System

Abstract

A system is provided.SOLUTION: A system comprising: means for detecting a timing at which a user finishes reading an electronic book; means for generating a quiz based on a predetermined period after finishing reading; means for notifying a user terminal of the generated quiz; means for collecting and evaluating an answer result of the quiz; and means for providing feedback to the user based on an evaluation result.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] Many people today face the problem of forgetting what they read. In particular, many find it difficult to retain the contents of books they read for study or information gathering over the long term. Traditional reading methods lack continuous review or follow-up after reading, making it difficult to retain information. There is a need for a system that can solve this problem and efficiently retain the contents of books in memory. [Means for solving the problem]

[0005] This invention provides a system that includes a means for detecting when a user has finished reading an e-book, a means for generating a quiz based on a specific period after completion of reading (2 days, 14 days, or 60 days), a means for notifying the user of the generated quiz, a means for collecting and evaluating the quiz answers, and a means for providing feedback to the user based on the evaluation results. This system encourages review at key times after reading, enabling the content of the book to be firmly ingrained in memory for a long period of time. Furthermore, by analyzing the content of the e-book and extracting key points to generate quizzes, a system is provided that is easy for users to understand and allows them to continue learning in a fun, game-like manner.

[0006] "User" refers to a person who uses an electronic book.

[0007] "E-Book" refers to a book provided in digital format.

[0008] "Finished reading" refers to a user reading an electronic book to the end.

[0009] "Timing" refers to a specific time or opportunity, in this case two days, 14 days, 60 days, etc., after reading.

[0010] "Quiz" refers to a series of questions created based on the content of the e-book you have read.

[0011] "Terminal" refers to a device that a user uses to read an e-book.

[0012] "Generation" refers to creating new data or content (in this case, quizzes) based on information.

[0013] "Notification" refers to informing a user of specific information.

[0014] "Means" refers to the methods or techniques used to achieve a particular goal.

[0015] "Answer results" refers to the results of the aggregation and evaluation of answers submitted by users to quizzes.

[0016] "Evaluation" refers to analyzing the answers and measuring their accuracy and level of understanding.

[0017] "Feedback" refers to advice or information provided to the user based on the evaluation results.

[0018] "Memory consolidation" refers to retaining learned information for a long period of time so that it is not forgotten.

[0019] "Analysis" refers to examining the contents of an e-book in detail and extracting important points.

[0020] "Key points" refer to information or facts that are considered particularly important within the content of an e-book.

[0021] "Game-like" refers to mechanisms and elements that allow users to learn while having fun. [Brief explanation of the drawings]

[0022] [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 illustrating 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

[0023] 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.

[0024] First, the terms used in the following description will be explained.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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."

[0030] [First embodiment]

[0031] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0032] 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.

[0033] 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).

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] 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."

[0043] This invention is a system that generates and notifies a user of a quiz after a certain period of time based on when the user finishes reading an e-book, evaluates the answers, and provides feedback. This system operates based on the roles of the server, terminal, and user.

[0044] Program processing explanation

[0045] 1. User registration and reading record

[0046] The user opens an e-book app on their device.

[0047] Users create an account and enter basic information.

[0048] The server stores user account information in a database.

[0049] When a user selects an e-book and starts reading, the device records and transmits the reading start time.

[0050] The server initiates the reading session and tracks its progress.

[0051] 2. Reading Completion and Quiz Generation

[0052] The user finishes reading the e-book.

[0053] The device records and transmits the reading time.

[0054] The server receives the read completion information and stores it in a database.

[0055] The server generates and prepares quizzes based on a specific period after completion of reading (2 days, 14 days, 60 days).

[0056] Analyze the contents of e-books, extract important points, and generate quizzes.

[0057] 3. Quiz Notifications

[0058] When the server reaches the quiz timing, it sends a notification to the device.

[0059] A push notification will be sent to the user's device containing a message that the quiz is ready and a link.

[0060] 4. Quiz

[0061] The user confirms the notification and starts the quiz.

[0062] The terminal displays a quiz screen and the user inputs an answer.

[0063] The quizzes are presented in multiple choice or free-form format, making them fun to play like a game.

[0064] 5. Recording and feedback of results

[0065] The terminal transmits the user's answers to the quiz to the server.

[0066] The server evaluates the answers and records them in a database.

[0067] Based on the evaluation results, feedback is provided to the user. For example, if the accuracy rate is high, a positive message such as "Your memory is firmly established" is sent.

[0068] Specific examples

[0069] Example of a user selecting the e-book "Study Guide" and starting to read

[0070] 1. The user selects an e-book

[0071] I choose the e-book "Study Guide" and start reading.

[0072] The device records the reading start time (e.g., 10:00 on October 1, 2023) and sends it to the server.

[0073] The server starts the reading session and stores the progress in a database.

[0074] 2. The user finishes reading the book

[0075] The user completes the Study Guide.

[0076] The device records the time of completion of reading (e.g., 18:00 on October 2, 2023) and sends it to the server.

[0077] The server receives the reading completion information and generates and schedules the quiz.

[0078] The quiz timings will be set for 2 days (October 4th), 14 days (October 16th), and 60 days (December 1st) after the reading is completed.

[0079] Generative AI analyzes the contents of the book and creates quiz questions.

[0080] 3. Quiz Notification and Implementation

[0081] When the time comes for the quiz, the server will send a notification.

[0082] Example: On October 4th, a push notification will be sent saying "It's time for a review quiz!"

[0083] The user confirms the notification and starts the quiz screen.

[0084] The terminal displays a quiz screen and the user inputs an answer.

[0085] 4. Evaluation results and feedback

[0086] The user answers the quiz, and the terminal transmits the answer to the server.

[0087] The server evaluates the answer and gives an 80% correct answer rate.

[0088] The server generates feedback and sends the message "Great! Your memory is firmly established" to the device.

[0089] The terminal displays a feedback message to the user.

[0090] This invention provides a system that effectively solidifies the contents of e-books into memory through the timing and content of quiz notifications, as well as a mechanism for evaluation and feedback, aiming to make learning more enjoyable and efficient for users.

[0091] The processing flow will be explained below.

[0092] Step 1:

[0093] The user downloads an e-book app on their device and creates an account.

[0094] The user enters their name, email address, and password.

[0095] The device sends the input information to the server, which then stores the account in a database.

[0096] Step 2:

[0097] The user selects an e-book.

[0098] The device displays a list of e-books, and the user selects the book they want to read.

[0099] The user selects the Study Guide and begins reading.

[0100] The device records the reading start time and sends it to the server.

[0101] The server initiates the reading session and stores it in a database.

[0102] Step 3:

[0103] The user finishes reading the e-book.

[0104] When the user finishes reading the last page, the device records the time it took to finish reading.

[0105] The device sends the reading time to the server, which stores it in a database.

[0106] Step 4:

[0107] The server sets the timing for generating the quiz based on the reading completion information.

[0108] The server calculates the timing of 2 days (48 hours), 14 days, and 60 days after the end of reading and sets the schedule for generating the quiz.

[0109] Step 5:

[0110] The server uses generated AI to analyze the contents of the book that has been read.

[0111] Generative AI extracts key points from text and converts them into quizzes.

[0112] Quizzes are created in multiple choice or free-form format.

[0113] Step 6:

[0114] When the quiz timing is reached, the server will send a push notification to the device.

[0115] Example: On the second day after finishing reading, you will receive a notification saying "It's time for a review quiz."

[0116] Step 7:

[0117] The user confirms the notification and starts the quiz.

[0118] The user clicks the link in the notification message, and the device displays the quiz screen.

[0119] The user answers the quiz.

[0120] Step 8:

[0121] The terminal sends the user's answer to the server.

[0122] The server receives the response data and evaluates the accuracy rate, etc.

[0123] The evaluation results are recorded in a database.

[0124] Step 9:

[0125] The server generates feedback based on the evaluation results.

[0126] If the score is high, create a positive message such as "Great! Your memory is well-established."

[0127] If the score is low, feedback is generated that includes study advice such as "Please review the following points."

[0128] Step 10:

[0129] The server sends a feedback message to the terminal.

[0130] The device displays the feedback to the user.

[0131] Example 1

[0132] 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."

[0133] Conventional e-book learning systems lack mechanisms for helping users effectively solidify the contents of e-books in their memories, making it difficult to fully utilize the learning benefits after reading. Specifically, it is difficult to review the content at an appropriate time after reading, or to extract important points and turn them into quizzes, making it difficult to maintain users' motivation to learn.

[0134] 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.

