help them learn English, and includes text data, audio data, video data, and the like.

[0609] "Customized" means adapted or modified to meet the needs and requirements of a particular user.

[0610] A "communication protocol" refers to a set of rules and procedures for data communication, and in this case refers to HTTPS.

[0611] "Server" refers to a computer system that receives and analyzes user requests and generates and provides study materials.

[0612] "Terminal" refers to a device operated by a user that provides an interface for sending study requests and receiving study materials.

[0613] The present invention is a system that allows users to efficiently learn a specific form of English, and is composed of a user terminal, a server, and a communication network. A specific embodiment of this system will be described below.

[0614] System Overview

[0615] The user's terminal is operated by the user and provides an interface for sending specific requests. The server is responsible for generating relevant learning materials based on the received requests and providing them to the user's terminal.

[0616] Hardware and software used

[0617] Hardware:

[0618] User's device (e.g., smartphone, tablet, PC)

[0619] Server (a computer server capable of high-performance calculations and data processing)

[0620] software:

[0621] User Interface (Web Browser, Mobile Application)

[0622] Server-side programs (Python, JavaScript, Node.js)

[0623] Database (MySQL, PostgreSQL)

[0624] Communication protocol (HTTPS)

[0625] Process Overview

[0626] 1. User submits a request

[0627] Users input their learning interests into the device, for example, requesting to learn business English or travel English.

[0628] 2. Request Format by Device

[0629] The terminal converts the request received from the user into a specified format (such as JSON format).

[0630] 3. Sending a request from the device to the server

[0631] The device sends the formatted request to the server over HTTPS.

[0632] 4. Server Parsing of the Request

[0633] The server analyzes the received request and understands its contents.

[0634] 5. Server Extraction of Relevant Data

[0635] The server extracts the necessary data from its internal database based on the request.

[0636] 6. Server-based generation of learning materials

[0637] The server generates customized learning materials based on the extracted data.

[0638] 7. Sending learning materials from the server to the device

[0639] The server transmits the generated study materials to the terminal.

[0640] 8. Receiving and analyzing learning materials by device

[0641] The terminal analyzes the learning materials received from the server and displays them in an easy-to-understand manner for the user.

[0642] 9. User Learning

[0643] The user studies using the provided study materials.

[0644] Specific examples

[0645] Example 1: Learning business vocabulary

[0646] User: Type "I want to learn American English business vocabulary" into the device.

[0647] Terminal: Converts the request into JSON format and sends it to the server.

[0648] Server: Analyzes the request and extracts relevant business terms from the database.

[0649] Server: Generates dialogue scripts based on business scenarios and audio for pronunciation practice.

[0650] Server: Sends the generated materials to the terminal.

[0651] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[0652] Users: Learn and practice business vocabulary with the learning materials.

[0653] Example prompt: "Please generate learning materials for American English business terminology."

[0654] Example 2: Learning Travel English

[0655] User: Type into the device, "I want to learn everyday conversation that I can use while traveling in the UK."

[0656] Terminal: Converts the request into a specific format and sends it to the server.

[0657] Server: Analyzes the request and extracts British English conversation data.

[0658] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[0659] Server: Sends the generated materials to the terminal.

[0660] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[0661] Users: Learn and practice everyday conversations using the materials provided.

[0662] This system allows users to efficiently receive English learning materials customized for specific purposes and situations, enabling learning that accommodates different pronunciations and accents, and is expected to be immediately usable in real-life communication situations.

[0663] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0664] Step 1: User submits request

[0665] The user inputs what they want to learn into the device. Specifically, they write the type of English they want to learn and its purpose (for example, "I want to learn American English business terms") in the input field and click the "Submit" button.

[0666] Input: Learning motivation and request details

[0667] Output: Request data entered on the terminal

[0668] Step 2: Formatting the request via the terminal

[0669] The terminal converts the request received from the user into a specific format (e.g., JSON format), which allows the server to accurately interpret the request content.

[0670] Input: The raw request data entered by the user

[0671] Output: Request data in JSON format

[0672] Specific operation: Structures request data using JavaScript or Python and converts it to JSON format.

[0673] Step 3: Sending a request from the device to the server

[0674] The terminal sends the formatted request data to the server via HTTPS, which allows the request data to be transmitted securely to the server.

[0675] Input: Request data in JSON format

[0676] Output: Request data sent to the server

[0677] Specific behavior: Sends a request to the server using the HTTPS protocol.

[0678] Step 4: Server Parses the Request

[0679] The server analyzes the received request data and understands its contents. For example, from a request such as "I want to learn American English business terms," ​​it extracts "Type of English: American English" and "Use: Business terms."

[0680] Input: JSON data sent to the server

[0681] Output: Extracted elements of the request content (type of English, purpose, etc.)

[0682] Specific operation: Parse the JSON data using a program such as Python and extract the necessary information.

[0683] Step 5: Server Extraction of Relevant Data

[0684] The server extracts relevant data from its internal database based on the request content. For example, based on the information "American English" and "business terminology," it retrieves a list of related business terms and audio guides.

[0685] Input: Extracted request content

[0686] Output: Relevant data extracted from the database

[0687] What it does: Retrieves relevant information from a database using SQL queries.

[0688] Step 6: Server generates learning materials

[0689] The server then generates customized learning materials based on the extracted data, which are tailored to the user's needs. These materials consist of text, audio, and video data.

[0690] Input: Extracted relevant data

[0691] Output: Learning materials suitable for the user

[0692] What it does: Consolidates and formats data using text and speech generation engines.

[0693] Step 7: Sending learning materials from the server to the device

[0694] The server packages the generated learning materials in JSON format and sends them back to the terminal via HTTPS.

[0695] Input: Generated learning materials

[0696] Output: Learning materials in JSON format sent to the device

[0697] Specific operation: Sends data to the device using HTTPS.

[0698] Step 8: Receiving and analyzing the learning materials on the device

[0699] The terminal parses the JSON data received from the server and displays the contents in an interactive user interface, allowing users to easily view the materials.

[0700] Input: JSON data sent from the server

[0701] Output: Learning materials displayed in a user interface

[0702] What it does: It parses the data using JavaScript and displays it in the interface using HTML and CSS.

[0703] Step 9: User Training

[0704] Users study using learning materials displayed on their devices, including audio files for pronunciation practice and conversation scripts based on specific scenarios. They can also get feedback on their pronunciation using audio playback and recording functions.

[0705] Input: Study materials

[0706] Output: Learning outcomes (improvement of knowledge and skills)

[0707] Specific actions: Playing audio files, displaying text, and conducting interactive practice sessions.

[0708] In this way, the system can efficiently provide users with English learning materials that are customized to their individual needs.

[0709] (Application example 1)

[0710] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0711] In food delivery, delivery workers often have difficulty communicating smoothly with English-speaking customers, which can lead to lower customer satisfaction and delivery delays, making it a major challenge for businesses.

[0712] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0713] In this invention, the server includes means for receiving a learning request for a specific form of English from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from an English database based on the analysis results, means for generating customized learning materials based on the extracted data, means for including English phrases used in delivery situations in the generated learning materials, means for adding audio guidance to the learning materials using speech synthesis technology, and means for providing the learning materials to the user. This enables delivery personnel to learn English phrases required for specific delivery situations and use them in actual delivery situations.

[0714] The "means for receiving a learning request from a user regarding a specific form of English" is a mechanism including an interface through which a user inputs a request to learn a specific form of English and the system receives the request.

[0715] The "means for converting the request into a predetermined format" refers to a process for converting a request entered by a user into a standardized data format within the system (e.g., JSON).

[0716] The "means for analyzing a request according to a predetermined format" refers to an algorithm or software for analyzing and understanding the request content based on the converted format.

[0717] "Means for extracting relevant data from an English database based on the analysis results" refers to the process of searching and extracting data related to English learning from a database based on the request analysis results.

[0718] "Means for generating customized learning materials based on extracted data" refers to a method for using extracted English data to create specific learning materials (text, audio, video, etc.) tailored to the user's learning goals and situation.

[0719] "Means for including English phrases used in delivery situations in the generated learning materials" refers to the process of incorporating English phrases required in specific delivery situations, such as food delivery, into the learning materials.

[0720] "Means for adding audio guidance to study materials using speech synthesis technology" refers to a method for adding audio guidance corresponding to the generated study materials using speech synthesis technology.

[0721] The "means for providing the learning materials to the user" refers to a mechanism for transmitting the finalized learning materials to the user's device so that the user can use them.

[0722] The system of this invention is designed to enable users to efficiently learn and use English in food delivery situations. The system is primarily composed of terminals, including smartphones, a server, and a communication network.

[0723] Hardware and Software

[0724] Hardware: Smartphone

[0725] software:

[0726] Development environment: Android Studio, Xcode

[0727] Backend: Node.js, Express.js

[0728] Database: MongoDB

[0729] Communication: HTTPS, REST API

[0730] Speech synthesis: Google Text-to-Speech API

[0731] Program processing overview

[0732] User submits request

[0733] Users use their smartphones to submit learning requests for specific English phrases, such as "I want to learn English phrases that can be used in delivery situations," to the application.

[0734] Request format conversion

[0735] The device converts this request into a predetermined format such as JSON and prepares it to be sent to the server.

[0736] Submitting a Request

[0737] The formatted request data is sent securely to the server over HTTPS.

[0738] Server parsing of the request

[0739] The server analyzes the received request and understands its contents, using a natural language processing engine such as the Google Cloud Natural Language API.

[0740] Extracting relevant data

[0741] Based on the analysis results, the server searches and extracts relevant English phrases and learning data from its internal MongoDB database.

[0742] Generating learning materials

[0743] Based on the extracted data, the server generates customized learning materials tailored to the user's needs, including English phrases and audio guides for delivery situations. The audio guides are generated using the Google Text-to-Speech API.

[0744] Providing learning materials

[0745] The generated learning materials are sent to the device in JSON format and provided through a user interface, allowing users to study text, audio, and video data through a smartphone app.

[0746] Specific examples

[0747] Prompt Sentence Examples

[0748] "What phrases should I use when delivering a package to a customer?"

[0749] "English to explain delivery delays"

[0750] This allows users to learn English phrases needed for specific delivery situations and use them in actual delivery situations. This system solves the problem of communicating smoothly with English-speaking customers and contributes to improving customer satisfaction.

[0751] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0752] Step 1:

[0753] A user launches the app on their smartphone and enters a specific learning request, such as "I want to learn English phrases that can be used in delivery situations." This request is received through the user interface.

[0754] Step 2:

[0755] Converts the request received by the terminal into a specified format (e.g. JSON). The input is a text request from the user, and the output is the formatted request data.

[0756] Step 3:

[0757] The terminal sends formatted request data to the server using a secure communication protocol (HTTPS). The input is the formatted request data, and the output is the request sent to the server.

[0758] Step 4:

[0759] The server analyzes the request it receives and understands its content. This analysis is performed using a natural language processing engine such as Google Cloud Natural Language API. The input is formatted request data, and the output obtained from the analysis is an understanding of the content: "English phrases that can be used in delivery situations."

[0760] Step 5:

[0761] The server searches and extracts related English phrase data from an internal MongoDB database based on the analysis results. The input is the analysis results, and the output is related English phrase data.

[0762] Step 6:

[0763] The server generates customized learning materials based on the extracted data, tailored to the user's needs. These materials include English phrases used in delivery situations and audio guides. The audio guides are generated using the Google Text-to-Speech API. The input is the extracted English phrase data and analysis results, and the output is customized learning materials.

[0764] Step 7:

[0765] The server sends the generated learning materials to the terminal. The input is the generated learning materials, and the output is the transmission of the materials to the terminal.

[0766] Step 8:

[0767] The terminal displays the received learning materials to the user. Through an interactive user interface, the user can view and study text, audio guides, and video data. The input is the received learning materials, and the output is the learning content provided to the user.

[0768] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0769] The present invention provides a system that allows users to efficiently learn a specific form of English, combined with an emotional engine that dynamically adjusts the learning content according to the user's emotional state.

[0770] System Overview

[0771] The system consists of a user's device, a server, and a communication network. The device is operated by the user and provides an interface for sending specific requests. The server generates relevant learning materials based on the received requests and provides them to the user's device. Furthermore, the system incorporates an emotion engine that recognizes the user's emotional state and dynamically adjusts the learning materials accordingly.

[0772] Program processing flow

[0773] User submits request

[0774] User: Inputs a request for learning, such as "I want to learn American English business terms," ​​into the terminal via the terminal's interactive user interface.

[0775] Request Format by Device

[0776] Terminal: Converts the request received from the user into a predetermined format (e.g., JSON). The converted request includes the type of English (American English) and the learning category (business term).

[0777] Sending a request from the device to the server

[0778] Terminal: Sends a formatted request to the server via the HTTPS protocol, along with a destination URL and an authentication token.

[0779] Server parsing of the request

[0780] Server: Analyzes requests received from devices and understands their content (e.g., "American English," "business terms").

[0781] Server-based extraction of relevant data

[0782] Server: Runs SQL queries against an internal database to extract relevant data based on the request, for example filtering data for "Type of English: American English" and "Study Category: Business Terms."

[0783] Emotion recognition by emotion engine

[0784] Emotion engine: Determines the user's emotional state by analyzing facial expressions, voice tone, and language patterns. Data is collected from sensors such as the device's camera and microphone.

[0785] Server-based generation of learning materials

[0786] Server: Based on the extracted data and the analysis results of the emotion engine, the server generates customized learning materials according to the user's emotional state. Specifically, it adjusts the learning content and approach depending on whether the user is relaxed or stressed.

[0787] Sending learning materials from the server to the device

[0788] Server: Sends the generated learning materials to the device. The materials are sent securely via HTTPS in JSON or binary format.

[0789] Receiving and analyzing learning materials via terminal

[0790] Terminal: Analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[0791] Providing data to users via terminals

[0792] Terminal: Provides learning materials to users through an interactive user interface, including interactive exercises, pronunciation practice, and feedback.

[0793] User learning

[0794] Users: Study a given form of English using the provided study materials, which may include audio files for pronunciation practice and conversation scripts based on specific scenarios.

[0795] Specific examples

[0796] Example 1: Learning business vocabulary

[0797] User: Type "I want to learn American English business vocabulary" into the device.

[0798] Terminal: Converts the request into JSON format and sends it to the server.

[0799] Server: Analyzes the request and extracts relevant business terms from the database.

