System

Abstract

A system is provided.SOLUTION: The system includes a user means for inputting text data, a server means for generating quiz question sentences from the text data, and a terminal means for displaying the generated quiz question sentences and choices 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 conventional learning methods, there was a lack of efficient ways to create quizzes from textbooks and other materials, and it took a great deal of time and effort for learners to generate their own questions. Furthermore, existing question sets were standardized, making it difficult to provide questions suited to the needs of individual learners. This resulted in issues such as a decline in learning efficiency and a loss of motivation. [Means for solving the problem]

[0005] The present invention proposes a system including a user means for inputting text data, a server means for generating quiz questions from the text data, and a terminal means for displaying the generated quiz questions and options to the user. This system can efficiently create quizzes by analyzing the text data using natural language processing technology and extracting keywords and key sentences. Furthermore, by providing a function that allows users to specify the quiz format and question conditions, it is possible to provide questions that can be customized to meet the learner's needs. Furthermore, by having a function to collect user answers, evaluate them on the server, and generate results, it is possible to provide quick and accurate feedback. In this way, it is possible to improve learning efficiency and maintain motivation.

[0006] The "user means" is a means having an interface and functions for inputting text data and specifying the quiz format and question conditions.

[0007] "Server means" refers to means having a computing device and software for analyzing text data sent from user means, generating quiz question sentences, and evaluating the user's answers to generate results.

[0008] The "terminal means" is a means having a device and an interface for displaying the generated quiz questions and options sent from the server means to the user, and collecting and sending the user's answers to the server means.

[0009] "Text data" refers to the data format of information sources entered by users, such as learning materials and documents, and includes sentences and phrases written in natural language.

[0010] The "quiz question sentence" is a question-type sentence for learning that is generated based on the text data analyzed by the server means, and is intended for the user to answer.

[0011] "Natural language processing" refers to techniques and methods for analyzing text data, extracting phrases and patterns, and understanding the meaning of the text.

[0012] "Choices" are information that provides multiple answer candidates for a quiz question, and include elements necessary for the user to select the correct answer.

[0013] "Evaluation" is the process by which the server means compares the user's answer with the correct answer to determine whether the answer is correct.

[0014] The "results" are information including scores and feedback generated by the server means after evaluating the user's answers, and indicate the user's learning status.

[0015] "Interface" refers to the screen and operation method in the user means and terminal means that allows the user to input text data, specify the quiz format and question conditions, and display the generated quiz. [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 "quiz generation system" of the present invention is a system including a user means for inputting text data, a server means for analyzing the text data and generating quiz questions, and a terminal means for displaying the generated quiz questions and options to the user.

[0038] Overall system configuration and roles

[0039] 1. User Method

[0040] Users input text data into a learning application or web interface.

[0041] Users set conditions such as the quiz format (true / false, multiple choice, written, etc.), number of questions, and difficulty level.

[0042] 2. Terminal means

[0043] The terminal transmits the text data and conditions sent from the user means to the server means.

[0044] The terminal displays the question sentences and options of the quiz sent from the server means to the user.

[0045] The terminal collects the user's answers and transmits them to the server means.

[0046] 3. Server Means

[0047] The server uses natural language processing (NLP) libraries to analyze the text data and extract keywords and key sentences.

[0048] The server generates quiz questions from the analyzed text data based on conditions specified by the user.

[0049] The server receives the user's answers, evaluates them against the correct answers, and generates a result.

[0050] The server transmits the result data to the terminal means.

[0051] Program processing flow and specific examples

[0052] 1. User enters text and sets conditions

[0053] The user inputs the text data they want to study from a particular chapter of a "history textbook" into the application. For example, the following text:

[0054] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[0055] The user sets the format to "True or False," 10 questions, and difficulty level to "medium."

[0056] 2. The device sends the data to the server

[0057] The terminal creates a request to send the user's input to the server.

[0058] 3. The server analyzes the text data

[0059] The server receives the text data and uses natural language processing to extract keywords and sentences such as:

[0060] Keywords: Tokugawa Ieyasu, Edo Shogunate, capital, Edo, domestic affairs, stability, reform

[0061] Extract: Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital.

[0062] 4. The server generates the quiz

[0063] The server generates true / false questions based on the extracted keywords and sentences:

[0064] Question 1: Tokugawa Ieyasu established the Edo Shogunate. (True or False)

[0065] Question 2: The capital of the Edo Shogunate was Osaka. (True or False)

[0066] 5. The server sends the generated quiz to the device.

[0067] The server sends the generated 10 questions to the terminal.

[0068] 6. The device displays the quiz to the user

[0069] The terminal provides an interface that displays the received quiz to the user.

[0070] 7. User takes the quiz

[0071] Users answer quizzes and submit their answers on their terminals.

[0072] 8. The device sends the answer to the server

[0073] The terminal transmits the user's answer to the server.

[0074] 9. The server evaluates the answers and generates a result

[0075] The server evaluates the user's answers and generates correct / incorrect results and a score.

[0076] 10. The device displays the results to the user

[0077] The terminal analyzes the received result data and displays the score and feedback to the user.

[0078] The above is a specific embodiment of the "quiz generation system" according to the present invention. This system allows users to efficiently generate quizzes from their own text materials and advance their studies.

[0079] The processing flow will be explained below.

[0080] Step 1:

[0081] The user launches the quiz generation app and inputs the text data they want to study. For example, they input the text "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital" from a specific chapter of a history textbook. The user also sets conditions such as the quiz format (true or false questions), number of questions (10), and difficulty level (medium).

[0082] Step 2:

[0083] The device creates an API request to send the text data entered by the user and the setting conditions to the server. This request includes information such as the text data, quiz format, and number of questions.

[0084] Step 3:

[0085] The server analyzes the API request received from the device and obtains the text data and user settings. Specifically, it stores the text data in memory and the settings in variables.

[0086] Step 4:

[0087] The server uses natural language processing (NLP) libraries to analyze the text data, tokenize it, split it into sentences, and extract keywords (e.g., "Tokugawa Ieyasu," "Edo Shogunate," "Capital," "Edo"), etc. It also evaluates the meaning and context of sentences to detect important sentences.

[0088] Step 5:

[0089] The server runs an algorithm to generate quiz questions based on the extracted keywords and key sentences. For example, for a true / false question, it generates the question, "Tokugawa Ieyasu established the Edo Shogunate. (True or False)." The generated questions follow the specified format and number of questions.

[0090] Step 6:

[0091] The server packages the generated quiz questions and options in JSON format and creates an API response to send to the device.

[0092] Step 7:

[0093] The device analyzes the JSON data received from the server and generates an interface that displays the quiz questions and options to the user. The UI is designed to make it easy for users to enter answers.

[0094] Step 8:

[0095] The user selects an answer to the displayed quiz and submits the answer. For example, the user selects "Yes" for the question "Tokugawa Ieyasu established the Edo Shogunate."

[0096] Step 9:

[0097] The device collects the user's answers and makes an API request to send to the server, which includes the user's answers for each quiz.

[0098] Step 10:

[0099] The server analyzes the user's answers received from the device and evaluates them against the correct answers. Specifically, it flags each question as correct or incorrect and calculates an overall score.

[0100] Step 11:

[0101] The server packages the evaluation results and scores in JSON format and creates an API response to send to the device.

[0102] Step 12:

[0103] The terminal analyzes the result data received from the server and generates an interface that displays the score and feedback to the user, such as "Your score is 8 / 10. Correct answer: Tokugawa Ieyasu established the Edo Shogunate."

[0104] Example 1

[0105] 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."

[0106] Conventional quiz generation systems have low accuracy when automatically generating quiz questions from text data, or have limited functionality for generating quizzes according to user-specified conditions. This makes it difficult for users to study quizzes satisfactorily. Furthermore, the series of operations, such as displaying the generated quiz questions and options, and evaluating the answers, are sometimes not performed quickly and accurately. Therefore, there is a need for an efficient and accurate way to generate quiz questions based on text data, thereby improving users' learning effectiveness.

[0107] 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.

[0108] In this invention, the server includes user means for inputting text data, information processing means for generating quiz questions from the text data, display means for displaying the generated quiz questions and options to the user, and answer collection means for collecting user answers and transmitting them to the information processing means. This makes it possible to efficiently and accurately generate quiz questions based on text data, and to display and evaluate them.

[0109] "User means" refers to a means by which a user inputs text data and sets the quiz format and question conditions.

[0110] The "information processing device means" refers to a server and related software libraries for analyzing text data and generating quiz question sentences based on extracted keywords and key sentences.

[0111] The term "display device" refers to a terminal having an interface that provides the user with the generated quiz questions and options, or a display device for that purpose.

[0112] The "answer collection means" is a means for collecting the answers given by users to the quiz and transmitting them to the information processing means.

[0113] The "quiz generation system" according to the present invention is a system including a user means for inputting text data, an information processing means for analyzing the text data and generating quiz questions, and a display means for displaying the generated quiz questions and options to the user and collecting answers. The following describes in detail how this system can be implemented.

[0114] Overall system configuration and roles

[0115] 1. User means

[0116] Users input text data using a learning application or web interface, providing the material they want to study by copying and pasting text into an input field or by typing it directly.

[0117] Users can set the quiz format (true / false, multiple choice, etc.), number of questions, difficulty level, and other parameters using drop-down menus and radio buttons on the interface.

[0118] 2. Information Processing Device Means

[0119] The information processing device (server) uses a natural language processing (NLP) library to analyze the received text data. As a specific example, the NLTK library of Python is used.

[0120] The server extracts keywords and key sentences from the text data and generates quiz questions based on the set conditions.

[0121] 3. Display device means

[0122] The terminal transmits the text data and conditions sent from the user means to the server means (information processing device) using a standard HTTP request for communication.

[0123] The terminal has an interface that provides the user with the question sentences and options of the generated quiz sent from the server.

[0124] The device collects the user's answers and sends them to the server, again using an HTTP request.

[0125] Program processing flow and specific examples

[0126] 1. User enters text and sets conditions

[0127] The user inputs the text data they want to study from a particular chapter of a "history textbook" into the application. For example, the following text:

[0128] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[0129] The user also sets the format to "True or False," 10 questions, and difficulty level to "Medium."

[0130] 2. Examples of prompts

[0131] Here are some example prompts to input to a generative AI model:

[0132] input:

[0133] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[0134] conditions:

[0135] Quiz format: True or False

[0136] Number of questions: 10 questions

[0137] Difficulty: Medium

[0138] output:

[0139] Question 1: Tokugawa Ieyasu established the Edo Shogunate. (True or False)

[0140] Question 2: The capital of the Edo Shogunate was Osaka. (True or False)

[0141] Hardware and software used

[0142] 1. User means

[0143] The user's personal computer or smartphone.

[0144] Learning applications and web interfaces (e.g. web front-ends using React, Angular, etc.).

[0145] 2. Information Processing Device Means

[0146] Server: Cloud-based server (e.g., Amazon Web Services, Microsoft Azure).

[0147] Natural language processing libraries: Python's NLTK, spaCy, etc.

[0148] 3. Display device means

[0149] The user's personal computer or smartphone.

[0150] A web interface that runs on a browser.

[0151] In this way, the "quiz generation system" based on the present invention functions as a tool for users to efficiently generate quizzes from any text material and deepen their learning.

[0152] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0153] Step 1:

[0154] The user inputs text data and sets the conditions for the quiz.

[0155] Input: Text data entered by the user using the learning application or web interface, as well as the type, number and difficulty of the quiz selected by the user.

[0156] Data processing: The text data provided by the user is saved and the selected conditions are stored in memory.

[0157] Output: The prepared data structure is passed to the terminal. Specifically, user actions in text fields and selection menus are constructed as requests to the server.

[0158] Step 2:

[0159] The terminal transmits the input text data and conditions to the server.

[0160] Input: The text data entered by the user, as well as the quiz format, number of questions, and difficulty level you set.

[0161] Data processing: Properly formatting this data to generate HTTP requests, for example, converting it to JSON format.

[0162] Output: Data structure as a request sent to the server. For example, JSON data like this:

[0163] json

[0164] {

[0165] "text": "Tokugawa Ieyasu established the Edo Shogunate and established its capital in Edo. He stabilized Japan's domestic politics and implemented many reforms.",

[0166] "quiz_format": "〇×Question",

[0167] "num_questions": 10,

[0168] "difficulty": "medium"

[0169] }

[0170] Step 3:

[0171] The server receives and analyzes the text data.

[0172] Input: Text data sent from the device and setting conditions.

[0173] Data processing: Extract keywords and key sentences using a natural language processing (NLP) library (e.g., Python's NLTK). For example, splitting a text into sentences and extracting keywords.

[0174] python

[0175] import nltk

[0176] from nltk.tokenize import sent_tokenize, word_tokenize

[0177] text = "Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms."

[0178] sentences = sent_tokenize(text)

[0179] words = word_tokenize(text)

[0180] keywords = [word for word in words if word in important_words_list]

[0181] Output: A list of extracted keywords and key sentences.

[0182] Step 4:

[0183] The server generates the quiz questions.

[0184] Input: Extracted keywords and key sentences, conditions set by the user (format, number of questions, difficulty level).

[0185] Data processing: Generate quiz questions based on the specified conditions. Specifically, if you want to create a true / false question, generate it as follows:

[0186] python

[0187] quizzes = [

[0188] {"question": "Tokugawa Ieyasu established the Edo Shogunate.", "correct_answer": "Yes"},

[0189] {"question": "The capital of the Edo Shogunate was Osaka.", "correct_answer": "×"}

[0190] ]

[0191] Output: The generated quiz question and answer options.

[0192] Step 5:

[0193] The server sends the generated quiz back to the terminal.

[0194] Input: The question text and answer choices for the generated quiz.

[0195] Data processing: Format these as an HTTP response and send it to the terminal. For example, generate a JSON format response.

[0196] json

[0197] {

[0198] "quizzes": [

[0199] {"question": "Tokugawa Ieyasu established the Edo Shogunate.", "options": ["Yes", "No"]},

[0200] {"question": "The capital of the Edo Shogunate was Osaka.", "options": ["Yes", "No"]}

[0201] ]

[0202] }

[0203] Output: The quiz data provided to the device.

[0204] Step 6:

[0205] The terminal displays the quiz to the user.

[0206] Input: Quiz data received from the server.

[0207] Data processing: The quiz questions and options are laid out and displayed in the user interface. This is implemented using HTML and JavaScript.

[0208] Output: Displaying quiz questions to the user. Specifically, a quiz screen is generated and the user is ready to answer.

[0209] Step 7:

[0210] The user answers the quiz.

[0211] Input: The displayed quiz question and choices.

[0212] Data processing: The user selects the answer to a question. The selection is reflected by clicking or tapping.

[0213] Output: User response data. Specifically, the selected options are collected.

[0214] Step 8:

[0215] The terminal sends the user's answer to the server.

[0216] Input: User selected answer data.

[0217] Data processing: The response data is formatted and sent to the server, again using an HTTP request.

[0218] Output: The response data sent to the server. For example, the following JSON data:

[0219] json

[0220] {

[0221] "answers": ["Yes", "No"]

[0222] }

[0223] Step 9:

[0224] The server evaluates the user's answers and generates a result.

[0225] Input: User response data.

[0226] Data processing: Compare with the correct answer data and calculate the evaluation and score. As an example of evaluation, we will determine whether the answer is correct or incorrect as follows.

[0227] python

[0228] correct_answers = ["〇", "×"]

[0229] user_answers = ["Yes", "No"]

[0230] results = [{"question": "Tokugawa Ieyasu established the Edo Shogunate.", "user_answer": "Yes", "correct": True},

[0231] {"question": "The capital of the Edo Shogunate was Osaka.", "user_answer": "×", "correct": True}]

[0232] Output: Evaluation results and score data.

[0233] Step 10:

[0234] The terminal displays the results to the user.

[0235] Input: Evaluation results and score data received from the server.

[0236] Data processing: Evaluation results and score data are laid out and displayed on the interface. This is implemented using HTML and JavaScript.

[0237] Output: Displaying the scores and evaluation results to the user. Specifically, a results screen is generated so that the user can check their performance.

[0238] (Application example 1)

[0239] 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."

[0240] Conventional quiz generation systems require the input of text data, which is a time-consuming process of manually inputting text from books or paper media. Additionally, while technology for generating quizzes using natural language processing is available, it lacks the functionality to directly extract text from images and use it to generate quizzes, making it difficult to provide learners with more intuitive, real-time learning support.

[0241] 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.

[0242] In this invention, the server includes information input means for inputting text data, analysis means for generating quiz questions from the text data, output means for displaying the generated quiz questions and options on information display means, character recognition means for extracting text from images, and question generation means for generating quizzes based on the text extracted by the character recognition means. This makes it possible to generate quizzes by extracting text directly from books or paper media and provide them to learners immediately.

[0243] "Text data" refers to information expressed as a string of characters, including sentences and paragraphs that form the basis for generating quizzes.

[0244] "Information input means" refers to an interface or device that allows a user to input text data into a system.

[0245] The "analysis means" is a part of the system that performs analysis to generate quiz questions based on the input text data.

[0246] "Information display means" refers to an interface or device used to display the generated quiz questions and options to the user.

[0247] The "output means" is a part of the system that provides the quiz questions and options to the user via the information display means.

[0248] A “character recognition means” is a part of a system that uses optical character recognition (OCR) technology to extract text from images.

[0249] The "question generation means" is a part of the system that generates quiz questions based on the text extracted by the character recognition means.

[0250] The "quiz generation system" according to the present invention is a system including information input means, analysis means, information display means, output means, character recognition means, and question generation means.

[0251] 1. Overall system configuration

[0252] Information input means: Users input text data or images into the system. Examples include smartphone or tablet applications.

[0253] Analysis method: Analyzes the text data sent from the information input method and extracts keywords and key sentences. This process uses a natural language processing (NLP) library.

[0254] Information display means: The quiz questions and options generated by the analysis means are displayed to the user. This corresponds to the application screen of a smartphone or tablet.

[0255] Output means: A part of the system that provides the quiz to the user via the information display means.

[0256] Character Recognition Method: Optical Character Recognition (OCR) technology is used to extract text from images. This process utilizes the Google Cloud Vision API.

[0257] Question generation: Quiz questions are generated based on the text extracted by the character recognition method. This process uses the Hugging Face Transformers library.

[0258] 2. Hardware and Software Used

[0259] Hardware: Smartphone, tablet, camera for OCR.

[0260] Software: Google Cloud Vision API, Hugging Face Transformers, Python.

[0261] 3. Example of a system

[0262] A user scans a book or specific materials from a cram school using their smartphone camera and inputs the image into the system. The text in this image is converted into text data using the Google Cloud Vision API, a character recognition method. The converted text data is analyzed using a natural language processing library, which serves as an analysis method, and keywords and key sentences are extracted. Quiz questions are then generated using the Hugging Face Transformers library, which serves as a question generation method. The generated quiz questions and answer options are displayed on the screen of a smartphone or tablet, which serves as an information display method, and provided to the user via an output method. The user answers the displayed quiz questions and progresses with their studies.

[0263] 4. Examples of prompt sentences

[0264] As part of the operation of this system, the user may enter prompts such as:

[0265] text

[0266] Enter text: Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[0267] Quiz format: 4 choices

[0268] Number of questions: 5 questions

[0269] The above is a specific embodiment of the "quiz generation system" of the present invention. This system allows users to extract text directly from images and automatically generate quizzes to advance their learning.

[0270] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0271] Step 1:

[0272] A user launches an application on their smartphone or tablet and scans a book or study material with the smartphone's camera, obtaining image data as input, which is then saved in the application as output.

[0273] Step 2:

[0274] The device sends image data to the Google Cloud Vision API, a character recognition tool. The character recognition tool then analyzes the characters in the image and obtains text data as output. Specifically, it processes the pixel data of the image and returns the recognized string of characters as text data.

[0275] Step 3:

[0276] The device sends the obtained text data to a natural language processing (NLP) library as an analysis means, which then extracts keywords and key sentences from the text data. The device receives the text data as input and obtains a list of keywords and extracted sentences as output.

[0277] Step 4:

[0278] The server generates quiz questions using the Hugging Face Transformers library, a question generation tool, based on the keywords and key sentences extracted by the analysis tool. Keywords and key sentences are received as input, and the quiz questions and options are obtained as output. Specifically, a prompt is input into the generation AI model, and questions and options that fit the quiz format are generated.

[0279] Step 5:

[0280] The server sends the generated quiz questions and options to the terminal, which receives data from the server as input and converts it into a format that can be displayed on the terminal as output.

[0281] Step 6:

[0282] The device displays the quiz question and options on a user interface as information display means, allowing the user to take the quiz. Specifically, the quiz question and multiple options are visually displayed on the screen.

[0283] Step 7:

[0284] The user answers the quiz and submits the answers on the device, which receives the user's selected options as input and sends the data to the server as output.

[0285] Step 8:

[0286] The server evaluates the user's answers and generates a result indicating whether they are correct or incorrect. The answer data received is used as input, and the evaluation result is obtained as output. Specifically, the result is calculated after comparing it with the correct answer, and a score and feedback are generated.

[0287] Step 9:

[0288] The server receives the evaluation result data as input and converts it into a format that can be sent to the terminal as output.

[0289] Step 10:

[0290] The device displays the assessment results to the user, allowing them to check their learning progress. Specifically, the device visually displays scores and feedback on the screen.

[0291] 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.

[0292] The "quiz generation system" according to the present invention is a system including a user means for inputting text data, a server means for analyzing the text data and generating quiz questions, a terminal means for displaying the generated quiz questions and options to the user, and an emotion engine for recognizing the user's emotions.