[0135] In this invention, the server includes a means for detecting when the user has finished reading the e-book, a means for generating a quiz based on a specific period after the user has finished reading (2 days, 14 days, or 60 days), and a means for sending prompts to the generation AI model, analyzing the contents of the e-book, and extracting important points. This allows for the provision of quizzes at appropriate times and for reviewing the contents.

[0136] A "user" is an individual who uses the system to read an electronic book.

[0137] A "terminal" is an electronic device that a user uses to read an e-book, such as a smartphone, tablet, or e-book reader.

[0138] A "server" is a central device that manages the operation of the entire system and communicates with users and terminals.

[0139] The "reading record" is data on the time when the user started reading an electronic book and the time when the user finished reading it.

[0140] A "reading session" is a record of a single e-book reading activity, including the start and end times of that activity.

[0141] A "database" is a storage system connected to a server for storing user account information and reading records.

[0142] A "generative AI model" is an artificial intelligence model that analyzes the contents of e-books and generates quizzes.

[0143] A "prompt" is an instruction given to a generative AI model, which serves as a guide for generating a quiz.

[0144] A "quiz" is a question-based test based on the content of an e-book, and is provided for the purpose of measuring the user's level of comprehension of the content.

[0145] A "push notification" is a real-time message sent from a server to a user device. An example is a quiz notification.

[0146] "Evaluation" refers to analyzing the percentage of correct answers and the level of comprehension of the content based on the answers entered by the user to the quiz.

[0147] "Feedback" refers to results reports and advice provided based on the user's answers to the quiz.

[0148] This invention is a system that generates and notifies a user of a quiz after a certain period of time based on when the user finishes reading an e-book, evaluates the answers, and provides feedback. This system operates based on the roles of the server, terminal, and user.

[0149] The server is the central device that manages the operation of the entire system and communicates with users and their devices. The server notifies the users of the generated quizzes, collects and evaluates the answers to the quizzes, and provides feedback based on the evaluation results.

[0150] A device is an electronic device used by a user to read e-books, such as a smartphone, tablet, or e-reader. The device records the user's start and end times and sends them to a server. It also has the ability to receive push notifications.

[0151] A user is an individual who uses the system to read an e-book and answer the subsequent quiz. The user creates an account, selects an e-book, and begins reading. After finishing the reading, the user answers the quiz sent by the server and receives feedback based on the results.

[0152] Specifically, the user first opens an e-book on their device, creates an account, and enters basic information. The device then sends this information to the server, which then stores it in a database. When the user selects an e-book and begins reading, the device records the start time of reading and sends it to the server.

[0153] When a user finishes reading an e-book, the device records the reading time and sends it to the server. The server stores the received information in a database and generates quizzes based on specific time periods (2 days, 14 days, or 60 days later). The AI ​​model then sends prompts to analyze the e-book's content, extracting key points and generating appropriate quizzes.

[0154] As a specific example, consider the case where a user selects the e-book "Study Guide" and begins reading. If the reading start time is, for example, 10:00 on October 1, 2023, the device records this information and sends it to the server. Later, when the user finishes reading at 18:00 on October 2, 2023, the device records the information again and sends it to the server. Based on this reading completion information, the server sets the timing of three quiz notifications for October 4, October 16, and December 1.

[0155] The server generates a quiz by sending the following prompt to the generative AI model: "For a user who has finished reading the e-book 'Study Guide', after two days, please generate four multiple-choice quiz questions based on the following content: The key points of Chapter 1 are..."

[0156] When it's time for a quiz notification, the server sends an appropriate push notification to the device. For example, on October 4th, a message saying "It's time for a review quiz!" is sent, and the user confirms the notification and opens the quiz screen on the device. The user answers the quiz and the results are sent from the device to the server. The server evaluates the results, generates a feedback message, and sends it to the device. The device displays the feedback to the user, allowing them to confirm the results.

[0157] Through the quizzes and feedback provided by this system, users can effectively solidify the contents of e-books into their memories.

[0158] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0159] Step 1: User registration and reading log

[0160] A user opens an e-book app on their device. First, the user creates an account and enters basic information such as their name and email address. The device sends this information to the server, which stores it in a database. Next, the user selects an e-book and begins reading. The device records the reading start time and sends the reading start information to the server. The server starts a reading session based on this information and stores it in a database. It also tracks the progress in real time. The input data is the user's basic information and reading start time, and the output data is the reading session information stored in the database.

[0161] Step 2: Reading and creating a quiz

[0162] The user finishes reading an e-book. The device records the completion time and sends that information to the server. The server stores the received completion information in a database. Next, it schedules quizzes to be given two days, 14 days, and 60 days after completion. The server sends prompts to the generative AI model, which analyzes the content of the e-book, extracts key points, and generates a quiz. For example, it creates a quiz question such as, "What are the key points of Chapter 1?" The input data is the reading time and the content of the e-book, and the output data is the generated quiz.

[0163] Step 3: Quiz Notification

[0164] The quiz notification timing arrives. Based on the configured timing, the server sends a push notification to the user device that the quiz is ready. The notification includes the message "It's time for a review quiz!" and a link to the quiz screen. This allows the user to start the quiz smoothly. The input data is the quiz notification schedule, and the output data is the sent notification message.

[0165] Step 4: Take the quiz

[0166] The user confirms the notification and starts the quiz. The device displays the quiz screen, and the user enters their answers. The quiz questions are presented in multiple choice or free description format, and the user answers according to the format. The input data are the quiz questions and the user's answers, and the output data are the user's answers.

[0167] Step 5: Recording and feedback

[0168] Once the quiz is complete, the device sends the user's answers to the server. The server evaluates the received answers and analyzes the accuracy rate and comprehension level. Based on this evaluation result, a feedback message is generated, such as "Excellent! Your memory is firmly established." The server sends this feedback message to the device, which then displays it to the user. The input data is the user's answers, and the output data is the feedback message.

[0169] (Application example 1)

[0170] 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."

[0171] Simply viewing conventional e-books or learning content is often insufficient to retain what has been learned. Another issue is the lack of appropriate review methods that allow users to review what they have viewed later and improve their learning effectiveness. Therefore, a support system is needed to effectively review and retain what has been viewed.

[0172] 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.

[0173] In this invention, the server includes a means for detecting when a user has finished viewing an e-book or learning content, a means for generating a quiz based on a specific period (2 days, 14 days, or 60 days) after the completion of the reading or viewing, a means for notifying the generated quiz to the user terminal, a means for collecting and evaluating the quiz answers, and a means for providing feedback to the user based on the evaluation results, thereby effectively helping the user to solidify the content they have viewed.

[0174] "User" refers to an individual who uses the system to read e-books or view learning content.

[0175] An "e-book" is a book that is distributed in digital form and is read using an electronic device.

[0176] "Learning content" refers to educational videos and materials designed to improve knowledge and skills.

[0177] "Viewing" refers to the act of a user reading an e-book or viewing learning content.

[0178] The "means for detecting timing" refers to a technique or device for identifying the point in time at which a user has finished viewing an e-book and learning content.

[0179] A "specific period" refers to a predetermined period, such as 2 days, 14 days, or 60 days after viewing.

[0180] "Quiz generating means" refers to a technique or device for creating a quiz based on the content viewed.

[0181] A "user terminal" is an electronic device used by a user, such as a computer, smartphone, or tablet.

[0182] The "notification means" refers to a technique or device for notifying the user terminal of the generated quiz.

[0183] The "means for collecting answer results" refers to a technique or device for obtaining the results of users' answers to the quiz.

[0184] "Means for evaluation" refers to technology or equipment for analyzing collected answers and measuring the user's level of understanding.

[0185] The "means for providing feedback" refers to a technology or device for sending advice or comments to the user based on the evaluation results.

[0186] In order to implement the present invention, it is necessary to construct the following system.

[0187] First, a user uses a device (such as a smartphone or tablet) to view e-books and learning content. After installing a dedicated application on the device, the user registers and begins viewing. When the user starts viewing, the device records the start time and sends it to the server.

[0188] Platform configuration:

[0189] Hardware: Smartphones, tablets, computers, head-mounted displays (HMDs)

[0190] Software: Dedicated learning application, Flask (web application framework), SQLAlchemy (database management), OpenAI GPT-3 (quiz generation), Firebase Cloud Messaging (notification service)

[0191] The server tracks the user's progress from the start of the session, records the completion time when the user finishes the session, and then generates quizzes based on specific time periods (2 days, 14 days, 60 days).