[0800] Emotion engine: Recognizes the user's emotional state and determines the appropriate learning approach.

[0801] Server: Generates dialogue scripts and pronunciation practice audio based on business scenarios, and adopts an approach that is tailored to the user's emotional state.

[0802] Server: Sends the generated materials to the terminal.

[0803] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[0804] Users: Learn and practice business vocabulary with the learning materials.

[0805] Example 2: Learning Travel English

[0806] User: Type into the device, "I want to learn everyday conversation that I can use while traveling in the UK."

[0807] Terminal: Converts the request into a specific format and sends it to the server.

[0808] Server: Analyzes the request and extracts British English conversation data.

[0809] Emotion engine: Recognizes the user's emotional state and provides relaxing content as needed.

[0810] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[0811] Server: Sends the generated materials to the terminal.

[0812] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[0813] Users: Learn and practice everyday conversations using the materials provided.

[0814] This system allows users to efficiently receive English learning materials customized to their specific goals and situations. Furthermore, the system's emotional engine reflects the user's emotional state in real time and provides optimal learning approaches, enabling an effective and flexible learning experience.

[0815] The processing flow will be explained below.

[0816] Step 1:

[0817] User: Enters a request to learn a particular form of English into an interactive user interface on a device. For example, the user might enter the text "I would like to learn American English business terms."

[0818] Step 2:

[0819] Terminal: Converts the request received from the user into a predetermined format (e.g., JSON). The converted request includes the type of English (American English) and the learning category (business term).

[0820] Step 3:

[0821] Terminal: Sends a formatted request to the server via the HTTPS protocol, along with a destination URL and an authentication token.

[0822] Step 4:

[0823] Server: Analyzes requests received from devices and parses JSON data to understand their contents. Extracts "type of English" and "learning category" from the parsed data.

[0824] Step 5:

[0825] Server: Runs SQL queries against an internal database to extract relevant data based on the request, for example filtering data for "Type of English: American English" and "Study Category: Business Terms."

[0826] Step 6:

[0827] Emotion engine: Recognizes the user's emotional state. It determines the user's emotional state by analyzing their facial expressions, voice tone, and language patterns. Data is collected from sensors such as the device's camera and microphone.

[0828] Step 7:

[0829] Server: Based on the extracted data and the analysis results of the emotion engine, it generates customized learning materials according to the user's emotional state. For example, if the user is relaxed, it provides regular learning materials, but if the user is stressed, it adds relaxing content or encouraging messages.

[0830] Step 8:

[0831] Server: Sends the generated learning materials to the device. The materials are sent securely via HTTPS in JSON or binary format.

[0832] Step 9:

[0833] Terminal: Analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[0834] Step 10:

[0835] Terminal: Provides learning materials to users through an interactive user interface, including interactive exercises, pronunciation practice, and feedback.

[0836] Step 11:

[0837] Users: Study a given form of English using the provided study materials, which may include audio files for pronunciation practice and conversation scripts based on specific scenarios.

[0838] Example 2

[0839] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0840] Conventional English learning systems provide uniform learning materials without considering the user's emotional state, making it difficult to provide an effective learning experience. Furthermore, they often lack the flexibility to respond to specific user needs, resulting in reduced learning efficiency.

[0841] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0842] In this invention, the server includes means for receiving a specific English learning request from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from an English database based on the analysis results, means for generating customized learning materials based on the extracted data, an emotion engine for recognizing the user's emotional state and dynamically adjusting the learning materials according to that state, and means for providing the learning materials to the user. This enables effective and flexible English learning by reflecting the user's emotional state in real time and providing an optimal learning approach.

[0843] "User" refers to a person or group of people who intend to use the System to learn a particular form of English.

[0844] A "request" refers to input data that indicates a user's request or desire regarding learning content to the system.

[0845] "Predetermined format" refers to the standardized data format required to parse and process a request.

[0846] "Analysis" refers to the process of interpreting the contents of a received request and performing the necessary processing within the system based on that information.

[0847] An "English database" refers to a collection of data that stores various data related to English (word lists, example sentences, conversation scripts, etc.).

[0848] "Related data" refers to data that is extracted from the English database based on the analysis results and is suitable for the user's learning objectives.

[0849] "Customization" refers to the process of individually tailoring learning materials to a user's specific needs and circumstances.

[0850] "Study materials" refers to various materials such as text data, audio data, and video data provided by the system for users to study English.

[0851] "Emotional state" refers to the emotions and psychological state (relaxed, stressed, etc.) that a user feels while using the system.

[0852] "Emotion engine" refers to a module within the system that recognizes the user's emotional state and dynamically adjusts learning materials accordingly.

[0853] "Dynamic adjustment" refers to the process of adaptively changing learning materials and methods in real time.

[0854] This invention provides a system that allows users to efficiently learn a specific form of English, and further combines it with an emotional engine that dynamically adjusts the learning content according to the user's emotional state. This system consists of a user terminal, a server, and a communication network. The specific configuration and operation procedure are described below.

[0855] System Overview

[0856] Hardware and Software

[0857] 1. User Device

[0858] Hardware: Personal computers, tablets, smartphones, etc.

[0859] Software: Web browser, dedicated application.

[0860] 2. Server

[0861] Hardware: High-performance cloud or on-premise servers.

[0862] Software: Web server software, database management systems (e.g., MySQL, PostgreSQL), emotion recognition engines (e.g., Microsoft Azure Emotion API, IBM Watson).

[0863] 3. Communication Network

[0864] Internet connection (e.g. Wi-Fi, 4G / 5G network)

[0865] Program processing flow

[0866] User operations

[0867] The user utilizes the device's interactive user interface to input a specific learning request, for example, "I want to learn American English business terms," ​​either by text or voice.

[0868] Terminal handling

[0869] The device receives requests entered by the user and converts them into a specific format (e.g., JSON format). The converted request includes the type of English (e.g., American English) and the learning category (e.g., business terminology).

[0870] The device sends a request to the server via the HTTPS protocol, along with the destination URL and an authentication token.

[0871] Server Processing

[0872] The server parses the request received from the device and understands its contents, which includes deserializing the JSON data.

[0873] The server runs SQL queries against an internal database to extract relevant data based on the request, such as word lists and example sentences for "American English" and "business terms."

[0874] The emotion engine determines a user's emotional state by analyzing facial expression data, voice tone, and language patterns, data collected from sensors such as the device's camera and microphone.

[0875] The server uses the extracted data and the analysis results of the emotion engine to generate customized learning materials according to the user's emotional state: for example, if the user is relaxed, it provides review materials on basic concepts, and if the user is stressed, it provides interactive exercises.

[0876] The server sends the generated learning materials to the device in JSON or binary format, securely transmitted via the HTTPS protocol.

[0877] Terminal handling

[0878] The device analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[0879] The device uses an interactive user interface to provide learning materials to the user, including interactive exercises, pronunciation practice, and feedback features.

[0880] Specific examples

[0881] Example 1: Learning business vocabulary

[0882] User: Type "I want to learn American English business vocabulary" into the terminal.

[0883] Terminal: Converts the request into JSON format and sends it to the server.

[0884] Server: Analyzes the request and extracts relevant business terms from the database.

[0885] Emotion engine: Recognizes the user's emotional state and determines the appropriate learning approach.

[0886] Server: Generates dialogue scripts and pronunciation practice audio based on business scenarios, and adopts an approach that is tailored to the user's emotional state.

[0887] Server: Sends the generated materials to the terminal.

[0888] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[0889] Users: Learn and practice business vocabulary with the learning materials.

[0890] Example 2: Learning Travel English

[0891] User: Type "I want to learn everyday conversations I can use while traveling in the UK" into the device.

[0892] Terminal: Converts the request into a specific format and sends it to the server.

[0893] Server: Analyzes the request and extracts British English conversation data.

[0894] Emotion engine: Recognizes the user's emotional state and provides relaxing content as needed.

[0895] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[0896] Server: Sends the generated materials to the terminal.

[0897] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[0898] Users: Learn and practice everyday conversations using the materials provided.

[0899] In this way, users can efficiently receive learning materials customized to their specific goals and situations. Furthermore, the emotional engine reflects the user's emotional state in real time and provides the optimal learning approach, enabling effective and flexible English learning.

[0900] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0901] Step 1:

[0902] The user inputs a learning request into the device, such as "I want to learn American English business terms." Text and voice input are possible through the user interface.

[0903] Input data: User learning request (e.g., American English business terms)

[0904] Output data: Request data containing the user's intent

[0905] Step 2:

[0906] The device converts the request received from the user into JSON format, which includes the type of English and the learning category.

[0907] Input data: Request data (text format)

[0908] Data processing: Converting request data to JSON format

[0909] Output data: Request data in JSON format

[0910] Step 3:

[0911] The terminal sends formatted request data to the server using the HTTPS protocol, which includes the destination URL and the authentication token.

[0912] Input data: JSON format request data, destination URL, authentication token

[0913] Data calculation: Secure data transmission (HTTPS protocol)

[0914] Output data: Sending request data to the server

[0915] Step 4:

[0916] The server analyzes the request data received from the terminal, understands its contents, deserializes the request, and checks for errors in the contents.

[0917] Input data: Request data in JSON format

[0918] Data processing: Deserializing and error checking the request data

[0919] Output data: Analysis results (type of English, learning category)

[0920] Step 5:

[0921] Based on the analysis results, the server runs SQL queries against an internal database to extract relevant English data.

[0922] Input data: Analysis results (type of English, learning category)

[0923] Data operations: executing SQL queries and database searches

[0924] Output data: Related English data (e.g., a list of business terms)

[0925] Step 6:

[0926] The emotion engine analyzes data collected from the device's camera and microphone to determine the user's emotional state.

[0927] Input data: User's facial expression data, voice tone, language patterns

[0928] Data Computation: Analysis with Emotion Recognition Algorithms

[0929] Output data: Emotional state (relaxed, stressed, etc.)

[0930] Step 7:

[0931] The server generates customized learning materials based on the extracted English data and the analysis results of the emotion engine, specifically incorporating the optimal learning approach according to the user's emotional state.

[0932] Input data: related English data, emotional state

[0933] Data calculation: Generation of learning materials (e.g., dialogue scripts, pronunciation practice audio)

[0934] Output data: customized learning materials

[0935] Step 8:

[0936] The server sends the generated learning materials to the device in JSON or binary format.

[0937] Input data: customized learning materials

[0938] Data processing: Format conversion and secure transmission of learning materials (HTTPS protocol)

[0939] Output data: Sending learning materials to the device

[0940] Step 9:

[0941] The device analyzes the learning materials received from the server and converts them into a format that can be provided to the user, including text display, audio playback, and video playback.

[0942] Input data: training materials (JSON or binary format)

[0943] Data processing: Analysis and format conversion of learning materials

[0944] Output data: learning materials provided to the user

[0945] Step 10:

[0946] The device provides learning materials to the user using an interactive user interface, including interactive exercises, pronunciation practice, and feedback features.

[0947] Input data: learning materials provided

[0948] Specific operations: text display, audio playback, video playback, recording function

[0949] Output data: User's interactive learning experience

[0950] Step 11:

[0951] Users use the provided learning materials to study designated English forms, practice pronunciation, and practice conversation scenarios.

[0952] Input data: learning materials

[0953] Specific actions: pronunciation practice (playing and recording audio files), scenario-based conversation practice

[0954] Output data: learning progress and outcomes

[0955] (Application example 2)

[0956] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0957] Conventional English learning systems provide uniform learning materials without considering the user's emotional state, which often reduces the user's concentration and motivation to learn. Furthermore, if the learning content does not match the user's emotional state, the learning effect is insufficient. Therefore, a flexible system that allows users to learn English effectively is needed.

[0958] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0959] In this invention, the server includes means for receiving a specific form of English learning request from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from an English database based on the analysis results, means for generating customized learning materials based on the extracted data, means for recognizing the user's emotional state and dynamically adjusting the learning materials according to the state, and means for providing the learning materials to the user. This makes it possible to provide optimal learning content according to the user's emotional state and maximize learning effectiveness.

[0960] "Means for receiving learning requests from users about a particular form of English" refers to an interface and communication device that allows a user to input and send learning requests about a particular form of English (e.g., American English business vocabulary, British English everyday conversation, etc.) to the system.

[0961] "Means for converting the request into a predetermined format" refers to a process or algorithm that converts a learning request received from a user into a specified data format (e.g., JSON).

[0962] The "means for parsing a request according to a predetermined format" refers to a program and logic for parsing formatted request data and extracting and understanding the content of the request.

[0963] The "means for extracting relevant data from an English database based on the analysis results" refers to algorithms and query execution means for searching and retrieving English data (e.g., specific words or phrases) from a database that corresponds to the analysis results of the request.

[0964] The "means for generating customized learning materials based on extracted data" refers to a program and system that creates learning materials tailored to the user based on the extracted relevant data.

[0965] "Means for recognizing the user's emotional state and dynamically adjusting learning materials according to that state" refers to an engine and algorithm that uses sensors such as cameras and microphones to analyze the user's emotional state (relaxation, stress, concentration, etc.) in real time and adjusts the learning content appropriately based on the results.

[0966] The "means for providing the learning materials to the user" refers to communication and display means for delivering the created customized learning materials to the user's terminal and enabling display and playback.

[0967] This invention is a system that allows users to efficiently learn a specific form of English, and further combines it with an emotional engine that dynamically adjusts the learning content according to the user's emotional state. The system consists of a user terminal, a server, and a communication network.

[0968] System configuration

[0969] 1. User's device

[0970] The user device can be a smartphone, VR headset, tablet, etc., and through the user interface, they can input learning requests, collect emotional data, and display learning materials. In particular, when using a VR headset, interactive English learning in a VR shop format is possible.

[0971] 2. Server

[0972] The server has the following features:

[0973] Request reception and format conversion: Receives an English learning request from the user and converts it into a specified format (e.g., JSON format).

[0974] Request analysis and data extraction: Analyze the request content and extract relevant data from the English database.

[0975] Generation of customized learning materials: Customized learning materials are generated based on the extracted data and the analysis results of the emotion engine.

[0976] Provision of learning materials: The generated learning materials are sent to the user's terminal for display and playback.

[0977] 3. Emotion Engine

[0978] The emotion engine analyzes the user's emotional state (relaxed, stressed, focused, etc.) through sensors such as cameras and microphones. This analysis data is used to dynamically adjust learning materials.