[0293] Overall system configuration and roles

[0294] 1. User Method

[0295] A user inputs text data into a learning application or web interface. For example, the text "Tokugawa Ieyasu established the Edo Shogunate and established its capital in Edo" from a specific chapter of a history textbook. The user also sets parameters such as the quiz format (true / false questions, multiple choice, etc.), the number of questions (10), and the difficulty level (medium).

[0296] 2. Terminal means

[0297] The terminal transmits the text data and conditions sent from the user means to the server means.

[0298] The terminal displays the question sentences and options of the quiz sent from the server means to the user.

[0299] The terminal collects the user's answers and emotional state and transmits them to the server means and the emotion engine.

[0300] 3. Server Means

[0301] The server uses natural language processing (NLP) libraries to analyze the text data and extract keywords and key sentences.

[0302] The server generates quiz questions from the analyzed text data based on conditions specified by the user.

[0303] The server receives the user's answers, evaluates them against the correct answers, and generates a result.

[0304] The server generates data based on the evaluation results and the user's emotional state to provide feedback and adjust the next quiz.

[0305] 4. Emotion Engine

[0306] The emotion engine has the ability to recognize the user's emotions, for example, by measuring the user's stress and concentration level using facial expression recognition technology and voice analysis technology.

[0307] The emotion engine dynamically adjusts the difficulty and content of the quiz based on the perceived emotional state.

[0308] The emotion engine visualizes the emotional state and displays it on the terminal means, thereby enabling the user to understand his or her own emotional state.

[0309] Program processing flow and specific examples

[0310] 1. User enters text and sets conditions

[0311] The user inputs the text data they want to study from a particular chapter of a "history textbook" into the application. For example, the following text:

[0312] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[0313] The user sets the format to "True or False," 10 questions, and difficulty level to "medium."

[0314] 2. The device sends the data to the server

[0315] The terminal creates a request to send the user's input to the server.

[0316] 3. The server analyzes the text data

[0317] The server receives the text data and uses natural language processing to extract keywords and sentences such as:

[0318] Keywords: Tokugawa Ieyasu, Edo Shogunate, capital, Edo, domestic affairs, stability, reform

[0319] Extract: Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital.

[0320] 4. The server generates the quiz

[0321] The server generates true / false questions based on the extracted keywords and sentences:

[0322] Question 1: Tokugawa Ieyasu established the Edo Shogunate. (True or False)

[0323] Question 2: The capital of the Edo Shogunate was Osaka. (True or False)

[0324] 5. The server sends the generated quiz to the device.

[0325] The server sends the generated 10 questions to the terminal.

[0326] 6. The device displays the quiz to the user

[0327] The terminal provides an interface that displays the received quiz to the user.

[0328] 7. Emotion engine recognizes user emotions

[0329] The emotion engine analyzes the user's facial expressions and voice to recognize their current emotional state, such as "concentrated" or "stressed."

[0330] 8. User takes the quiz

[0331] The user selects an answer to the displayed quiz and submits the answer. For example, the user selects "Yes" for the question "Tokugawa Ieyasu established the Edo Shogunate."

[0332] 9. The device sends the answer and emotional state to the server.

[0333] The terminal transmits the user's response and the emotional state recognized by the emotion engine to the server.

[0334] 10. The server evaluates the answers and generates the results

[0335] The server evaluates the user's answers and generates correct / incorrect results and a score.

[0336] 11. The server generates feedback based on the emotional state

[0337] The server uses data from the emotion engine to generate feedback based on the user's emotional state, such as "You are concentrating on your studies" or "We recommend you take a break."

[0338] 12. The device displays the results and feedback to the user

[0339] The device generates an interface that displays the received result data and feedback to the user, such as "Score: 8 / 10" or "Feedback: You are concentrating on your studies."

[0340] The above is a specific embodiment of the "quiz generation system" based on the present invention. This system allows users to efficiently generate quizzes from their own text materials and further progress in their studies while understanding their own emotional state.

[0341] The processing flow will be explained below.

[0342] Step 1:

[0343] The user launches the quiz generation app and inputs the text data they want to study. For example, they input the text "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital" from a specific chapter of a history textbook. The user also sets conditions such as the quiz format (true or false questions), number of questions (10), and difficulty level (medium).

[0344] Step 2:

[0345] The device creates an API request to send the text data entered by the user and the setting conditions to the server. This request includes information such as the text data, quiz format, and number of questions.

[0346] Step 3:

[0347] The server analyzes the API request received from the device and obtains the text data and user settings. Specifically, it stores the text data in memory and the settings in variables.

[0348] Step 4:

[0349] The server uses natural language processing (NLP) libraries to analyze the text data, tokenize it, split it into sentences, and extract keywords (e.g., "Tokugawa Ieyasu," "Edo Shogunate," "Capital," "Edo"), etc. It also evaluates the meaning and context of sentences to detect important sentences.

[0350] Step 5:

[0351] The server runs an algorithm to generate quiz questions based on the extracted keywords and key sentences. For example, for a true / false question, it generates the question, "Tokugawa Ieyasu established the Edo Shogunate. (True or False)." The generated questions follow the specified format and number of questions.

[0352] Step 6:

[0353] The server packages the generated quiz questions and options in JSON format and creates an API response to send to the device.

[0354] Step 7:

[0355] The device analyzes the JSON data received from the server and generates an interface that displays the quiz questions and options to the user. The UI is designed to make it easy for users to enter answers.

[0356] Step 8:

[0357] The device activates an emotion engine, analyzes the user's facial expressions and voice in real time, and measures their emotional state. For example, if the user is smiling, it is recognized as "having fun," and if they frown, it is recognized as "feeling stressed."

[0358] Step 9:

[0359] The user selects an answer to the displayed quiz and submits the answer. For example, the user selects "Yes" for the question "Tokugawa Ieyasu established the Edo Shogunate."

[0360] Step 10:

[0361] The device collects the user's answers and makes an API request to send to the server along with the emotional state data from the emotion engine. The request includes the user's answers and emotional state for each quiz.

[0362] Step 11:

[0363] The server analyzes the user's answers received from the device and evaluates them against the correct answers. Specifically, it flags each question as correct or incorrect and calculates an overall score.

[0364] Step 12:

[0365] The server generates feedback based on the user's emotional state based on data from the emotion engine. For example, if the user is concentrating, it generates a message such as "You are studying very hard," and if the user is feeling stressed, it generates a message such as "We recommend that you take a break."

[0366] Step 13:

[0367] The server packages the evaluation results and feedback in JSON format and creates an API response to send to the device.

[0368] Step 14:

[0369] The device analyzes the results and feedback received from the server and generates an interface to display to the user, such as "Score: 8 / 10" or "Feedback: Very focused on studying."

[0370] This is the specific processing flow of the "quiz generation system." This system allows users to efficiently generate and answer quizzes, and progress in their studies while understanding their own emotional state.

[0371] Example 2

[0372] 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."

[0373] In conventional quiz generation systems, generating quizzes from text data is a simple, routine task, making it difficult to dynamically adjust the system to maximize the user's learning effectiveness. Furthermore, because questions are generated without taking into account the user's emotional state, they are unable to adapt to changes in stress or concentration, resulting in a decline in learning efficiency.

[0374] 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.

[0375] In this invention, the server includes a user means for inputting text data, a server for generating quiz questions from the text data, a terminal for displaying the generated quiz questions and options to the user, and an emotion analysis engine for recognizing the user's emotions and adjusting the difficulty of the quiz, thereby enabling dynamic quiz generation and question setting according to the user's learning situation and emotional state.

[0376] "Text data" refers to character string information data entered by the user, and is used as material for quiz questions.

[0377] The "user means" is an interface that allows the user to input text data and set the format and conditions of the quiz.

[0378] The "server" is a computer system that receives text data sent by users, analyzes it using natural language processing, and generates quiz questions.

[0379] "Natural language processing" is a technology that analyzes text data, extracts keywords and key sentences, and generates quiz questions.

[0380] A "terminal" is a device that displays input data from a user and quiz questions and options sent from a server.

[0381] The "emotion analysis engine" is a system that analyzes the user's facial expressions and voice data, recognizes their emotional state, and adjusts the difficulty of the quiz accordingly.

[0382] A "quiz question" is a question-style sentence generated based on text data, to which the user responds.

[0383] "Choices" are multiple answer options for a quiz question, from which the user selects the correct answer.

[0384] "Feedback" refers to advice or evaluation provided based on the user's answers and emotional state.

[0385] The "quiz generation system" according to the present invention is a system including a user means for inputting text data, a server means for analyzing the text data and generating quiz questions, a terminal means for displaying the generated quiz questions and options to the user, and an emotion analysis engine for recognizing the emotions of the user. Specific embodiments of each means are described below.

[0386] User Means

[0387] A user inputs text data into a learning application or web interface. For example, they input the text "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital" from a specific chapter in a history textbook. The user also sets conditions such as the quiz format (true / false questions, multiple choice, etc.), number of questions (10), difficulty level (medium), etc. These settings are made through the UI (user interface).

[0388] Terminal means

[0389] The terminal transmits the text data and conditions sent from the user means to the server means, for example, using an HTTP request.

[0390] The terminal displays the questions and options of the quiz sent from the server means to the user, using an interface that is dynamically generated using HTML and JavaScript.

[0391] The terminal collects the user's answers and emotional state and transmits them to the server means and the emotion analysis engine.

[0392] Server Means

[0393] The server receives the text data sent by the user and analyzes it using, for example, Python's Natural Language Toolkit (NLTK) or Spacy. Specifically, the analysis is performed using the following steps:

[0394] The server divides the text data into sentence units.

[0395] The server extracts key keywords from each sentence, such as "Tokugawa Ieyasu," "Edo Shogunate," and "Edo."

[0396] The server generates quiz questions from the analyzed text data based on the user's criteria. For example, it generates a question such as "Tokugawa Ieyasu established the Edo Shogunate. (True or False)." It also sends the generated quiz questions and options to the terminal.

[0397] The server receives the user's answers, evaluates them against the correct answers, and generates a result. It also generates data to provide feedback and adjust the next quiz based on the evaluation results and the user's emotional state.

[0398] Sentiment Analysis Engine

[0399] The emotion analysis engine analyzes the user's facial expressions and voice to recognize their current emotional state (e.g., "concentrated" or "stressed") using OpenCV and voice emotion analysis tools.

[0400] The emotion analysis engine dynamically adjusts the difficulty of the quiz and the content of the questions based on the emotional state it recognizes. It also visualizes the emotional state and displays it on the device, allowing users to understand their own emotional state.

[0401] Specific examples of operation

[0402] User enters text and sets conditions

[0403] The user inputs text such as "Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital" into the learning application, and sets the question format to true / false, with 10 questions and medium difficulty.

[0404] The device sends data to the server

[0405] The terminal sends a request to the server with conditions set by the user.

[0406] The server parses the text data

[0407] The server analyzes the received text data using a natural language processing library to extract keywords and key phrases, such as "Tokugawa Ieyasu," "Edo Shogunate," "Edo," "domestic stability," and "reform."

[0408] The server generates the quiz

[0409] The server generates quiz questions based on the extracted keywords. Example questions include "Tokugawa Ieyasu established the Edo Shogunate. (True or False)" and "The capital of the Edo Shogunate was Osaka. (True or False)."

[0410] Prompt Sentence Examples

[0411] User: Enter the following text from a history textbook into the quiz generation system: "Tokugawa Ieyasu established the Edo Shogunate and established its capital in Edo. He stabilized Japan's domestic politics and implemented many reforms."

[0412] Prompt: Generate a true / false question based on the following text: "Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and carried out many reforms."

[0413] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0414] Step 1:

[0415] The user inputs text data and sets the quiz format and question conditions.

[0416] Input: Text data to be studied (e.g., "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital"), quiz format (true / false questions, multiple choice, etc.), number of questions (e.g., 10 questions), difficulty level (e.g., medium).

[0417] Output: The input data and the set conditions.

[0418] Specific operation: The user enters text data and selects various settings via the learning application or web interface.

[0419] Step 2:

[0420] The terminal transmits the user's input data and setting conditions to the server.

[0421] Input: Text data and setting conditions entered by the user.

[0422] Output: The request to the server.

[0423] Specific operation: The terminal creates an HTTP request and sends the user's input and setting conditions to the server.

[0424] Step 3:

[0425] The server analyzes the received text data.

[0426] Input: Text data sent from the terminal.

[0427] Output: Extracted keywords and key sentences.

[0428] Specific operation: The server uses a natural language processing library (e.g., Python's NLTK library or Spacy) to divide the text data into sentences and extract key keywords and sentences.

[0429] Step 4:

[0430] The server generates quiz questions based on the analysis results.

[0431] Input: Extracted keywords and key sentences, set quiz format and conditions.

[0432] Output: The generated quiz question and answer options.

[0433] Specific operation: The server generates quiz questions and answer options based on the extracted keywords and the user's settings. For example, it creates a question such as "Tokugawa Ieyasu established the Edo Shogunate. (True or False)."

[0434] Step 5:

[0435] The server transmits the generated quiz question text and options to the terminal.

[0436] Input: The question text and answer choices for the generated quiz.

[0437] Output: The response to the device.

[0438] Specific operation: The server converts the generated quiz into JSON format or similar and sends it to the device.

[0439] Step 6:

[0440] The terminal displays the received quiz to the user.

[0441] Input: Quiz question text and options sent from the server.

[0442] Output: The quiz screen shown to the user.

[0443] Specific operation: The device uses HTML and JavaScript to generate an interface for displaying the quiz and presents it to the user.

[0444] Step 7:

[0445] The sentiment analysis engine recognizes the user's emotions.

[0446] Input: User's facial expression and voice data.

[0447] Output: Perceived emotional state (e.g., "concentrated" or "stressed").

[0448] How it works: The emotion analysis engine uses OpenCV and speech analysis tools to analyze the user's emotional state in real time.

[0449] Step 8:

[0450] The user answers the quiz.

[0451] Input: Quiz question, answer choices, and user answer (e.g. "Yes").

[0452] Output: User response data.

[0453] Specific operation: The user selects an answer to a displayed quiz question and submits the answer.

[0454] Step 9:

[0455] The terminal transmits the user's answers and emotional state to the server.

[0456] Input: User response data, emotional state recognized by the sentiment analysis engine.

[0457] Output: The request to the server.

[0458] Specific operation: The device sends the user's answer and emotional state to the server again via an HTTP request.

[0459] Step 10:

[0460] The server evaluates the answers and generates a result.

[0461] Input: User's answer data, correct answer data.

[0462] Output: Evaluation results and scores.

[0463] Specific operation: The server evaluates the user's answer against the correct answer and calculates a score. For example, if the user answers "Yes" to the question "Tokugawa Ieyasu established the Edo Shogunate," the server will add a score to the answer.

[0464] Step 11:

[0465] The server generates feedback based on the emotional state.

[0466] Input: Evaluation results and emotional state.

[0467] Output: The feedback message.

[0468] Specific behavior: The server generates feedback based on the user's emotional state, such as messages like "You are concentrating on your studies" or "We recommend you take a break."

[0469] Step 12:

[0470] The terminal displays the results and feedback to the user.

[0471] Input: Evaluation results and feedback messages sent by the server.

[0472] Output: The results screen and feedback shown to the user.

[0473] Specific operation: The device generates an interface to display the result data and feedback messages to the user, and presents them to the user. For example, it displays information such as "Score: 8 / 10" and "Feedback: You are concentrating on your studies."

[0474] (Application example 2)

[0475] 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."

[0476] Current quiz generation systems lack the ability to dynamically adapt to the user's learning style and emotional state, resulting in poor learning efficiency. Another issue is that systems that generate quizzes based on specific content users want to learn lack adequate feedback to improve the user experience.

[0477] 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.

[0478] In this invention, the server includes user means for inputting text data, server means for generating quiz questions from the text data, terminal means for displaying the generated quiz questions and options to the user, emotion engine means for recognizing the user's emotions, and feedback means having a function of dynamically adjusting the difficulty level of the quiz and the content of the questions based on the recognition results of the emotion engine means, thereby enabling a personalized learning experience that suits the user's emotions and learning style.

[0479] "User means" is an interface for inputting text data.

[0480] The "server means" is the core of the system that generates quiz questions from text data.

[0481] The "terminal means" is a device that displays the generated quiz questions and options to the user.

[0482] The "emotion engine means" is a technology for recognizing the user's emotions.

[0483] The "feedback means" is a device or system that has the function of dynamically adjusting the difficulty level of the quiz and the content of the questions based on the recognition results of the emotion engine means.

[0484] "Natural language processing" is a technology that analyzes text data and extracts keywords and key sentences.

[0485] "Quiz format" refers to the way questions are presented in the quiz, and includes true / false questions and multiple choice questions, for example.

[0486] "Question conditions" are parameters designated by the user, such as the number of questions to be asked and the level of difficulty.

[0487] A system for carrying out the present invention includes user means for inputting text data, server means for analyzing the text data and generating quiz question sentences, terminal means for displaying the generated quiz question sentences and options to the user, emotion engine means for recognizing the user's emotions, and feedback means.

[0488] The user means is an interface for inputting text data. For example, a user uses a terminal at a theme park or museum to input information learned from exhibits or guidebooks. The input data is transmitted to the server means via the terminal means.

[0489] The server means analyzes the text data using natural language processing (NLP). Specifically, it uses an NLP library (e.g., Transformers) to extract keywords and key sentences, and generates quiz questions based on the extracted keywords and key sentences. The generated quiz is then transmitted to the terminal means.

[0490] The terminal means is a device that displays the questions and options of the quiz to the user. For example, the quiz is displayed using an interactive display or a smartphone.

[0491] The emotion engine is a technology for recognizing the user's emotional state. It uses a camera to capture the user's facial expressions and analyzes their emotions using image processing and facial recognition technology. The emotion analysis is performed using machine learning libraries such as TensorFlow.

[0492] The feedback means has a function of dynamically adjusting the difficulty level and question content of the quiz based on the recognized emotional state. For example, if the emotion recognition result indicates that the user is "concentrating," feedback is provided to slightly increase the difficulty level of the next quiz.

[0493] This system allows users to have a personalized learning experience that is tailored to their individual emotional state and learning style, and the feedback provided by the system allows users to receive appropriate adjustments based on their own learning progress and emotional state.

[0494] For example, if a visitor to a dinosaur exhibition inputs the text "Tyrannosaurus is a carnivorous dinosaur," the system generates a quiz question such as "Tyrannosaurus is a herbivorous dinosaur (True or False)," which is adjusted based on the user's emotional state.

[0495] An example of a prompt sentence to be input to the generative AI model is as follows:

[0496] Input text: Tyrannosaurus is a carnivorous dinosaur

[0497] conditions:

[0498] Quiz format: True or False

[0499] Difficulty: Medium

[0500] Number of questions: 3 questions

[0501] Generate quiz questions and options based on this.

[0502] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0503] Step 1:

[0504] The user inputs text data and sets the quiz format and question conditions.

[0505] Input: Text data obtained from exhibits and guidebooks, quiz format, number of questions, and difficulty level.

[0506] Output: The quiz generation request sent to the server.

[0507] Specific operation: The user means collects the text data and quiz conditions entered by the user through the interface, and generates a request to send them to the server.

[0508] Step 2:

[0509] The device sends the data to the server.

[0510] Input: A request for text data and conditions set by the user.

[0511] Output: The request sent to the server.

[0512] Specific operation: The terminal means transmits the data input by the user to the server using a communication means such as an HTTP request.

[0513] Step 3:

[0514] The server analyzes the text data and generates a quiz.

[0515] Input: Text data and conditions sent to the server.

[0516] Output: The generated quiz question and answer options.

[0517] Specific operation: The server uses a natural language processing (NLP) library to analyze the text data, extract keywords and key sentences, and then generate quiz questions based on the conditions set by the user.

[0518] Step 4:

[0519] The server sends the generated quiz to the terminal.

[0520] Input: The question text and answer choices for the generated quiz.

[0521] Output: Quiz data sent to the device.

[0522] Specific operation: The server sends the generated quiz data to the terminal. This is also done via an HTTP request.

[0523] Step 5:

[0524] The terminal displays the quiz to the user.

[0525] Input: Quiz data received from the server.

[0526] Output: The quiz question and answer choices that are displayed to the user.

[0527] Specific operation: The terminal means analyzes the received quiz data and displays it in a format that is easy for the user to view.

[0528] Step 6:

[0529] The emotion engine recognizes the user's emotions.

[0530] Input: User's facial expression data.

[0531] Output: Perceived emotional state.

[0532] How it works: The emotion engine captures the user's facial expressions with a camera, analyzes the images using facial recognition technology, and uses machine learning libraries such as TensorFlow to recognize the user's emotional state.

[0533] Step 7:

[0534] The user answers the quiz.

[0535] Input: The answer selected by the user.

[0536] Output: The response data sent from the device to the server.

[0537] Specific operation: The user selects an answer from the quiz question and options displayed on the terminal, and sends this from the terminal to the server.

[0538] Step 8:

[0539] The device sends the answer and emotional state to the server.

[0540] Input: User's answer and the emotion engine's recognition results.

[0541] Output: The data sent to the server.

[0542] Specific operation: The terminal means compiles the user's answers and the emotional state obtained from the emotion engine as data and sends it to the server.

[0543] Step 9:

[0544] The server evaluates the answers and generates a result.

[0545] Input: User response data.

[0546] Output: Evaluation results and scores.

[0547] Specific operation: The server means evaluates the user's answers against the correct answers and generates a score and evaluation result.

[0548] Step 10:

[0549] The server generates feedback based on the emotional state.

[0550] Input: Recognition data for the emotion engine.

[0551] Output: Feedback data.