[0192] To generate the quiz, the server analyzes the key points of the viewed content and creates the quiz using a generative AI model (e.g., OpenAI GPT-3). The generation process uses the following prompt sentence as input:

[0193] Example prompt sentence:

[0194] Generate a quiz with multiple choice questions based on the content of the documentary "Miracles of Earth". Include questions that test the viewer's understanding of key concepts discussed in the documentary.

[0195] The generated quiz is notified to the user's device using Firebase Cloud Messaging. The user receives the notification and answers the quiz. The user's answers are sent from the device to the server, which evaluates them. Based on the evaluation results, feedback is generated and sent to the user's device. This feedback allows the user to understand their level of understanding and obtain guidelines for further study.

[0196] For example, after a user finishes watching the science documentary "Miracles of the Earth," they are notified of different quizzes two days, 14 days, and 60 days later. Each quiz is based on the content viewed and is designed to help users retain their knowledge. Depending on the evaluation results, the user is given feedback such as "Excellent! Your memory is firmly established."

[0197] In this way, the present invention serves as a support system that effectively helps users to solidify their memory of what they have viewed and improves their learning effectiveness.

[0198] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0199] Step 1:

[0200] A dedicated application is installed on the device (such as a smartphone or tablet) on which the user will view the e-books and learning content.

[0201] Input: User basic information, installed apps.

[0202] Output: Initial setup completed, user account created.

[0203] Specific behavior: The user creates an account in the launched application and enters basic information.

[0204] Step 2:

[0205] Users view e-books and learning content.

[0206] Enter: Select the content you want to watch.

[0207] Output: Recording of viewing start time, viewing status tracking.

[0208] Specific operation: When a user starts watching, the device records the start time of watching and sends it to the server.

[0209] Step 3:

[0210] When viewing is finished, the time of completion of reading or viewing is recorded.

[0211] Input: End View action.

[0212] Output: Record of viewing end time.

[0213] Specific operation: When the user finishes watching, the device records the end time and sends it to the server.

[0214] Step 4:

[0215] Generate quizzes based on a specific time period (2 days, 14 days, 60 days).

[0216] Input: End time of viewing, content viewed.

[0217] Output: Generate a quiz.

[0218] Specific operation: The server sets the timing for generating the quiz based on the end time of viewing, and generates a quiz based on the viewing content using a generative AI model (OpenAI GPT-3).

[0219] Step 5:

[0220] The generated quiz is notified to the user terminal.

[0221] Input: The generated quiz.

[0222] Output: Push quiz notification.

[0223] Specific operation: The server uses Firebase Cloud Messaging to send a quiz notification to the user's device.

[0224] Step 6:

[0225] The user answers the quiz.

[0226] Input: Notified quiz.

[0227] Output: Quiz answer results.

[0228] Specific operation: The user receives a quiz notification, opens the quiz screen, enters the answer, and the device sends the answer to the server.

[0229] Step 7:

[0230] The server evaluates the quiz answers.

[0231] Input: The user's quiz answer result.

[0232] Output: Producing the evaluation results.

[0233] Specific operation: The server compiles the quiz answer results and evaluates the user's accuracy rate, etc.

[0234] Step 8:

[0235] Based on the evaluation results, feedback is provided to the user.

[0236] Input: Evaluation result.

[0237] Output: Generate and send feedback messages.

[0238] Specific operation: Based on the evaluation result, the server generates a feedback message and sends it to the user terminal.

[0239] In this way, the operation of the entire system is explained in detail at each step, linking the user's viewing experience to improved learning outcomes.

[0240] 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.

[0241] This invention combines a system that detects when a user has finished reading an e-book, generates and notifies a user of a quiz after a specific period of time, evaluates the results of the quiz, and provides feedback, with an emotion engine that recognizes the user's emotions. This system operates based on the roles of the server, the terminal, and the user.

[0242] Program processing explanation

[0243] 1. User registration and reading record

[0244] The user opens the e-book app on their device and creates an account.

[0245] The user enters their name, email address, and password, and the device sends the information to the server.

[0246] The server stores the account information in a database.

[0247] When a user selects an electronic book and starts reading, the terminal records the reading start time and transmits it to the server.

[0248] The server initiates the reading session and tracks its progress.

[0249] 2. Reading Completion and Quiz Generation

[0250] The user finishes reading the e-book.

[0251] The device records the reading time and sends it to the server.

[0252] The server receives the read completion information and stores it in a database.

[0253] The server generates and prepares quizzes based on specific time periods after completion of reading (2 days, 14 days, 60 days).

[0254] Analyze the contents of e-books, extract important points, and generate quizzes.

[0255] 3. Emotional engine for recognizing user emotions

[0256] When a user starts a quiz, the emotion engine kicks in.

[0257] The device's camera and microphone are used to analyze the user's facial expressions and voice to determine their emotional state.

[0258] The emotion engine sends the user's emotion data to the server.

[0259] 4. Quiz Notifications and Adjustments

[0260] The server adjusts the content and timing of the quiz based on the emotional data.

[0261] For example, if it is determined that the user is tired, it may present questions with lower difficulty or postpone notifications.

[0262] When the server is ready to quiz, it will send a push notification to the user's device. Example: "Time for a review quiz!"

[0263] 5. Quiz

[0264] The user confirms the notification and starts the quiz.

[0265] The terminal displays a quiz screen and the user inputs an answer.

[0266] The quizzes are presented in multiple choice or free-form format, with the appropriate content selected based on the analysis results of the emotion engine.

[0267] 6. Recording and feedback of results

[0268] The terminal transmits the user's answers to the quiz to the server.

[0269] The server evaluates the answers and records them in a database.

[0270] Based on the evaluation results, feedback is provided to the user. For example, if the accuracy rate is high, a positive message such as "Your memory is firmly established" is sent.

[0271] Consider the results of the emotion engine and adjust the tone and content of your feedback as needed.

[0272] Specific examples

[0273] Example of a user selecting the e-book "Study Guide" and starting to read

[0274] 1. The user selects an e-book

[0275] The user selects the e-book "Study Guide" and begins reading.

[0276] The device records the reading start time (e.g., 10:00 on October 1, 2023) and sends it to the server.

[0277] The server starts the reading session and stores the progress in a database.

[0278] 2. The user finishes reading the book

[0279] The user completes the Study Guide.

[0280] The device records the time of completion of reading (e.g., 18:00 on October 2, 2023) and sends it to the server.

[0281] The server receives the reading completion information and generates and schedules the quiz.

[0282] The quiz timings will be set for 2 days (October 4th), 14 days (October 16th), and 60 days (December 1st) after the reading is completed.

[0283] Generative AI analyzes the contents of the book and creates quiz questions.

[0284] 3. Emotional Engine Activation

[0285] When a user starts a quiz, the device's camera and microphone collect and analyze the user's emotions (e.g., the emotion engine determines that the user is relaxed).

[0286] The emotion engine sends the results to the server.

[0287] 4. Quiz Notifications and Coordination

[0288] When it's time for a quiz, the server takes into account the results of the emotion engine and adjusts the notification message.

[0289] Example: On October 4th, a push notification will be sent saying "It's time for a review quiz!"

[0290] 5. Conducting a quiz

[0291] The user confirms the notification and starts the quiz screen.

[0292] The terminal displays a quiz screen and the user inputs an answer.

[0293] The difficulty of the quiz is adjusted to suit the user's emotional state.

[0294] 6. Evaluation results and feedback

[0295] The user answers the quiz, and the terminal transmits the answer to the server.

[0296] The server evaluates the answer and gives an 80% correct answer rate.

[0297] The server generates feedback and, based on the results of the emotion engine, sends a message to the device saying, "Great! Your memory is well-established. Keep up the great work!"

[0298] The terminal displays a feedback message to the user.

[0299] This invention aims to provide more effective and personalized learning by taking into account the user's emotional state. By combining it with an emotion engine, it is possible to review at the most appropriate time and with the most appropriate content for the user, significantly improving the efficiency and enjoyment of learning.

[0300] The processing flow will be explained below.

[0301] Step 1:

[0302] The user downloads an e-book app on their device and creates an account.

[0303] The user enters their name, email address, and password.

[0304] The device sends the input information to the server, which then stores the account in a database.

[0305] Step 2:

[0306] The user selects an e-book.

[0307] The device displays a list of e-books, and the user selects the book they want to read.

[0308] The user selects the Study Guide and begins reading.

[0309] The device records the reading start time and sends it to the server.

[0310] The server initiates the reading session and stores it in a database.

[0311] Step 3:

[0312] The user finishes reading the e-book.