[0979] Hardware and software used

[0980] Hardware: smartphone, VR headset, camera, microphone

[0981] Software: Flask (a Python web framework), Emotion API (an emotion recognition library), database management system (e.g., MySQL or SQLite)

[0982] A concrete example of the processing flow

[0983] Example 1: Learning business vocabulary

[0984] The user uses the user interface of the terminal to input a request such as "I would like to learn American English business terms."

[0985] The terminal converts this request into JSON format and sends it to the server.

[0986] The server parses the request and extracts relevant business terms from a database.

[0987] The emotion engine recognizes the user's emotional state as "relaxed" and generates learning materials with a calm tone.

[0988] The server sends the generated learning materials to the user's terminal, and the user learns in an interactive format in a VR environment.

[0989] Example 2: Learning Travel English

[0990] The user uses the user interface of the terminal to input a request such as "I would like to learn everyday conversation that can be used while traveling in England."

[0991] The terminal converts this request into a predetermined format and sends it to the server.

[0992] The server analyzes the request content and extracts everyday conversation data from a database.

[0993] The emotion engine recognizes the user's emotional state as "stress" and generates support-oriented learning materials.

[0994] The server sends the generated learning materials to the user's terminal, and the user studies in a VR environment.

[0995] Prompt Sentence Examples

[0996] A user has submitted a request to learn "Business English." Their current emotional state is perceived as "Relaxed." Use this information to generate Business English learning materials presented in a calm tone.

[0997] This system allows users to efficiently receive English learning materials customized to their specific goals and situations. Furthermore, the system's emotional engine reflects the user's emotional state in real time and provides the optimal learning approach, resulting in an effective and flexible learning experience.

[0998] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0999] Step 1:

[1000] The user uses the device's user interface to input a request for English learning. The device receives the input request and converts it into a specified format (e.g., JSON format). Specifically, the user might input something like "I want to learn American English business terms," ​​and format it as JSON data. The input is the user's learning request, and the output is formatted JSON data.

[1001] Step 2:

[1002] The terminal sends a formatted request to the server via the HTTPS protocol. The sent data also includes the destination URL and an authentication token. In this step, the input is JSON data generated on the terminal, and the output is the data sent to the server as an HTTPS request.

[1003] Step 3:

[1004] The server analyzes the request data received from the device. The analysis includes reading the type of English and learning category (e.g., "American English," "Business Terms," ​​etc.) contained in the request. The input is the JSON data received by the server, and the output is the type of English and learning category as the analysis results.

[1005] Step 4:

[1006] The server queries the internal database based on the analysis results and extracts relevant data. Specifically, it filters data that matches "English type: American English" and "Learning category: Business terms." The input is the analysis results, and the output is the filtered relevant data.

[1007] Step 5:

[1008] The server sends data collected from the camera and microphone to the emotion engine to recognize the user's emotional state. The emotion engine performs facial expression and voice analysis to determine whether the user is relaxed or stressed. The input is sensor data from the camera and microphone, and the output is the analyzed emotional state.

[1009] Step 6:

[1010] The server generates learning materials according to the user's emotional state based on the extracted data and the analysis results of the emotion engine. For example, if the user is relaxed, it generates learning materials with a calm tone, and if the user is stressed, it generates materials with a supportive tone. The input is the filtered data and the user's emotional state, and the output is customized learning materials.

[1011] Step 7:

[1012] The server sends the generated learning materials to the terminal. The materials are sent securely via the HTTPS protocol in JSON or binary format. The input is the generated learning materials, and the output is the data sent to the terminal.

[1013] Step 8:

[1014] The terminal analyzes the learning materials received from the server and converts them into a format that can be provided to the user, such as text display, audio playback, and video playback. The input is the material received from the server, and the output is the learning materials in the interface provided to the user.

[1015] Step 9:

[1016] Users study English using the learning materials displayed on the device. Through user operation, they efficiently learn the target English form through interactive dialogue-style exercises, pronunciation practice, and feedback functions. The input is the learning materials provided by the device, and the output is the user's learning progress.

[1017] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1018] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1019] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1020] [Third embodiment]

[1021] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1022] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1023] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1024] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1025] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1026] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1027] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1028] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1029] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1030] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1031] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1032] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1033] The present invention provides a system that allows users to efficiently learn a specific form of English. A specific embodiment of this system will be described below.

[1034] System Overview

[1035] The system consists of a user terminal, a server, and a communication network. The terminal is operated by the user and provides an interface for sending specific requests. The server generates relevant learning materials based on the received requests and provides them to the user terminal.

[1036] Program processing flow

[1037] User submits request

[1038] User: Enters their learning interest, such as a request like "I want to learn American English business terms," ​​into the device.

[1039] Request Format by Device

[1040] Terminal: Converts the request received from the user into a predetermined format and prepares it for sending to the server, for example, converting it into JSON format.

[1041] Sending a request from the device to the server

[1042] Terminal: Sends formatted request data to the server via a secure communication protocol (e.g., HTTPS).

[1043] Server parsing of the request

[1044] Server: Analyzes the received request and understands its content (e.g., "American English," "business terms").

[1045] Server-based extraction of relevant data

[1046] Server: Extracts the necessary English data from the internal database based on the request. The data used includes audio guides, vocabulary lists, and sample business conversations.

[1047] Server-based generation of learning materials

[1048] Server: Based on the extracted data, it generates customized learning materials tailored to the user's needs. These materials are provided in the form of text, audio, video, etc.

[1049] Sending learning materials from the server to the device

[1050] Server: Sends the generated learning materials to the device.

[1051] Receiving and analyzing learning materials via terminal

[1052] Terminal: Analyzes the learning materials received from the server and displays them in a user-friendly format. An interactive user interface is used to help users study effectively.

[1053] User learning

[1054] Users: Study specific forms of English using provided learning materials, such as audio files for pronunciation practice and conversation scripts based on specific scenarios.

[1055] Specific examples

[1056] Example 1: Learning business vocabulary

[1057] User: Type "I want to learn American English business vocabulary" into the device.

[1058] Terminal: Converts the request into JSON format and sends it to the server.

[1059] Server: Analyzes the request and extracts relevant business terms from the database.

[1060] Server: Generates dialogue scripts based on business scenarios and audio for pronunciation practice.

[1061] Server: Sends the generated materials to the terminal.

[1062] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[1063] Users: Learn and practice business vocabulary with the learning materials.

[1064] Example 2: Learning Travel English

[1065] User: Type into the device, "I want to learn everyday conversation that I can use while traveling in the UK."

[1066] Terminal: Converts the request into a specific format and sends it to the server.

[1067] Server: Analyzes the request and extracts British English conversation data.

[1068] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[1069] Server: Sends the generated materials to the terminal.

[1070] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[1071] Users: Learn and practice everyday conversations using the materials provided.

[1072] This system allows users to efficiently receive English learning materials customized for specific purposes and situations, enabling learning that accommodates different pronunciations and accents and is expected to be immediately usable in real-life communication situations.

[1073] The processing flow will be explained below.

[1074] Step 1:

[1075] User: Enters a request to learn a particular form of English into an interactive user interface on a device. For example, the user might enter the text "I would like to learn American English business terms."

[1076] Step 2:

[1077] Terminal: Converts the request received from the user into a predetermined format (e.g., JSON). The converted request includes the type of English (American English) and the learning category (business term).

[1078] Step 3:

[1079] Terminal: Sends a formatted request to the server via the HTTPS protocol, along with a destination URL and an authentication token.

[1080] Step 4:

[1081] Server: Analyzes requests received from devices and parses JSON data to understand the request content. Extracts "type of English" and "learning category" from the parsed data.

[1082] Step 5:

[1083] Server: Runs SQL queries against an internal database to extract relevant data based on the request, for example filtering data for "Type of English: American English" and "Study Category: Business Terms."

[1084] Step 6:

[1085] Server: Based on the extracted data, it generates customized learning materials tailored to the user's learning style. Specifically, it generates dialogue scripts based on a business meeting scenario, audio files for pronunciation practice, and related video materials.

[1086] Step 7:

[1087] Server: Sends the generated learning materials to the device. The materials are sent securely via HTTPS in JSON or binary format.

[1088] Step 8:

[1089] Terminal: Analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[1090] Step 9:

[1091] Terminal: Provides learning materials to users through an interactive user interface, including interactive exercises, pronunciation practice, and feedback.

[1092] Step 10:

[1093] User: Study the assigned English form using the provided study materials, which may include pronunciation practice, reading dialogue scripts, and watching related videos.

[1094] Example 1

[1095] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1096] Conventional English learning systems have had difficulty efficiently processing learning requests for specific forms of English and providing users with appropriate learning materials. As a result, they have been unable to provide customized learning support tailored to individual users' needs, resulting in ineffective English learning.

[1097] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1098] In this invention, the server includes means for receiving a specific form of English learning request from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from a database based on the analysis result, means for generating customized learning materials based on the extracted data, means for providing the learning materials to the user, means for transmitting the request from the terminal to the server via a secure communication protocol, and means for transmitting the learning materials from the server to the terminal, thereby enabling efficient provision of customized learning materials tailored to the individual needs of the user.

[1099] "User" refers to a person who uses the system to learn English.

[1100] "Study Request" means a desire or request for a particular form of English that a User wishes to learn through the System.

[1101] "Means" refers to a method or apparatus designed to perform a particular function or operation.

[1102] "Predetermined format" refers to a format in which data is structured according to a particular format or standard.

[1103] "Analyzing" refers to the operation of interpreting received data and extracting necessary information from it.

[1104] A "database" refers to a system for efficiently storing, managing, and retrieving structured information.

[1105] "Related data" refers to information useful for learning that is extracted based on the user's learning request.

[1106] "Study materials" refers to learning materials provided to users to help them learn English, and includes text data, audio data, video data, and the like.

[1107] "Customized" means adapted or modified to meet the needs and requirements of a particular user.

[1108] A "communication protocol" refers to a set of rules and procedures for data communication, and in this case refers to HTTPS.

[1109] "Server" refers to a computer system that receives and analyzes user requests and generates and provides study materials.

[1110] "Terminal" refers to a device operated by a user that provides an interface for sending study requests and receiving study materials.

[1111] The present invention is a system that allows users to efficiently learn a specific form of English, and is composed of a user terminal, a server, and a communication network. A specific embodiment of this system will be described below.

[1112] System Overview

[1113] The user's terminal is operated by the user and provides an interface for sending specific requests. The server is responsible for generating relevant learning materials based on the received requests and providing them to the user's terminal.

[1114] Hardware and software used

[1115] Hardware:

[1116] User's device (e.g., smartphone, tablet, PC)

[1117] Server (a computer server capable of high-performance calculations and data processing)

[1118] software:

[1119] User Interface (Web Browser, Mobile Application)

[1120] Server-side programs (Python, JavaScript, Node.js)

[1121] Database (MySQL, PostgreSQL)

[1122] Communication protocol (HTTPS)

[1123] Process Overview

[1124] 1. User submits a request

[1125] Users input their learning interests into the device, for example, requesting to learn business English or travel English.

[1126] 2. Request Format by Device

[1127] The terminal converts the request received from the user into a specified format (such as JSON format).

[1128] 3. Sending a request from the device to the server

[1129] The device sends the formatted request to the server over HTTPS.

[1130] 4. Server Parsing of the Request

[1131] The server analyzes the received request and understands its contents.

[1132] 5. Server Extraction of Relevant Data

[1133] The server extracts the necessary data from its internal database based on the request.

[1134] 6. Server-based generation of learning materials

[1135] The server generates customized learning materials based on the extracted data.

[1136] 7. Sending learning materials from the server to the device

[1137] The server transmits the generated study materials to the terminal.

[1138] 8. Receiving and analyzing learning materials by device

[1139] The terminal analyzes the learning materials received from the server and displays them in an easy-to-understand manner for the user.

[1140] 9. User Learning

[1141] The user studies using the provided study materials.

[1142] Specific examples

[1143] Example 1: Learning business vocabulary

[1144] User: Type "I want to learn American English business vocabulary" into the device.

[1145] Terminal: Converts the request into JSON format and sends it to the server.

[1146] Server: Analyzes the request and extracts relevant business terms from the database.

[1147] Server: Generates dialogue scripts based on business scenarios and audio for pronunciation practice.

[1148] Server: Sends the generated materials to the terminal.

[1149] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[1150] Users: Learn and practice business vocabulary with the learning materials.

[1151] Example prompt: "Please generate learning materials for American English business terminology."

[1152] Example 2: Learning Travel English

[1153] User: Type into the device, "I want to learn everyday conversation that I can use while traveling in the UK."

[1154] Terminal: Converts the request into a specific format and sends it to the server.

[1155] Server: Analyzes the request and extracts British English conversation data.

[1156] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[1157] Server: Sends the generated materials to the terminal.

[1158] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[1159] Users: Learn and practice everyday conversations using the materials provided.

[1160] This system allows users to efficiently receive English learning materials customized for specific purposes and situations, enabling learning that accommodates different pronunciations and accents, and is expected to be immediately usable in real-life communication situations.

[1161] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1162] Step 1: User submits request

[1163] The user inputs what they want to learn into the device. Specifically, they write the type of English they want to learn and its purpose (for example, "I want to learn American English business terms") in the input field and click the "Submit" button.

[1164] Input: Learning motivation and request details

[1165] Output: Request data entered on the terminal

[1166] Step 2: Formatting the request via the terminal

[1167] The terminal converts the request received from the user into a specific format (e.g., JSON format), which allows the server to accurately interpret the request content.

[1168] Input: The raw request data entered by the user

[1169] Output: Request data in JSON format

[1170] Specific operation: Structures request data using JavaScript or Python and converts it to JSON format.

[1171] Step 3: Sending a request from the device to the server

[1172] The terminal sends the formatted request data to the server via HTTPS, which allows the request data to be transmitted securely to the server.

[1173] Input: Request data in JSON format

[1174] Output: Request data sent to the server

[1175] Specific behavior: Sends a request to the server using the HTTPS protocol.

[1176] Step 4: Server Parses the Request

[1177] The server analyzes the received request data and understands its contents. For example, from a request such as "I want to learn American English business terms," ​​it extracts "Type of English: American English" and "Use: Business terms."

[1178] Input: JSON data sent to the server

[1179] Output: Extracted elements of the request content (type of English, purpose, etc.)