[0552] Specific operation: The server means generates feedback according to the user's emotional state based on data from the emotion engine.

[0553] Step 11:

[0554] The device displays the results and feedback to the user.

[0555] Input: Assessment results and feedback data.

[0556] Output: Quiz score and feedback displayed to the user.

[0557] Specific operation: The terminal means generates and displays an interface for displaying the received result data and feedback to the user.

[0558] 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.

[0559] 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.

[0560] 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.

[0561] [Second embodiment]

[0562] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0563] 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.

[0564] 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).

[0565] 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.

[0566] 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.

[0567] 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).

[0568] 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.

[0569] 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.

[0570] 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.

[0571] 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.

[0572] 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.

[0573] 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."

[0574] The "quiz generation system" of the present invention is a system including a user means for inputting text data, a server means for analyzing the text data and generating quiz questions, and a terminal means for displaying the generated quiz questions and options to the user.

[0575] Overall system configuration and roles

[0576] 1. User Method

[0577] Users input text data into a learning application or web interface.

[0578] Users set conditions such as the quiz format (true / false, multiple choice, written, etc.), number of questions, and difficulty level.

[0579] 2. Terminal means

[0580] The terminal transmits the text data and conditions sent from the user means to the server means.

[0581] The terminal displays the question sentences and options of the quiz sent from the server means to the user.

[0582] The terminal collects the user's answers and transmits them to the server means.

[0583] 3. Server Means

[0584] The server uses natural language processing (NLP) libraries to analyze the text data and extract keywords and key sentences.

[0585] The server generates quiz questions from the analyzed text data based on conditions specified by the user.

[0586] The server receives the user's answers, evaluates them against the correct answers, and generates a result.

[0587] The server transmits the result data to the terminal means.

[0588] Program processing flow and specific examples

[0589] 1. User enters text and sets conditions

[0590] The user inputs the text data they want to study from a particular chapter of a "history textbook" into the application. For example, the following text:

[0591] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[0592] The user sets the format to "True or False," 10 questions, and difficulty level to "medium."

[0593] 2. The device sends the data to the server

[0594] The terminal creates a request to send the user's input to the server.

[0595] 3. The server analyzes the text data

[0596] The server receives the text data and uses natural language processing to extract keywords and sentences such as:

[0597] Keywords: Tokugawa Ieyasu, Edo Shogunate, capital, Edo, domestic affairs, stability, reform

[0598] Extract: Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital.

[0599] 4. The server generates the quiz

[0600] The server generates true / false questions based on the extracted keywords and sentences:

[0601] Question 1: Tokugawa Ieyasu established the Edo Shogunate. (True or False)

[0602] Question 2: The capital of the Edo Shogunate was Osaka. (True or False)

[0603] 5. The server sends the generated quiz to the device.

[0604] The server sends the generated 10 questions to the terminal.

[0605] 6. The device displays the quiz to the user

[0606] The terminal provides an interface that displays the received quiz to the user.

[0607] 7. User takes the quiz

[0608] Users answer quizzes and submit their answers on their terminals.

[0609] 8. The device sends the answer to the server

[0610] The terminal transmits the user's answer to the server.

[0611] 9. The server evaluates the answers and generates a result

[0612] The server evaluates the user's answers and generates correct / incorrect results and a score.

[0613] 10. The device displays the results to the user

[0614] The terminal analyzes the received result data and displays the score and feedback to the user.

[0615] The above is a specific embodiment of the "quiz generation system" based on the present invention. This system allows users to efficiently generate quizzes from their own text materials and advance their studies.

[0616] The processing flow will be explained below.

[0617] Step 1:

[0618] The user launches the quiz generation app and inputs the text data they want to study. For example, they input the text "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital" from a specific chapter of a history textbook. The user also sets conditions such as the quiz format (true or false questions), number of questions (10), and difficulty level (medium).

[0619] Step 2:

[0620] The device creates an API request to send the text data entered by the user and the setting conditions to the server. This request includes information such as the text data, quiz format, and number of questions.

[0621] Step 3:

[0622] The server analyzes the API request received from the device and obtains the text data and user settings. Specifically, it stores the text data in memory and the settings in variables.

[0623] Step 4:

[0624] The server uses natural language processing (NLP) libraries to analyze the text data, tokenize it, split it into sentences, and extract keywords (e.g., "Tokugawa Ieyasu," "Edo Shogunate," "Capital," "Edo"), etc. It also evaluates the meaning and context of sentences to detect important sentences.

[0625] Step 5:

[0626] The server runs an algorithm to generate quiz questions based on the extracted keywords and key sentences. For example, for a true / false question, it generates the question, "Tokugawa Ieyasu established the Edo Shogunate. (True or False)." The generated questions follow the specified format and number of questions.

[0627] Step 6:

[0628] The server packages the generated quiz questions and options in JSON format and creates an API response to send to the device.

[0629] Step 7:

[0630] The device analyzes the JSON data received from the server and generates an interface that displays the quiz questions and options to the user. The UI is designed to make it easy for users to enter answers.

[0631] Step 8:

[0632] The user selects an answer to the displayed quiz and submits the answer. For example, the user selects "Yes" for the question "Tokugawa Ieyasu established the Edo Shogunate."

[0633] Step 9:

[0634] The device collects the user's answers and makes an API request to send to the server, which includes the user's answers for each quiz.

[0635] Step 10:

[0636] The server analyzes the user's answers received from the device and evaluates them against the correct answers. Specifically, it flags each question as correct or incorrect and calculates an overall score.

[0637] Step 11:

[0638] The server packages the evaluation results and scores in JSON format and creates an API response to send to the device.

[0639] Step 12:

[0640] The terminal analyzes the result data received from the server and generates an interface that displays the score and feedback to the user, such as "Your score is 8 / 10. Correct answer: Tokugawa Ieyasu established the Edo Shogunate."

[0641] Example 1

[0642] 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."

[0643] Conventional quiz generation systems have low accuracy when automatically generating quiz questions from text data, or have limited functionality for generating quizzes according to user-specified conditions. This makes it difficult for users to study quizzes satisfactorily. Furthermore, the series of operations, such as displaying the generated quiz questions and options, and evaluating the answers, are sometimes not performed quickly and accurately. Therefore, there is a need for an efficient and accurate way to generate quiz questions based on text data, thereby improving users' learning effectiveness.

[0644] 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.

[0645] In this invention, the server includes user means for inputting text data, information processing means for generating quiz questions from the text data, display means for displaying the generated quiz questions and options to the user, and answer collection means for collecting user answers and transmitting them to the information processing means. This makes it possible to efficiently and accurately generate quiz questions based on text data, and to display and evaluate them.

[0646] "User means" refers to a means by which a user inputs text data and sets the quiz format and question conditions.

[0647] The "information processing device means" refers to a server and related software libraries for analyzing text data and generating quiz question sentences based on extracted keywords and key sentences.

[0648] The term "display device" refers to a terminal having an interface that provides the user with the generated quiz questions and options, or a display device for that purpose.

[0649] The "answer collection means" is a means for collecting the answers given by users to the quiz and transmitting them to the information processing means.

[0650] The "quiz generation system" according to the present invention is a system including a user means for inputting text data, an information processing means for analyzing the text data and generating quiz questions, and a display means for displaying the generated quiz questions and options to the user and collecting answers. The following describes in detail how this system can be implemented.

[0651] Overall system configuration and roles

[0652] 1. User means

[0653] Users input text data using a learning application or web interface, providing the material they want to study by copying and pasting text into an input field or by typing it directly.

[0654] Users can set the quiz format (true / false, multiple choice, etc.), number of questions, difficulty level, and other parameters using drop-down menus and radio buttons on the interface.

[0655] 2. Information Processing Device Means

[0656] The information processing device (server) uses a natural language processing (NLP) library to analyze the received text data. As a specific example, the NLTK library of Python is used.

[0657] The server extracts keywords and key sentences from the text data and generates quiz questions based on the set conditions.

[0658] 3. Display device means

[0659] The terminal transmits the text data and conditions sent from the user means to the server means (information processing device) using a standard HTTP request for communication.

[0660] The terminal has an interface that provides the user with the question sentences and options of the generated quiz sent from the server.

[0661] The device collects the user's answers and sends them to the server, again using an HTTP request.

[0662] Program processing flow and specific examples

[0663] 1. User enters text and sets conditions

[0664] The user inputs the text data they want to study from a particular chapter of a "history textbook" into the application. For example, the following text:

[0665] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[0666] The user also sets the format to "True or False," 10 questions, and difficulty level to "Medium."

[0667] 2. Examples of prompts

[0668] Here are some example prompts to input to a generative AI model:

[0669] input:

[0670] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[0671] conditions:

[0672] Quiz format: True or False

[0673] Number of questions: 10 questions

[0674] Difficulty: Medium

[0675] output:

[0676] Question 1: Tokugawa Ieyasu established the Edo Shogunate. (True or False)

[0677] Question 2: The capital of the Edo Shogunate was Osaka. (True or False)

[0678] Hardware and software used

[0679] 1. User means

[0680] The user's personal computer or smartphone.

[0681] Learning applications and web interfaces (e.g. web front-ends using React, Angular, etc.).

[0682] 2. Information Processing Device Means

[0683] Server: Cloud-based server (e.g., Amazon Web Services, Microsoft Azure).

[0684] Natural language processing libraries: Python's NLTK, spaCy, etc.

[0685] 3. Display device means

[0686] The user's personal computer or smartphone.

[0687] A web interface that runs on a browser.

[0688] In this way, the "quiz generation system" based on the present invention functions as a tool for users to efficiently generate quizzes from any text material and deepen their learning.

[0689] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0690] Step 1:

[0691] The user inputs text data and sets the conditions for the quiz.

[0692] Input: Text data entered by the user using the learning application or web interface, as well as the type, number and difficulty of the quiz selected by the user.

[0693] Data processing: The text data provided by the user is saved and the selected conditions are stored in memory.

[0694] Output: The prepared data structure is passed to the terminal. Specifically, user actions in text fields and selection menus are constructed as requests to the server.

[0695] Step 2:

[0696] The terminal transmits the input text data and conditions to the server.

[0697] Input: The text data entered by the user, as well as the quiz format, number of questions, and difficulty level you set.

[0698] Data processing: Properly formatting this data to generate HTTP requests, for example, converting it to JSON format.

[0699] Output: Data structure as a request sent to the server. For example, JSON data like this:

[0700] json

[0701] {

[0702] "text": "Tokugawa Ieyasu established the Edo Shogunate and established its capital in Edo. He stabilized Japan's domestic politics and implemented many reforms.",

[0703] "quiz_format": "〇×Question",

[0704] "num_questions": 10,

[0705] "difficulty": "medium"

[0706] }

[0707] Step 3:

[0708] The server receives and analyzes the text data.

[0709] Input: Text data sent from the device and setting conditions.

[0710] Data processing: Extract keywords and key sentences using a natural language processing (NLP) library (e.g., Python's NLTK). For example, splitting a text into sentences and extracting keywords.

[0711] python

[0712] import nltk

[0713] from nltk.tokenize import sent_tokenize, word_tokenize

[0714] text = "Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms."

[0715] sentences = sent_tokenize(text)

[0716] words = word_tokenize(text)

[0717] keywords = [word for word in words if word in important_words_list]

[0718] Output: A list of extracted keywords and key sentences.

[0719] Step 4:

[0720] The server generates the quiz questions.

[0721] Input: Extracted keywords and key sentences, conditions set by the user (format, number of questions, difficulty level).

[0722] Data processing: Generate quiz questions based on the specified conditions. Specifically, if you want to create a true / false question, generate it as follows:

[0723] python

[0724] quizzes = [

[0725] {"question": "Tokugawa Ieyasu established the Edo Shogunate.", "correct_answer": "Yes"},

[0726] {"question": "The capital of the Edo Shogunate was Osaka.", "correct_answer": "×"}

[0727] ]

[0728] Output: The generated quiz question and answer options.

[0729] Step 5:

[0730] The server sends the generated quiz back to the terminal.

[0731] Input: The question text and answer choices for the generated quiz.

[0732] Data processing: Format these as an HTTP response and send it to the terminal. For example, generate a JSON format response.

[0733] json

[0734] {

[0735] "quizzes": [

[0736] {"question": "Tokugawa Ieyasu established the Edo Shogunate.", "options": ["Yes", "No"]},

[0737] {"question": "The capital of the Edo Shogunate was Osaka.", "options": ["Yes", "No"]}

[0738] ]

[0739] }

[0740] Output: The quiz data provided to the device.

[0741] Step 6:

[0742] The terminal displays the quiz to the user.

[0743] Input: Quiz data received from the server.

[0744] Data processing: The quiz questions and options are laid out and displayed in the user interface. This is implemented using HTML and JavaScript.

[0745] Output: Displaying quiz questions to the user. Specifically, a quiz screen is generated and the user is ready to answer.

[0746] Step 7:

[0747] The user answers the quiz.

[0748] Input: The displayed quiz question and choices.

[0749] Data processing: The user selects the answer to a question. The selection is reflected by clicking or tapping.

[0750] Output: User response data. Specifically, the selected options are collected.

[0751] Step 8:

[0752] The terminal sends the user's answer to the server.

[0753] Input: User selected answer data.

[0754] Data processing: The response data is formatted and sent to the server, again using an HTTP request.

[0755] Output: The response data sent to the server. For example, the following JSON data:

[0756] json

[0757] {

[0758] "answers": ["Yes", "No"]

[0759] }

[0760] Step 9:

[0761] The server evaluates the user's answers and generates a result.

[0762] Input: User response data.

[0763] Data processing: Compare with the correct answer data and calculate the evaluation and score. As an example of evaluation, we will determine whether the answer is correct or incorrect as follows.

[0764] python

[0765] correct_answers = ["〇", "×"]

[0766] user_answers = ["Yes", "No"]

[0767] results = [{"question": "Tokugawa Ieyasu established the Edo Shogunate.", "user_answer": "Yes", "correct": True},

[0768] {"question": "The capital of the Edo Shogunate was Osaka.", "user_answer": "×", "correct": True}]

[0769] Output: Evaluation results and score data.

[0770] Step 10:

[0771] The terminal displays the results to the user.

[0772] Input: Evaluation results and score data received from the server.

[0773] Data processing: Evaluation results and score data are laid out and displayed on the interface. This is implemented using HTML and JavaScript.

[0774] Output: Displaying the scores and evaluation results to the user. Specifically, a results screen is generated so that the user can check their performance.

[0775] (Application example 1)

[0776] 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."

[0777] Conventional quiz generation systems require the input of text data, which is a time-consuming process of manually inputting text from books or paper media. Additionally, while technology for generating quizzes using natural language processing is available, it lacks the functionality to directly extract text from images and use it to generate quizzes, making it difficult to provide learners with more intuitive, real-time learning support.

[0778] 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.

[0779] In this invention, the server includes information input means for inputting text data, analysis means for generating quiz questions from the text data, output means for displaying the generated quiz questions and options on information display means, character recognition means for extracting text from images, and question generation means for generating quizzes based on the text extracted by the character recognition means. This makes it possible to generate quizzes by extracting text directly from books or paper media and provide them to learners immediately.

[0780] "Text data" refers to information expressed as a string of characters, including sentences and paragraphs that form the basis for generating quizzes.

[0781] "Information input means" refers to an interface or device that allows a user to input text data into a system.

[0782] The "analysis means" is a part of the system that performs analysis to generate quiz questions based on the input text data.

[0783] "Information display means" refers to an interface or device used to display the generated quiz questions and options to the user.

[0784] The "output means" is a part of the system that provides the quiz questions and options to the user via the information display means.

[0785] A “character recognition means” is a part of a system that uses optical character recognition (OCR) technology to extract text from images.

[0786] The "question generation means" is a part of the system that generates quiz questions based on the text extracted by the character recognition means.

[0787] The "quiz generation system" according to the present invention is a system including information input means, analysis means, information display means, output means, character recognition means, and question generation means.

[0788] 1. Overall system configuration

[0789] Information input means: Users input text data or images into the system. Examples include smartphone or tablet applications.

[0790] Analysis method: Analyzes the text data sent from the information input method and extracts keywords and key sentences. This process uses a natural language processing (NLP) library.

[0791] Information display means: The quiz questions and options generated by the analysis means are displayed to the user. This corresponds to the application screen of a smartphone or tablet.

[0792] Output means: A part of the system that provides the quiz to the user via the information display means.

[0793] Character Recognition Method: Optical Character Recognition (OCR) technology is used to extract text from images. This process utilizes the Google Cloud Vision API.

[0794] Question generation: Quiz questions are generated based on the text extracted by the character recognition method. This process uses the Hugging Face Transformers library.

[0795] 2. Hardware and Software Used

[0796] Hardware: Smartphone, tablet, camera for OCR.

[0797] Software: Google Cloud Vision API, Hugging Face Transformers, Python.

[0798] 3. Example of a system

[0799] A user scans a book or specific materials from a cram school using their smartphone camera and inputs the image into the system. The text in this image is converted into text data using the Google Cloud Vision API, a character recognition method. The converted text data is analyzed using a natural language processing library, which serves as an analysis method, and keywords and key sentences are extracted. Quiz questions are then generated using the Hugging Face Transformers library, which serves as a question generation method. The generated quiz questions and answer options are displayed on the screen of a smartphone or tablet, which serves as an information display method, and provided to the user via an output method. The user answers the displayed quiz questions and progresses with their studies.

[0800] 4. Examples of prompt sentences

[0801] As part of the operation of this system, the user may enter prompts such as:

[0802] text

[0803] Enter text: Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[0804] Quiz format: 4 choices

[0805] Number of questions: 5 questions

[0806] The above is a specific embodiment of the "quiz generation system" of the present invention. This system allows users to extract text directly from images and automatically generate quizzes to advance their learning.

[0807] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0808] Step 1:

[0809] A user launches an application on their smartphone or tablet and scans a book or study material with the smartphone's camera, obtaining image data as input, which is then saved in the application as output.

[0810] Step 2:

[0811] The device sends image data to the Google Cloud Vision API, a character recognition tool. The character recognition tool then analyzes the characters in the image and obtains text data as output. Specifically, it processes the pixel data of the image and returns the recognized string of characters as text data.

[0812] Step 3:

[0813] The device sends the obtained text data to a natural language processing (NLP) library as an analysis means, which then extracts keywords and key sentences from the text data. The device receives the text data as input and obtains a list of keywords and extracted sentences as output.

[0814] Step 4:

[0815] The server generates quiz questions using the Hugging Face Transformers library, a question generation tool, based on the keywords and key sentences extracted by the analysis tool. Keywords and key sentences are received as input, and the quiz questions and options are obtained as output. Specifically, a prompt is input into the generation AI model, and questions and options that fit the quiz format are generated.

[0816] Step 5:

[0817] The server sends the generated quiz questions and options to the terminal, which receives data from the server as input and converts it into a format that can be displayed on the terminal as output.

[0818] Step 6:

[0819] The device displays the quiz question and options on a user interface as information display means, allowing the user to take the quiz. Specifically, the quiz question and multiple options are visually displayed on the screen.

[0820] Step 7:

[0821] The user answers the quiz and submits the answers on the device, which receives the user's selected options as input and sends the data to the server as output.

[0822] Step 8:

[0823] The server evaluates the user's answers and generates a result indicating whether they are correct or incorrect. The answer data received is used as input, and the evaluation result is obtained as output. Specifically, the result is calculated after comparing it with the correct answer, and a score and feedback are generated.

[0824] Step 9:

[0825] The server receives the evaluation result data as input and converts it into a format that can be sent to the terminal as output.

[0826] Step 10:

[0827] The device displays the assessment results to the user, allowing them to check their learning progress. Specifically, the device visually displays scores and feedback on the screen.

[0828] 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.

[0829] The "quiz generation system" according to the present invention is a system including a user means for inputting text data, a server means for analyzing the text data and generating quiz questions, a terminal means for displaying the generated quiz questions and options to the user, and an emotion engine for recognizing the user's emotions.

[0830] Overall system configuration and roles

[0831] 1. User Method

[0832] A user inputs text data into a learning application or web interface. For example, the text "Tokugawa Ieyasu established the Edo Shogunate and established its capital in Edo" from a specific chapter of a history textbook. The user also sets parameters such as the quiz format (true / false questions, multiple choice, etc.), the number of questions (10), and the difficulty level (medium).

[0833] 2. Terminal means

[0834] The terminal transmits the text data and conditions sent from the user means to the server means.

[0835] The terminal displays the question sentences and options of the quiz sent from the server means to the user.

[0836] The terminal collects the user's answers and emotional state and transmits them to the server means and the emotion engine.

[0837] 3. Server Means

[0838] The server uses natural language processing (NLP) libraries to analyze the text data and extract keywords and key sentences.

[0839] The server generates quiz questions from the analyzed text data based on conditions specified by the user.

[0840] The server receives the user's answers, evaluates them against the correct answers, and generates a result.

[0841] The server generates data based on the evaluation results and the user's emotional state to provide feedback and adjust the next quiz.

[0842] 4. Emotion Engine

[0843] The emotion engine has the ability to recognize the user's emotions, for example, by measuring the user's stress and concentration level using facial expression recognition technology and voice analysis technology.

[0844] The emotion engine dynamically adjusts the difficulty and content of the quiz based on the perceived emotional state.

[0845] The emotion engine visualizes the emotional state and displays it on the terminal means, thereby enabling the user to understand his or her own emotional state.

[0846] Program processing flow and specific examples

[0847] 1. User enters text and sets conditions

[0848] The user inputs the text data they want to study from a particular chapter of a "history textbook" into the application. For example, the following text:

[0849] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[0850] The user sets the format to "True or False," 10 questions, and difficulty level to "medium."