[0313] When the user finishes reading the last page, the device records the time it took to finish reading.

[0314] The device sends the reading time to the server, which stores it in a database.

[0315] Step 4:

[0316] The server sets the timing for generating the quiz based on the reading completion information.

[0317] The server calculates the timing of 2 days (48 hours), 14 days, and 60 days after the end of reading and sets the schedule for generating the quiz.

[0318] Step 5:

[0319] The server uses generated AI to analyze the contents of the book that has been read.

[0320] Generative AI extracts key points from text and creates quizzes.

[0321] The quiz will consist of multiple choice and free-form questions.

[0322] Step 6:

[0323] When the quiz timing is reached, the server will send a push notification to the device.

[0324] For example, you will receive a notification saying, "Take the quiz two days after you finish reading."

[0325] Step 7:

[0326] The user confirms the notification and starts the quiz.

[0327] The user clicks the link in the notification message, and the device displays the quiz screen.

[0328] The user answers the quiz.

[0329] Step 8:

[0330] The terminal transmits the user's response data to the server.

[0331] The server evaluates the answers and calculates the accuracy rate, etc.

[0332] The evaluation results are recorded in the user's database.

[0333] Step 9:

[0334] When a user starts a quiz, the emotion engine kicks in.

[0335] The device's camera and microphone are used to analyze the user's facial expressions and voice to determine their emotional state.

[0336] The emotion engine sends the user's emotion data to the server.

[0337] Step 10:

[0338] The server adjusts the quiz content and the timing of the next notification based on the emotional data.

[0339] For example, if it is determined that the user is tired, it may present questions with lower difficulty or postpone notifications.

[0340] When the server is ready for the quiz, it will send the following push notification to the user's device:

[0341] Step 11:

[0342] The server generates feedback based on the evaluation results.

[0343] If the score is high, create a positive message such as "Great! Your memory is well-established."

[0344] If the score is low, feedback is generated that includes study advice such as "Please review the following points."

[0345] Step 12:

[0346] The server sends a feedback message to the terminal.

[0347] The device displays feedback to the user.

[0348] Example 2

[0349] 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."

[0350] In conventional learning systems, there are limited ways for users to effectively check their understanding of an e-book after they have finished reading it, and the timing for reviewing the learning content is fixed, making it difficult to maximize the learning effect of each individual user. Furthermore, conventional systems do not take into account the user's emotional state, which creates the risk of the learning load becoming too high and lowering user motivation.

[0351] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for detecting the timing when the user finishes reading an e-book, means for generating a quiz based on a specific period after the completion of reading (2 days, 14 days, or 60 days), means for notifying the user terminal of the generated quiz, means for collecting and evaluating quiz answer results, means for providing feedback to the user based on the evaluation results, emotion recognition means for recognizing the user's emotion, and means for adjusting the quiz content and notification timing based on the emotion recognition data. This enables review at the optimal timing and content according to each user's emotional state, thereby improving learning effectiveness and motivation.

[0352] "User" refers to an individual who operates this system to read e-books and answer quizzes.

[0353] "Device" refers to any computer system used by a user that can run an e-book app, including, for example, a smartphone, tablet, or PC.

[0354] "Server" refers to a computer system that receives data from the terminal, processes it, and generates appropriate feedback and quizzes.

[0355] The "timing of completion of reading" refers to the time when the user has finished reading all the pages of the electronic book.

[0356] "Quiz generation" refers to the process of analyzing the content of an e-book and creating questions based on a specific period after reading.

[0357] "Notification" refers to the process of sending a push notification or alert to the user's device when the generated quiz is ready.

[0358] "Answer result" refers to the answer entered by the user to the quiz.

[0359] "Evaluation" refers to the process of analyzing the user's answers and measuring the percentage of correct answers and learning progress.

[0360] "Feedback" refers to specific advice or messages provided to users based on the evaluation results to improve their learning effectiveness.

[0361] "Emotion recognition" refers to the process of analyzing a user's facial expressions and voice data collected using the device's camera and microphone to determine the user's emotional state.

[0362] "Emotion recognition data" refers to data obtained through an emotion recognition process that indicates a user's emotional state.

[0363] "Adjustment" refers to the process of changing the content of the quiz or the timing of notifications based on emotion recognition data.

[0364] This invention is a system that detects when a user has finished reading an e-book, generates and notifies a user of a quiz after a specific period of time, evaluates the results of the quiz and provides feedback, and combines it with an emotion recognition engine that recognizes the user's emotions. This system operates based on the roles of the server, terminal, and user.

[0365] Specific hardware includes devices such as smartphones, tablets, and PCs. Servers are built as cloud servers or dedicated servers. Software includes e-book apps, emotion recognition engines, generative AI models, etc.

[0366] 1. User registration and reading record

[0367] A user opens an e-book app and creates an account. Specifically, the user enters their name, email address, and password, and the device sends that information to the server. The server saves the account information in a database and notifies the user when the account is complete. When the user selects an e-book and starts reading, the device records the reading start time and sends it to the server. The server starts the reading session and saves the progress in a database.

[0368] 2. Reading Completion and Quiz Generation

[0369] When a user finishes reading an e-book, the device records the time the user has finished reading and sends it to the server. The server then stores this information in a database and generates a quiz for a specific period of time after the user has finished reading (for example, 2 days, 14 days, or 60 days later). The generative AI model analyzes the content of the e-book, extracts key points, and creates the quiz.

[0370] 3. Emotional engine for recognizing user emotions

[0371] When a user receives a quiz notification and starts the quiz, the device's camera and microphone collect the user's facial expressions and voice data, which are then analyzed by an emotion recognition engine. The emotion recognition engine determines the user's emotional state (e.g., relaxed, tired) and sends the data to the server.

[0372] 4. Quiz Notifications and Adjustments

[0373] The server adjusts the content of the quiz and the timing of notifications based on emotion recognition data. For example, if the server determines that the user is tired, it will select less difficult questions or postpone notifications. When the quiz is ready, the server sends a push notification to the user's device. For example, it could send a message saying, "It's time for a review quiz!"

[0374] 5. Quiz

[0375] The user confirms the notification and starts the quiz. The device displays the quiz screen and the user enters their answers. Questions are presented in multiple choice or free-form format, and the appropriate content is selected based on the analysis results of the emotion recognition engine.

[0376] 6. Recording and feedback of results

[0377] The user answers the quiz, and the device sends the results to the server. The server evaluates the answer (for example, "80% correct") and records it in a database. Based on the evaluation results, the server provides feedback to the user. For example, if the user answers correctly, the server may generate a message such as "Great! Your memory is well-established. Keep up the good work!", adjusting the tone and content of the feedback based on the results of the emotion recognition engine. The feedback message is sent to the user's device, where it is displayed to the user.

[0378] Example prompt sentence:

[0379] "Detect when a user has finished reading a specific e-book and generate a quiz based on a specific period after reading. Also, recognize the user's emotional state and adjust the optimal quiz content and notification timing."

[0380] The above system provides personalized learning that takes into account the user's emotional state, and is expected to significantly improve the efficiency and enjoyment of learning.

[0381] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0382] Step 1:

[0383] Create an account

[0384] A user opens an e-book app and enters their name, email address, and password.

[0385] Enter your name, email address, and password.

[0386] Output: The user's account information.

[0387] The terminal sends the input information to the server.

[0388] The server saves the account information to the database, performs a database update operation, and logs the completion of the save.

[0389] Step 2:

[0390] Select an e-book and start reading

[0391] The user selects an e-book in the app (e.g., "Study Guide").

[0392] Input: Information about the selected e-book.

[0393] Output: Triggers the reading start event.

[0394] The terminal records the user's reading start time and sends that information to the server.

[0395] The server starts a reading session and saves the progress to a database, writes the start time to the database, and generates a session ID.

[0396] Step 3:

[0397] Record reading time

[0398] The user reads the e-book to the end.

[0399] Input: Information on the page you have read.

[0400] Output: Triggers a read event.

[0401] The device records the time it takes to finish reading and sends that information to the server.

[0402] The server saves the completion information to a database, records the completion time, and updates the relevant session data.

[0403] Step 4:

[0404] Quiz Generation

[0405] The server sets a specific period after reading (e.g., 2 days, 14 days, or 60 days).

[0406] Input: Reading information, specific period.

[0407] Output:Quiz schedule.

[0408] The server uses a generative AI model to analyze the contents of the e-book, extract key points, and create quiz questions.

[0409] Input: E-book text data.

[0410] Output: A set of quiz questions.

[0411] The server stores the generated quiz in a database.