[1180] Specific operation: Parse the JSON data using a program such as Python and extract the necessary information.

[1181] Step 5: Server Extraction of Relevant Data

[1182] The server extracts relevant data from its internal database based on the request content. For example, based on the information "American English" and "business terminology," it retrieves a list of related business terms and audio guides.

[1183] Input: Extracted request content

[1184] Output: Relevant data extracted from the database

[1185] What it does: Retrieves relevant information from a database using SQL queries.

[1186] Step 6: Server generates learning materials

[1187] The server then generates customized learning materials based on the extracted data, which are tailored to the user's needs. These materials consist of text, audio, and video data.

[1188] Input: Extracted relevant data

[1189] Output: Learning materials suitable for the user

[1190] What it does: Consolidates and formats data using text and speech generation engines.

[1191] Step 7: Sending learning materials from the server to the device

[1192] The server packages the generated learning materials in JSON format and sends them back to the terminal via HTTPS.

[1193] Input: Generated learning materials

[1194] Output: Learning materials in JSON format sent to the device

[1195] Specific operation: Sends data to the device using HTTPS.

[1196] Step 8: Receiving and analyzing the learning materials on the device

[1197] The terminal parses the JSON data received from the server and displays the contents in an interactive user interface, allowing users to easily view the materials.

[1198] Input: JSON data sent from the server

[1199] Output: Learning materials displayed in a user interface

[1200] What it does: It parses the data using JavaScript and displays it in the interface using HTML and CSS.

[1201] Step 9: User Training

[1202] Users study using learning materials displayed on their devices, including audio files for pronunciation practice and conversation scripts based on specific scenarios. They can also get feedback on their pronunciation using audio playback and recording functions.

[1203] Input: Study materials

[1204] Output: Learning outcomes (improvement of knowledge and skills)

[1205] Specific actions: Playing audio files, displaying text, and conducting interactive practice sessions.

[1206] In this way, the system can efficiently provide users with English learning materials that are customized to their individual needs.

[1207] (Application example 1)

[1208] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1209] In food delivery, delivery workers often have difficulty communicating smoothly with English-speaking customers, which can lead to lower customer satisfaction and delivery delays, making it a major challenge for businesses.

[1210] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1211] In this invention, the server includes means for receiving a learning request for a specific form of English from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from an English database based on the analysis results, means for generating customized learning materials based on the extracted data, means for including English phrases used in delivery situations in the generated learning materials, means for adding audio guidance to the learning materials using speech synthesis technology, and means for providing the learning materials to the user. This enables delivery personnel to learn English phrases required for specific delivery situations and use them in actual delivery situations.

[1212] The "means for receiving a learning request from a user regarding a specific form of English" is a mechanism including an interface through which a user inputs a request to learn a specific form of English and the system receives the request.

[1213] The "means for converting the request into a predetermined format" refers to a process for converting a request entered by a user into a standardized data format within the system (e.g., JSON).

[1214] The "means for analyzing a request according to a predetermined format" refers to an algorithm or software for analyzing and understanding the request content based on the converted format.

[1215] "Means for extracting relevant data from an English database based on the analysis results" refers to the process of searching and extracting data related to English learning from a database based on the request analysis results.

[1216] "Means for generating customized learning materials based on extracted data" refers to a method for using extracted English data to create specific learning materials (text, audio, video, etc.) tailored to the user's learning goals and situation.

[1217] "Means for including English phrases used in delivery situations in the generated learning materials" refers to the process of incorporating English phrases required in specific delivery situations, such as food delivery, into the learning materials.

[1218] "Means for adding audio guidance to study materials using speech synthesis technology" refers to a method for adding audio guidance corresponding to the generated study materials using speech synthesis technology.

[1219] The "means for providing the learning materials to the user" refers to a mechanism for transmitting the finalized learning materials to the user's device so that the user can use them.

[1220] The system of this invention is designed to enable users to efficiently learn and use English in food delivery situations. The system is primarily composed of terminals, including smartphones, a server, and a communication network.

[1221] Hardware and Software

[1222] Hardware: Smartphone

[1223] software:

[1224] Development environment: Android Studio, Xcode

[1225] Backend: Node.js, Express.js

[1226] Database: MongoDB

[1227] Communication: HTTPS, REST API

[1228] Speech synthesis: Google Text-to-Speech API

[1229] Program processing overview

[1230] User submits request

[1231] Users use their smartphones to submit learning requests for specific English phrases, such as "I want to learn English phrases that can be used in delivery situations," to the application.

[1232] Request format conversion

[1233] The device converts this request into a predetermined format such as JSON and prepares it to be sent to the server.

[1234] Submitting a Request

[1235] The formatted request data is sent securely to the server over HTTPS.

[1236] Server parsing of the request

[1237] The server analyzes the received request and understands its contents, using a natural language processing engine such as the Google Cloud Natural Language API.

[1238] Extracting relevant data

[1239] Based on the analysis results, the server searches and extracts relevant English phrases and learning data from its internal MongoDB database.

[1240] Generating learning materials

[1241] Based on the extracted data, the server generates customized learning materials tailored to the user's needs, including English phrases and audio guides for delivery situations. The audio guides are generated using the Google Text-to-Speech API.

[1242] Providing learning materials

[1243] The generated learning materials are sent to the device in JSON format and provided through a user interface, allowing users to study text, audio, and video data through a smartphone app.

[1244] Specific examples

[1245] Prompt Sentence Examples

[1246] "What phrases should I use when delivering a package to a customer?"

[1247] "English to explain delivery delays"

[1248] This allows users to learn English phrases needed for specific delivery situations and use them in actual delivery situations. This system solves the problem of communicating smoothly with English-speaking customers and contributes to improving customer satisfaction.

[1249] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1250] Step 1:

[1251] A user launches the app on their smartphone and enters a specific learning request, such as "I want to learn English phrases that can be used in delivery situations." This request is received through the user interface.

[1252] Step 2:

[1253] Converts the request received by the terminal into a specified format (e.g. JSON). The input is a text request from the user, and the output is the formatted request data.

[1254] Step 3:

[1255] The terminal sends formatted request data to the server using a secure communication protocol (HTTPS). The input is the formatted request data, and the output is the request sent to the server.

[1256] Step 4:

[1257] The server analyzes the request it receives and understands its content. This analysis is performed using a natural language processing engine such as Google Cloud Natural Language API. The input is formatted request data, and the output obtained from the analysis is an understanding of the content: "English phrases that can be used in delivery situations."

[1258] Step 5:

[1259] The server searches and extracts related English phrase data from an internal MongoDB database based on the analysis results. The input is the analysis results, and the output is related English phrase data.

[1260] Step 6:

[1261] The server generates customized learning materials based on the extracted data, tailored to the user's needs. These materials include English phrases used in delivery situations and audio guides. The audio guides are generated using the Google Text-to-Speech API. The input is the extracted English phrase data and analysis results, and the output is customized learning materials.

[1262] Step 7:

[1263] The server sends the generated learning materials to the terminal. The input is the generated learning materials, and the output is the transmission of the materials to the terminal.

[1264] Step 8:

[1265] The terminal displays the received learning materials to the user. Through an interactive user interface, the user can view and study text, audio guides, and video data. The input is the received learning materials, and the output is the learning content provided to the user.

[1266] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1267] The present invention provides a system that allows users to efficiently learn a specific form of English, combined with an emotional engine that dynamically adjusts the learning content according to the user's emotional state.

[1268] System Overview

[1269] The system consists of a user's device, a server, and a communication network. The device is operated by the user and provides an interface for sending specific requests. The server generates relevant learning materials based on the received requests and provides them to the user's device. Furthermore, the system incorporates an emotion engine that recognizes the user's emotional state and dynamically adjusts the learning materials accordingly.

[1270] Program processing flow

[1271] User submits request

[1272] User: Inputs a request for learning, such as "I want to learn American English business terms," ​​into the terminal via the terminal's interactive user interface.

[1273] Request Format by Device

[1274] Terminal: Converts the request received from the user into a predetermined format (e.g., JSON). The converted request includes the type of English (American English) and the learning category (business term).

[1275] Sending a request from the device to the server

[1276] Terminal: Sends a formatted request to the server via the HTTPS protocol, along with a destination URL and an authentication token.

[1277] Server parsing of the request

[1278] Server: Analyzes requests received from devices and understands their content (e.g., "American English," "business terms").

[1279] Server-based extraction of relevant data

[1280] Server: Runs SQL queries against an internal database to extract relevant data based on the request, for example filtering data for "Type of English: American English" and "Study Category: Business Terms."

[1281] Emotion recognition by emotion engine

[1282] Emotion engine: Determines the user's emotional state by analyzing facial expressions, voice tone, and language patterns. Data is collected from sensors such as the device's camera and microphone.

[1283] Server-based generation of learning materials

[1284] Server: Based on the extracted data and the analysis results of the emotion engine, the server generates customized learning materials according to the user's emotional state. Specifically, it adjusts the learning content and approach depending on whether the user is relaxed or stressed.

[1285] Sending learning materials from the server to the device

[1286] Server: Sends the generated learning materials to the device. The materials are sent securely via HTTPS in JSON or binary format.

[1287] Receiving and analyzing learning materials via terminal

[1288] Terminal: Analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[1289] Providing data to users via terminals

[1290] Terminal: Provides learning materials to users through an interactive user interface, including interactive exercises, pronunciation practice, and feedback.

[1291] User learning

[1292] Users: Study a given form of English using the provided study materials, which may include audio files for pronunciation practice and conversation scripts based on specific scenarios.

[1293] Specific examples

[1294] Example 1: Learning business vocabulary

[1295] User: Type "I want to learn American English business vocabulary" into the device.

[1296] Terminal: Converts the request into JSON format and sends it to the server.

[1297] Server: Analyzes the request and extracts relevant business terms from the database.

[1298] Emotion engine: Recognizes the user's emotional state and determines the appropriate learning approach.

[1299] Server: Generates dialogue scripts and pronunciation practice audio based on business scenarios, and adopts an approach that is tailored to the user's emotional state.

[1300] Server: Sends the generated materials to the terminal.

[1301] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[1302] Users: Learn and practice business vocabulary with the learning materials.

[1303] Example 2: Learning Travel English

[1304] User: Type into the device, "I want to learn everyday conversation that I can use while traveling in the UK."

[1305] Terminal: Converts the request into a specific format and sends it to the server.

[1306] Server: Analyzes the request and extracts British English conversation data.

[1307] Emotion engine: Recognizes the user's emotional state and provides relaxing content as needed.

[1308] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[1309] Server: Sends the generated materials to the terminal.

[1310] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[1311] Users: Learn and practice everyday conversations using the materials provided.

[1312] This system allows users to efficiently receive English learning materials customized to their specific goals and situations. Furthermore, the system's emotional engine reflects the user's emotional state in real time and provides optimal learning approaches, enabling an effective and flexible learning experience.

[1313] The processing flow will be explained below.

[1314] Step 1:

[1315] User: Enters a request to learn a particular form of English into an interactive user interface on a device. For example, the user might enter the text "I would like to learn American English business terms."

[1316] Step 2:

[1317] Terminal: Converts the request received from the user into a predetermined format (e.g., JSON). The converted request includes the type of English (American English) and the learning category (business term).

[1318] Step 3:

[1319] Terminal: Sends a formatted request to the server via the HTTPS protocol, along with a destination URL and an authentication token.

[1320] Step 4:

[1321] Server: Analyzes requests received from devices and parses JSON data to understand their contents. Extracts "type of English" and "learning category" from the parsed data.

[1322] Step 5:

[1323] Server: Runs SQL queries against an internal database to extract relevant data based on the request, for example filtering data for "Type of English: American English" and "Study Category: Business Terms."

[1324] Step 6:

[1325] Emotion engine: Recognizes the user's emotional state. It determines the user's emotional state by analyzing their facial expressions, voice tone, and language patterns. Data is collected from sensors such as the device's camera and microphone.

[1326] Step 7:

[1327] Server: Based on the extracted data and the analysis results of the emotion engine, it generates customized learning materials according to the user's emotional state. For example, if the user is relaxed, it provides regular learning materials, but if the user is stressed, it adds relaxing content or encouraging messages.

[1328] Step 8:

[1329] Server: Sends the generated learning materials to the device. The materials are sent securely via HTTPS in JSON or binary format.

[1330] Step 9:

[1331] Terminal: Analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[1332] Step 10:

[1333] Terminal: Provides learning materials to users through an interactive user interface, including interactive exercises, pronunciation practice, and feedback.

[1334] Step 11:

[1335] Users: Study a given form of English using the provided study materials, which may include audio files for pronunciation practice and conversation scripts based on specific scenarios.

[1336] Example 2

[1337] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1338] Conventional English learning systems provide uniform learning materials without considering the user's emotional state, making it difficult to provide an effective learning experience. Furthermore, they often lack the flexibility to respond to specific user needs, resulting in reduced learning efficiency.

[1339] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1340] In this invention, the server includes means for receiving a specific English learning request from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from an English database based on the analysis results, means for generating customized learning materials based on the extracted data, an emotion engine for recognizing the user's emotional state and dynamically adjusting the learning materials according to that state, and means for providing the learning materials to the user. This enables effective and flexible English learning by reflecting the user's emotional state in real time and providing an optimal learning approach.

[1341] "User" refers to a person or group of people who intend to use the System to learn a particular form of English.

[1342] A "request" refers to input data that indicates a user's request or desire regarding learning content to the system.

[1343] "Predetermined format" refers to the standardized data format required to parse and process a request.

[1344] "Analysis" refers to the process of interpreting the contents of a received request and performing the necessary processing within the system based on that information.

[1345] An "English database" refers to a collection of data that stores various data related to English (word lists, example sentences, conversation scripts, etc.).

[1346] "Related data" refers to data that is extracted from the English database based on the analysis results and is suitable for the user's learning objectives.

[1347] "Customization" refers to the process of individually tailoring learning materials to a user's specific needs and circumstances.

[1348] "Study materials" refers to various materials such as text data, audio data, and video data provided by the system for users to study English.

[1349] "Emotional state" refers to the emotions and psychological state (relaxed, stressed, etc.) that a user feels while using the system.

[1350] "Emotion engine" refers to a module within the system that recognizes the user's emotional state and dynamically adjusts learning materials accordingly.

[1351] "Dynamic adjustment" refers to the process of adaptively changing learning materials and methods in real time.