[0851] 2. The device sends the data to the server

[0852] The terminal creates a request to send the user's input to the server.

[0853] 3. The server analyzes the text data

[0854] The server receives the text data and uses natural language processing to extract keywords and sentences such as:

[0855] Keywords: Tokugawa Ieyasu, Edo Shogunate, capital, Edo, domestic affairs, stability, reform

[0856] Extract: Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital.

[0857] 4. The server generates the quiz

[0858] The server generates true / false questions based on the extracted keywords and sentences:

[0859] Question 1: Tokugawa Ieyasu established the Edo Shogunate. (True or False)

[0860] Question 2: The capital of the Edo Shogunate was Osaka. (True or False)

[0861] 5. The server sends the generated quiz to the device.

[0862] The server sends the generated 10 questions to the terminal.

[0863] 6. The device displays the quiz to the user

[0864] The terminal provides an interface that displays the received quiz to the user.

[0865] 7. Emotion engine recognizes user emotions

[0866] The emotion engine analyzes the user's facial expressions and voice to recognize their current emotional state, such as "concentrated" or "stressed."

[0867] 8. User takes the quiz

[0868] The user selects an answer to the displayed quiz and submits the answer. For example, the user selects "Yes" for the question "Tokugawa Ieyasu established the Edo Shogunate."

[0869] 9. The device sends the answer and emotional state to the server.

[0870] The terminal transmits the user's response and the emotional state recognized by the emotion engine to the server.

[0871] 10. The server evaluates the answers and generates the results

[0872] The server evaluates the user's answers and generates correct / incorrect results and a score.

[0873] 11. The server generates feedback based on the emotional state

[0874] The server uses data from the emotion engine to generate feedback based on the user's emotional state, such as "You are concentrating on your studies" or "We recommend you take a break."

[0875] 12. The device displays the results and feedback to the user

[0876] The device generates an interface that displays the received result data and feedback to the user, such as "Score: 8 / 10" or "Feedback: You are concentrating on your studies."

[0877] The above is a specific embodiment of the "quiz generation system" based on the present invention. This system allows users to efficiently generate quizzes from their own text materials and further progress in their studies while understanding their own emotional state.

[0878] The processing flow will be explained below.

[0879] Step 1:

[0880] The user launches the quiz generation app and inputs the text data they want to study. For example, they input the text "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital" from a specific chapter of a history textbook. The user also sets conditions such as the quiz format (true or false questions), number of questions (10), and difficulty level (medium).

[0881] Step 2:

[0882] The device creates an API request to send the text data entered by the user and the setting conditions to the server. This request includes information such as the text data, quiz format, and number of questions.

[0883] Step 3:

[0884] The server analyzes the API request received from the device and obtains the text data and user settings. Specifically, it stores the text data in memory and the settings in variables.

[0885] Step 4:

[0886] The server uses natural language processing (NLP) libraries to analyze the text data, tokenize it, split it into sentences, and extract keywords (e.g., "Tokugawa Ieyasu," "Edo Shogunate," "Capital," "Edo"), etc. It also evaluates the meaning and context of sentences to detect important sentences.

[0887] Step 5:

[0888] The server runs an algorithm to generate quiz questions based on the extracted keywords and key sentences. For example, for a true / false question, it generates the question, "Tokugawa Ieyasu established the Edo Shogunate. (True or False)." The generated questions follow the specified format and number of questions.

[0889] Step 6:

[0890] The server packages the generated quiz questions and options in JSON format and creates an API response to send to the device.

[0891] Step 7:

[0892] The device analyzes the JSON data received from the server and generates an interface that displays the quiz questions and options to the user. The UI is designed to make it easy for users to enter answers.

[0893] Step 8:

[0894] The device activates an emotion engine, analyzes the user's facial expressions and voice in real time, and measures their emotional state. For example, if the user is smiling, it is recognized as "having fun," and if they frown, it is recognized as "feeling stressed."

[0895] Step 9:

[0896] The user selects an answer to the displayed quiz and submits the answer. For example, the user selects "Yes" for the question "Tokugawa Ieyasu established the Edo Shogunate."

[0897] Step 10:

[0898] The device collects the user's answers and makes an API request to send to the server along with the emotional state data from the emotion engine. The request includes the user's answers and emotional state for each quiz.

[0899] Step 11:

[0900] The server analyzes the user's answers received from the device and evaluates them against the correct answers. Specifically, it flags each question as correct or incorrect and calculates an overall score.

[0901] Step 12:

[0902] The server generates feedback based on the user's emotional state based on data from the emotion engine. For example, if the user is concentrating, it generates a message such as "You are studying very hard," and if the user is feeling stressed, it generates a message such as "We recommend that you take a break."

[0903] Step 13:

[0904] The server packages the evaluation results and feedback in JSON format and creates an API response to send to the device.

[0905] Step 14:

[0906] The device analyzes the results and feedback received from the server and generates an interface to display to the user, such as "Score: 8 / 10" or "Feedback: Very focused on studying."

[0907] This is the specific processing flow of the "quiz generation system." This system allows users to efficiently generate and answer quizzes, and progress in their studies while understanding their own emotional state.

[0908] Example 2

[0909] 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."

[0910] In conventional quiz generation systems, generating quizzes from text data is a simple, routine task, making it difficult to dynamically adjust the system to maximize the user's learning effectiveness. Furthermore, because questions are generated without taking into account the user's emotional state, they are unable to adapt to changes in stress or concentration, resulting in a decline in learning efficiency.

[0911] 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.

[0912] In this invention, the server includes a user means for inputting text data, a server for generating quiz questions from the text data, a terminal for displaying the generated quiz questions and options to the user, and an emotion analysis engine for recognizing the user's emotions and adjusting the difficulty of the quiz, thereby enabling dynamic quiz generation and question setting according to the user's learning situation and emotional state.

[0913] "Text data" refers to character string information data entered by the user, and is used as material for quiz questions.

[0914] The "user means" is an interface that allows the user to input text data and set the format and conditions of the quiz.

[0915] The "server" is a computer system that receives text data sent by users, analyzes it using natural language processing, and generates quiz questions.

[0916] "Natural language processing" is a technology that analyzes text data, extracts keywords and key sentences, and generates quiz questions.

[0917] A "terminal" is a device that displays input data from a user and quiz questions and options sent from a server.

[0918] The "emotion analysis engine" is a system that analyzes the user's facial expressions and voice data, recognizes their emotional state, and adjusts the difficulty of the quiz accordingly.

[0919] A "quiz question" is a question-style sentence generated based on text data, to which the user responds.

[0920] "Choices" are multiple answer options for a quiz question, from which the user selects the correct answer.

[0921] "Feedback" refers to advice or evaluation provided based on the user's answers and emotional state.

[0922] The "quiz generation system" according to the present invention is a system including a user means for inputting text data, a server means for analyzing the text data and generating quiz questions, a terminal means for displaying the generated quiz questions and options to the user, and an emotion analysis engine for recognizing the emotions of the user. Specific embodiments of each means are described below.

[0923] User Means

[0924] A user inputs text data into a learning application or web interface. For example, they input the text "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital" from a specific chapter in a history textbook. The user also sets conditions such as the quiz format (true / false questions, multiple choice, etc.), the number of questions (10), and the difficulty level (medium). These settings are made through the UI (user interface).

[0925] Terminal means

[0926] The terminal transmits the text data and conditions sent from the user means to the server means, for example, using an HTTP request.

[0927] The terminal displays the questions and options of the quiz sent from the server means to the user, using an interface that is dynamically generated using HTML and JavaScript.

[0928] The terminal collects the user's answers and emotional state and transmits them to the server means and the emotion analysis engine.

[0929] Server Means

[0930] The server receives the text data sent by the user and analyzes it using, for example, Python's Natural Language Toolkit (NLTK) or Spacy. Specifically, the analysis is performed in the following steps:

[0931] The server divides the text data into sentence units.

[0932] The server extracts key keywords from each sentence, such as "Tokugawa Ieyasu," "Edo Shogunate," and "Edo."

[0933] The server generates quiz questions from the analyzed text data based on the user's criteria. For example, it generates a question such as "Tokugawa Ieyasu established the Edo Shogunate. (True or False)." It also sends the generated quiz questions and options to the terminal.

[0934] The server receives the user's answers, evaluates them against the correct answers, and generates a result. It also generates data to provide feedback and adjust the next quiz based on the evaluation results and the user's emotional state.

[0935] Sentiment Analysis Engine

[0936] The emotion analysis engine analyzes the user's facial expressions and voice to recognize their current emotional state (e.g., "concentrated" or "stressed") using OpenCV and voice emotion analysis tools.

[0937] The emotion analysis engine dynamically adjusts the difficulty of the quiz and the content of the questions based on the emotional state it recognizes. It also visualizes the emotional state and displays it on the device, allowing users to understand their own emotional state.

[0938] Specific examples of operation

[0939] User enters text and sets conditions

[0940] The user inputs text such as "Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital" into the learning application, and sets the question format to true / false, with 10 questions and medium difficulty.

[0941] The device sends data to the server

[0942] The terminal sends a request to the server with conditions set by the user.

[0943] The server parses the text data

[0944] The server analyzes the received text data using a natural language processing library to extract keywords and key phrases, such as "Tokugawa Ieyasu," "Edo Shogunate," "Edo," "domestic stability," and "reform."

[0945] The server generates the quiz

[0946] The server generates quiz questions based on the extracted keywords. Example questions include "Tokugawa Ieyasu established the Edo Shogunate (True or False)" and "The capital of the Edo Shogunate was Osaka (True or False)."

[0947] Prompt Sentence Examples

[0948] User: Enter the following text from a history textbook into the quiz generation system: "Tokugawa Ieyasu established the Edo Shogunate and established its capital in Edo. He stabilized Japan's domestic politics and implemented many reforms."

[0949] Prompt: Generate a true / false question based on the following text: "Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and carried out many reforms."

[0950] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0951] Step 1:

[0952] The user inputs text data and sets the quiz format and question conditions.

[0953] Input: Text data to be studied (e.g., "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital"), quiz format (true / false questions, multiple choice, etc.), number of questions (e.g., 10 questions), difficulty level (e.g., medium).

[0954] Output: The input data and the set conditions.

[0955] Specific operation: The user enters text data and selects various settings via the learning application or web interface.

[0956] Step 2:

[0957] The terminal transmits the user's input data and setting conditions to the server.

[0958] Input: Text data and setting conditions entered by the user.

[0959] Output: The request to the server.

[0960] Specific operation: The terminal creates an HTTP request and sends the user's input and setting conditions to the server.

[0961] Step 3:

[0962] The server analyzes the received text data.

[0963] Input: Text data sent from the terminal.

[0964] Output: Extracted keywords and key sentences.

[0965] Specific operation: The server uses a natural language processing library (e.g., Python's NLTK library or Spacy) to divide the text data into sentences and extract key keywords and sentences.

[0966] Step 4:

[0967] The server generates quiz questions based on the analysis results.

[0968] Input: Extracted keywords and key sentences, set quiz format and conditions.

[0969] Output: The generated quiz question and answer options.

[0970] Specific operation: The server generates quiz questions and answer options based on the extracted keywords and the user's settings. For example, it creates a question such as "Tokugawa Ieyasu established the Edo Shogunate. (True or False)."

[0971] Step 5:

[0972] The server transmits the generated quiz question text and options to the terminal.

[0973] Input: The question text and answer choices for the generated quiz.

[0974] Output: The response to the device.

[0975] Specific operation: The server converts the generated quiz into JSON format or similar and sends it to the device.

[0976] Step 6:

[0977] The terminal displays the received quiz to the user.

[0978] Input: Quiz question text and options sent from the server.

[0979] Output: The quiz screen shown to the user.

[0980] Specific operation: The device uses HTML and JavaScript to generate an interface for displaying the quiz and presents it to the user.

[0981] Step 7:

[0982] The sentiment analysis engine recognizes the user's emotions.

[0983] Input: User's facial expression and voice data.

[0984] Output: Perceived emotional state (e.g., "concentrated" or "stressed").

[0985] How it works: The emotion analysis engine uses OpenCV and speech analysis tools to analyze the user's emotional state in real time.

[0986] Step 8:

[0987] The user answers the quiz.

[0988] Input: Quiz question, answer choices, and user answer (e.g. "Yes").

[0989] Output: User response data.

[0990] Specific operation: The user selects an answer to a displayed quiz question and submits the answer.

[0991] Step 9:

[0992] The terminal transmits the user's answers and emotional state to the server.

[0993] Input: User response data, emotional state recognized by the sentiment analysis engine.

[0994] Output: The request to the server.

[0995] Specific operation: The device sends the user's answer and emotional state to the server again via an HTTP request.

[0996] Step 10:

[0997] The server evaluates the answers and generates a result.

[0998] Input: User's answer data, correct answer data.

[0999] Output: Evaluation results and scores.

[1000] Specific operation: The server evaluates the user's answer against the correct answer and calculates a score. For example, if the user answers "Yes" to the question "Tokugawa Ieyasu established the Edo Shogunate," the server will add a score to the answer.

[1001] Step 11:

[1002] The server generates feedback based on the emotional state.

[1003] Input: Evaluation results and emotional state.

[1004] Output: The feedback message.

[1005] Specific behavior: The server generates feedback based on the user's emotional state, such as messages like "You are concentrating on your studies" or "We recommend you take a break."

[1006] Step 12:

[1007] The terminal displays the results and feedback to the user.

[1008] Input: Evaluation results and feedback messages sent by the server.

[1009] Output: The results screen and feedback shown to the user.

[1010] Specific operation: The device generates an interface to display the result data and feedback messages to the user, and presents them to the user. For example, it displays information such as "Score: 8 / 10" and "Feedback: You are concentrating on your studies."

[1011] (Application example 2)

[1012] 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."

[1013] Current quiz generation systems lack the ability to dynamically adapt to the user's learning style and emotional state, resulting in poor learning efficiency. Another issue is that systems that generate quizzes based on specific content users want to learn lack adequate feedback to improve the user experience.

[1014] 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.

[1015] In this invention, the server includes user means for inputting text data, server means for generating quiz questions from the text data, terminal means for displaying the generated quiz questions and options to the user, emotion engine means for recognizing the user's emotions, and feedback means having a function of dynamically adjusting the difficulty level of the quiz and the content of the questions based on the recognition results of the emotion engine means, thereby enabling a personalized learning experience that suits the user's emotions and learning style.

[1016] "User means" is an interface for inputting text data.

[1017] The "server means" is the core of the system that generates quiz questions from text data.

[1018] The "terminal means" is a device that displays the generated quiz questions and options to the user.

[1019] The "emotion engine means" is a technology for recognizing the user's emotions.

[1020] The "feedback means" is a device or system that has the function of dynamically adjusting the difficulty level of the quiz and the content of the questions based on the recognition results of the emotion engine means.

[1021] "Natural language processing" is a technology that analyzes text data and extracts keywords and key sentences.

[1022] "Quiz format" refers to the way questions are presented in the quiz, and includes true / false questions and multiple choice questions, for example.

[1023] "Question conditions" are parameters designated by the user, such as the number of questions to be asked and the level of difficulty.

[1024] A system for carrying out the present invention includes user means for inputting text data, server means for analyzing the text data and generating quiz question sentences, terminal means for displaying the generated quiz question sentences and options to the user, emotion engine means for recognizing the user's emotions, and feedback means.

[1025] The user means is an interface for inputting text data. For example, a user uses a terminal at a theme park or museum to input information learned from exhibits or guidebooks. The input data is transmitted to the server means via the terminal means.

[1026] The server means analyzes the text data using natural language processing (NLP). Specifically, it uses an NLP library (e.g., Transformers) to extract keywords and key sentences, and generates quiz questions based on the extracted keywords and key sentences. The generated quiz is then transmitted to the terminal means.

[1027] The terminal means is a device that displays the questions and options of the quiz to the user. For example, the quiz is displayed using an interactive display or a smartphone.

[1028] The emotion engine is a technology for recognizing the user's emotional state. It uses a camera to capture the user's facial expressions and analyzes their emotions using image processing and facial recognition technology. The emotion analysis is performed using machine learning libraries such as TensorFlow.

[1029] The feedback means has a function of dynamically adjusting the difficulty level and question content of the quiz based on the recognized emotional state. For example, if the emotion recognition result indicates that the user is "concentrating," feedback is provided to slightly increase the difficulty level of the next quiz.

[1030] This system allows users to have a personalized learning experience that is tailored to their individual emotional state and learning style, and the feedback provided by the system allows users to receive appropriate adjustments based on their own learning progress and emotional state.

[1031] For example, if a visitor to a dinosaur exhibition inputs the text "Tyrannosaurus is a carnivorous dinosaur," the system generates a quiz question such as "Tyrannosaurus is a herbivorous dinosaur (True or False)," which is adjusted based on the user's emotional state.

[1032] An example of a prompt sentence to be input to the generative AI model is as follows:

[1033] Input text: Tyrannosaurus is a carnivorous dinosaur

[1034] conditions:

[1035] Quiz format: True or False

[1036] Difficulty: Medium

[1037] Number of questions: 3 questions

[1038] Generate quiz questions and options based on this.

[1039] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1040] Step 1:

[1041] The user inputs text data and sets the quiz format and question conditions.

[1042] Input: Text data obtained from exhibits and guidebooks, quiz format, number of questions, and difficulty level.

[1043] Output: The quiz generation request sent to the server.

[1044] Specific operation: The user means collects the text data and quiz conditions entered by the user through the interface, and generates a request to send them to the server.

[1045] Step 2:

[1046] The device sends the data to the server.

[1047] Input: A request for text data and conditions set by the user.

[1048] Output: The request sent to the server.

[1049] Specific operation: The terminal means transmits the data input by the user to the server using a communication means such as an HTTP request.

[1050] Step 3:

[1051] The server analyzes the text data and generates a quiz.

[1052] Input: Text data and conditions sent to the server.

[1053] Output: The generated quiz question and answer options.

[1054] Specific operation: The server uses a natural language processing (NLP) library to analyze the text data, extract keywords and key sentences, and then generate quiz questions based on the conditions set by the user.

[1055] Step 4:

[1056] The server sends the generated quiz to the terminal.

[1057] Input: The question text and answer choices for the generated quiz.

[1058] Output: Quiz data sent to the device.

[1059] Specific operation: The server sends the generated quiz data to the terminal. This is also done via an HTTP request.

[1060] Step 5:

[1061] The terminal displays the quiz to the user.

[1062] Input: Quiz data received from the server.

[1063] Output: The quiz question and answer choices that are displayed to the user.

[1064] Specific operation: The terminal means analyzes the received quiz data and displays it in a format that is easy for the user to view.

[1065] Step 6:

[1066] The emotion engine recognizes the user's emotions.

[1067] Input: User's facial expression data.

[1068] Output: Perceived emotional state.

[1069] How it works: The emotion engine captures the user's facial expressions with a camera, analyzes the images using facial recognition technology, and uses machine learning libraries such as TensorFlow to recognize the user's emotional state.

[1070] Step 7:

[1071] The user answers the quiz.

[1072] Input: The answer selected by the user.

[1073] Output: The response data sent from the device to the server.

[1074] Specific operation: The user selects an answer from the quiz question and options displayed on the terminal, and sends this from the terminal to the server.

[1075] Step 8:

[1076] The device sends the answer and emotional state to the server.

[1077] Input: User's answer and the emotion engine's recognition results.

[1078] Output: The data sent to the server.

[1079] Specific operation: The terminal means compiles the user's answers and the emotional state obtained from the emotion engine as data and sends it to the server.

[1080] Step 9:

[1081] The server evaluates the answers and generates a result.

[1082] Input: User response data.

[1083] Output: Evaluation results and scores.

[1084] Specific operation: The server means evaluates the user's answers against the correct answers and generates a score and evaluation result.

[1085] Step 10:

[1086] The server generates feedback based on the emotional state.

[1087] Input: Recognition data for the emotion engine.

[1088] Output: Feedback data.

[1089] Specific operation: The server means generates feedback according to the user's emotional state based on data from the emotion engine.

[1090] Step 11:

[1091] The device displays the results and feedback to the user.

[1092] Input: Assessment results and feedback data.

[1093] Output: Quiz score and feedback displayed to the user.

[1094] Specific operation: The terminal means generates and displays an interface for displaying the received result data and feedback to the user.

[1095] 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.

[1096] 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.

[1097] 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.

[1098] [Third embodiment]

[1099] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1100] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1101] 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).

[1102] 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.

[1103] 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.

[1104] 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).

[1105] 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.

[1106] 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.

[1107] 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.

[1108] 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.

[1109] 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.

[1110] 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."

[1111] The "quiz generation system" of the present invention is a system including a user means for inputting text data, a server means for analyzing the text data and generating quiz questions, and a terminal means for displaying the generated quiz questions and options to the user.

[1112] Overall system configuration and roles

[1113] 1. User Method

[1114] Users input text data into a learning application or web interface.

[1115] Users set conditions such as the quiz format (true / false, multiple choice, written, etc.), number of questions, and difficulty level.

[1116] 2. Terminal means

[1117] The terminal transmits the text data and conditions sent from the user means to the server means.

[1118] The terminal displays the question sentences and options of the quiz sent from the server means to the user.

[1119] The terminal collects the user's answers and transmits them to the server means.

[1120] 3. Server Means

[1121] The server uses natural language processing (NLP) libraries to analyze the text data and extract keywords and key sentences.

[1122] The server generates quiz questions from the analyzed text data based on conditions specified by the user.

[1123] The server receives the user's answers, evaluates them against the correct answers, and generates a result.

[1124] The server transmits the result data to the terminal means.