[0412] Step 5:

[0413] Quiz Notifications

[0414] When the server is ready for the quiz based on the specified quiz notification timing, it sends a push notification to the user terminal.

[0415] Input: Quiz schedule, user's device information.

[0416] Output: Push notification (e.g. "Time for a review quiz!").

[0417] The server records the notification content and timing and sets retransmission logic.

[0418] Step 6:

[0419] Emotion recognition and quiz start

[0420] The user receives the quiz notification and starts the quiz.

[0421] Input: Acknowledgement of notification receipt.

[0422] Output: Quiz screen display.

[0423] The device's camera and microphone collect the user's facial expressions and voice data, which is then analyzed by an emotion recognition engine.

[0424] Input: User's facial expressions and voice data.

[0425] Output: Emotion recognition result (e.g. "Relaxed" or "Tired").

[0426] The emotion recognition engine sends the analysis results to the server.

[0427] Step 7:

[0428] Adjustment and implementation of quiz content

[0429] The server adjusts the content and difficulty of the quiz based on the emotion recognition data.

[0430] Input: Emotion recognition data, generated quiz questions.

[0431] Output: The adjusted quiz questions.

[0432] The terminal displays the adjusted quiz questions and the user inputs the answers.

[0433] Input: The user's answer.

[0434] Output: Response data.

[0435] Step 8:

[0436] Submitting and evaluating answer results

[0437] The terminal transmits the user's answer results to the server.

[0438] Input: Response data.

[0439] Output: Sending data to the server.

[0440] The server evaluates the answer results and stores the evaluation results in a database.

[0441] Input: Response data.

[0442] Output: Evaluation results such as accuracy rate.

[0443] Based on the evaluation results, the server generates feedback.

[0444] Step 9:

[0445] Providing Feedback

[0446] The server provides feedback to the user based on the evaluation results.

[0447] Input: Evaluation results, emotion recognition data.

[0448] Output: A feedback message (e.g., "Great! Your memory is solid. Keep it up!").

[0449] The terminal displays a feedback message to the user.

[0450] (Application example 2)

[0451] 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."

[0452] Conventional learning systems using e-books provide quizzes uniformly without considering the user's emotions, which means that they are unable to provide optimal review timing or difficulty for each individual user. Furthermore, to maximize learning efficiency, it is important to adjust the timing and content according to the user's emotional state, but no such system has existed. Furthermore, when using e-payment services, users have had the problem of not receiving appropriate feedback after selecting a product.

[0453] 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.

[0454] In this invention, the server includes a means for detecting when a user has finished reading an e-book, a means for generating a quiz based on a specific period of time since the user finished reading, and a means for recognizing the user's emotions using an emotion engine. This makes it possible to adjust the content of the quiz and the timing of notifications according to the user's emotional state and provide personalized feedback. Furthermore, emotion recognition can be utilized when using electronic payment services, providing appropriate feedback and recommendations to the user to increase their motivation to purchase.

[0455] The "means for detecting when the user has finished reading the e-book" is a mechanism that automatically detects when the user has read to the last page of the e-book and records that point in time.

[0456] The "means for generating quizzes" is a function that analyzes the contents of an e-book and creates multiple questions based on a specific algorithm.

[0457] "Means for notifying the user terminal" refers to a method for sending quizzes and other information to the user's device as alerts or push notifications.

[0458] "Means for collecting and evaluating quiz answer results" refers to a system for collecting data on users' answers to quizzes and analyzing and evaluating their accuracy and completeness.

[0459] The "means for providing feedback" is a system that returns appropriate advice and comments to the user based on the evaluation results of the quiz.

[0460] The "means for recognizing a user's emotions using an emotion engine" is a device equipped with an algorithm that analyzes a user's facial expressions, voice, and other biometric data to determine their psychological state.

[0461] The "means for adjusting the quiz content and notification timing according to the user's emotions" is a mechanism for optimizing the difficulty of the quiz and the timing of sending notifications based on the user's current emotional state.

[0462] This invention is a system that detects when a user has finished reading an e-book, generates a quiz after a specific period of time has passed, notifies the user of the quiz, evaluates the answers, and provides feedback.The system is characterized by using an emotion engine to recognize the user's emotions and adjusts the quiz content and notification timing accordingly.

[0463] System Configuration

[0464] The system consists of the following major hardware and software components:

[0465] Server: Contains the database, quiz generation algorithm, and emotion engine.

[0466] User device: A device such as a smartphone that is equipped with a camera and microphone.

[0467] Database: Stores user reading records, emotion data, and quiz results.

[0468] Emotion engine: A software module that recognizes emotions by analyzing the user's facial expressions and voice.

[0469] Quiz generation module: Analyzes the content of the e-book and generates quizzes based on key points.

[0470] System Operation

[0471] 1. User registration and reading record

[0472] Users create an account using a smartphone app, select an e-book, and begin reading. The device records the start time and sends it to the server, which then starts the reading session and stores the progress in a database.

[0473] 2. Reading Completion and Quiz Generation

[0474] When a user finishes reading an e-book, the device records the reading time and sends it to the server. The server receives the reading completion information and stores it in a database. A quiz is then generated and prepared based on a specific period after the reading (2 days, 14 days, or 60 days later). A generative AI model is used to analyze the content of the e-book, extract key points, and generate the quiz.

[0475] 3. Emotional engine for recognizing user emotions

[0476] When a user starts a quiz, the device's camera and microphone are used to recognize the user's emotions. The emotion engine analyzes the user's emotional data and sends this data to the server.

[0477] 4. Quiz Notifications and Adjustments

[0478] The server adjusts the quiz content and notification timing based on the emotion data. For example, if it determines that the user is tired, it can present easier questions or postpone notifications. When the quiz is ready, the server sends a push notification to the user's device. The notification reads, "Time for a review quiz!"

[0479] 5. Quiz and feedback

[0480] The user confirms the notification and begins the quiz. The quiz screen displays questions tailored to the user's emotional state, and the user enters their answers. The answers are sent from the device to the server, which evaluates them and provides feedback. For example, if the user answers correctly, a positive message such as "your memory is firmly established" is sent.

[0481] Examples of specific examples and prompts

[0482] For example, if a user starts reading the e-book "Study Guide" and finishes it, and the emotion engine determines that they are in a "Relaxed" state, the quiz notification will look like this:

[0483] Quiz notification example

[0484] "Time for a review quiz!"

[0485] Prompt Sentence Examples

[0486] Feedback when the user is relaxed:

[0487] Feedback message: "Amazing! I recommend you buy this product."

[0488] This allows for personalized quizzes and feedback that take into account the user's emotional state.

[0489] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0490] Step 1:

[0491] User registration and reading log

[0492] A user creates an account using a smartphone app and enters their name, email address, and password. The device sends this information to the server, which stores the account information in a database. When the user selects an e-book and begins reading, the device records the start time of the reading and sends it to the server. The server starts the reading session and stores the progress in a database.

[0493] Input: User information (name, email address, password) and e-book selection information

[0494] Data processing and calculation: User information verification and storage, recording of reading start time

[0495] Output: User account created, reading session started

[0496] Step 2:

[0497] Reading Completion and Quiz Generation

[0498] When a user finishes reading an e-book, the device records the reading time and sends it to the server. The server receives the reading completion information and stores it in a database. It then generates a quiz based on a specific period after reading (e.g., 2 days, 14 days, or 60 days). A generative AI model is used to analyze the content of the e-book, extract key points, and create a quiz.

[0499] Input: Reading time, e-book content

[0500] Data processing and calculation: saving reading completion information, generating quizzes

[0501] Output:Quiz preparation

[0502] Step 3:

[0503] Recognizing user emotions with an emotion engine

[0504] When a user starts a quiz, the device's camera and microphone capture the user's facial expressions and voice, and send them to the emotion engine, which analyzes them, determines the user's emotional state, and sends the results to the server.

[0505] Input: User's facial expression and voice data

[0506] Data processing and calculation: Analysis of emotional data

[0507] Output: User's emotional state

[0508] Step 4:

[0509] Quiz Notifications and Adjustments

[0510] The server adjusts the quiz content and notification timing based on the emotion data. For example, if the server determines that the user is "tired," it can lower the difficulty of the questions or postpone the notification. The server sends a push notification to the user's device when the quiz is ready. It also sends a message saying, "It's time for a review quiz!"