[1352] This invention provides a system that allows users to efficiently learn a specific form of English, and further combines it with an emotional engine that dynamically adjusts the learning content according to the user's emotional state. This system consists of a user terminal, a server, and a communication network. The specific configuration and operation procedure are described below.

[1353] System Overview

[1354] Hardware and Software

[1355] 1. User Device

[1356] Hardware: Personal computers, tablets, smartphones, etc.

[1357] Software: Web browser, dedicated application.

[1358] 2. Server

[1359] Hardware: High-performance cloud or on-premise servers.

[1360] Software: Web server software, database management systems (e.g., MySQL, PostgreSQL), emotion recognition engines (e.g., Microsoft Azure Emotion API, IBM Watson).

[1361] 3. Communication Network

[1362] Internet connection (e.g. Wi-Fi, 4G / 5G network)

[1363] Program processing flow

[1364] User operations

[1365] The user utilizes the device's interactive user interface to input a specific learning request, for example, "I want to learn American English business terms," ​​either by text or voice.

[1366] Terminal handling

[1367] The device receives requests entered by the user and converts them into a specific format (e.g., JSON format). The converted request includes the type of English (e.g., American English) and the learning category (e.g., business terminology).

[1368] The device sends a request to the server via the HTTPS protocol, along with the destination URL and an authentication token.

[1369] Server Processing

[1370] The server parses the request received from the device and understands its contents, which includes deserializing the JSON data.

[1371] The server runs SQL queries against an internal database to extract relevant data based on the request, such as word lists and example sentences for "American English" and "business terms."

[1372] The emotion engine determines a user's emotional state by analyzing facial expression data, voice tone, and language patterns, data collected from sensors such as the device's camera and microphone.

[1373] The server uses the extracted data and the analysis results of the emotion engine to generate customized learning materials according to the user's emotional state: for example, if the user is relaxed, it provides review materials on basic concepts, and if the user is stressed, it provides interactive exercises.

[1374] The server sends the generated learning materials to the device in JSON or binary format, securely transmitted via the HTTPS protocol.

[1375] Terminal handling

[1376] The device analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[1377] The device uses an interactive user interface to provide learning materials to the user, including interactive exercises, pronunciation practice, and feedback features.

[1378] Specific examples

[1379] Example 1: Learning business vocabulary

[1380] User: Type "I want to learn American English business vocabulary" into the terminal.

[1381] Terminal: Converts the request into JSON format and sends it to the server.

[1382] Server: Analyzes the request and extracts relevant business terms from the database.

[1383] Emotion engine: Recognizes the user's emotional state and determines the appropriate learning approach.

[1384] Server: Generates dialogue scripts and pronunciation practice audio based on business scenarios, and adopts an approach that is tailored to the user's emotional state.

[1385] Server: Sends the generated materials to the terminal.

[1386] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[1387] Users: Learn and practice business vocabulary with the learning materials.

[1388] Example 2: Learning Travel English

[1389] User: Type "I want to learn everyday conversations I can use while traveling in the UK" into the device.

[1390] Terminal: Converts the request into a specific format and sends it to the server.

[1391] Server: Analyzes the request and extracts British English conversation data.

[1392] Emotion engine: Recognizes the user's emotional state and provides relaxing content as needed.

[1393] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[1394] Server: Sends the generated materials to the terminal.

[1395] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[1396] Users: Learn and practice everyday conversations using the materials provided.

[1397] In this way, users can efficiently receive learning materials customized to their specific goals and situations. Furthermore, the emotional engine reflects the user's emotional state in real time and provides the optimal learning approach, enabling effective and flexible English learning.

[1398] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1399] Step 1:

[1400] The user inputs a learning request into the device, such as "I want to learn American English business terms." Text and voice input are possible through the user interface.

[1401] Input data: User learning request (e.g., American English business terms)

[1402] Output data: Request data containing the user's intent

[1403] Step 2:

[1404] The device converts the request received from the user into JSON format, which includes the type of English and the learning category.

[1405] Input data: Request data (text format)

[1406] Data processing: Converting request data to JSON format

[1407] Output data: Request data in JSON format

[1408] Step 3:

[1409] The terminal sends formatted request data to the server using the HTTPS protocol, which includes the destination URL and the authentication token.

[1410] Input data: JSON format request data, destination URL, authentication token

[1411] Data calculation: Secure data transmission (HTTPS protocol)

[1412] Output data: Sending request data to the server

[1413] Step 4:

[1414] The server analyzes the request data received from the terminal, understands its contents, deserializes the request, and checks for errors in the contents.

[1415] Input data: Request data in JSON format

[1416] Data processing: Deserializing and error checking the request data

[1417] Output data: Analysis results (type of English, learning category)

[1418] Step 5:

[1419] Based on the analysis results, the server runs SQL queries against an internal database to extract relevant English data.

[1420] Input data: Analysis results (type of English, learning category)

[1421] Data operations: executing SQL queries and database searches

[1422] Output data: Related English data (e.g., a list of business terms)

[1423] Step 6:

[1424] The emotion engine analyzes data collected from the device's camera and microphone to determine the user's emotional state.

[1425] Input data: User's facial expression data, voice tone, language patterns

[1426] Data Computation: Analysis with Emotion Recognition Algorithms

[1427] Output data: Emotional state (relaxed, stressed, etc.)

[1428] Step 7:

[1429] The server generates customized learning materials based on the extracted English data and the analysis results of the emotion engine, specifically incorporating the optimal learning approach according to the user's emotional state.

[1430] Input data: related English data, emotional state

[1431] Data calculation: Generation of learning materials (e.g., dialogue scripts, pronunciation practice audio)

[1432] Output data: customized learning materials

[1433] Step 8:

[1434] The server sends the generated learning materials to the device in JSON or binary format.

[1435] Input data: customized learning materials

[1436] Data processing: Format conversion and secure transmission of learning materials (HTTPS protocol)

[1437] Output data: Sending learning materials to the device

[1438] Step 9:

[1439] The device analyzes the learning materials received from the server and converts them into a format that can be provided to the user, including text display, audio playback, and video playback.

[1440] Input data: training materials (JSON or binary format)

[1441] Data processing: Analysis and format conversion of learning materials

[1442] Output data: learning materials provided to the user

[1443] Step 10:

[1444] The device provides learning materials to the user using an interactive user interface, including interactive exercises, pronunciation practice, and feedback features.

[1445] Input data: learning materials provided

[1446] Specific operations: text display, audio playback, video playback, recording function

[1447] Output data: User's interactive learning experience

[1448] Step 11:

[1449] Users use the provided learning materials to study designated English forms, practice pronunciation, and practice conversation scenarios.

[1450] Input data: learning materials

[1451] Specific actions: pronunciation practice (playing and recording audio files), scenario-based conversation practice

[1452] Output data: learning progress and outcomes

[1453] (Application example 2)

[1454] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1455] Conventional English learning systems provide uniform learning materials without considering the user's emotional state, which often reduces the user's concentration and motivation to learn. Furthermore, if the learning content does not match the user's emotional state, the learning effect is insufficient. Therefore, a flexible system that allows users to learn English effectively is needed.

[1456] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1457] In this invention, the server includes means for receiving a specific form of English learning request from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from an English database based on the analysis results, means for generating customized learning materials based on the extracted data, means for recognizing the user's emotional state and dynamically adjusting the learning materials according to the state, and means for providing the learning materials to the user. This makes it possible to provide optimal learning content according to the user's emotional state and maximize learning effectiveness.

[1458] "Means for receiving learning requests from users about a particular form of English" refers to an interface and communication device that allows a user to input and send learning requests about a particular form of English (e.g., American English business vocabulary, British English everyday conversation, etc.) to the system.

[1459] "Means for converting the request into a predetermined format" refers to a process or algorithm that converts a learning request received from a user into a specified data format (e.g., JSON).

[1460] The "means for parsing a request according to a predetermined format" refers to a program and logic for parsing formatted request data and extracting and understanding the content of the request.

[1461] The "means for extracting relevant data from an English database based on the analysis results" refers to algorithms and query execution means for searching and retrieving English data (e.g., specific words or phrases) from a database that corresponds to the analysis results of the request.

[1462] The "means for generating customized learning materials based on extracted data" refers to a program and system that creates learning materials tailored to the user based on the extracted relevant data.

[1463] "Means for recognizing the user's emotional state and dynamically adjusting learning materials according to that state" refers to an engine and algorithm that uses sensors such as cameras and microphones to analyze the user's emotional state (relaxation, stress, concentration, etc.) in real time and adjusts the learning content appropriately based on the results.

[1464] The "means for providing the learning materials to the user" refers to communication and display means for delivering the created customized learning materials to the user's terminal and enabling display and playback.

[1465] This invention is a system that allows users to efficiently learn a specific form of English, and further combines it with an emotional engine that dynamically adjusts the learning content according to the user's emotional state. The system consists of a user terminal, a server, and a communication network.

[1466] System configuration

[1467] 1. User's device

[1468] The user device can be a smartphone, VR headset, tablet, etc., and through the user interface, they can input learning requests, collect emotional data, and display learning materials. In particular, when using a VR headset, interactive English learning in a VR shop format is possible.

[1469] 2. Server

[1470] The server has the following features:

[1471] Request reception and format conversion: Receives an English learning request from the user and converts it into a specified format (e.g., JSON format).

[1472] Request analysis and data extraction: Analyze the request content and extract relevant data from the English database.

[1473] Generation of customized learning materials: Customized learning materials are generated based on the extracted data and the analysis results of the emotion engine.

[1474] Provision of learning materials: The generated learning materials are sent to the user's terminal for display and playback.

[1475] 3. Emotion Engine

[1476] The emotion engine analyzes the user's emotional state (relaxed, stressed, focused, etc.) through sensors such as cameras and microphones. This analysis data is used to dynamically adjust learning materials.

[1477] Hardware and software used

[1478] Hardware: smartphone, VR headset, camera, microphone

[1479] Software: Flask (a Python web framework), Emotion API (an emotion recognition library), database management system (e.g., MySQL or SQLite)

[1480] A concrete example of the processing flow

[1481] Example 1: Learning business vocabulary

[1482] The user uses the user interface of the terminal to input a request such as "I would like to learn American English business terms."

[1483] The terminal converts this request into JSON format and sends it to the server.

[1484] The server parses the request and extracts relevant business terms from a database.

[1485] The emotion engine recognizes the user's emotional state as "relaxed" and generates learning materials with a calm tone.

[1486] The server sends the generated learning materials to the user's terminal, and the user learns in an interactive format in a VR environment.

[1487] Example 2: Learning Travel English

[1488] The user uses the user interface of the terminal to input a request such as "I would like to learn everyday conversation that can be used while traveling in England."

[1489] The terminal converts this request into a predetermined format and sends it to the server.

[1490] The server analyzes the request content and extracts everyday conversation data from a database.

[1491] The emotion engine recognizes the user's emotional state as "stress" and generates support-oriented learning materials.

[1492] The server sends the generated learning materials to the user's terminal, and the user studies in a VR environment.

[1493] Prompt Sentence Examples

[1494] A user has submitted a request to learn "Business English." Their current emotional state is perceived as "Relaxed." Use this information to generate Business English learning materials presented in a calm tone.

[1495] This system allows users to efficiently receive English learning materials customized to their specific goals and situations. Furthermore, the system's emotional engine reflects the user's emotional state in real time and provides the optimal learning approach, resulting in an effective and flexible learning experience.

[1496] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1497] Step 1:

[1498] The user uses the device's user interface to input a request for English learning. The device receives the input request and converts it into a specified format (e.g., JSON format). Specifically, the user might input something like "I want to learn American English business terms," ​​and format it as JSON data. The input is the user's learning request, and the output is formatted JSON data.

[1499] Step 2:

[1500] The terminal sends a formatted request to the server via the HTTPS protocol. The sent data also includes the destination URL and an authentication token. In this step, the input is JSON data generated on the terminal, and the output is the data sent to the server as an HTTPS request.

[1501] Step 3:

[1502] The server analyzes the request data received from the device. The analysis includes reading the type of English and learning category (e.g., "American English," "Business Terms," ​​etc.) contained in the request. The input is the JSON data received by the server, and the output is the type of English and learning category as the analysis results.

[1503] Step 4:

[1504] The server queries the internal database based on the analysis results and extracts relevant data. Specifically, it filters data that matches "English type: American English" and "Learning category: Business terms." The input is the analysis results, and the output is the filtered relevant data.

[1505] Step 5:

[1506] The server sends data collected from the camera and microphone to the emotion engine to recognize the user's emotional state. The emotion engine performs facial expression and voice analysis to determine whether the user is relaxed or stressed. The input is sensor data from the camera and microphone, and the output is the analyzed emotional state.

[1507] Step 6:

[1508] The server generates learning materials according to the user's emotional state based on the extracted data and the analysis results of the emotion engine. For example, if the user is relaxed, it generates learning materials with a calm tone, and if the user is stressed, it generates materials with a supportive tone. The input is the filtered data and the user's emotional state, and the output is customized learning materials.

[1509] Step 7:

[1510] The server sends the generated learning materials to the terminal. The materials are sent securely via the HTTPS protocol in JSON or binary format. The input is the generated learning materials, and the output is the data sent to the terminal.

[1511] Step 8:

[1512] The terminal analyzes the learning materials received from the server and converts them into a format that can be provided to the user, such as text display, audio playback, and video playback. The input is the material received from the server, and the output is the learning materials in the interface provided to the user.

[1513] Step 9:

[1514] Users study English using the learning materials displayed on the device. Through user operation, they efficiently learn the target English form through interactive dialogue-style exercises, pronunciation practice, and feedback functions. The input is the learning materials provided by the device, and the output is the user's learning progress.

[1515] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1516] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1517] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1518] [Fourth embodiment]

[1519] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1520] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1521] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1522] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1523] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1524] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1525] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1526] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1527] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1528] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1529] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1530] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1531] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1532] The present invention provides a system that allows users to efficiently learn a specific form of English. A specific embodiment of this system will be described below.

[1533] System Overview

[1534] The system consists of a user terminal, a server, and a communication network. The terminal is operated by the user and provides an interface for sending specific requests. The server generates relevant learning materials based on the received requests and provides them to the user terminal.

[1535] Program processing flow

[1536] User submits request

[1537] User: Enters their learning interest, such as a request like "I want to learn American English business terms," ​​into the device.