[1125] Program processing flow and specific examples

[1126] 1. User enters text and sets conditions

[1127] The user inputs the text data they want to study from a particular chapter of a "history textbook" into the application. For example, the following text:

[1128] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[1129] The user sets the format to "True or False," 10 questions, and difficulty level to "medium."

[1130] 2. The device sends the data to the server

[1131] The terminal creates a request to send the user's input to the server.

[1132] 3. The server analyzes the text data

[1133] The server receives the text data and uses natural language processing to extract keywords and sentences such as:

[1134] Keywords: Tokugawa Ieyasu, Edo Shogunate, capital, Edo, domestic affairs, stability, reform

[1135] Extract: Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital.

[1136] 4. The server generates the quiz

[1137] The server generates true / false questions based on the extracted keywords and sentences:

[1138] Question 1: Tokugawa Ieyasu established the Edo Shogunate. (True or False)

[1139] Question 2: The capital of the Edo Shogunate was Osaka. (True or False)

[1140] 5. The server sends the generated quiz to the device.

[1141] The server sends the generated 10 questions to the terminal.

[1142] 6. The device displays the quiz to the user

[1143] The terminal provides an interface that displays the received quiz to the user.

[1144] 7. User takes the quiz

[1145] Users answer quizzes and submit their answers on their terminals.

[1146] 8. The device sends the answer to the server

[1147] The terminal transmits the user's answer to the server.

[1148] 9. The server evaluates the answers and generates a result

[1149] The server evaluates the user's answers and generates correct / incorrect results and a score.

[1150] 10. The device displays the results to the user

[1151] The terminal analyzes the received result data and displays the score and feedback to the user.

[1152] The above is a specific embodiment of the "quiz generation system" based on the present invention. This system allows users to efficiently generate quizzes from their own text materials and advance their studies.

[1153] The processing flow will be explained below.

[1154] Step 1:

[1155] The user launches the quiz generation app and inputs the text data they want to study. For example, they input the text "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital" from a specific chapter of a history textbook. The user also sets conditions such as the quiz format (true or false questions), number of questions (10), and difficulty level (medium).

[1156] Step 2:

[1157] The device creates an API request to send the text data entered by the user and the setting conditions to the server. This request includes information such as the text data, quiz format, and number of questions.

[1158] Step 3:

[1159] The server analyzes the API request received from the device and obtains the text data and user settings. Specifically, it stores the text data in memory and the settings in variables.

[1160] Step 4:

[1161] The server uses natural language processing (NLP) libraries to analyze the text data, tokenize it, split it into sentences, and extract keywords (e.g., "Tokugawa Ieyasu," "Edo Shogunate," "Capital," "Edo"), etc. It also evaluates the meaning and context of sentences to detect important sentences.

[1162] Step 5:

[1163] The server runs an algorithm to generate quiz questions based on the extracted keywords and key sentences. For example, for a true / false question, it generates the question, "Tokugawa Ieyasu established the Edo Shogunate. (True or False)." The generated questions follow the specified format and number of questions.

[1164] Step 6:

[1165] The server packages the generated quiz questions and options in JSON format and creates an API response to send to the device.

[1166] Step 7:

[1167] The device analyzes the JSON data received from the server and generates an interface that displays the quiz questions and options to the user. The UI is designed to make it easy for users to enter answers.

[1168] Step 8:

[1169] The user selects an answer to the displayed quiz and submits the answer. For example, the user selects "Yes" for the question "Tokugawa Ieyasu established the Edo Shogunate."

[1170] Step 9:

[1171] The device collects the user's answers and makes an API request to send to the server, which includes the user's answers for each quiz.

[1172] Step 10:

[1173] The server analyzes the user's answers received from the device and evaluates them against the correct answers. Specifically, it flags each question as correct or incorrect and calculates an overall score.

[1174] Step 11:

[1175] The server packages the evaluation results and scores in JSON format and creates an API response to send to the device.

[1176] Step 12:

[1177] The terminal analyzes the result data received from the server and generates an interface that displays the score and feedback to the user, such as "Your score is 8 / 10. Correct answer: Tokugawa Ieyasu established the Edo Shogunate."

[1178] Example 1

[1179] 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."

[1180] Conventional quiz generation systems have low accuracy when automatically generating quiz questions from text data, or have limited functionality for generating quizzes according to user-specified conditions. This makes it difficult for users to study quizzes satisfactorily. Furthermore, the series of operations, such as displaying the generated quiz questions and options, and evaluating the answers, are sometimes not performed quickly and accurately. Therefore, there is a need for an efficient and accurate way to generate quiz questions based on text data, thereby improving users' learning effectiveness.

[1181] 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.

[1182] In this invention, the server includes user means for inputting text data, information processing means for generating quiz questions from the text data, display means for displaying the generated quiz questions and options to the user, and answer collection means for collecting user answers and transmitting them to the information processing means. This makes it possible to efficiently and accurately generate quiz questions based on text data, and to display and evaluate them.

[1183] "User means" refers to a means by which a user inputs text data and sets the quiz format and question conditions.

[1184] The "information processing device means" refers to a server and related software libraries for analyzing text data and generating quiz question sentences based on extracted keywords and key sentences.

[1185] The term "display device" refers to a terminal having an interface that provides the user with the generated quiz questions and options, or a display device for that purpose.

[1186] The "answer collection means" is a means for collecting the answers given by users to the quiz and transmitting them to the information processing means.

[1187] The "quiz generation system" according to the present invention is a system including a user means for inputting text data, an information processing means for analyzing the text data and generating quiz questions, and a display means for displaying the generated quiz questions and options to the user and collecting answers. The following describes in detail how this system can be implemented.

[1188] Overall system configuration and roles

[1189] 1. User means

[1190] Users input text data using a learning application or web interface, providing the material they want to study by copying and pasting text into an input field or by typing it directly.

[1191] Users can set the quiz format (true / false, multiple choice, etc.), number of questions, difficulty level, and other parameters using drop-down menus and radio buttons on the interface.

[1192] 2. Information Processing Device Means

[1193] The information processing device (server) uses a natural language processing (NLP) library to analyze the received text data. As a specific example, the NLTK library of Python is used.

[1194] The server extracts keywords and key sentences from the text data and generates quiz questions based on the set conditions.

[1195] 3. Display device means

[1196] The terminal transmits the text data and conditions sent from the user means to the server means (information processing device) using a standard HTTP request for communication.

[1197] The terminal has an interface that provides the user with the question sentences and options of the generated quiz sent from the server.

[1198] The device collects the user's answers and sends them to the server, again using an HTTP request.

[1199] Program processing flow and specific examples

[1200] 1. User enters text and sets conditions

[1201] The user inputs the text data they want to study from a particular chapter of a "history textbook" into the application. For example, the following text:

[1202] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[1203] The user also sets the format to "True or False," 10 questions, and difficulty level to "Medium."

[1204] 2. Examples of prompts

[1205] Here are some example prompts to input to a generative AI model:

[1206] input:

[1207] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[1208] conditions:

[1209] Quiz format: True or False

[1210] Number of questions: 10 questions

[1211] Difficulty: Medium

[1212] output:

[1213] Question 1: Tokugawa Ieyasu established the Edo Shogunate. (True or False)

[1214] Question 2: The capital of the Edo Shogunate was Osaka. (True or False)

[1215] Hardware and software used

[1216] 1. User means

[1217] The user's personal computer or smartphone.

[1218] Learning applications and web interfaces (e.g. web front-ends using React, Angular, etc.).

[1219] 2. Information Processing Device Means

[1220] Server: Cloud-based server (e.g., Amazon Web Services, Microsoft Azure).

[1221] Natural language processing libraries: Python's NLTK, spaCy, etc.

[1222] 3. Display device means

[1223] The user's personal computer or smartphone.

[1224] A web interface that runs on a browser.

[1225] In this way, the "quiz generation system" based on the present invention functions as a tool for users to efficiently generate quizzes from any text material and deepen their learning.

[1226] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1227] Step 1:

[1228] The user inputs text data and sets the conditions for the quiz.

[1229] Input: Text data entered by the user using the learning application or web interface, as well as the type, number and difficulty of the quiz selected by the user.

[1230] Data processing: The text data provided by the user is saved and the selected conditions are stored in memory.

[1231] Output: The prepared data structure is passed to the terminal. Specifically, user actions in text fields and selection menus are constructed as requests to the server.

[1232] Step 2:

[1233] The terminal transmits the input text data and conditions to the server.

[1234] Input: The text data entered by the user, as well as the quiz format, number of questions, and difficulty level you set.

[1235] Data processing: Properly formatting this data to generate HTTP requests, for example, converting it to JSON format.

[1236] Output: Data structure as a request sent to the server. For example, JSON data like this:

[1237] json

[1238] {

[1239] "text": "Tokugawa Ieyasu established the Edo Shogunate and established its capital in Edo. He stabilized Japan's domestic politics and implemented many reforms.",

[1240] "quiz_format": "〇×Question",

[1241] "num_questions": 10,

[1242] "difficulty": "medium"

[1243] }

[1244] Step 3:

[1245] The server receives and analyzes the text data.

[1246] Input: Text data sent from the device and setting conditions.

[1247] Data processing: Extract keywords and key sentences using a natural language processing (NLP) library (e.g., Python's NLTK). For example, split the text into sentences and extract keywords.

[1248] python

[1249] import nltk

[1250] from nltk.tokenize import sent_tokenize, word_tokenize

[1251] text = "Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms."

[1252] sentences = sent_tokenize(text)

[1253] words = word_tokenize(text)

[1254] keywords = [word for word in words if word in important_words_list]

[1255] Output: A list of extracted keywords and key sentences.

[1256] Step 4:

[1257] The server generates the quiz questions.

[1258] Input: Extracted keywords and key sentences, conditions set by the user (format, number of questions, difficulty level).

[1259] Data processing: Generate quiz questions based on the specified conditions. Specifically, if you want to create a true / false question, generate it as follows:

[1260] python

[1261] quizzes = [

[1262] {"question": "Tokugawa Ieyasu established the Edo Shogunate.", "correct_answer": "Yes"},

[1263] {"question": "The capital of the Edo Shogunate was Osaka.", "correct_answer": "×"}

[1264] ]

[1265] Output: The generated quiz question and answer options.

[1266] Step 5:

[1267] The server sends the generated quiz back to the terminal.

[1268] Input: The question text and answer choices for the generated quiz.

[1269] Data processing: Format these as an HTTP response and send it to the terminal. For example, generate a JSON format response.

[1270] json

[1271] {

[1272] "quizzes": [

[1273] {"question": "Tokugawa Ieyasu established the Edo Shogunate.", "options": ["Yes", "No"]},

[1274] {"question": "The capital of the Edo Shogunate was Osaka.", "options": ["Yes", "No"]}

[1275] ]

[1276] }

[1277] Output: The quiz data provided to the device.

[1278] Step 6:

[1279] The terminal displays the quiz to the user.

[1280] Input: Quiz data received from the server.

[1281] Data processing: The quiz questions and options are laid out and displayed in the user interface. This is implemented using HTML and JavaScript.

[1282] Output: Displaying quiz questions to the user. Specifically, a quiz screen is generated and the user is ready to answer.

[1283] Step 7:

[1284] The user answers the quiz.

[1285] Input: The displayed quiz question and choices.

[1286] Data processing: The user selects the answer to a question. The selection is reflected by clicking or tapping.

[1287] Output: User response data. Specifically, the selected options are collected.

[1288] Step 8:

[1289] The terminal sends the user's answer to the server.

[1290] Input: User selected answer data.

[1291] Data processing: The response data is formatted and sent to the server, again using an HTTP request.

[1292] Output: The response data sent to the server. For example, the following JSON data:

[1293] json

[1294] {

[1295] "answers": ["Yes", "No"]

[1296] }

[1297] Step 9:

[1298] The server evaluates the user's answers and generates a result.

[1299] Input: User response data.

[1300] Data processing: Compare with the correct answer data and calculate the evaluation and score. As an example of evaluation, we will determine whether the answer is correct or incorrect as follows.

[1301] python

[1302] correct_answers = ["〇", "×"]

[1303] user_answers = ["Yes", "No"]

[1304] results = [{"question": "Tokugawa Ieyasu established the Edo Shogunate.", "user_answer": "Yes", "correct": True},

[1305] {"question": "The capital of the Edo Shogunate was Osaka.", "user_answer": "×", "correct": True}]

[1306] Output: Evaluation results and score data.

[1307] Step 10:

[1308] The terminal displays the results to the user.

[1309] Input: Evaluation results and score data received from the server.

[1310] Data processing: Evaluation results and score data are laid out and displayed on the interface. This is implemented using HTML and JavaScript.

[1311] Output: Displaying the scores and evaluation results to the user. Specifically, a results screen is generated so that the user can check their performance.

[1312] (Application example 1)

[1313] 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."

[1314] Conventional quiz generation systems require the input of text data, which is a time-consuming process of manually inputting text from books or paper media. Additionally, while technology for generating quizzes using natural language processing is available, it lacks the functionality to directly extract text from images and use it to generate quizzes, making it difficult to provide learners with more intuitive, real-time learning support.

[1315] 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.

[1316] In this invention, the server includes information input means for inputting text data, analysis means for generating quiz questions from the text data, output means for displaying the generated quiz questions and options on information display means, character recognition means for extracting text from images, and question generation means for generating quizzes based on the text extracted by the character recognition means. This makes it possible to generate quizzes by extracting text directly from books or paper media and provide them to learners immediately.

[1317] "Text data" refers to information expressed as a string of characters, including sentences and paragraphs that form the basis for generating quizzes.

[1318] "Information input means" refers to an interface or device that allows a user to input text data into a system.

[1319] The "analysis means" is a part of the system that performs analysis to generate quiz questions based on the input text data.

[1320] "Information display means" refers to an interface or device used to display the generated quiz questions and options to the user.

[1321] The "output means" is a part of the system that provides the quiz questions and options to the user via the information display means.

[1322] A “character recognition means” is a part of a system that uses optical character recognition (OCR) technology to extract text from images.

[1323] The "question generation means" is a part of the system that generates quiz questions based on the text extracted by the character recognition means.

[1324] The "quiz generation system" according to the present invention is a system including information input means, analysis means, information display means, output means, character recognition means, and question generation means.

[1325] 1. Overall system configuration

[1326] Information input means: Users input text data or images into the system. Examples include smartphone or tablet applications.

[1327] Analysis method: Analyzes the text data sent from the information input method and extracts keywords and key sentences. This process uses a natural language processing (NLP) library.

[1328] Information display means: The quiz questions and options generated by the analysis means are displayed to the user. This corresponds to the application screen of a smartphone or tablet.

[1329] Output means: A part of the system that provides the quiz to the user via the information display means.

[1330] Character Recognition Method: Optical Character Recognition (OCR) technology is used to extract text from images. This process utilizes the Google Cloud Vision API.

[1331] Question generation: Quiz questions are generated based on the text extracted by the character recognition method. This process uses the Hugging Face Transformers library.

[1332] 2. Hardware and Software Used

[1333] Hardware: Smartphone, tablet, camera for OCR.

[1334] Software: Google Cloud Vision API, Hugging Face Transformers, Python.

[1335] 3. Example of a system

[1336] A user scans a book or specific materials from a cram school using their smartphone camera and inputs the image into the system. The text in this image is converted into text data using the Google Cloud Vision API, a character recognition method. The converted text data is analyzed using a natural language processing library, which serves as an analysis method, and keywords and key sentences are extracted. Quiz questions are then generated using the Hugging Face Transformers library, which serves as a question generation method. The generated quiz questions and answer options are displayed on the screen of a smartphone or tablet, which serves as an information display method, and provided to the user via an output method. The user answers the displayed quiz questions and progresses with their studies.

[1337] 4. Examples of prompt sentences

[1338] As part of the operation of this system, the user may enter prompts such as:

[1339] text

[1340] Enter text: Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[1341] Quiz format: 4 choices

[1342] Number of questions: 5 questions

[1343] The above is a specific embodiment of the "quiz generation system" of the present invention. This system allows users to extract text directly from images and automatically generate quizzes to advance their learning.

[1344] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1345] Step 1:

[1346] A user launches an application on their smartphone or tablet and scans a book or study material with the smartphone's camera, obtaining image data as input, which is then saved in the application as output.

[1347] Step 2:

[1348] The device sends image data to the Google Cloud Vision API, a character recognition tool. The character recognition tool then analyzes the characters in the image and obtains text data as output. Specifically, it processes the pixel data of the image and returns the recognized string of characters as text data.

[1349] Step 3:

[1350] The device sends the obtained text data to a natural language processing (NLP) library as an analysis means, which then extracts keywords and key sentences from the text data. The device receives the text data as input and obtains a list of keywords and extracted sentences as output.

[1351] Step 4:

[1352] The server generates quiz questions using the Hugging Face Transformers library, a question generation tool, based on the keywords and key sentences extracted by the analysis tool. Keywords and key sentences are received as input, and the quiz questions and options are obtained as output. Specifically, a prompt is input into the generation AI model, and questions and options that fit the quiz format are generated.

[1353] Step 5:

[1354] The server sends the generated quiz questions and options to the terminal, which receives data from the server as input and converts it into a format that can be displayed on the terminal as output.

[1355] Step 6:

[1356] The device displays the quiz question and options on a user interface as information display means, allowing the user to take the quiz. Specifically, the quiz question and multiple options are visually displayed on the screen.

[1357] Step 7:

[1358] The user answers the quiz and submits the answers on the device, which receives the user's selected options as input and sends the data to the server as output.

[1359] Step 8:

[1360] The server evaluates the user's answers and generates a result indicating whether they are correct or incorrect. The answer data received is used as input, and the evaluation result is obtained as output. Specifically, the result is calculated after comparing it with the correct answer, and a score and feedback are generated.

[1361] Step 9:

[1362] The server receives the evaluation result data as input and converts it into a format that can be sent to the terminal as output.

[1363] Step 10:

[1364] The device displays the assessment results to the user, allowing them to check their learning progress. Specifically, the device visually displays scores and feedback on the screen.

[1365] 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.

[1366] The "quiz generation system" according to the present invention is a system including a user means for inputting text data, a server means for analyzing the text data and generating quiz questions, a terminal means for displaying the generated quiz questions and options to the user, and an emotion engine for recognizing the user's emotions.

[1367] Overall system configuration and roles

[1368] 1. User Method

[1369] A user inputs text data into a learning application or web interface. For example, the text "Tokugawa Ieyasu established the Edo Shogunate and established its capital in Edo" from a specific chapter of a history textbook. The user also sets parameters such as the quiz format (true / false questions, multiple choice, etc.), the number of questions (10), and the difficulty level (medium).

[1370] 2. Terminal means

[1371] The terminal transmits the text data and conditions sent from the user means to the server means.

[1372] The terminal displays the question sentences and options of the quiz sent from the server means to the user.

[1373] The terminal collects the user's answers and emotional state and transmits them to the server means and the emotion engine.

[1374] 3. Server Means

[1375] The server uses natural language processing (NLP) libraries to analyze the text data and extract keywords and key sentences.

[1376] The server generates quiz questions from the analyzed text data based on conditions specified by the user.

[1377] The server receives the user's answers, evaluates them against the correct answers, and generates a result.

[1378] The server generates data based on the evaluation results and the user's emotional state to provide feedback and adjust the next quiz.

[1379] 4. Emotion Engine

[1380] The emotion engine has the ability to recognize the user's emotions, for example, by measuring the user's stress and concentration level using facial expression recognition technology and voice analysis technology.

[1381] The emotion engine dynamically adjusts the difficulty and content of the quiz based on the perceived emotional state.

[1382] The emotion engine visualizes the emotional state and displays it on the terminal means, thereby enabling the user to understand his or her own emotional state.

[1383] Program processing flow and specific examples

[1384] 1. User enters text and sets conditions

[1385] The user inputs the text data they want to study from a particular chapter of a "history textbook" into the application. For example, the following text:

[1386] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[1387] The user sets the format to "True or False," 10 questions, and difficulty level to "medium."

[1388] 2. The device sends the data to the server

[1389] The terminal creates a request to send the user's input to the server.

[1390] 3. The server analyzes the text data

[1391] The server receives the text data and uses natural language processing to extract keywords and sentences such as:

[1392] Keywords: Tokugawa Ieyasu, Edo Shogunate, capital, Edo, domestic affairs, stability, reform

[1393] Extract: Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital.

[1394] 4. The server generates the quiz

[1395] The server generates true / false questions based on the extracted keywords and sentences:

[1396] Question 1: Tokugawa Ieyasu established the Edo Shogunate. (True or False)

[1397] Question 2: The capital of the Edo Shogunate was Osaka. (True or False)

[1398] 5. The server sends the generated quiz to the device.

[1399] The server sends the generated 10 questions to the terminal.

[1400] 6. The device displays the quiz to the user

[1401] The terminal provides an interface that displays the received quiz to the user.

[1402] 7. Emotion engine recognizes user emotions

[1403] The emotion engine analyzes the user's facial expressions and voice to recognize their current emotional state, such as "concentrated" or "stressed."

[1404] 8. User takes the quiz

[1405] The user selects an answer to the displayed quiz and submits the answer. For example, the user selects "Yes" for the question "Tokugawa Ieyasu established the Edo Shogunate."

[1406] 9. The device sends the answer and emotional state to the server.

[1407] The terminal transmits the user's response and the emotional state recognized by the emotion engine to the server.

[1408] 10. The server evaluates the answers and generates the results

[1409] The server evaluates the user's answers and generates correct / incorrect results and a score.

[1410] 11. The server generates feedback based on the emotional state

[1411] The server uses data from the emotion engine to generate feedback based on the user's emotional state, such as "You are concentrating on your studies" or "We recommend you take a break."