[0511] Input: User's emotional state, prepared quiz

[0512] Data processing and calculation: Adjustment of quiz content and notification timing

[0513] Output: Adjusted quiz and notifications

[0514] Step 5:

[0515] Quiz and feedback

[0516] The user confirms the quiz notification and starts the quiz. The device displays the quiz screen, and the user answers the questions. The answers are sent from the device to the server, which evaluates them. Based on the evaluation, personalized feedback is generated; for example, if the user answers correctly, a message such as "Your memory is firmly established" is sent to the user.

[0517] Input: User's quiz answer

[0518] Data processing and calculation: Evaluation of quiz answers, generation of feedback

[0519] Output: Feedback message

[0520] By clarifying the specific operations and inputs / outputs, the overall flow of the system becomes easier to understand and implement. The above step-by-step process allows users to have a more personalized and effective learning experience.

[0521] 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.

[0522] 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.

[0523] 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.

[0524] [Second embodiment]

[0525] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0526] 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.

[0527] 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).

[0528] 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.

[0529] 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.

[0530] 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).

[0531] 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.

[0532] 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.

[0533] 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.

[0534] 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.

[0535] 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.

[0536] 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."

[0537] This invention is a system that generates and notifies a user of a quiz after a certain period of time based on when the user finishes reading an e-book, evaluates the answers, and provides feedback. This system operates based on the roles of the server, terminal, and user.

[0538] Program processing explanation

[0539] 1. User registration and reading record

[0540] The user opens an e-book app on their device.

[0541] Users create an account and enter basic information.

[0542] The server stores user account information in a database.

[0543] When a user selects an e-book and starts reading, the device records and transmits the reading start time.

[0544] The server initiates the reading session and tracks its progress.

[0545] 2. Reading Completion and Quiz Generation

[0546] The user finishes reading the e-book.

[0547] The device records and transmits the reading time.

[0548] The server receives the read completion information and stores it in a database.

[0549] The server generates and prepares quizzes based on a specific period after completion of reading (2 days, 14 days, 60 days).

[0550] Analyze the contents of e-books, extract important points, and generate quizzes.

[0551] 3. Quiz Notifications

[0552] When the server reaches the quiz timing, it sends a notification to the device.

[0553] A push notification will be sent to the user's device containing a message that the quiz is ready and a link.

[0554] 4. Quiz

[0555] The user confirms the notification and starts the quiz.

[0556] The terminal displays a quiz screen and the user inputs an answer.

[0557] The quizzes are presented in multiple choice or free-form format, making them fun to play like a game.

[0558] 5. Recording and feedback of results

[0559] The terminal transmits the user's answers to the quiz to the server.

[0560] The server evaluates the answers and records them in a database.

[0561] Based on the evaluation results, feedback is provided to the user. For example, if the accuracy rate is high, a positive message such as "Your memory is firmly established" is sent.

[0562] Specific examples

[0563] Example of a user selecting the e-book "Study Guide" and starting to read

[0564] 1. The user selects an e-book

[0565] I choose the e-book "Study Guide" and start reading.

[0566] The device records the reading start time (e.g., 10:00 on October 1, 2023) and sends it to the server.

[0567] The server starts the reading session and stores the progress in a database.

[0568] 2. The user finishes reading the book

[0569] The user completes the Study Guide.

[0570] The device records the time of completion of reading (e.g., 18:00 on October 2, 2023) and sends it to the server.

[0571] The server receives the reading completion information and generates and schedules the quiz.

[0572] The quiz timings will be set for 2 days (October 4th), 14 days (October 16th), and 60 days (December 1st) after the reading is completed.

[0573] Generative AI analyzes the contents of the book and creates quiz questions.

[0574] 3. Quiz Notification and Implementation

[0575] When the time comes for the quiz, the server will send a notification.

[0576] Example: On October 4th, a push notification will be sent saying "It's time for a review quiz!"

[0577] The user confirms the notification and starts the quiz screen.

[0578] The terminal displays a quiz screen and the user inputs an answer.

[0579] 4. Evaluation results and feedback

[0580] The user answers the quiz, and the terminal transmits the answer to the server.

[0581] The server evaluates the answer and gives an 80% correct answer rate.

[0582] The server generates feedback and sends the message "Great! Your memory is firmly established" to the device.

[0583] The terminal displays a feedback message to the user.

[0584] This invention provides a system that effectively solidifies the contents of e-books into memory through the timing and content of quiz notifications, as well as a mechanism for evaluation and feedback, aiming to make learning more enjoyable and efficient for users.

[0585] The processing flow will be explained below.

[0586] Step 1:

[0587] The user downloads an e-book app on their device and creates an account.

[0588] The user enters their name, email address, and password.

[0589] The device sends the input information to the server, which then stores the account in a database.

[0590] Step 2:

[0591] The user selects an e-book.

[0592] The device displays a list of e-books, and the user selects the book they want to read.

[0593] The user selects the Study Guide and begins reading.

[0594] The device records the reading start time and sends it to the server.

[0595] The server initiates the reading session and stores it in a database.

[0596] Step 3:

[0597] The user finishes reading the e-book.

[0598] When the user finishes reading the last page, the device records the time it took to finish reading.

[0599] The device sends the reading time to the server, which stores it in a database.

[0600] Step 4:

[0601] The server sets the timing for generating the quiz based on the reading completion information.

[0602] The server calculates the timing of 2 days (48 hours), 14 days, and 60 days after the end of reading and sets the schedule for generating the quiz.

[0603] Step 5:

[0604] The server uses generated AI to analyze the contents of the book that has been read.

[0605] Generative AI extracts key points from text and converts them into quizzes.

[0606] Quizzes are created in multiple choice or free-form format.

[0607] Step 6:

[0608] When the quiz timing is reached, the server will send a push notification to the device.

[0609] Example: On the second day after finishing reading, you will receive a notification saying "It's time for a review quiz."

[0610] Step 7:

[0611] The user confirms the notification and starts the quiz.

[0612] The user clicks the link in the notification message, and the device displays the quiz screen.

[0613] The user answers the quiz.

[0614] Step 8:

[0615] The terminal sends the user's answer to the server.

[0616] The server receives the response data and evaluates the accuracy rate, etc.

[0617] The evaluation results are recorded in a database.

[0618] Step 9:

[0619] The server generates feedback based on the evaluation results.

[0620] If the score is high, create a positive message such as "Great! Your memory is well-established."

[0621] If the score is low, feedback is generated that includes study advice such as "Please review the following points."

[0622] Step 10:

[0623] The server sends a feedback message to the terminal.

[0624] The device displays the feedback to the user.

[0625] Example 1

[0626] 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."

[0627] Conventional e-book learning systems lack mechanisms for helping users effectively solidify the contents of e-books in their memories, making it difficult to fully utilize the learning benefits after reading. Specifically, it is difficult to review the content at an appropriate time after reading, or to extract important points and turn them into quizzes, making it difficult to maintain users' motivation to learn.

[0628] 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.

[0629] In this invention, the server includes a means for detecting when the user has finished reading the e-book, a means for generating a quiz based on a specific period after the user has finished reading (2 days, 14 days, or 60 days), and a means for sending prompts to the generation AI model, analyzing the contents of the e-book, and extracting important points. This allows for the provision of quizzes at appropriate times and for reviewing the contents.

[0630] A "user" is an individual who uses the system to read an electronic book.

[0631] A "terminal" is an electronic device that a user uses to read an e-book, such as a smartphone, tablet, or e-book reader.

[0632] A "server" is a central device that manages the operation of the entire system and communicates with users and terminals.

[0633] The "reading record" is data on the time when the user started reading an electronic book and the time when the user finished reading it.

[0634] A "reading session" is a record of a single e-book reading activity, including the start and end times of that activity.

[0635] A "database" is a storage system connected to a server for storing user account information and reading records.

[0636] A "generative AI model" is an artificial intelligence model that analyzes the contents of e-books and generates quizzes.

[0637] A "prompt" is an instruction given to a generative AI model, which serves as a guide for generating a quiz.

[0638] A "quiz" is a question-based test based on the content of an e-book, and is provided for the purpose of measuring the user's level of comprehension of the content.

[0639] A "push notification" is a real-time message sent from a server to a user device. An example is a quiz notification.

[0640] "Evaluation" refers to analyzing the percentage of correct answers and the level of comprehension of the content based on the answers entered by the user to the quiz.

[0641] "Feedback" refers to results reports and advice provided based on the user's answers to the quiz.

[0642] This invention is a system that generates and notifies a user of a quiz after a certain period of time based on when the user finishes reading an e-book, evaluates the answers, and provides feedback. This system operates based on the roles of the server, terminal, and user.