[1538] Request Format by Device

[1539] Terminal: Converts the request received from the user into a predetermined format and prepares it for sending to the server, for example, converting it into JSON format.

[1540] Sending a request from the device to the server

[1541] Terminal: Sends formatted request data to the server via a secure communication protocol (e.g., HTTPS).

[1542] Server parsing of the request

[1543] Server: Analyzes the received request and understands its content (e.g., "American English," "business terms").

[1544] Server-based extraction of relevant data

[1545] Server: Extracts the necessary English data from the internal database based on the request. The data used includes audio guides, vocabulary lists, and sample business conversations.

[1546] Server-based generation of learning materials

[1547] Server: Based on the extracted data, it generates customized learning materials tailored to the user's needs. These materials are provided in the form of text, audio, video, etc.

[1548] Sending learning materials from the server to the device

[1549] Server: Sends the generated learning materials to the device.

[1550] Receiving and analyzing learning materials via terminal

[1551] Terminal: Analyzes the learning materials received from the server and displays them in a user-friendly format. An interactive user interface is used to help users study effectively.

[1552] User learning

[1553] Users: Study specific forms of English using provided learning materials, such as audio files for pronunciation practice and conversation scripts based on specific scenarios.

[1554] Specific examples

[1555] Example 1: Learning business vocabulary

[1556] User: Type "I want to learn American English business vocabulary" into the device.

[1557] Terminal: Converts the request into JSON format and sends it to the server.

[1558] Server: Analyzes the request and extracts relevant business terms from the database.

[1559] Server: Generates dialogue scripts based on business scenarios and audio for pronunciation practice.

[1560] Server: Sends the generated materials to the terminal.

[1561] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[1562] Users: Learn and practice business vocabulary with the learning materials.

[1563] Example 2: Learning Travel English

[1564] User: Type into the device, "I want to learn everyday conversation that I can use while traveling in the UK."

[1565] Terminal: Converts the request into a specific format and sends it to the server.

[1566] Server: Analyzes the request and extracts British English conversation data.

[1567] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[1568] Server: Sends the generated materials to the terminal.

[1569] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[1570] Users: Learn and practice everyday conversations using the materials provided.

[1571] This system allows users to efficiently receive English learning materials customized for specific purposes and situations, enabling learning that accommodates different pronunciations and accents and is expected to be immediately usable in real-life communication situations.

[1572] The processing flow will be explained below.

[1573] Step 1:

[1574] User: Enters a request to learn a particular form of English into an interactive user interface on a device. For example, the user might enter the text "I would like to learn American English business terms."

[1575] Step 2:

[1576] Terminal: Converts the request received from the user into a predetermined format (e.g., JSON). The converted request includes the type of English (American English) and the learning category (business term).

[1577] Step 3:

[1578] Terminal: Sends a formatted request to the server via the HTTPS protocol, along with a destination URL and an authentication token.

[1579] Step 4:

[1580] Server: Analyzes requests received from devices and parses JSON data to understand the request content. Extracts "type of English" and "learning category" from the parsed data.

[1581] Step 5:

[1582] Server: Runs SQL queries against an internal database to extract relevant data based on the request, for example filtering data for "Type of English: American English" and "Study Category: Business Terms."

[1583] Step 6:

[1584] Server: Based on the extracted data, it generates customized learning materials tailored to the user's learning style. Specifically, it generates dialogue scripts based on a business meeting scenario, audio files for pronunciation practice, and related video materials.

[1585] Step 7:

[1586] Server: Sends the generated learning materials to the device. The materials are sent securely via HTTPS in JSON or binary format.

[1587] Step 8:

[1588] Terminal: Analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[1589] Step 9:

[1590] Terminal: Provides learning materials to users through an interactive user interface, including interactive exercises, pronunciation practice, and feedback.

[1591] Step 10:

[1592] User: Study the assigned English form using the provided study materials, which may include pronunciation practice, reading dialogue scripts, and watching related videos.

[1593] Example 1

[1594] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1595] Conventional English learning systems have had difficulty efficiently processing learning requests for specific forms of English and providing users with appropriate learning materials. As a result, they have been unable to provide customized learning support tailored to individual users' needs, resulting in ineffective English learning.

[1596] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1597] In this invention, the server includes means for receiving a specific form of English learning request from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from a database based on the analysis result, means for generating customized learning materials based on the extracted data, means for providing the learning materials to the user, means for transmitting the request from the terminal to the server via a secure communication protocol, and means for transmitting the learning materials from the server to the terminal, thereby enabling efficient provision of customized learning materials tailored to the individual needs of the user.

[1598] "User" refers to a person who uses the system to learn English.

[1599] "Study Request" means a desire or request for a particular form of English that a User wishes to learn through the System.

[1600] "Means" refers to a method or apparatus designed to perform a particular function or operation.

[1601] "Predetermined format" refers to a format in which data is structured according to a particular format or standard.

[1602] "Analyzing" refers to the operation of interpreting received data and extracting necessary information from it.

[1603] A "database" refers to a system for efficiently storing, managing, and retrieving structured information.

[1604] "Related data" refers to information useful for learning that is extracted based on the user's learning request.

[1605] "Study materials" refers to learning materials provided to users to help them learn English, and includes text data, audio data, video data, and the like.

[1606] "Customized" means adapted or modified to meet the needs and requirements of a particular user.

[1607] A "communication protocol" refers to a set of rules and procedures for data communication, and in this case refers to HTTPS.

[1608] "Server" refers to a computer system that receives and analyzes user requests and generates and provides study materials.

[1609] "Terminal" refers to a device operated by a user that provides an interface for sending study requests and receiving study materials.

[1610] The present invention is a system that allows users to efficiently learn a specific form of English, and is composed of a user terminal, a server, and a communication network. A specific embodiment of this system will be described below.

[1611] System Overview

[1612] The user's terminal is operated by the user and provides an interface for sending specific requests. The server is responsible for generating relevant learning materials based on the received requests and providing them to the user's terminal.

[1613] Hardware and software used

[1614] Hardware:

[1615] User's device (e.g., smartphone, tablet, PC)

[1616] Server (a computer server capable of high-performance calculations and data processing)

[1617] software:

[1618] User Interface (Web Browser, Mobile Application)

[1619] Server-side programs (Python, JavaScript, Node.js)

[1620] Database (MySQL, PostgreSQL)

[1621] Communication protocol (HTTPS)

[1622] Process Overview

[1623] 1. User submits a request

[1624] Users input their learning interests into the device, for example, requesting to learn business English or travel English.

[1625] 2. Request Format by Device

[1626] The terminal converts the request received from the user into a specified format (such as JSON format).

[1627] 3. Sending a request from the device to the server

[1628] The device sends the formatted request to the server over HTTPS.

[1629] 4. Server Parsing of the Request

[1630] The server analyzes the received request and understands its contents.

[1631] 5. Server Extraction of Relevant Data

[1632] The server extracts the necessary data from its internal database based on the request.

[1633] 6. Server-based generation of learning materials

[1634] The server generates customized learning materials based on the extracted data.

[1635] 7. Sending learning materials from the server to the device

[1636] The server transmits the generated study materials to the terminal.

[1637] 8. Receiving and analyzing learning materials by device

[1638] The terminal analyzes the learning materials received from the server and displays them in an easy-to-understand manner for the user.

[1639] 9. User Learning

[1640] The user studies using the provided study materials.

[1641] Specific examples

[1642] Example 1: Learning business vocabulary

[1643] User: Type "I want to learn American English business vocabulary" into the device.

[1644] Terminal: Converts the request into JSON format and sends it to the server.

[1645] Server: Analyzes the request and extracts relevant business terms from the database.

[1646] Server: Generates dialogue scripts based on business scenarios and audio for pronunciation practice.

[1647] Server: Sends the generated materials to the terminal.

[1648] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[1649] Users: Learn and practice business vocabulary with the learning materials.

[1650] Example prompt: "Please generate learning materials for American English business terminology."

[1651] Example 2: Learning Travel English

[1652] User: Type into the device, "I want to learn everyday conversation that I can use while traveling in the UK."

[1653] Terminal: Converts the request into a specific format and sends it to the server.

[1654] Server: Analyzes the request and extracts British English conversation data.

[1655] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[1656] Server: Sends the generated materials to the terminal.

[1657] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[1658] Users: Learn and practice everyday conversations using the materials provided.

[1659] This system allows users to efficiently receive English learning materials customized for specific purposes and situations, enabling learning that accommodates different pronunciations and accents, and is expected to be immediately usable in real-life communication situations.

[1660] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1661] Step 1: User submits request

[1662] The user inputs what they want to learn into the device. Specifically, they write the type of English they want to learn and its purpose (for example, "I want to learn American English business terms") in the input field and click the "Submit" button.

[1663] Input: Learning motivation and request details

[1664] Output: Request data entered on the terminal

[1665] Step 2: Formatting the request via the terminal

[1666] The terminal converts the request received from the user into a specific format (e.g., JSON format), which allows the server to accurately interpret the request content.

[1667] Input: The raw request data entered by the user

[1668] Output: Request data in JSON format

[1669] Specific operation: Structures request data using JavaScript or Python and converts it to JSON format.

[1670] Step 3: Sending a request from the device to the server

[1671] The terminal sends the formatted request data to the server via HTTPS, which allows the request data to be transmitted securely to the server.

[1672] Input: Request data in JSON format

[1673] Output: Request data sent to the server

[1674] Specific behavior: Sends a request to the server using the HTTPS protocol.

[1675] Step 4: Server Parses the Request

[1676] The server analyzes the received request data and understands its contents. For example, from a request such as "I want to learn American English business terms," ​​it extracts "Type of English: American English" and "Use: Business terms."

[1677] Input: JSON data sent to the server

[1678] Output: Extracted elements of the request content (type of English, purpose, etc.)

[1679] Specific operation: Parse the JSON data using a program such as Python and extract the necessary information.

[1680] Step 5: Server Extraction of Relevant Data

[1681] The server extracts relevant data from its internal database based on the request content. For example, based on the information "American English" and "business terminology," it retrieves a list of related business terms and audio guides.

[1682] Input: Extracted request content

[1683] Output: Relevant data extracted from the database

[1684] What it does: Retrieves relevant information from a database using SQL queries.

[1685] Step 6: Server generates learning materials

[1686] The server then generates customized learning materials based on the extracted data, which are tailored to the user's needs. These materials consist of text, audio, and video data.

[1687] Input: Extracted relevant data

[1688] Output: Learning materials suitable for the user

[1689] What it does: Consolidates and formats data using text and speech generation engines.

[1690] Step 7: Sending learning materials from the server to the device

[1691] The server packages the generated learning materials in JSON format and sends them back to the terminal via HTTPS.

[1692] Input: Generated learning materials

[1693] Output: Learning materials in JSON format sent to the device

[1694] Specific operation: Sends data to the device using HTTPS.

[1695] Step 8: Receiving and analyzing the learning materials on the device

[1696] The terminal parses the JSON data received from the server and displays the contents in an interactive user interface, allowing users to easily view the materials.

[1697] Input: JSON data sent from the server

[1698] Output: Learning materials displayed in a user interface

[1699] What it does: It parses the data using JavaScript and displays it in the interface using HTML and CSS.

[1700] Step 9: User Training

[1701] Users study using learning materials displayed on their devices, including audio files for pronunciation practice and conversation scripts based on specific scenarios. They can also get feedback on their pronunciation using audio playback and recording functions.

[1702] Input: Study materials

[1703] Output: Learning outcomes (improvement of knowledge and skills)

[1704] Specific actions: Playing audio files, displaying text, and conducting interactive practice sessions.

[1705] In this way, the system can efficiently provide users with English learning materials that are customized to their individual needs.

[1706] (Application example 1)

[1707] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1708] In food delivery, delivery workers often have difficulty communicating smoothly with English-speaking customers, which can lead to lower customer satisfaction and delivery delays, making it a major challenge for businesses.

[1709] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1710] In this invention, the server includes means for receiving a learning request for a specific form of English from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from an English database based on the analysis results, means for generating customized learning materials based on the extracted data, means for including English phrases used in delivery situations in the generated learning materials, means for adding audio guidance to the learning materials using speech synthesis technology, and means for providing the learning materials to the user. This enables delivery personnel to learn English phrases required for specific delivery situations and use them in actual delivery situations.

[1711] The "means for receiving a learning request from a user regarding a specific form of English" is a mechanism including an interface through which a user inputs a request to learn a specific form of English and the system receives the request.

[1712] The "means for converting the request into a predetermined format" refers to a process for converting a request entered by a user into a standardized data format within the system (e.g., JSON).

[1713] The "means for analyzing a request according to a predetermined format" refers to an algorithm or software for analyzing and understanding the request content based on the converted format.

[1714] "Means for extracting relevant data from an English database based on the analysis results" refers to the process of searching and extracting data related to English learning from a database based on the request analysis results.

[1715] "Means for generating customized learning materials based on extracted data" refers to a method for using extracted English data to create specific learning materials (text, audio, video, etc.) tailored to the user's learning goals and situation.

[1716] "Means for including English phrases used in delivery situations in the generated learning materials" refers to the process of incorporating English phrases required in specific delivery situations, such as food delivery, into the learning materials.

[1717] "Means for adding audio guidance to study materials using speech synthesis technology" refers to a method for adding audio guidance corresponding to the generated study materials using speech synthesis technology.

[1718] The "means for providing the learning materials to the user" refers to a mechanism for transmitting the finalized learning materials to the user's device so that the user can use them.

[1719] The system of this invention is designed to enable users to efficiently learn and use English in food delivery situations. The system is primarily composed of terminals, including smartphones, a server, and a communication network.

[1720] Hardware and Software

[1721] Hardware: Smartphone

[1722] software:

[1723] Development environment: Android Studio, Xcode

[1724] Backend: Node.js, Express.js

[1725] Database: MongoDB

[1726] Communication: HTTPS, REST API

[1727] Speech synthesis: Google Text-to-Speech API

[1728] Program processing overview

[1729] User submits request

[1730] Users use their smartphones to submit learning requests for specific English phrases, such as "I want to learn English phrases that can be used in delivery situations," to the application.

[1731] Request format conversion

[1732] The device converts this request into a predetermined format such as JSON and prepares it to be sent to the server.

[1733] Submitting a Request

[1734] The formatted request data is sent securely to the server over HTTPS.