[1412] 12. The device displays the results and feedback to the user

[1413] The device generates an interface that displays the received result data and feedback to the user, such as "Score: 8 / 10" or "Feedback: You are concentrating on your studies."

[1414] The above is a specific embodiment of the "quiz generation system" based on the present invention. This system allows users to efficiently generate quizzes from their own text materials and further progress in their studies while understanding their own emotional state.

[1415] The processing flow will be explained below.

[1416] Step 1:

[1417] The user launches the quiz generation app and inputs the text data they want to study. For example, they input the text "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital" from a specific chapter of a history textbook. The user also sets conditions such as the quiz format (true or false questions), number of questions (10), and difficulty level (medium).

[1418] Step 2:

[1419] The device creates an API request to send the text data entered by the user and the setting conditions to the server. This request includes information such as the text data, quiz format, and number of questions.

[1420] Step 3:

[1421] The server analyzes the API request received from the device and obtains the text data and user settings. Specifically, it stores the text data in memory and the settings in variables.

[1422] Step 4:

[1423] The server uses natural language processing (NLP) libraries to analyze the text data, tokenize it, split it into sentences, and extract keywords (e.g., "Tokugawa Ieyasu," "Edo Shogunate," "Capital," "Edo"), etc. It also evaluates the meaning and context of sentences to detect important sentences.

[1424] Step 5:

[1425] The server runs an algorithm to generate quiz questions based on the extracted keywords and key sentences. For example, for a true / false question, it generates the question, "Tokugawa Ieyasu established the Edo Shogunate. (True or False)." The generated questions follow the specified format and number of questions.

[1426] Step 6:

[1427] The server packages the generated quiz questions and options in JSON format and creates an API response to send to the device.

[1428] Step 7:

[1429] The device analyzes the JSON data received from the server and generates an interface that displays the quiz questions and options to the user. The UI is designed to make it easy for users to enter answers.

[1430] Step 8:

[1431] The device activates an emotion engine, analyzes the user's facial expressions and voice in real time, and measures their emotional state. For example, if the user is smiling, it is recognized as "having fun," and if they frown, it is recognized as "feeling stressed."

[1432] Step 9:

[1433] The user selects an answer to the displayed quiz and submits the answer. For example, the user selects "Yes" for the question "Tokugawa Ieyasu established the Edo Shogunate."

[1434] Step 10:

[1435] The device collects the user's answers and makes an API request to send to the server along with the emotional state data from the emotion engine. The request includes the user's answers and emotional state for each quiz.

[1436] Step 11:

[1437] The server analyzes the user's answers received from the device and evaluates them against the correct answers. Specifically, it flags each question as correct or incorrect and calculates an overall score.

[1438] Step 12:

[1439] The server generates feedback based on the user's emotional state based on data from the emotion engine. For example, if the user is concentrating, it generates a message such as "You are studying very hard," and if the user is feeling stressed, it generates a message such as "We recommend that you take a break."

[1440] Step 13:

[1441] The server packages the evaluation results and feedback in JSON format and creates an API response to send to the device.

[1442] Step 14:

[1443] The device analyzes the results and feedback received from the server and generates an interface to display to the user, such as "Score: 8 / 10" or "Feedback: Very focused on studying."

[1444] This is the specific processing flow of the "quiz generation system." This system allows users to efficiently generate and answer quizzes, and progress in their studies while understanding their own emotional state.

[1445] Example 2

[1446] 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."

[1447] In conventional quiz generation systems, generating quizzes from text data is a simple, routine task, making it difficult to dynamically adjust the system to maximize the user's learning effectiveness. Furthermore, because questions are generated without taking into account the user's emotional state, they are unable to adapt to changes in stress or concentration, resulting in a decline in learning efficiency.

[1448] 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.

[1449] In this invention, the server includes a user means for inputting text data, a server for generating quiz questions from the text data, a terminal for displaying the generated quiz questions and options to the user, and an emotion analysis engine for recognizing the user's emotions and adjusting the difficulty of the quiz, thereby enabling dynamic quiz generation and question setting according to the user's learning situation and emotional state.

[1450] "Text data" refers to character string information data entered by the user, and is used as material for quiz questions.

[1451] The "user means" is an interface that allows the user to input text data and set the format and conditions of the quiz.

[1452] The "server" is a computer system that receives text data sent by users, analyzes it using natural language processing, and generates quiz questions.

[1453] "Natural language processing" is a technology that analyzes text data, extracts keywords and key sentences, and generates quiz questions.

[1454] A "terminal" is a device that displays input data from a user and quiz questions and options sent from a server.

[1455] The "emotion analysis engine" is a system that analyzes the user's facial expressions and voice data, recognizes their emotional state, and adjusts the difficulty of the quiz accordingly.

[1456] A "quiz question" is a question-style sentence generated based on text data, to which the user responds.

[1457] "Choices" are multiple answer options for a quiz question, from which the user selects the correct answer.

[1458] "Feedback" refers to advice or evaluation provided based on the user's answers and emotional state.

[1459] The "quiz generation system" according to the present invention is a system including a user means for inputting text data, a server means for analyzing the text data and generating quiz questions, a terminal means for displaying the generated quiz questions and options to the user, and an emotion analysis engine for recognizing the emotions of the user. Specific embodiments of each means are described below.

[1460] User Means

[1461] A user inputs text data into a learning application or web interface. For example, they input the text "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital" from a specific chapter in a history textbook. The user also sets conditions such as the quiz format (true / false questions, multiple choice, etc.), number of questions (10), difficulty level (medium), etc. These settings are made through the UI (user interface).

[1462] Terminal means

[1463] The terminal transmits the text data and conditions sent from the user means to the server means, for example, using an HTTP request.

[1464] The terminal displays the questions and options of the quiz sent from the server means to the user, using an interface that is dynamically generated using HTML and JavaScript.

[1465] The terminal collects the user's answers and emotional state and transmits them to the server means and the emotion analysis engine.

[1466] Server Means

[1467] The server receives the text data sent by the user and analyzes it using, for example, Python's Natural Language Toolkit (NLTK) or Spacy. Specifically, the analysis is performed using the following steps:

[1468] The server divides the text data into sentence units.

[1469] The server extracts key keywords from each sentence, such as "Tokugawa Ieyasu," "Edo Shogunate," and "Edo."

[1470] The server generates quiz questions from the analyzed text data based on the user's criteria. For example, it generates a question such as "Tokugawa Ieyasu established the Edo Shogunate. (True or False)." It also sends the generated quiz questions and options to the terminal.

[1471] The server receives the user's answers, evaluates them against the correct answers, and generates a result. It also generates data to provide feedback and adjust the next quiz based on the evaluation results and the user's emotional state.

[1472] Sentiment Analysis Engine

[1473] The emotion analysis engine analyzes the user's facial expressions and voice to recognize their current emotional state (e.g., "concentrated" or "stressed") using OpenCV and voice emotion analysis tools.

[1474] The emotion analysis engine dynamically adjusts the difficulty of the quiz and the content of the questions based on the emotional state it recognizes. It also visualizes the emotional state and displays it on the device, allowing users to understand their own emotional state.

[1475] Specific examples of operation

[1476] User enters text and sets conditions

[1477] The user inputs text such as "Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital" into the learning application, and sets the question format to true / false, with 10 questions and medium difficulty.

[1478] The device sends data to the server

[1479] The terminal sends a request to the server with conditions set by the user.

[1480] The server parses the text data

[1481] The server analyzes the received text data using a natural language processing library to extract keywords and key phrases, such as "Tokugawa Ieyasu," "Edo Shogunate," "Edo," "domestic stability," and "reform."

[1482] The server generates the quiz

[1483] The server generates quiz questions based on the extracted keywords. Example questions include "Tokugawa Ieyasu established the Edo Shogunate (True or False)" and "The capital of the Edo Shogunate was Osaka (True or False)."

[1484] Prompt Sentence Examples

[1485] User: Enter the following text from a history textbook into the quiz generation system: "Tokugawa Ieyasu established the Edo Shogunate and established its capital in Edo. He stabilized Japan's domestic politics and implemented many reforms."

[1486] Prompt: Generate a true / false question based on the following text: "Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and carried out many reforms."

[1487] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1488] Step 1:

[1489] The user inputs text data and sets the quiz format and question conditions.

[1490] Input: Text data to be studied (e.g., "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital"), quiz format (true / false questions, multiple choice, etc.), number of questions (e.g., 10 questions), difficulty level (e.g., medium).

[1491] Output: The input data and the set conditions.

[1492] Specific operation: The user enters text data and selects various settings via the learning application or web interface.

[1493] Step 2:

[1494] The terminal transmits the user's input data and setting conditions to the server.

[1495] Input: Text data and setting conditions entered by the user.

[1496] Output: The request to the server.

[1497] Specific operation: The terminal creates an HTTP request and sends the user's input and setting conditions to the server.

[1498] Step 3:

[1499] The server analyzes the received text data.

[1500] Input: Text data sent from the terminal.

[1501] Output: Extracted keywords and key sentences.

[1502] Specific operation: The server uses a natural language processing library (e.g., Python's NLTK library or Spacy) to divide the text data into sentences and extract key keywords and sentences.

[1503] Step 4:

[1504] The server generates quiz questions based on the analysis results.

[1505] Input: Extracted keywords and key sentences, set quiz format and conditions.

[1506] Output: The generated quiz question and answer options.

[1507] Specific operation: The server generates quiz questions and answer options based on the extracted keywords and the user's settings. For example, it creates a question such as "Tokugawa Ieyasu established the Edo Shogunate. (True or False)."

[1508] Step 5:

[1509] The server transmits the generated quiz question text and options to the terminal.

[1510] Input: The question text and answer choices for the generated quiz.

[1511] Output: The response to the device.

[1512] Specific operation: The server converts the generated quiz into JSON format or similar and sends it to the device.

[1513] Step 6:

[1514] The terminal displays the received quiz to the user.

[1515] Input: Quiz question text and options sent from the server.

[1516] Output: The quiz screen shown to the user.

[1517] Specific operation: The device uses HTML and JavaScript to generate an interface for displaying the quiz and presents it to the user.

[1518] Step 7:

[1519] The sentiment analysis engine recognizes the user's emotions.

[1520] Input: User's facial expression and voice data.

[1521] Output: Perceived emotional state (e.g., "concentrated" or "stressed").

[1522] How it works: The emotion analysis engine uses OpenCV and speech analysis tools to analyze the user's emotional state in real time.

[1523] Step 8:

[1524] The user answers the quiz.

[1525] Input: Quiz question, answer choices, and user answer (e.g. "Yes").

[1526] Output: User response data.

[1527] Specific operation: The user selects an answer to a displayed quiz question and submits the answer.

[1528] Step 9:

[1529] The terminal transmits the user's answers and emotional state to the server.

[1530] Input: User response data, emotional state recognized by the sentiment analysis engine.

[1531] Output: The request to the server.

[1532] Specific operation: The device sends the user's answer and emotional state to the server again via an HTTP request.

[1533] Step 10:

[1534] The server evaluates the answers and generates a result.

[1535] Input: User's answer data, correct answer data.

[1536] Output: Evaluation results and scores.

[1537] Specific operation: The server evaluates the user's answer against the correct answer and calculates a score. For example, if the user answers "Yes" to the question "Tokugawa Ieyasu established the Edo Shogunate," the server will add a score to the answer.

[1538] Step 11:

[1539] The server generates feedback based on the emotional state.

[1540] Input: Evaluation results and emotional state.

[1541] Output: The feedback message.

[1542] Specific behavior: The server generates feedback based on the user's emotional state, such as messages like "You are concentrating on your studies" or "We recommend you take a break."

[1543] Step 12:

[1544] The terminal displays the results and feedback to the user.

[1545] Input: Evaluation results and feedback messages sent by the server.

[1546] Output: The results screen and feedback shown to the user.

[1547] Specific operation: The device generates an interface to display the result data and feedback messages to the user, and presents them to the user. For example, it displays information such as "Score: 8 / 10" and "Feedback: You are concentrating on your studies."

[1548] (Application example 2)

[1549] 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."

[1550] Current quiz generation systems lack the ability to dynamically adapt to the user's learning style and emotional state, resulting in poor learning efficiency. Another issue is that systems that generate quizzes based on specific content users want to learn lack adequate feedback to improve the user experience.

[1551] 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.

[1552] In this invention, the server includes user means for inputting text data, server means for generating quiz questions from the text data, terminal means for displaying the generated quiz questions and options to the user, emotion engine means for recognizing the user's emotions, and feedback means having a function of dynamically adjusting the difficulty level of the quiz and the content of the questions based on the recognition results of the emotion engine means, thereby enabling a personalized learning experience that suits the user's emotions and learning style.

[1553] "User means" is an interface for inputting text data.

[1554] The "server means" is the core of the system that generates quiz questions from text data.

[1555] The "terminal means" is a device that displays the generated quiz questions and options to the user.

[1556] The "emotion engine means" is a technology for recognizing the user's emotions.

[1557] The "feedback means" is a device or system that has the function of dynamically adjusting the difficulty level of the quiz and the content of the questions based on the recognition results of the emotion engine means.

[1558] "Natural language processing" is a technology that analyzes text data and extracts keywords and key sentences.

[1559] "Quiz format" refers to the way questions are presented in the quiz, and includes true / false questions and multiple choice questions, for example.

[1560] "Question conditions" are parameters designated by the user, such as the number of questions to be asked and the level of difficulty.

[1561] A system for carrying out the present invention includes user means for inputting text data, server means for analyzing the text data and generating quiz question sentences, terminal means for displaying the generated quiz question sentences and options to the user, emotion engine means for recognizing the user's emotions, and feedback means.

[1562] The user means is an interface for inputting text data. For example, a user uses a terminal at a theme park or museum to input information learned from exhibits or guidebooks. The input data is transmitted to the server means via the terminal means.

[1563] The server means analyzes the text data using natural language processing (NLP). Specifically, it uses an NLP library (e.g., Transformers) to extract keywords and key sentences, and generates quiz questions based on the extracted keywords and key sentences. The generated quiz is then transmitted to the terminal means.

[1564] The terminal means is a device that displays the questions and options of the quiz to the user. For example, the quiz is displayed using an interactive display or a smartphone.

[1565] The emotion engine is a technology for recognizing the user's emotional state. It uses a camera to capture the user's facial expressions and analyzes their emotions using image processing and facial recognition technology. The emotion analysis is performed using machine learning libraries such as TensorFlow.

[1566] The feedback means has a function of dynamically adjusting the difficulty level and question content of the quiz based on the recognized emotional state. For example, if the emotion recognition result indicates that the user is "concentrating," feedback is provided to slightly increase the difficulty level of the next quiz.

[1567] This system allows users to have a personalized learning experience that is tailored to their individual emotional state and learning style, and the feedback provided by the system allows users to receive appropriate adjustments based on their own learning progress and emotional state.

[1568] For example, if a visitor to a dinosaur exhibition inputs the text "Tyrannosaurus is a carnivorous dinosaur," the system generates a quiz question such as "Tyrannosaurus is a herbivorous dinosaur (True or False)," which is adjusted based on the user's emotional state.

[1569] An example of a prompt sentence to be input to the generative AI model is as follows:

[1570] Input text: Tyrannosaurus is a carnivorous dinosaur

[1571] conditions:

[1572] Quiz format: True or False

[1573] Difficulty: Medium

[1574] Number of questions: 3 questions

[1575] Generate quiz questions and options based on this.

[1576] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1577] Step 1:

[1578] The user inputs text data and sets the quiz format and question conditions.

[1579] Input: Text data obtained from exhibits and guidebooks, quiz format, number of questions, and difficulty level.

[1580] Output: The quiz generation request sent to the server.

[1581] Specific operation: The user means collects the text data and quiz conditions entered by the user through the interface, and generates a request to send them to the server.

[1582] Step 2:

[1583] The device sends the data to the server.

[1584] Input: A request for text data and conditions set by the user.

[1585] Output: The request sent to the server.

[1586] Specific operation: The terminal means transmits the data input by the user to the server using a communication means such as an HTTP request.

[1587] Step 3:

[1588] The server analyzes the text data and generates a quiz.

[1589] Input: Text data and conditions sent to the server.

[1590] Output: The generated quiz question and answer options.

[1591] Specific operation: The server uses a natural language processing (NLP) library to analyze the text data, extract keywords and key sentences, and then generate quiz questions based on the conditions set by the user.

[1592] Step 4:

[1593] The server sends the generated quiz to the terminal.

[1594] Input: The question text and answer choices for the generated quiz.

[1595] Output: Quiz data sent to the device.

[1596] Specific operation: The server sends the generated quiz data to the terminal. This is also done via an HTTP request.

[1597] Step 5:

[1598] The terminal displays the quiz to the user.

[1599] Input: Quiz data received from the server.

[1600] Output: The quiz question and answer choices that are displayed to the user.

[1601] Specific operation: The terminal means analyzes the received quiz data and displays it in a format that is easy for the user to view.

[1602] Step 6:

[1603] The emotion engine recognizes the user's emotions.

[1604] Input: User's facial expression data.

[1605] Output: Perceived emotional state.

[1606] How it works: The emotion engine captures the user's facial expressions with a camera, analyzes the images using facial recognition technology, and uses machine learning libraries such as TensorFlow to recognize the user's emotional state.

[1607] Step 7:

[1608] The user answers the quiz.

[1609] Input: The answer selected by the user.

[1610] Output: The response data sent from the device to the server.

[1611] Specific operation: The user selects an answer from the quiz question and options displayed on the terminal, and sends this from the terminal to the server.

[1612] Step 8:

[1613] The device sends the answer and emotional state to the server.

[1614] Input: User's answer and the emotion engine's recognition results.

[1615] Output: The data sent to the server.

[1616] Specific operation: The terminal means compiles the user's answers and the emotional state obtained from the emotion engine as data and sends it to the server.

[1617] Step 9:

[1618] The server evaluates the answers and generates a result.

[1619] Input: User response data.

[1620] Output: Evaluation results and scores.

[1621] Specific operation: The server means evaluates the user's answers against the correct answers and generates a score and evaluation result.

[1622] Step 10:

[1623] The server generates feedback based on the emotional state.

[1624] Input: Recognition data for the emotion engine.

[1625] Output: Feedback data.

[1626] Specific operation: The server means generates feedback according to the user's emotional state based on data from the emotion engine.

[1627] Step 11:

[1628] The device displays the results and feedback to the user.

[1629] Input: Assessment results and feedback data.

[1630] Output: Quiz score and feedback displayed to the user.

[1631] Specific operation: The terminal means generates and displays an interface for displaying the received result data and feedback to the user.

[1632] 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.

[1633] 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.

[1634] 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.

[1635] [Fourth embodiment]

[1636] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1637] 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.

[1638] 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).

[1639] 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.

[1640] 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.

[1641] 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).

[1642] 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.

[1643] 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.

[1644] 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.

[1645] 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.

[1646] 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.

[1647] 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.

[1648] 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."

[1649] The "quiz generation system" of the present invention is a system including a user means for inputting text data, a server means for analyzing the text data and generating quiz questions, and a terminal means for displaying the generated quiz questions and options to the user.

[1650] Overall system configuration and roles

[1651] 1. User Method

[1652] Users input text data into a learning application or web interface.

[1653] Users set conditions such as the quiz format (true / false, multiple choice, written, etc.), number of questions, and difficulty level.

[1654] 2. Terminal means

[1655] The terminal transmits the text data and conditions sent from the user means to the server means.

[1656] The terminal displays the question sentences and options of the quiz sent from the server means to the user.

[1657] The terminal collects the user's answers and transmits them to the server means.

[1658] 3. Server Means

[1659] The server uses natural language processing (NLP) libraries to analyze the text data and extract keywords and key sentences.

[1660] The server generates quiz questions from the analyzed text data based on conditions specified by the user.

[1661] The server receives the user's answers, evaluates them against the correct answers, and generates a result.

[1662] The server transmits the result data to the terminal means.

[1663] Program processing flow and specific examples

[1664] 1. User enters text and sets conditions

[1665] The user inputs the text data they want to study from a particular chapter of a "history textbook" into the application. For example, the following text:

[1666] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[1667] The user sets the format to "True or False," 10 questions, and difficulty level to "medium."

[1668] 2. The device sends the data to the server

[1669] The terminal creates a request to send the user's input to the server.

[1670] 3. The server analyzes the text data

[1671] The server receives the text data and uses natural language processing to extract keywords and sentences such as:

[1672] Keywords: Tokugawa Ieyasu, Edo Shogunate, capital, Edo, domestic affairs, stability, reform

[1673] Extract: Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital.

[1674] 4. The server generates the quiz

[1675] The server generates true / false questions based on the extracted keywords and sentences:

[1676] Question 1: Tokugawa Ieyasu established the Edo Shogunate. (True or False)

[1677] Question 2: The capital of the Edo Shogunate was Osaka. (True or False)

[1678] 5. The server sends the generated quiz to the device.

[1679] The server sends the generated 10 questions to the terminal.

[1680] 6. The device displays the quiz to the user

[1681] The terminal provides an interface that displays the received quiz to the user.

[1682] 7. User takes the quiz

[1683] Users answer quizzes and submit their answers on their terminals.

[1684] 8. The device sends the answer to the server

[1685] The terminal transmits the user's answer to the server.

[1686] 9. The server evaluates the answers and generates a result

[1687] The server evaluates the user's answers and generates correct / incorrect results and a score.

[1688] 10. The device displays the results to the user

[1689] The terminal analyzes the received result data and displays the score and feedback to the user.

[1690] The above is a specific embodiment of the "quiz generation system" based on the present invention. This system allows users to efficiently generate quizzes from their own text materials and advance their studies.