[0643] The server is the central device that manages the operation of the entire system and communicates with users and their devices. The server notifies the users of the generated quizzes, collects and evaluates the answers to the quizzes, and provides feedback based on the evaluation results.

[0644] A device is an electronic device used by a user to read e-books, such as a smartphone, tablet, or e-reader. The device records the user's start and end times and sends them to a server. It also has the ability to receive push notifications.

[0645] A user is an individual who uses the system to read an e-book and answer the subsequent quiz. The user creates an account, selects an e-book, and begins reading. After finishing the reading, the user answers the quiz sent by the server and receives feedback based on the results.

[0646] Specifically, the user first opens an e-book on their device, creates an account, and enters basic information. The device then sends this information to the server, which then stores it in a database. When the user selects an e-book and begins reading, the device records the start time of reading and sends it to the server.

[0647] When a user finishes reading an e-book, the device records the reading time and sends it to the server. The server stores the received information in a database and generates quizzes based on specific time periods (2 days, 14 days, or 60 days later). The AI ​​model then sends prompts to analyze the e-book's content, extracting key points and generating appropriate quizzes.

[0648] As a specific example, consider the case where a user selects the e-book "Study Guide" and begins reading. If the reading start time is, for example, 10:00 on October 1, 2023, the device records this information and sends it to the server. Later, when the user finishes reading at 18:00 on October 2, 2023, the device records the information again and sends it to the server. Based on this reading completion information, the server sets the timing of three quiz notifications for October 4, October 16, and December 1.

[0649] The server generates a quiz by sending the following prompt to the generative AI model: "For a user who has finished reading the e-book 'Study Guide', after two days, please generate four multiple-choice quiz questions based on the following content: The key points of Chapter 1 are..."

[0650] When it's time for a quiz notification, the server sends an appropriate push notification to the device. For example, on October 4th, a message saying "It's time for a review quiz!" is sent, and the user confirms the notification and opens the quiz screen on the device. The user answers the quiz and the results are sent from the device to the server. The server evaluates the results, generates a feedback message, and sends it to the device. The device displays the feedback to the user, allowing them to confirm the results.

[0651] Through the quizzes and feedback provided by this system, users can effectively solidify the contents of e-books into their memories.

[0652] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0653] Step 1: User registration and reading log

[0654] A user opens an e-book app on their device. First, the user creates an account and enters basic information such as their name and email address. The device sends this information to the server, which stores it in a database. Next, the user selects an e-book and begins reading. The device records the reading start time and sends the reading start information to the server. The server starts a reading session based on this information and stores it in a database. It also tracks the progress in real time. The input data is the user's basic information and reading start time, and the output data is the reading session information stored in the database.

[0655] Step 2: Reading and creating a quiz

[0656] The user finishes reading an e-book. The device records the completion time and sends that information to the server. The server stores the received completion information in a database. Next, it schedules quizzes to be given two days, 14 days, and 60 days after completion. The server sends prompts to the generative AI model, which analyzes the content of the e-book, extracts key points, and generates a quiz. For example, it creates a quiz question such as, "What are the key points of Chapter 1?" The input data is the reading time and the content of the e-book, and the output data is the generated quiz.

[0657] Step 3: Quiz Notification

[0658] The quiz notification timing arrives. Based on the configured timing, the server sends a push notification to the user device that the quiz is ready. The notification includes the message "It's time for a review quiz!" and a link to the quiz screen. This allows the user to start the quiz smoothly. The input data is the quiz notification schedule, and the output data is the sent notification message.

[0659] Step 4: Take the quiz

[0660] The user confirms the notification and starts the quiz. The device displays the quiz screen, and the user enters their answers. The quiz questions are presented in multiple choice or free description format, and the user answers according to the format. The input data are the quiz questions and the user's answers, and the output data are the user's answers.

[0661] Step 5: Recording and feedback

[0662] Once the quiz is complete, the device sends the user's answers to the server. The server evaluates the received answers and analyzes the accuracy rate and comprehension level. Based on this evaluation result, a feedback message is generated, such as "Excellent! Your memory is firmly established." The server sends this feedback message to the device, which then displays it to the user. The input data is the user's answers, and the output data is the feedback message.

[0663] (Application example 1)

[0664] 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."

[0665] Simply viewing conventional e-books or learning content is often insufficient to retain what has been learned. Another issue is the lack of appropriate review methods that allow users to review what they have viewed later and improve their learning effectiveness. Therefore, a support system is needed to effectively review and retain what has been viewed.

[0666] 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.

[0667] In this invention, the server includes a means for detecting when a user has finished viewing an e-book or learning content, a means for generating a quiz based on a specific period (2 days, 14 days, or 60 days) after the completion of the reading or viewing, a means for notifying the generated quiz to the user terminal, a means for collecting and evaluating the quiz answers, and a means for providing feedback to the user based on the evaluation results, thereby effectively helping the user to solidify the content they have viewed.

[0668] "User" refers to an individual who uses the system to read e-books or view learning content.

[0669] An "e-book" is a book that is distributed in digital form and is read using an electronic device.

[0670] "Learning content" refers to educational videos and materials designed to improve knowledge and skills.

[0671] "Viewing" refers to the act of a user reading an e-book or viewing learning content.

[0672] The "means for detecting timing" refers to a technique or device for identifying the point in time at which a user has finished viewing an e-book and learning content.

[0673] A "specific period" refers to a predetermined period, such as 2 days, 14 days, or 60 days after viewing.

[0674] "Quiz generating means" refers to a technique or device for creating a quiz based on the content viewed.

[0675] A "user terminal" is an electronic device used by a user, such as a computer, smartphone, or tablet.

[0676] The "notification means" refers to a technique or device for notifying the user terminal of the generated quiz.

[0677] The "means for collecting answer results" refers to a technique or device for obtaining the results of users' answers to the quiz.

[0678] "Means for evaluation" refers to technology or equipment for analyzing collected answers and measuring the user's level of understanding.

[0679] The "means for providing feedback" refers to a technology or device for sending advice or comments to the user based on the evaluation results.

[0680] In order to implement the present invention, it is necessary to construct the following system.

[0681] First, a user uses a device (such as a smartphone or tablet) to view e-books and learning content. After installing a dedicated application on the device, the user registers and begins viewing. When the user starts viewing, the device records the start time and sends it to the server.

[0682] Platform configuration:

[0683] Hardware: Smartphones, tablets, computers, head-mounted displays (HMDs)

[0684] Software: Dedicated learning application, Flask (web application framework), SQLAlchemy (database management), OpenAI GPT-3 (quiz generation), Firebase Cloud Messaging (notification service)

[0685] The server tracks the user's progress from the start of the session, records the completion time when the user finishes the session, and then generates quizzes based on specific time periods (2 days, 14 days, 60 days).

[0686] To generate the quiz, the server analyzes the key points of the viewed content and creates the quiz using a generative AI model (e.g., OpenAI GPT-3). The generation process uses the following prompt sentence as input:

[0687] Example prompt sentence:

[0688] Generate a quiz with multiple choice questions based on the content of the documentary "Miracles of Earth". Include questions that test the viewer's understanding of key concepts discussed in the documentary.

[0689] The generated quiz is notified to the user's device using Firebase Cloud Messaging. The user receives the notification and answers the quiz. The user's answers are sent from the device to the server, which evaluates them. Based on the evaluation results, feedback is generated and sent to the user's device. This feedback allows the user to understand their level of understanding and obtain guidelines for further study.

[0690] For example, after a user finishes watching the science documentary "Miracles of the Earth," they are notified of different quizzes two days, 14 days, and 60 days later. Each quiz is based on the content viewed and is designed to help users retain their knowledge. Depending on the evaluation results, the user is given feedback such as "Excellent! Your memory is firmly established."

[0691] In this way, the present invention serves as a support system that effectively helps users to solidify their memory of what they have viewed and improves their learning effectiveness.

[0692] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0693] Step 1:

[0694] A dedicated application is installed on the device (such as a smartphone or tablet) on which the user will view the e-books and learning content.

[0695] Input: User basic information, installed apps.

[0696] Output: Initial setup completed, user account created.

[0697] Specific behavior: The user creates an account in the launched application and enters basic information.

[0698] Step 2:

[0699] Users view e-books and learning content.

[0700] Enter: Select the content you want to watch.

[0701] Output: Recording of viewing start time, viewing status tracking.

[0702] Specific operation: When a user starts watching, the device records the start time of watching and sends it to the server.

[0703] Step 3:

[0704] When viewing is finished, the time of completion of reading or viewing is recorded.