[1735] Server parsing of the request

[1736] The server analyzes the received request and understands its contents, using a natural language processing engine such as the Google Cloud Natural Language API.

[1737] Extracting relevant data

[1738] Based on the analysis results, the server searches and extracts relevant English phrases and learning data from its internal MongoDB database.

[1739] Generating learning materials

[1740] Based on the extracted data, the server generates customized learning materials tailored to the user's needs, including English phrases and audio guides for delivery situations. The audio guides are generated using the Google Text-to-Speech API.

[1741] Providing learning materials

[1742] The generated learning materials are sent to the device in JSON format and provided through a user interface, allowing users to study text, audio, and video data through a smartphone app.

[1743] Specific examples

[1744] Prompt Sentence Examples

[1745] "What phrases should I use when delivering a package to a customer?"

[1746] "English to explain delivery delays"

[1747] This allows users to learn English phrases needed for specific delivery situations and use them in actual delivery situations. This system solves the problem of communicating smoothly with English-speaking customers and contributes to improving customer satisfaction.

[1748] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1749] Step 1:

[1750] A user launches the app on their smartphone and enters a specific learning request, such as "I want to learn English phrases that can be used in delivery situations." This request is received through the user interface.

[1751] Step 2:

[1752] Converts the request received by the terminal into a specified format (e.g. JSON). The input is a text request from the user, and the output is the formatted request data.

[1753] Step 3:

[1754] The terminal sends formatted request data to the server using a secure communication protocol (HTTPS). The input is the formatted request data, and the output is the request sent to the server.

[1755] Step 4:

[1756] The server analyzes the request it receives and understands its content. This analysis is performed using a natural language processing engine such as Google Cloud Natural Language API. The input is formatted request data, and the output obtained from the analysis is an understanding of the content: "English phrases that can be used in delivery situations."

[1757] Step 5:

[1758] The server searches and extracts related English phrase data from an internal MongoDB database based on the analysis results. The input is the analysis results, and the output is related English phrase data.

[1759] Step 6:

[1760] The server generates customized learning materials based on the extracted data, tailored to the user's needs. These materials include English phrases used in delivery situations and audio guides. The audio guides are generated using the Google Text-to-Speech API. The input is the extracted English phrase data and analysis results, and the output is customized learning materials.

[1761] Step 7:

[1762] The server sends the generated learning materials to the terminal. The input is the generated learning materials, and the output is the transmission of the materials to the terminal.

[1763] Step 8:

[1764] The terminal displays the received learning materials to the user. Through an interactive user interface, the user can view and study text, audio guides, and video data. The input is the received learning materials, and the output is the learning content provided to the user.

[1765] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1766] The present invention provides a system that allows users to efficiently learn a specific form of English, combined with an emotional engine that dynamically adjusts the learning content according to the user's emotional state.

[1767] System Overview

[1768] The system consists of a user's device, a server, and a communication network. The device is operated by the user and provides an interface for sending specific requests. The server generates relevant learning materials based on the received requests and provides them to the user's device. Furthermore, the system incorporates an emotion engine that recognizes the user's emotional state and dynamically adjusts the learning materials accordingly.

[1769] Program processing flow

[1770] User submits request

[1771] User: Inputs a request for learning, such as "I want to learn American English business terms," ​​into the terminal via the terminal's interactive user interface.

[1772] Request Format by Device

[1773] Terminal: Converts the request received from the user into a predetermined format (e.g., JSON). The converted request includes the type of English (American English) and the learning category (business term).

[1774] Sending a request from the device to the server

[1775] Terminal: Sends a formatted request to the server via the HTTPS protocol, along with a destination URL and an authentication token.

[1776] Server parsing of the request

[1777] Server: Analyzes requests received from devices and understands their content (e.g., "American English," "business terms").

[1778] Server-based extraction of relevant data

[1779] Server: Runs SQL queries against an internal database to extract relevant data based on the request, for example filtering data for "Type of English: American English" and "Study Category: Business Terms."

[1780] Emotion recognition by emotion engine

[1781] Emotion engine: Determines the user's emotional state by analyzing facial expressions, voice tone, and language patterns. Data is collected from sensors such as the device's camera and microphone.

[1782] Server-based generation of learning materials

[1783] Server: Based on the extracted data and the analysis results of the emotion engine, the server generates customized learning materials according to the user's emotional state. Specifically, it adjusts the learning content and approach depending on whether the user is relaxed or stressed.

[1784] Sending learning materials from the server to the device

[1785] Server: Sends the generated learning materials to the device. The materials are sent securely via HTTPS in JSON or binary format.

[1786] Receiving and analyzing learning materials via terminal

[1787] Terminal: Analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[1788] Providing data to users via terminals

[1789] Terminal: Provides learning materials to users through an interactive user interface, including interactive exercises, pronunciation practice, and feedback.

[1790] User learning

[1791] Users: Study a given form of English using the provided study materials, which may include audio files for pronunciation practice and conversation scripts based on specific scenarios.

[1792] Specific examples

[1793] Example 1: Learning business vocabulary

[1794] User: Type "I want to learn American English business vocabulary" into the device.

[1795] Terminal: Converts the request into JSON format and sends it to the server.

[1796] Server: Analyzes the request and extracts relevant business terms from the database.

[1797] Emotion engine: Recognizes the user's emotional state and determines the appropriate learning approach.

[1798] Server: Generates dialogue scripts and pronunciation practice audio based on business scenarios, and adopts an approach that is tailored to the user's emotional state.

[1799] Server: Sends the generated materials to the terminal.

[1800] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[1801] Users: Learn and practice business vocabulary with the learning materials.

[1802] Example 2: Learning Travel English

[1803] User: Type into the device, "I want to learn everyday conversation that I can use while traveling in the UK."

[1804] Terminal: Converts the request into a specific format and sends it to the server.

[1805] Server: Analyzes the request and extracts British English conversation data.

[1806] Emotion engine: Recognizes the user's emotional state and provides relaxing content as needed.

[1807] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[1808] Server: Sends the generated materials to the terminal.

[1809] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[1810] Users: Learn and practice everyday conversations using the materials provided.

[1811] This system allows users to efficiently receive English learning materials customized to their specific goals and situations. Furthermore, the system's emotional engine reflects the user's emotional state in real time and provides optimal learning approaches, enabling an effective and flexible learning experience.

[1812] The processing flow will be explained below.

[1813] Step 1:

[1814] User: Enters a request to learn a particular form of English into an interactive user interface on a device. For example, the user might enter the text "I would like to learn American English business terms."

[1815] Step 2:

[1816] Terminal: Converts the request received from the user into a predetermined format (e.g., JSON). The converted request includes the type of English (American English) and the learning category (business term).

[1817] Step 3:

[1818] Terminal: Sends a formatted request to the server via the HTTPS protocol, along with a destination URL and an authentication token.

[1819] Step 4:

[1820] Server: Analyzes requests received from devices and parses JSON data to understand their contents. Extracts "type of English" and "learning category" from the parsed data.

[1821] Step 5:

[1822] Server: Runs SQL queries against an internal database to extract relevant data based on the request, for example filtering data for "Type of English: American English" and "Study Category: Business Terms."

[1823] Step 6:

[1824] Emotion engine: Recognizes the user's emotional state. It determines the user's emotional state by analyzing their facial expressions, voice tone, and language patterns. Data is collected from sensors such as the device's camera and microphone.

[1825] Step 7:

[1826] Server: Based on the extracted data and the analysis results of the emotion engine, it generates customized learning materials according to the user's emotional state. For example, if the user is relaxed, it provides regular learning materials, but if the user is stressed, it adds relaxing content or encouraging messages.

[1827] Step 8:

[1828] Server: Sends the generated learning materials to the device. The materials are sent securely via HTTPS in JSON or binary format.

[1829] Step 9:

[1830] Terminal: Analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[1831] Step 10:

[1832] Terminal: Provides learning materials to users through an interactive user interface, including interactive exercises, pronunciation practice, and feedback.

[1833] Step 11:

[1834] Users: Study a given form of English using the provided study materials, which may include audio files for pronunciation practice and conversation scripts based on specific scenarios.

[1835] Example 2

[1836] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1837] Conventional English learning systems provide uniform learning materials without considering the user's emotional state, making it difficult to provide an effective learning experience. Furthermore, they often lack the flexibility to respond to specific user needs, resulting in reduced learning efficiency.

[1838] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1839] In this invention, the server includes means for receiving a specific English learning request from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from an English database based on the analysis results, means for generating customized learning materials based on the extracted data, an emotion engine for recognizing the user's emotional state and dynamically adjusting the learning materials according to that state, and means for providing the learning materials to the user. This enables effective and flexible English learning by reflecting the user's emotional state in real time and providing an optimal learning approach.

[1840] "User" refers to a person or group of people who intend to use the System to learn a particular form of English.

[1841] A "request" refers to input data that indicates a user's request or desire regarding learning content to the system.

[1842] "Predetermined format" refers to the standardized data format required to parse and process a request.

[1843] "Analysis" refers to the process of interpreting the contents of a received request and performing the necessary processing within the system based on that information.

[1844] An "English database" refers to a collection of data that stores various data related to English (word lists, example sentences, conversation scripts, etc.).

[1845] "Related data" refers to data that is extracted from the English database based on the analysis results and is suitable for the user's learning objectives.

[1846] "Customization" refers to the process of individually tailoring learning materials to a user's specific needs and circumstances.

[1847] "Study materials" refers to various materials such as text data, audio data, and video data provided by the system for users to study English.

[1848] "Emotional state" refers to the emotions and psychological state (relaxed, stressed, etc.) that a user feels while using the system.

[1849] "Emotion engine" refers to a module within the system that recognizes the user's emotional state and dynamically adjusts learning materials accordingly.

[1850] "Dynamic adjustment" refers to the process of adaptively changing learning materials and methods in real time.

[1851] This invention provides a system that allows users to efficiently learn a specific form of English, and further combines it with an emotional engine that dynamically adjusts the learning content according to the user's emotional state. This system consists of a user terminal, a server, and a communication network. The specific configuration and operation procedure are described below.

[1852] System Overview

[1853] Hardware and Software

[1854] 1. User Device

[1855] Hardware: Personal computers, tablets, smartphones, etc.

[1856] Software: Web browser, dedicated application.

[1857] 2. Server

[1858] Hardware: High-performance cloud or on-premise servers.

[1859] Software: Web server software, database management systems (e.g., MySQL, PostgreSQL), emotion recognition engines (e.g., Microsoft Azure Emotion API, IBM Watson).

[1860] 3. Communication Network

[1861] Internet connection (e.g. Wi-Fi, 4G / 5G network)

[1862] Program processing flow

[1863] User operations

[1864] The user utilizes the device's interactive user interface to input a specific learning request, for example, "I want to learn American English business terms," ​​either by text or voice.

[1865] Terminal handling

[1866] The device receives requests entered by the user and converts them into a specific format (e.g., JSON format). The converted request includes the type of English (e.g., American English) and the learning category (e.g., business terminology).

[1867] The device sends a request to the server via the HTTPS protocol, along with the destination URL and an authentication token.

[1868] Server Processing

[1869] The server parses the request received from the device and understands its contents, which includes deserializing the JSON data.

[1870] The server runs SQL queries against an internal database to extract relevant data based on the request, such as word lists and example sentences for "American English" and "business terms."

[1871] The emotion engine determines a user's emotional state by analyzing facial expression data, voice tone, and language patterns, data collected from sensors such as the device's camera and microphone.

[1872] The server uses the extracted data and the analysis results of the emotion engine to generate customized learning materials according to the user's emotional state: for example, if the user is relaxed, it provides review materials on basic concepts, and if the user is stressed, it provides interactive exercises.

[1873] The server sends the generated learning materials to the device in JSON or binary format, securely transmitted via the HTTPS protocol.

[1874] Terminal handling

[1875] The device analyzes the learning materials received from the server and converts them into a format that can be presented to the user, including text display, audio playback, and video playback.

[1876] The device uses an interactive user interface to provide learning materials to the user, including interactive exercises, pronunciation practice, and feedback features.

[1877] Specific examples

[1878] Example 1: Learning business vocabulary

[1879] User: Type "I want to learn American English business vocabulary" into the terminal.

[1880] Terminal: Converts the request into JSON format and sends it to the server.

[1881] Server: Analyzes the request and extracts relevant business terms from the database.

[1882] Emotion engine: Recognizes the user's emotional state and determines the appropriate learning approach.

[1883] Server: Generates dialogue scripts and pronunciation practice audio based on business scenarios, and adopts an approach that is tailored to the user's emotional state.

[1884] Server: Sends the generated materials to the terminal.

[1885] Terminal: Provides users with interactive materials and feedback for pronunciation practice.

[1886] Users: Learn and practice business vocabulary with the learning materials.

[1887] Example 2: Learning Travel English

[1888] User: Type "I want to learn everyday conversations I can use while traveling in the UK" into the device.

[1889] Terminal: Converts the request into a specific format and sends it to the server.

[1890] Server: Analyzes the request and extracts British English conversation data.

[1891] Emotion engine: Recognizes the user's emotional state and provides relaxing content as needed.

[1892] Server: Generates learning materials including situation-specific conversation examples and pronunciation guides.

[1893] Server: Sends the generated materials to the terminal.

[1894] Terminal: Provides users with an interface that supports learning through audio playback and recording functions.

[1895] Users: Learn and practice everyday conversations using the materials provided.

[1896] In this way, users can efficiently receive learning materials customized to their specific goals and situations. Furthermore, the emotional engine reflects the user's emotional state in real time and provides the optimal learning approach, enabling effective and flexible English learning.

[1897] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1898] Step 1:

[1899] The user inputs a learning request into the device, such as "I want to learn American English business terms." Text and voice input are possible through the user interface.

[1900] Input data: User learning request (e.g., American English business terms)

[1901] Output data: Request data containing the user's intent

[1902] Step 2:

[1903] The device converts the request received from the user into JSON format, which includes the type of English and the learning category.

[1904] Input data: Request data (text format)

[1905] Data processing: Converting request data to JSON format

[1906] Output data: Request data in JSON format

[1907] Step 3:

[1908] The terminal sends formatted request data to the server using the HTTPS protocol, which includes the destination URL and the authentication token.