[1691] The processing flow will be explained below.

[1692] Step 1:

[1693] The user launches the quiz generation app and inputs the text data they want to study. For example, they input the text "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital" from a specific chapter of a history textbook. The user also sets conditions such as the quiz format (true or false questions), number of questions (10), and difficulty level (medium).

[1694] Step 2:

[1695] The device creates an API request to send the text data entered by the user and the setting conditions to the server. This request includes information such as the text data, quiz format, and number of questions.

[1696] Step 3:

[1697] The server analyzes the API request received from the device and obtains the text data and user settings. Specifically, it stores the text data in memory and the settings in variables.

[1698] Step 4:

[1699] The server uses natural language processing (NLP) libraries to analyze the text data, tokenize it, split it into sentences, and extract keywords (e.g., "Tokugawa Ieyasu," "Edo Shogunate," "Capital," "Edo"), etc. It also evaluates the meaning and context of sentences to detect important sentences.

[1700] Step 5:

[1701] The server runs an algorithm to generate quiz questions based on the extracted keywords and key sentences. For example, for a true / false question, it generates the question, "Tokugawa Ieyasu established the Edo Shogunate. (True or False)." The generated questions follow the specified format and number of questions.

[1702] Step 6:

[1703] The server packages the generated quiz questions and options in JSON format and creates an API response to send to the device.

[1704] Step 7:

[1705] The device analyzes the JSON data received from the server and generates an interface that displays the quiz questions and options to the user. The UI is designed to make it easy for users to enter answers.

[1706] Step 8:

[1707] The user selects an answer to the displayed quiz and submits the answer. For example, the user selects "Yes" for the question "Tokugawa Ieyasu established the Edo Shogunate."

[1708] Step 9:

[1709] The device collects the user's answers and makes an API request to send to the server, which includes the user's answers for each quiz.

[1710] Step 10:

[1711] The server analyzes the user's answers received from the device and evaluates them against the correct answers. Specifically, it flags each question as correct or incorrect and calculates an overall score.

[1712] Step 11:

[1713] The server packages the evaluation results and scores in JSON format and creates an API response to send to the device.

[1714] Step 12:

[1715] The terminal analyzes the result data received from the server and generates an interface that displays the score and feedback to the user, such as "Your score is 8 / 10. Correct answer: Tokugawa Ieyasu established the Edo Shogunate."

[1716] Example 1

[1717] 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."

[1718] Conventional quiz generation systems have low accuracy when automatically generating quiz questions from text data, or have limited functionality for generating quizzes according to user-specified conditions. This makes it difficult for users to study quizzes satisfactorily. Furthermore, the series of operations, such as displaying the generated quiz questions and options, and evaluating the answers, are sometimes not performed quickly and accurately. Therefore, there is a need for an efficient and accurate way to generate quiz questions based on text data, thereby improving users' learning effectiveness.

[1719] 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.

[1720] In this invention, the server includes user means for inputting text data, information processing means for generating quiz questions from the text data, display means for displaying the generated quiz questions and options to the user, and answer collection means for collecting user answers and transmitting them to the information processing means. This makes it possible to efficiently and accurately generate quiz questions based on text data, and to display and evaluate them.

[1721] "User means" refers to a means by which a user inputs text data and sets the quiz format and question conditions.

[1722] The "information processing device means" refers to a server and related software libraries for analyzing text data and generating quiz question sentences based on extracted keywords and key sentences.

[1723] The term "display device" refers to a terminal having an interface that provides the user with the generated quiz questions and options, or a display device for that purpose.

[1724] The "answer collection means" is a means for collecting the answers given by users to the quiz and transmitting them to the information processing means.

[1725] The "quiz generation system" according to the present invention is a system including a user means for inputting text data, an information processing means for analyzing the text data and generating quiz questions, and a display means for displaying the generated quiz questions and options to the user and collecting answers. The following describes in detail how this system can be implemented.

[1726] Overall system configuration and roles

[1727] 1. User means

[1728] Users input text data using a learning application or web interface, providing the material they want to study by copying and pasting text into an input field or by typing it directly.

[1729] Users can set the quiz format (true / false, multiple choice, etc.), number of questions, difficulty level, and other parameters using drop-down menus and radio buttons on the interface.

[1730] 2. Information Processing Device Means

[1731] The information processing device (server) uses a natural language processing (NLP) library to analyze the received text data. As a specific example, the NLTK library of Python is used.

[1732] The server extracts keywords and key sentences from the text data and generates quiz questions based on the set conditions.

[1733] 3. Display device means

[1734] The terminal transmits the text data and conditions sent from the user means to the server means (information processing device) using a standard HTTP request for communication.

[1735] The terminal has an interface that provides the user with the question sentences and options of the generated quiz sent from the server.

[1736] The device collects the user's answers and sends them to the server, again using an HTTP request.

[1737] Program processing flow and specific examples

[1738] 1. User enters text and sets conditions

[1739] The user inputs the text data they want to study from a particular chapter of a "history textbook" into the application. For example, the following text:

[1740] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[1741] The user also sets the format to "True or False," 10 questions, and difficulty level to "Medium."

[1742] 2. Examples of prompts

[1743] Here are some example prompts to input to a generative AI model:

[1744] input:

[1745] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[1746] conditions:

[1747] Quiz format: True or False

[1748] Number of questions: 10 questions

[1749] Difficulty: Medium

[1750] output:

[1751] Question 1: Tokugawa Ieyasu established the Edo Shogunate. (True or False)

[1752] Question 2: The capital of the Edo Shogunate was Osaka. (True or False)

[1753] Hardware and software used

[1754] 1. User means

[1755] The user's personal computer or smartphone.

[1756] Learning applications and web interfaces (e.g. web front-ends using React, Angular, etc.).

[1757] 2. Information Processing Device Means

[1758] Server: Cloud-based server (e.g., Amazon Web Services, Microsoft Azure).

[1759] Natural language processing libraries: Python's NLTK, spaCy, etc.

[1760] 3. Display device means

[1761] The user's personal computer or smartphone.

[1762] A web interface that runs on a browser.

[1763] In this way, the "quiz generation system" based on the present invention functions as a tool for users to efficiently generate quizzes from any text material and deepen their learning.

[1764] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1765] Step 1:

[1766] The user inputs text data and sets the conditions for the quiz.

[1767] Input: Text data entered by the user using the learning application or web interface, as well as the type, number and difficulty of the quiz selected by the user.

[1768] Data processing: The text data provided by the user is saved and the selected conditions are stored in memory.

[1769] Output: The prepared data structure is passed to the terminal. Specifically, user actions in text fields and selection menus are constructed as requests to the server.

[1770] Step 2:

[1771] The terminal transmits the input text data and conditions to the server.

[1772] Input: The text data entered by the user, as well as the quiz format, number of questions, and difficulty level you set.

[1773] Data processing: Properly formatting this data to generate HTTP requests, for example, converting it to JSON format.

[1774] Output: Data structure as a request sent to the server. For example, JSON data like this:

[1775] json

[1776] {

[1777] "text": "Tokugawa Ieyasu established the Edo Shogunate and established its capital in Edo. He stabilized Japan's domestic politics and implemented many reforms.",

[1778] "quiz_format": "〇×Question",

[1779] "num_questions": 10,

[1780] "difficulty": "medium"

[1781] }

[1782] Step 3:

[1783] The server receives and analyzes the text data.

[1784] Input: Text data sent from the device and setting conditions.

[1785] Data processing: Extract keywords and key sentences using a natural language processing (NLP) library (e.g., Python's NLTK). For example, splitting a text into sentences and extracting keywords.

[1786] python

[1787] import nltk

[1788] from nltk.tokenize import sent_tokenize, word_tokenize

[1789] text = "Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms."

[1790] sentences = sent_tokenize(text)

[1791] words = word_tokenize(text)

[1792] keywords = [word for word in words if word in important_words_list]

[1793] Output: A list of extracted keywords and key sentences.

[1794] Step 4:

[1795] The server generates the quiz questions.

[1796] Input: Extracted keywords and key sentences, conditions set by the user (format, number of questions, difficulty level).

[1797] Data processing: Generate quiz questions based on the specified conditions. Specifically, if you want to create a true / false question, generate it as follows:

[1798] python

[1799] quizzes = [

[1800] {"question": "Tokugawa Ieyasu established the Edo Shogunate.", "correct_answer": "Yes"},

[1801] {"question": "The capital of the Edo Shogunate was Osaka.", "correct_answer": "×"}

[1802] ]

[1803] Output: The generated quiz question and answer options.

[1804] Step 5:

[1805] The server sends the generated quiz back to the terminal.

[1806] Input: The question text and answer choices for the generated quiz.

[1807] Data processing: Format these as an HTTP response and send it to the terminal. For example, generate a JSON format response.

[1808] json

[1809] {

[1810] "quizzes": [

[1811] {"question": "Tokugawa Ieyasu established the Edo Shogunate.", "options": ["Yes", "No"]},

[1812] {"question": "The capital of the Edo Shogunate was Osaka.", "options": ["Yes", "No"]}

[1813] ]

[1814] }

[1815] Output: The quiz data provided to the device.

[1816] Step 6:

[1817] The terminal displays the quiz to the user.

[1818] Input: Quiz data received from the server.

[1819] Data processing: The quiz questions and options are laid out and displayed in the user interface. This is implemented using HTML and JavaScript.

[1820] Output: Displaying quiz questions to the user. Specifically, a quiz screen is generated and the user is ready to answer.

[1821] Step 7:

[1822] The user answers the quiz.

[1823] Input: The displayed quiz question and choices.

[1824] Data processing: The user selects the answer to a question. The selection is reflected by clicking or tapping.

[1825] Output: User response data. Specifically, the selected options are collected.

[1826] Step 8:

[1827] The terminal sends the user's answer to the server.

[1828] Input: User selected answer data.

[1829] Data processing: The response data is formatted and sent to the server, again using an HTTP request.

[1830] Output: The response data sent to the server. For example, the following JSON data:

[1831] json

[1832] {

[1833] "answers": ["Yes", "No"]

[1834] }

[1835] Step 9:

[1836] The server evaluates the user's answers and generates a result.

[1837] Input: User response data.

[1838] Data processing: Compare with the correct answer data and calculate the evaluation and score. As an example of evaluation, we will determine whether the answer is correct or incorrect as follows.

[1839] python

[1840] correct_answers = ["〇", "×"]

[1841] user_answers = ["Yes", "No"]

[1842] results = [{"question": "Tokugawa Ieyasu established the Edo Shogunate.", "user_answer": "Yes", "correct": True},

[1843] {"question": "The capital of the Edo Shogunate was Osaka.", "user_answer": "×", "correct": True}]

[1844] Output: Evaluation results and score data.

[1845] Step 10:

[1846] The terminal displays the results to the user.

[1847] Input: Evaluation results and score data received from the server.

[1848] Data processing: Evaluation results and score data are laid out and displayed on the interface. This is implemented using HTML and JavaScript.

[1849] Output: Displaying the scores and evaluation results to the user. Specifically, a results screen is generated so that the user can check their performance.

[1850] (Application example 1)

[1851] 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."

[1852] Conventional quiz generation systems require the input of text data, which is a time-consuming process of manually inputting text from books or paper media. Additionally, while technology for generating quizzes using natural language processing is available, it lacks the functionality to directly extract text from images and use it to generate quizzes, making it difficult to provide learners with more intuitive, real-time learning support.

[1853] 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.

[1854] In this invention, the server includes information input means for inputting text data, analysis means for generating quiz questions from the text data, output means for displaying the generated quiz questions and options on information display means, character recognition means for extracting text from images, and question generation means for generating quizzes based on the text extracted by the character recognition means. This makes it possible to generate quizzes by extracting text directly from books or paper media and provide them to learners immediately.

[1855] "Text data" refers to information expressed as a string of characters, including sentences and paragraphs that form the basis for generating quizzes.

[1856] "Information input means" refers to an interface or device that allows a user to input text data into a system.

[1857] The "analysis means" is a part of the system that performs analysis to generate quiz questions based on the input text data.

[1858] "Information display means" refers to an interface or device used to display the generated quiz questions and options to the user.

[1859] The "output means" is a part of the system that provides the quiz questions and options to the user via the information display means.

[1860] A “character recognition means” is a part of a system that uses optical character recognition (OCR) technology to extract text from images.

[1861] The "question generation means" is a part of the system that generates quiz questions based on the text extracted by the character recognition means.

[1862] The "quiz generation system" according to the present invention is a system including information input means, analysis means, information display means, output means, character recognition means, and question generation means.

[1863] 1. Overall system configuration

[1864] Information input means: Users input text data or images into the system. Examples include smartphone or tablet applications.

[1865] Analysis method: Analyzes the text data sent from the information input method and extracts keywords and key sentences. This process uses a natural language processing (NLP) library.

[1866] Information display means: The quiz questions and options generated by the analysis means are displayed to the user. This corresponds to the application screen of a smartphone or tablet.

[1867] Output means: A part of the system that provides the quiz to the user via the information display means.

[1868] Character Recognition Method: Optical Character Recognition (OCR) technology is used to extract text from images. This process utilizes the Google Cloud Vision API.

[1869] Question generation: Quiz questions are generated based on the text extracted by the character recognition method. This process uses the Hugging Face Transformers library.

[1870] 2. Hardware and Software Used

[1871] Hardware: Smartphone, tablet, camera for OCR.

[1872] Software: Google Cloud Vision API, Hugging Face Transformers, Python.

[1873] 3. Example of a system

[1874] A user scans a book or specific materials from a cram school using their smartphone camera and inputs the image into the system. The text in this image is converted into text data using the Google Cloud Vision API, a character recognition method. The converted text data is analyzed using a natural language processing library, which serves as an analysis method, and keywords and key sentences are extracted. Quiz questions are then generated using the Hugging Face Transformers library, which serves as a question generation method. The generated quiz questions and answer options are displayed on the screen of a smartphone or tablet, which serves as an information display method, and provided to the user via an output method. The user answers the displayed quiz questions and progresses with their studies.

[1875] 4. Examples of prompt sentences

[1876] As part of the operation of this system, the user may enter prompts such as:

[1877] text

[1878] Enter text: Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[1879] Quiz format: 4 choices

[1880] Number of questions: 5 questions

[1881] The above is a specific embodiment of the "quiz generation system" of the present invention. This system allows users to extract text directly from images and automatically generate quizzes to advance their learning.

[1882] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1883] Step 1:

[1884] A user launches an application on their smartphone or tablet and scans a book or study material with the smartphone's camera, obtaining image data as input, which is then saved in the application as output.

[1885] Step 2:

[1886] The device sends image data to the Google Cloud Vision API, a character recognition tool. The character recognition tool then analyzes the characters in the image and obtains text data as output. Specifically, it processes the pixel data of the image and returns the recognized string of characters as text data.

[1887] Step 3:

[1888] The device sends the obtained text data to a natural language processing (NLP) library as an analysis means, which then extracts keywords and key sentences from the text data. The device receives the text data as input and obtains a list of keywords and extracted sentences as output.

[1889] Step 4:

[1890] The server generates quiz questions using the Hugging Face Transformers library, a question generation tool, based on the keywords and key sentences extracted by the analysis tool. Keywords and key sentences are received as input, and the quiz questions and options are obtained as output. Specifically, a prompt is input into the generation AI model, and questions and options that fit the quiz format are generated.

[1891] Step 5:

[1892] The server sends the generated quiz questions and options to the terminal, which receives data from the server as input and converts it into a format that can be displayed on the terminal as output.

[1893] Step 6:

[1894] The device displays the quiz question and options on a user interface as information display means, allowing the user to take the quiz. Specifically, the quiz question and multiple options are visually displayed on the screen.

[1895] Step 7:

[1896] The user answers the quiz and submits the answers on the device, which receives the user's selected options as input and sends the data to the server as output.

[1897] Step 8:

[1898] The server evaluates the user's answers and generates a result indicating whether they are correct or incorrect. The answer data received is used as input, and the evaluation result is obtained as output. Specifically, the result is calculated after comparing it with the correct answer, and a score and feedback are generated.

[1899] Step 9:

[1900] The server receives the evaluation result data as input and converts it into a format that can be sent to the terminal as output.

[1901] Step 10:

[1902] The device displays the assessment results to the user, allowing them to check their learning progress. Specifically, the device visually displays scores and feedback on the screen.

[1903] 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.

[1904] The "quiz generation system" according to the present invention is a system including a user means for inputting text data, a server means for analyzing the text data and generating quiz questions, a terminal means for displaying the generated quiz questions and options to the user, and an emotion engine for recognizing the user's emotions.

[1905] Overall system configuration and roles

[1906] 1. User Method

[1907] A user inputs text data into a learning application or web interface. For example, the text "Tokugawa Ieyasu established the Edo Shogunate and established its capital in Edo" from a specific chapter of a history textbook. The user also sets parameters such as the quiz format (true / false questions, multiple choice, etc.), the number of questions (10), and the difficulty level (medium).

[1908] 2. Terminal means

[1909] The terminal transmits the text data and conditions sent from the user means to the server means.

[1910] The terminal displays the question sentences and options of the quiz sent from the server means to the user.

[1911] The terminal collects the user's answers and emotional state and transmits them to the server means and the emotion engine.

[1912] 3. Server Means

[1913] The server uses natural language processing (NLP) libraries to analyze the text data and extract keywords and key sentences.

[1914] The server generates quiz questions from the analyzed text data based on conditions specified by the user.

[1915] The server receives the user's answers, evaluates them against the correct answers, and generates a result.

[1916] The server generates data based on the evaluation results and the user's emotional state to provide feedback and adjust the next quiz.

[1917] 4. Emotion Engine

[1918] The emotion engine has the ability to recognize the user's emotions, for example, by measuring the user's stress and concentration level using facial expression recognition technology and voice analysis technology.

[1919] The emotion engine dynamically adjusts the difficulty and content of the quiz based on the perceived emotional state.

[1920] The emotion engine visualizes the emotional state and displays it on the terminal means, thereby enabling the user to understand his or her own emotional state.

[1921] Program processing flow and specific examples

[1922] 1. User enters text and sets conditions

[1923] The user inputs the text data they want to study from a particular chapter of a "history textbook" into the application. For example, the following text:

[1924] Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and implemented many reforms.

[1925] The user sets the format to "True or False," 10 questions, and difficulty level to "medium."

[1926] 2. The device sends the data to the server

[1927] The terminal creates a request to send the user's input to the server.

[1928] 3. The server analyzes the text data

[1929] The server receives the text data and uses natural language processing to extract keywords and sentences such as:

[1930] Keywords: Tokugawa Ieyasu, Edo Shogunate, capital, Edo, domestic affairs, stability, reform

[1931] Extract: Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital.

[1932] 4. The server generates the quiz

[1933] The server generates true / false questions based on the extracted keywords and sentences:

[1934] Question 1: Tokugawa Ieyasu established the Edo Shogunate. (True or False)

[1935] Question 2: The capital of the Edo Shogunate was Osaka. (True or False)

[1936] 5. The server sends the generated quiz to the device.

[1937] The server sends the generated 10 questions to the terminal.

[1938] 6. The device displays the quiz to the user

[1939] The terminal provides an interface that displays the received quiz to the user.

[1940] 7. Emotion engine recognizes user emotions

[1941] The emotion engine analyzes the user's facial expressions and voice to recognize their current emotional state, such as "concentrated" or "stressed."

[1942] 8. User takes the quiz

[1943] The user selects an answer to the displayed quiz and submits the answer. For example, the user selects "Yes" for the question "Tokugawa Ieyasu established the Edo Shogunate."

[1944] 9. The device sends the answer and emotional state to the server.

[1945] The terminal transmits the user's response and the emotional state recognized by the emotion engine to the server.

[1946] 10. The server evaluates the answers and generates the results

[1947] The server evaluates the user's answers and generates correct / incorrect results and a score.

[1948] 11. The server generates feedback based on the emotional state

[1949] The server uses data from the emotion engine to generate feedback based on the user's emotional state, such as "You are concentrating on your studies" or "We recommend you take a break."

[1950] 12. The device displays the results and feedback to the user

[1951] The device generates an interface that displays the received result data and feedback to the user, such as "Score: 8 / 10" or "Feedback: You are concentrating on your studies."

[1952] The above is a specific embodiment of the "quiz generation system" based on the present invention. This system allows users to efficiently generate quizzes from their own text materials and further progress in their studies while understanding their own emotional state.

[1953] The processing flow will be explained below.

[1954] Step 1:

[1955] The user launches the quiz generation app and inputs the text data they want to study. For example, they input the text "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital" from a specific chapter of a history textbook. The user also sets conditions such as the quiz format (true or false questions), number of questions (10), and difficulty level (medium).

[1956] Step 2:

[1957] The device creates an API request to send the text data entered by the user and the setting conditions to the server. This request includes information such as the text data, quiz format, and number of questions.

[1958] Step 3:

[1959] The server analyzes the API request received from the device and obtains the text data and user settings. Specifically, it stores the text data in memory and the settings in variables.

[1960] Step 4:

[1961] The server uses natural language processing (NLP) libraries to analyze the text data, tokenize it, split it into sentences, and extract keywords (e.g., "Tokugawa Ieyasu," "Edo Shogunate," "Capital," "Edo"), etc. It also evaluates the meaning and context of sentences to detect important sentences.

[1962] Step 5:

[1963] The server runs an algorithm to generate quiz questions based on the extracted keywords and key sentences. For example, for a true / false question, it generates the question, "Tokugawa Ieyasu established the Edo Shogunate. (True or False)." The generated questions follow the specified format and number of questions.

[1964] Step 6:

[1965] The server packages the generated quiz questions and options in JSON format and creates an API response to send to the device.

[1966] Step 7:

[1967] The device analyzes the JSON data received from the server and generates an interface that displays the quiz questions and options to the user. The UI is designed to make it easy for users to enter answers.

[1968] Step 8:

[1969] The device activates an emotion engine, analyzes the user's facial expressions and voice in real time, and measures their emotional state. For example, if the user is smiling, it is recognized as "having fun," and if they frown, it is recognized as "feeling stressed."

[1970] Step 9:

[1971] The user selects an answer to the displayed quiz and submits the answer. For example, the user selects "Yes" for the question "Tokugawa Ieyasu established the Edo Shogunate."

[1972] Step 10:

[1973] The device collects the user's answers and makes an API request to send to the server along with the emotional state data from the emotion engine. The request includes the user's answers and emotional state for each quiz.

[1974] Step 11:

[1975] The server analyzes the user's answers received from the device and evaluates them against the correct answers. Specifically, it flags each question as correct or incorrect and calculates an overall score.

[1976] Step 12:

[1977] The server generates feedback based on the user's emotional state based on data from the emotion engine. For example, if the user is concentrating, it generates a message such as "You are studying very hard," and if the user is feeling stressed, it generates a message such as "We recommend that you take a break."

[1978] Step 13:

[1979] The server packages the evaluation results and feedback in JSON format and creates an API response to send to the device.

[1980] Step 14:

[1981] The device analyzes the results and feedback received from the server and generates an interface to display to the user, such as "Score: 8 / 10" or "Feedback: Very focused on studying."

[1982] This is the specific processing flow of the "quiz generation system." This system allows users to efficiently generate and answer quizzes, and progress in their studies while understanding their own emotional state.

[1983] Example 2

[1984] 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."

[1985] In conventional quiz generation systems, generating quizzes from text data is a simple, routine task, making it difficult to dynamically adjust the system to maximize the user's learning effectiveness. Furthermore, because questions are generated without taking into account the user's emotional state, they are unable to adapt to changes in stress or concentration, resulting in a decline in learning efficiency.

[1986] 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.

[1987] In this invention, the server includes a user means for inputting text data, a server for generating quiz questions from the text data, a terminal for displaying the generated quiz questions and options to the user, and an emotion analysis engine for recognizing the user's emotions and adjusting the difficulty of the quiz, thereby enabling dynamic quiz generation and question setting according to the user's learning situation and emotional state.

[1988] "Text data" refers to character string information data entered by the user, and is used as material for quiz questions.

[1989] The "user means" is an interface that allows the user to input text data and set the format and conditions of the quiz.

[1990] The "server" is a computer system that receives text data sent by users, analyzes it using natural language processing, and generates quiz questions.

[1991] "Natural language processing" is a technology that analyzes text data, extracts keywords and key sentences, and generates quiz questions.

[1992] A "terminal" is a device that displays input data from a user and quiz questions and options sent from a server.

[1993] The "emotion analysis engine" is a system that analyzes the user's facial expressions and voice data, recognizes their emotional state, and adjusts the difficulty of the quiz accordingly.

[1994] A "quiz question" is a question-style sentence generated based on text data, to which the user responds.

[1995] "Choices" are multiple answer options for a quiz question, from which the user selects the correct answer.

[1996] "Feedback" refers to advice or evaluation provided based on the user's answers and emotional state.

[1997] The "quiz generation system" according to the present invention is a system including a user means for inputting text data, a server means for analyzing the text data and generating quiz questions, a terminal means for displaying the generated quiz questions and options to the user, and an emotion analysis engine for recognizing the emotions of the user. Specific embodiments of each means are described below.

[1998] User Means

[1999] A user inputs text data into a learning application or web interface. For example, they input the text "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital" from a specific chapter in a history textbook. The user also sets conditions such as the quiz format (true / false questions, multiple choice, etc.), number of questions (10), difficulty level (medium), etc. These settings are made through the UI (user interface).

[2000] Terminal means

[2001] The terminal transmits the text data and conditions sent from the user means to the server means, for example, using an HTTP request.

[2002] The terminal displays the questions and options of the quiz sent from the server means to the user, using an interface that is dynamically generated using HTML and JavaScript.

[2003] The terminal collects the user's answers and emotional state and transmits them to the server means and the emotion analysis engine.

[2004] Server Means

[2005] The server receives the text data sent by the user and analyzes it using, for example, Python's Natural Language Toolkit (NLTK) or Spacy. Specifically, the analysis is performed using the following steps:

[2006] The server divides the text data into sentence units.

[2007] The server extracts key keywords from each sentence, such as "Tokugawa Ieyasu," "Edo Shogunate," and "Edo."

[2008] The server generates quiz questions from the analyzed text data based on the user's criteria. For example, it generates a question such as "Tokugawa Ieyasu established the Edo Shogunate. (True or False)." It also sends the generated quiz questions and options to the terminal.

[2009] The server receives the user's answers, evaluates them against the correct answers, and generates a result. It also generates data to provide feedback and adjust the next quiz based on the evaluation results and the user's emotional state.

[2010] Sentiment Analysis Engine

[2011] The emotion analysis engine analyzes the user's facial expressions and voice to recognize their current emotional state (e.g., "concentrated" or "stressed") using OpenCV and voice emotion analysis tools.

[2012] The emotion analysis engine dynamically adjusts the difficulty of the quiz and the content of the questions based on the emotional state it recognizes. It also visualizes the emotional state and displays it on the device, allowing users to understand their own emotional state.

[2013] Specific examples of operation

[2014] User enters text and sets conditions

[2015] The user inputs text such as "Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital" into the learning application, and sets the question format to true / false, with 10 questions and medium difficulty.

[2016] The device sends data to the server

[2017] The terminal sends a request to the server with conditions set by the user.

[2018] The server parses the text data

[2019] The server analyzes the received text data using a natural language processing library to extract keywords and key phrases, such as "Tokugawa Ieyasu," "Edo Shogunate," "Edo," "domestic stability," and "reform."

[2020] The server generates the quiz

[2021] The server generates quiz questions based on the extracted keywords. Example questions include "Tokugawa Ieyasu established the Edo Shogunate (True or False)" and "The capital of the Edo Shogunate was Osaka (True or False)."

[2022] Prompt Sentence Examples

[2023] User: Enter the following text from a history textbook into the quiz generation system: "Tokugawa Ieyasu established the Edo Shogunate and established its capital in Edo. He stabilized Japan's domestic politics and implemented many reforms."

[2024] Prompt: Generate a true / false question based on the following text: "Tokugawa Ieyasu established the Edo Shogunate and made Edo its capital. He stabilized Japan's domestic politics and carried out many reforms."

[2025] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2026] Step 1:

[2027] The user inputs text data and sets the quiz format and question conditions.

[2028] Input: Text data to be studied (e.g., "Tokugawa Ieyasu established the Edo Shogunate and designated Edo as its capital"), quiz format (true / false questions, multiple choice, etc.), number of questions (e.g., 10 questions), difficulty level (e.g., medium).

[2029] Output: The input data and the set conditions.

[2030] Specific operation: The user enters text data and selects various settings via the learning application or web interface.

[2031] Step 2:

[2032] The terminal transmits the user's input data and setting conditions to the server.

[2033] Input: Text data and setting conditions entered by the user.

[2034] Output: The request to the server.

[2035] Specific operation: The terminal creates an HTTP request and sends the user's input and setting conditions to the server.

[2036] Step 3:

[2037] The server analyzes the received text data.

[2038] Input: Text data sent from the terminal.

[2039] Output: Extracted keywords and key sentences.

[2040] Specific operation: The server uses a natural language processing library (e.g., Python's NLTK library or Spacy) to divide the text data into sentences and extract key keywords and sentences.

[2041] Step 4:

[2042] The server generates quiz questions based on the analysis results.

[2043] Input: Extracted keywords and key sentences, set quiz format and conditions.

[2044] Output: The generated quiz question and answer options.

[2045] Specific operation: The server generates quiz questions and answer options based on the extracted keywords and the user's settings. For example, it creates a question such as "Tokugawa Ieyasu established the Edo Shogunate. (True or False)."

[2046] Step 5:

[2047] The server transmits the generated quiz question text and options to the terminal.

[2048] Input: The question text and answer choices for the generated quiz.

[2049] Output: The response to the device.

[2050] Specific operation: The server converts the generated quiz into JSON format or similar and sends it to the device.

[2051] Step 6:

[2052] The terminal displays the received quiz to the user.

[2053] Input: Quiz question text and options sent from the server.

[2054] Output: The quiz screen shown to the user.

[2055] Specific operation: The device uses HTML and JavaScript to generate an interface for displaying the quiz and presents it to the user.

[2056] Step 7:

[2057] The sentiment analysis engine recognizes the user's emotions.

[2058] Input: User's facial expression and voice data.

[2059] Output: Perceived emotional state (e.g., "concentrated" or "stressed").

[2060] How it works: The emotion analysis engine uses OpenCV and speech analysis tools to analyze the user's emotional state in real time.

[2061] Step 8:

[2062] The user answers the quiz.

[2063] Input: Quiz question, answer choices, and user answer (e.g. "Yes").

[2064] Output: User response data.

[2065] Specific operation: The user selects an answer to a displayed quiz question and submits the answer.

[2066] Step 9:

[2067] The terminal transmits the user's answers and emotional state to the server.

[2068] Input: User response data, emotional state recognized by the sentiment analysis engine.

[2069] Output: The request to the server.

[2070] Specific operation: The device sends the user's answer and emotional state to the server again via an HTTP request.

[2071] Step 10:

[2072] The server evaluates the answers and generates a result.

[2073] Input: User's answer data, correct answer data.

[2074] Output: Evaluation results and scores.

[2075] Specific operation: The server evaluates the user's answer against the correct answer and calculates a score. For example, if the user answers "Yes" to the question "Tokugawa Ieyasu established the Edo Shogunate," the server will add a score to the answer.

[2076] Step 11:

[2077] The server generates feedback based on the emotional state.

[2078] Input: Evaluation results and emotional state.

[2079] Output: The feedback message.

[2080] Specific behavior: The server generates feedback based on the user's emotional state, such as messages like "You are concentrating on your studies" or "We recommend you take a break."

[2081] Step 12:

[2082] The terminal displays the results and feedback to the user.

[2083] Input: Evaluation results and feedback messages sent by the server.

[2084] Output: The results screen and feedback shown to the user.

[2085] Specific operation: The device generates an interface to display the result data and feedback messages to the user, and presents them to the user. For example, it displays information such as "Score: 8 / 10" and "Feedback: You are concentrating on your studies."

[2086] (Application example 2)

[2087] 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."

[2088] Current quiz generation systems lack the ability to dynamically adapt to the user's learning style and emotional state, resulting in poor learning efficiency. Another issue is that systems that generate quizzes based on specific content users want to learn lack adequate feedback to improve the user experience.

[2089] 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.

[2090] In this invention, the server includes user means for inputting text data, server means for generating quiz questions from the text data, terminal means for displaying the generated quiz questions and options to the user, emotion engine means for recognizing the user's emotions, and feedback means having a function of dynamically adjusting the difficulty level of the quiz and the content of the questions based on the recognition results of the emotion engine means, thereby enabling a personalized learning experience that suits the user's emotions and learning style.

[2091] "User means" is an interface for inputting text data.

[2092] The "server means" is the core of the system that generates quiz questions from text data.

[2093] The "terminal means" is a device that displays the generated quiz questions and options to the user.

[2094] The "emotion engine means" is a technology for recognizing the user's emotions.

[2095] The "feedback means" is a device or system that has the function of dynamically adjusting the difficulty level of the quiz and the content of the questions based on the recognition results of the emotion engine means.

[2096] "Natural language processing" is a technology that analyzes text data and extracts keywords and key sentences.

[2097] "Quiz format" refers to the way questions are presented in the quiz, and includes true / false questions and multiple choice questions, for example.

[2098] "Question conditions" are parameters designated by the user, such as the number of questions to be asked and the level of difficulty.

[2099] A system for carrying out the present invention includes user means for inputting text data, server means for analyzing the text data and generating quiz question sentences, terminal means for displaying the generated quiz question sentences and options to the user, emotion engine means for recognizing the user's emotions, and feedback means.

[2100] The user means is an interface for inputting text data. For example, a user uses a terminal at a theme park or museum to input information learned from exhibits or guidebooks. The input data is transmitted to the server means via the terminal means.

[2101] The server means analyzes the text data using natural language processing (NLP). Specifically, it uses an NLP library (e.g., Transformers) to extract keywords and key sentences, and generates quiz questions based on the extracted keywords and key sentences. The generated quiz is then transmitted to the terminal means.

[2102] The terminal means is a device that displays the questions and options of the quiz to the user. For example, the quiz is displayed using an interactive display or a smartphone.

[2103] The emotion engine is a technology for recognizing the user's emotional state. It uses a camera to capture the user's facial expressions and analyzes their emotions using image processing and facial recognition technology. The emotion analysis is performed using machine learning libraries such as TensorFlow.

[2104] The feedback means has a function of dynamically adjusting the difficulty level and question content of the quiz based on the recognized emotional state. For example, if the emotion recognition result indicates that the user is "concentrating," feedback is provided to slightly increase the difficulty level of the next quiz.

[2105] This system allows users to have a personalized learning experience that is tailored to their individual emotional state and learning style, and the feedback provided by the system allows users to receive appropriate adjustments based on their own learning progress and emotional state.

[2106] For example, if a visitor to a dinosaur exhibition inputs the text "Tyrannosaurus is a carnivorous dinosaur," the system generates a quiz question such as "Tyrannosaurus is a herbivorous dinosaur (True or False)," which is adjusted based on the user's emotional state.

[2107] An example of a prompt sentence to be input to the generative AI model is as follows:

[2108] Input text: Tyrannosaurus is a carnivorous dinosaur

[2109] conditions:

[2110] Quiz format: True or False

[2111] Difficulty: Medium

[2112] Number of questions: 3 questions

[2113] Generate quiz questions and options based on this.

[2114] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2115] Step 1:

[2116] The user inputs text data and sets the quiz format and question conditions.

[2117] Input: Text data obtained from exhibits and guidebooks, quiz format, number of questions, and difficulty level.

[2118] Output: The quiz generation request sent to the server.

[2119] Specific operation: The user means collects the text data and quiz conditions entered by the user through the interface, and generates a request to send them to the server.

[2120] Step 2:

[2121] The device sends the data to the server.

[2122] Input: A request for text data and conditions set by the user.

[2123] Output: The request sent to the server.

[2124] Specific operation: The terminal means transmits the data input by the user to the server using a communication means such as an HTTP request.

[2125] Step 3:

[2126] The server analyzes the text data and generates a quiz.

[2127] Input: Text data and conditions sent to the server.

[2128] Output: The generated quiz question and answer options.

[2129] Specific operation: The server uses a natural language processing (NLP) library to analyze the text data, extract keywords and key sentences, and then generate quiz questions based on the conditions set by the user.

[2130] Step 4:

[2131] The server sends the generated quiz to the terminal.

[2132] Input: The question text and answer choices for the generated quiz.

[2133] Output: Quiz data sent to the device.

[2134] Specific operation: The server sends the generated quiz data to the terminal. This is also done via an HTTP request.

[2135] Step 5:

[2136] The terminal displays the quiz to the user.

[2137] Input: Quiz data received from the server.

[2138] Output: The quiz question and answer choices that are displayed to the user.

[2139] Specific operation: The terminal means analyzes the received quiz data and displays it in a format that is easy for the user to view.

[2140] Step 6:

[2141] The emotion engine recognizes the user's emotions.

[2142] Input: User's facial expression data.

[2143] Output: Perceived emotional state.

[2144] How it works: The emotion engine captures the user's facial expressions with a camera, analyzes the images using facial recognition technology, and uses machine learning libraries such as TensorFlow to recognize the user's emotional state.

[2145] Step 7:

[2146] The user answers the quiz.

[2147] Input: The answer selected by the user.

[2148] Output: The response data sent from the device to the server.

[2149] Specific operation: The user selects an answer from the quiz question and options displayed on the terminal, and sends this from the terminal to the server.

[2150] Step 8:

[2151] The device sends the answer and emotional state to the server.

[2152] Input: User's answer and the emotion engine's recognition results.

[2153] Output: The data sent to the server.

[2154] Specific operation: The terminal means compiles the user's answers and the emotional state obtained from the emotion engine as data and sends it to the server.

[2155] Step 9:

[2156] The server evaluates the answers and generates a result.

[2157] Input: User response data.

[2158] Output: Evaluation results and scores.

[2159] Specific operation: The server means evaluates the user's answers against the correct answers and generates a score and evaluation result.

[2160] Step 10:

[2161] The server generates feedback based on the emotional state.

[2162] Input: Recognition data for the emotion engine.

[2163] Output: Feedback data.

[2164] Specific operation: The server means generates feedback according to the user's emotional state based on data from the emotion engine.

[2165] Step 11:

[2166] The device displays the results and feedback to the user.

[2167] Input: Assessment results and feedback data.

[2168] Output: Quiz score and feedback displayed to the user.

[2169] Specific operation: The terminal means generates and displays an interface for displaying the received result data and feedback to the user.

[2170] 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.

[2171] 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.

[2172] 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.

[2173] 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.

[2174] 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.

[2175] 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.

[2176] 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).

[2177] 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.

[2178] 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."

[2179] 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.

[2180] 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).

[2181] 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.

[2182] 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.

[2183] 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.

[2184] 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.

[2185] 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.

[2186] 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.

[2187] 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.

[2188] 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.

[2189] 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.

[2190] 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.

[2191] The following is further disclosed regarding the above embodiment.

[2192] (Claim 1)

[2193] a user means for inputting text data;

[2194] a server means for generating quiz question sentences from the text data;

[2195] a terminal means for displaying the generated question sentences and options of the quiz to a user;

[2196] A system including:

[2197] (Claim 2)

[2198] 2. The system of claim 1, wherein the server means analyzes the text data using natural language processing to extract keywords and key sentences.

[2199] (Claim 3)

[2200] 2. The system according to claim 1, wherein the user means has a function of specifying the format of the quiz and the conditions for asking the questions.

[2201] (Claim 4)

[2202] 2. The system according to claim 1, wherein said terminal means has a function of collecting answers from said users and transmitting them to said server means.

[2203] (Claim 5)

[2204] 2. The system of claim 1, wherein the server means is operable to evaluate the user's answers and generate a result.

[2205] "Example 1"

[2206] (Claim 1)

[2207] a user means for inputting text data;

[2208] an information processing device that generates question sentences for a quiz from the text data;

[2209] a display device for displaying the generated quiz questions and options to a user;

[2210] a response collection means for collecting responses from users and transmitting the collected responses to the information processing means;

[2211] A system including:

[2212] (Claim 2)

[2213] 2. The system of claim 1, wherein the information processing means analyzes the text data using natural language processing to extract keywords and key sentences.

[2214] (Claim 3)

[2215] 2. The system according to claim 1, wherein the user means has a function of specifying the format of the quiz and the conditions for asking the question.

[2216] "Application Example 1"

[2217] (Claim 1)

[2218] an information input means for inputting text data;

[2219] an analysis means for generating quiz question sentences from the text data;

[2220] an output means for displaying the generated question sentence and options of the quiz on an information display means;

[2221] character recognition means for extracting text from images;

[2222] a question generation means for generating a quiz based on the text extracted by the character recognition means;

[2223] A system including:

[2224] (Claim 2)

[2225] 2. The system according to claim 1, wherein the analyzing means analyzes the text data using natural language processing to extract keywords and main sentences.

[2226] (Claim 3)

[2227] 2. The system according to claim 1, wherein the information input means has a function of specifying the format of the quiz and the conditions for asking questions.

[2228] "Example 2: Combining Emotion Engines"

[2229] (Claim 1)

[2230] a user means for inputting text data;

[2231] a server that generates quiz question sentences from the text data;

[2232] a terminal that displays the generated quiz question and options to a user;

[2233] A sentiment analysis engine that recognizes the user's emotions and adjusts the difficulty of the quiz;

[2234] A system including:

[2235] (Claim 2)

[2236] 10. The system of claim 1, wherein the server analyzes the text data using natural language processing to extract keywords and key sentences.

[2237] (Claim 3)

[2238] 2. The system according to claim 1, wherein the user means has a function of specifying the format of the quiz and the conditions for asking the questions.

[2239] "Application example 2 when combining emotion engines"

[2240] (Claim 1)

[2241] a user means for inputting text data;

[2242] a server means for generating quiz question sentences from the text data;

[2243] a terminal means for displaying the generated question sentences and options of the quiz to a user;

[2244] emotion engine means for recognizing the emotion of the user;

[2245] a feedback means having a function of dynamically adjusting the difficulty level of the quiz and the content of questions based on the recognition result of the emotion engine means;

[2246] A system including:

[2247] (Claim 2)

[2248] 2. The system of claim 1, wherein the server means analyzes the text data using natural language processing to extract keywords and key sentences.

[2249] (Claim 3)

[2250] 2. The system according to claim 1, wherein the user means has a function of specifying the format of the quiz and the conditions for asking the questions. [Explanation of symbols]

[2251] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a user means for inputting text data; a server means for generating quiz question sentences from the text data; a terminal means for displaying the generated question sentences and options of the quiz to a user; A system including:

2. 2. The system of claim 1, wherein said server means analyzes said text data using natural language processing to extract keywords and key sentences.

3. 2. The system according to claim 1, wherein said user means has a function of specifying the format of the quiz and the conditions for asking questions.

4. 2. The system according to claim 1, wherein said terminal means has a function of collecting answers from said users and transmitting them to said server means.

5. 2. The system of claim 1, wherein said server means is operable to evaluate said user's answers and generate results.

Images