[1909] Input data: JSON format request data, destination URL, authentication token

[1910] Data calculation: Secure data transmission (HTTPS protocol)

[1911] Output data: Sending request data to the server

[1912] Step 4:

[1913] The server analyzes the request data received from the terminal, understands its contents, deserializes the request, and checks for errors in the contents.

[1914] Input data: Request data in JSON format

[1915] Data processing: Deserializing and error checking the request data

[1916] Output data: Analysis results (type of English, learning category)

[1917] Step 5:

[1918] Based on the analysis results, the server runs SQL queries against an internal database to extract relevant English data.

[1919] Input data: Analysis results (type of English, learning category)

[1920] Data operations: executing SQL queries and database searches

[1921] Output data: Related English data (e.g., a list of business terms)

[1922] Step 6:

[1923] The emotion engine analyzes data collected from the device's camera and microphone to determine the user's emotional state.

[1924] Input data: User's facial expression data, voice tone, language patterns

[1925] Data Computation: Analysis with Emotion Recognition Algorithms

[1926] Output data: Emotional state (relaxed, stressed, etc.)

[1927] Step 7:

[1928] The server generates customized learning materials based on the extracted English data and the analysis results of the emotion engine, specifically incorporating the optimal learning approach according to the user's emotional state.

[1929] Input data: related English data, emotional state

[1930] Data calculation: Generation of learning materials (e.g., dialogue scripts, pronunciation practice audio)

[1931] Output data: customized learning materials

[1932] Step 8:

[1933] The server sends the generated learning materials to the device in JSON or binary format.

[1934] Input data: customized learning materials

[1935] Data processing: Format conversion and secure transmission of learning materials (HTTPS protocol)

[1936] Output data: Sending learning materials to the device

[1937] Step 9:

[1938] The device analyzes the learning materials received from the server and converts them into a format that can be provided to the user, including text display, audio playback, and video playback.

[1939] Input data: training materials (JSON or binary format)

[1940] Data processing: Analysis and format conversion of learning materials

[1941] Output data: learning materials provided to the user

[1942] Step 10:

[1943] The device provides learning materials to the user using an interactive user interface, including interactive exercises, pronunciation practice, and feedback features.

[1944] Input data: learning materials provided

[1945] Specific operations: text display, audio playback, video playback, recording function

[1946] Output data: User's interactive learning experience

[1947] Step 11:

[1948] Users use the provided learning materials to study designated English forms, practice pronunciation, and practice conversation scenarios.

[1949] Input data: learning materials

[1950] Specific actions: pronunciation practice (playing and recording audio files), scenario-based conversation practice

[1951] Output data: learning progress and outcomes

[1952] (Application example 2)

[1953] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1954] Conventional English learning systems provide uniform learning materials without considering the user's emotional state, which often reduces the user's concentration and motivation to learn. Furthermore, if the learning content does not match the user's emotional state, the learning effect is insufficient. Therefore, a flexible system that allows users to learn English effectively is needed.

[1955] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1956] In this invention, the server includes means for receiving a specific form of English learning request from a user, means for converting the request into a predetermined format, means for analyzing the request according to the predetermined format, means for extracting relevant data from an English database based on the analysis results, means for generating customized learning materials based on the extracted data, means for recognizing the user's emotional state and dynamically adjusting the learning materials according to the state, and means for providing the learning materials to the user. This makes it possible to provide optimal learning content according to the user's emotional state and maximize learning effectiveness.

[1957] "Means for receiving learning requests from users about a particular form of English" refers to an interface and communication device that allows a user to input and send learning requests about a particular form of English (e.g., American English business vocabulary, British English everyday conversation, etc.) to the system.

[1958] "Means for converting the request into a predetermined format" refers to a process or algorithm that converts a learning request received from a user into a specified data format (e.g., JSON).

[1959] The "means for parsing a request according to a predetermined format" refers to a program and logic for parsing formatted request data and extracting and understanding the content of the request.

[1960] The "means for extracting relevant data from an English database based on the analysis results" refers to algorithms and query execution means for searching and retrieving English data (e.g., specific words or phrases) from a database that corresponds to the analysis results of the request.

[1961] The "means for generating customized learning materials based on extracted data" refers to a program and system that creates learning materials tailored to the user based on the extracted relevant data.

[1962] "Means for recognizing the user's emotional state and dynamically adjusting learning materials according to that state" refers to an engine and algorithm that uses sensors such as cameras and microphones to analyze the user's emotional state (relaxation, stress, concentration, etc.) in real time and adjusts the learning content appropriately based on the results.

[1963] The "means for providing the learning materials to the user" refers to communication and display means for delivering the created customized learning materials to the user's terminal and enabling display and playback.

[1964] This invention is a system that allows users to efficiently learn a specific form of English, and further combines it with an emotional engine that dynamically adjusts the learning content according to the user's emotional state. The system consists of a user terminal, a server, and a communication network.

[1965] System configuration

[1966] 1. User's device

[1967] The user device can be a smartphone, VR headset, tablet, etc., and through the user interface, they can input learning requests, collect emotional data, and display learning materials. In particular, when using a VR headset, interactive English learning in a VR shop format is possible.

[1968] 2. Server

[1969] The server has the following features:

[1970] Request reception and format conversion: Receives an English learning request from the user and converts it into a specified format (e.g., JSON format).

[1971] Request analysis and data extraction: Analyze the request content and extract relevant data from the English database.

[1972] Generation of customized learning materials: Customized learning materials are generated based on the extracted data and the analysis results of the emotion engine.

[1973] Provision of learning materials: The generated learning materials are sent to the user's terminal for display and playback.

[1974] 3. Emotion Engine

[1975] The emotion engine analyzes the user's emotional state (relaxed, stressed, focused, etc.) through sensors such as cameras and microphones. This analysis data is used to dynamically adjust learning materials.

[1976] Hardware and software used

[1977] Hardware: smartphone, VR headset, camera, microphone

[1978] Software: Flask (a Python web framework), Emotion API (an emotion recognition library), database management system (e.g., MySQL or SQLite)

[1979] A concrete example of the processing flow

[1980] Example 1: Learning business vocabulary

[1981] The user uses the user interface of the terminal to input a request such as "I would like to learn American English business terms."

[1982] The terminal converts this request into JSON format and sends it to the server.

[1983] The server parses the request and extracts relevant business terms from a database.

[1984] The emotion engine recognizes the user's emotional state as "relaxed" and generates learning materials with a calm tone.

[1985] The server sends the generated learning materials to the user's terminal, and the user learns in an interactive format in a VR environment.

[1986] Example 2: Learning Travel English

[1987] The user uses the user interface of the terminal to input a request such as "I would like to learn everyday conversation that can be used while traveling in England."

[1988] The terminal converts this request into a predetermined format and sends it to the server.

[1989] The server analyzes the request content and extracts everyday conversation data from a database.

[1990] The emotion engine recognizes the user's emotional state as "stress" and generates support-oriented learning materials.

[1991] The server sends the generated learning materials to the user's terminal, and the user studies in a VR environment.

[1992] Prompt Sentence Examples

[1993] A user has submitted a request to learn "Business English." Their current emotional state is perceived as "Relaxed." Use this information to generate Business English learning materials presented in a calm tone.

[1994] This system allows users to efficiently receive English learning materials customized to their specific goals and situations. Furthermore, the system's emotional engine reflects the user's emotional state in real time and provides the optimal learning approach, resulting in an effective and flexible learning experience.

[1995] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1996] Step 1:

[1997] The user uses the device's user interface to input a request for English learning. The device receives the input request and converts it into a specified format (e.g., JSON format). Specifically, the user might input something like "I want to learn American English business terms," ​​and format it as JSON data. The input is the user's learning request, and the output is formatted JSON data.

[1998] Step 2:

[1999] The terminal sends a formatted request to the server via the HTTPS protocol. The sent data also includes the destination URL and an authentication token. In this step, the input is JSON data generated on the terminal, and the output is the data sent to the server as an HTTPS request.

[2000] Step 3:

[2001] The server analyzes the request data received from the device. The analysis includes reading the type of English and learning category (e.g., "American English," "Business Terms," ​​etc.) contained in the request. The input is the JSON data received by the server, and the output is the type of English and learning category as the analysis results.

[2002] Step 4:

[2003] The server queries the internal database based on the analysis results and extracts relevant data. Specifically, it filters data that matches "English type: American English" and "Learning category: Business terms." The input is the analysis results, and the output is the filtered relevant data.

[2004] Step 5:

[2005] The server sends data collected from the camera and microphone to the emotion engine to recognize the user's emotional state. The emotion engine performs facial expression and voice analysis to determine whether the user is relaxed or stressed. The input is sensor data from the camera and microphone, and the output is the analyzed emotional state.

[2006] Step 6:

[2007] The server generates learning materials according to the user's emotional state based on the extracted data and the analysis results of the emotion engine. For example, if the user is relaxed, it generates learning materials with a calm tone, and if the user is stressed, it generates materials with a supportive tone. The input is the filtered data and the user's emotional state, and the output is customized learning materials.

[2008] Step 7:

[2009] The server sends the generated learning materials to the terminal. The materials are sent securely via the HTTPS protocol in JSON or binary format. The input is the generated learning materials, and the output is the data sent to the terminal.

[2010] Step 8:

[2011] The terminal analyzes the learning materials received from the server and converts them into a format that can be provided to the user, such as text display, audio playback, and video playback. The input is the material received from the server, and the output is the learning materials in the interface provided to the user.

[2012] Step 9:

[2013] Users study English using the learning materials displayed on the device. Through user operation, they efficiently learn the target English form through interactive dialogue-style exercises, pronunciation practice, and feedback functions. The input is the learning materials provided by the device, and the output is the user's learning progress.

[2014] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2015] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2016] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2017] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2018] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2019] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2020] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2021] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2022] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2023] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2024] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2025] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2026] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2027] 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.

[2028] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2029] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2030] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2031] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2032] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2033] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2034] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2035] The following is further disclosed regarding the above embodiment.

[2036] (Claim 1)

[2037] means for receiving a learning request from a user regarding a particular form of English;

[2038] means for converting the request into a predetermined format;

[2039] means for parsing requests according to a predetermined format;

[2040] means for extracting relevant data from the English database based on the analysis results;

[2041] means for generating customized learning materials based on the extracted data;

[2042] means for providing said learning materials to a user;

[2043] A system including:

[2044] (Claim 2)

[2045] 2. The system according to claim 1, wherein the means for receiving a request from a user accepts the request via an interactive user interface.

[2046] (Claim 3)

[2047] 10. The system of claim 1, wherein the customized learning materials include text data, audio data, and video data, and are adapted according to a user's learning style.

[2048] "Example 1"

[2049] (Claim 1)

[2050] means for receiving a learning request from a user regarding a particular form of English;

[2051] means for converting the request into a predetermined format;

[2052] means for parsing requests according to a predetermined format;

[2053] means for extracting relevant data from the database based on the analysis results;

[2054] means for generating customized learning materials based on the extracted data;

[2055] means for providing said learning materials to a user;

[2056] means for transmitting a request from the terminal to a server via a secure communications protocol;

[2057] means for transmitting learning materials from the server to the terminal;

[2058] A system including:

[2059] (Claim 2)

[2060] 2. The system according to claim 1, wherein the means for receiving a request from a user accepts the request via an interactive user interface.

[2061] (Claim 3)

[2062] 10. The system of claim 1, wherein the customized learning materials include text data, audio data, and video data, and are adapted according to a user's learning style.

[2063] "Application Example 1"

[2064] (Claim 1)

[2065] means for receiving a learning request from a user regarding a particular form of English;

[2066] means for converting the request into a predetermined format;

[2067] means for parsing requests according to a predetermined format;

[2068] means for extracting relevant data from the English database based on the analysis results;

[2069] means for generating customized learning materials based on the extracted data;

[2070] A means of including English phrases used in delivery situations in the generated learning materials;

[2071] a means of adding audio descriptions to learning materials using text-to-speech technology;

[2072] means for providing said learning materials to a user;

[2073] A system including:

[2074] (Claim 2)

[2075] 2. The system according to claim 1, wherein the means for receiving a request from a user accepts the request via an interactive user interface.

[2076] (Claim 3)

[2077] 10. The system of claim 1, wherein the customized learning materials include text data, audio data, and video data, and are adapted according to a user's learning style.

[2078] "Example 2: Combining Emotion Engines"

[2079] (Claim 1)

[2080] means for receiving a learning request from a user regarding a particular form of English;

[2081] means for converting the request into a predetermined format;

[2082] means for parsing requests according to a predetermined format;

[2083] means for extracting relevant data from the English database based on the analysis results;

[2084] means for generating customized learning materials based on the extracted data;

[2085] an emotion engine that recognizes the user's emotional state and dynamically adjusts learning materials accordingly;

[2086] means for providing said learning materials to a user;

[2087] A system including:

[2088] (Claim 2)

[2089] 2. The system according to claim 1, wherein the means for receiving a request from a user accepts the request via an interactive user interface.

[2090] (Claim 3)

[2091] 10. The system of claim 1, wherein the customized learning materials include text data, audio data, and video data, and are adapted according to a user's learning style.

[2092] "Application example 2 when combining emotion engines"

[2093] (Claim 1)

[2094] means for receiving a learning request from a user regarding a particular form of English;

[2095] means for converting the request into a predetermined format;

[2096] means for parsing requests according to a predetermined format;

[2097] means for extracting relevant data from the English database based on the analysis results;

[2098] means for generating customized learning materials based on the extracted data;

[2099] means for recognizing a user's emotional state and dynamically adjusting learning materials in response to that state;

[2100] means for providing said learning materials to a user;

[2101] A system including:

[2102] (Claim 2)

[2103] 2. The system according to claim 1, wherein the means for receiving a request from a user accepts the request via an interactive user interface.

[2104] (Claim 3)

[2105] 10. The system of claim 1, wherein the customized learning materials include text data, audio data, and video data, and are adapted according to a user's learning style. [Explanation of symbols]

[2106] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving a learning request from a user regarding a particular form of English; means for converting the request into a predetermined format; means for parsing requests according to a predetermined format; means for extracting relevant data from the English database based on the analysis results; means for generating customized learning materials based on the extracted data; means for providing said learning materials to a user; A system including:

2. 2. The system of claim 1, wherein the means for receiving a request from a user accepts the request via an interactive user interface.

3. 10. The system of claim 1, wherein the customized learning materials include text data, audio data, and video data, and are adapted according to a user's learning style.

Images