[0705] Input: End View action.

[0706] Output: Record of viewing end time.

[0707] Specific operation: When the user finishes watching, the device records the end time and sends it to the server.

[0708] Step 4:

[0709] Generate quizzes based on a specific time period (2 days, 14 days, 60 days).

[0710] Input: End time of viewing, content viewed.

[0711] Output: Generate a quiz.

[0712] Specific operation: The server sets the timing for generating the quiz based on the end time of viewing, and generates a quiz based on the viewing content using a generative AI model (OpenAI GPT-3).

[0713] Step 5:

[0714] The generated quiz is notified to the user terminal.

[0715] Input: The generated quiz.

[0716] Output: Push quiz notification.

[0717] Specific operation: The server uses Firebase Cloud Messaging to send a quiz notification to the user's device.

[0718] Step 6:

[0719] The user answers the quiz.

[0720] Input: Notified quiz.

[0721] Output: Quiz answer results.

[0722] Specific operation: The user receives a quiz notification, opens the quiz screen, enters the answer, and the device sends the answer to the server.

[0723] Step 7:

[0724] The server evaluates the quiz answers.

[0725] Input: The user's quiz answer result.

[0726] Output: Producing the evaluation results.

[0727] Specific operation: The server compiles the quiz answer results and evaluates the user's accuracy rate, etc.

[0728] Step 8:

[0729] Based on the evaluation results, feedback is provided to the user.

[0730] Input: Evaluation result.

[0731] Output: Generate and send feedback messages.

[0732] Specific operation: Based on the evaluation result, the server generates a feedback message and sends it to the user terminal.

[0733] In this way, the operation of the entire system is explained in detail at each step, linking the user's viewing experience to improved learning outcomes.

[0734] 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.

[0735] This invention combines a system that detects when a user has finished reading an e-book, generates and notifies a user of a quiz after a specific period of time, evaluates the results of the quiz, and provides feedback, with an emotion engine that recognizes the user's emotions. This system operates based on the roles of the server, the terminal, and the user.

[0736] Program processing explanation

[0737] 1. User registration and reading record

[0738] The user opens the e-book app on their device and creates an account.

[0739] The user enters their name, email address, and password, and the device sends the information to the server.

[0740] The server stores the account information in a database.

[0741] When a user selects an electronic book and starts reading, the terminal records the reading start time and transmits it to the server.

[0742] The server initiates the reading session and tracks its progress.

[0743] 2. Reading Completion and Quiz Generation

[0744] The user finishes reading the e-book.

[0745] The device records the reading time and sends it to the server.

[0746] The server receives the read completion information and stores it in a database.

[0747] The server generates and prepares quizzes based on specific time periods after completion of reading (2 days, 14 days, 60 days).

[0748] Analyze the contents of e-books, extract important points, and generate quizzes.

[0749] 3. Emotional engine for recognizing user emotions

[0750] When a user starts a quiz, the emotion engine kicks in.

[0751] The device's camera and microphone are used to analyze the user's facial expressions and voice to determine their emotional state.

[0752] The emotion engine sends the user's emotion data to the server.

[0753] 4. Quiz Notifications and Adjustments

[0754] The server adjusts the content and timing of the quiz based on the emotional data.

[0755] For example, if it is determined that the user is tired, it may present questions with lower difficulty or postpone notifications.

[0756] When the server is ready to quiz, it will send a push notification to the user's device. Example: "Time for a review quiz!"

[0757] 5. Quiz

[0758] The user confirms the notification and starts the quiz.

[0759] The terminal displays a quiz screen and the user inputs an answer.

[0760] The quizzes are presented in multiple choice or free-form format, with the appropriate content selected based on the analysis results of the emotion engine.

[0761] 6. Recording and feedback of results

[0762] The terminal transmits the user's answers to the quiz to the server.

[0763] The server evaluates the answers and records them in a database.

[0764] Based on the evaluation results, feedback is provided to the user. For example, if the accuracy rate is high, a positive message such as "Your memory is firmly established" is sent.

[0765] Consider the results of the emotion engine and adjust the tone and content of your feedback as needed.

[0766] Specific examples

[0767] Example of a user selecting the e-book "Study Guide" and starting to read

[0768] 1. The user selects an e-book

[0769] The user selects the e-book "Study Guide" and begins reading.

[0770] The device records the reading start time (e.g., 10:00 on October 1, 2023) and sends it to the server.

[0771] The server starts the reading session and stores the progress in a database.

[0772] 2. The user finishes reading the book

[0773] The user completes the Study Guide.

[0774] The device records the time of completion of reading (e.g., 18:00 on October 2, 2023) and sends it to the server.

[0775] The server receives the reading completion information and generates and schedules the quiz.

[0776] The quiz timings will be set for 2 days (October 4th), 14 days (October 16th), and 60 days (December 1st) after the reading is completed.

[0777] Generative AI analyzes the contents of the book and creates quiz questions.

[0778] 3. Emotional Engine Activation

[0779] When a user starts a quiz, the device's camera and microphone collect and analyze the user's emotions (e.g., the emotion engine determines that the user is relaxed).

[0780] The emotion engine sends the results to the server.

[0781] 4. Quiz Notifications and Coordination

[0782] When it's time for a quiz, the server takes into account the results of the emotion engine and adjusts the notification message.

[0783] Example: On October 4th, a push notification will be sent saying "It's time for a review quiz!"

[0784] 5. Conducting a quiz

[0785] The user confirms the notification and starts the quiz screen.

[0786] The terminal displays a quiz screen and the user inputs an answer.

[0787] The difficulty of the quiz is adjusted to suit the user's emotional state.

[0788] 6. Evaluation results and feedback

[0789] The user answers the quiz, and the terminal transmits the answer to the server.

[0790] The server evaluates the answer and gives an 80% correct answer rate.

[0791] The server generates feedback and, based on the results of the emotion engine, sends a message to the device saying, "Great! Your memory is well-established. Keep up the great work!"

[0792] The terminal displays a feedback message to the user.

[0793] This invention aims to provide more effective and personalized learning by taking into account the user's emotional state. By combining it with an emotion engine, it is possible to review at the most appropriate time and with the most appropriate content for the user, significantly improving the efficiency and enjoyment of learning.

[0794] The processing flow will be explained below.

[0795] Step 1:

[0796] The user downloads an e-book app on their device and creates an account.

[0797] The user enters their name, email address, and password.

[0798] The device sends the input information to the server, which then stores the account in a database.

[0799] Step 2:

[0800] The user selects an e-book.

[0801] The device displays a list of e-books, and the user selects the book they want to read.

[0802] The user selects the Study Guide and begins reading.

[0803] The device records the reading start time and sends it to the server.

[0804] The server initiates the reading session and stores it in a database.

[0805] Step 3:

[0806] The user finishes reading the e-book.

[0807] When the user finishes reading the last page, the device records the time it took to finish reading.

[0808] The device sends the reading time to the server, which stores it in a database.

[0809] Step 4:

[0810] The server sets the timing for generating the quiz based on the reading completion information.

[0811] The server calculates the timing of 2 days (48 hours), 14 days, and 60 days after the end of reading and sets the schedule for generating the quiz.

[0812] Step 5:

[0813] The server uses generated AI to analyze the contents of the book that has been read.

[0814] Generative AI extracts key points from text and creates quizzes.

[0815] The quiz will consist of multiple choice and free-form questions.

[0816] Step 6:

[0817] When the quiz timing is reached, the server will send a push notification to the device.

[0818] For example, you will receive a notification saying, "Take the quiz two days after you finish reading."

[0819] Step 7:

[0820] The user confirms the notification and starts the quiz.

[0821] The user clicks the link in the notification message, and the device displays the quiz screen.

[0822] The user answers the quiz.

[0823] Step 8:

[0824] The terminal transmits the user's response data to the server.

[0825] The server evaluates the answers and calculates the accuracy rate, etc.

[0826] The evaluation results are recorded in the user's database.

[0827] Step 9:

[0828] When a user starts a quiz, the emotion engine kicks in.

[0829] The device's camera and microphone are used to analyze the user's facial expressions and voice to determine their emotional state.

[0830] The emotion engine sends the user's emotion data to the server.

[0831] Step 10:

[0832] The server adjusts the quiz content and the timing of the next notification based on the emotional data.

[0833] For example, if it is determined that the user is tired, it may present questions with lower difficulty or postpone notifications.

[0834] When the server is ready for the quiz, it will send the following push notification to the user's device:

[0835] Step 11:

[0836] The server generates feedback based on the evaluation results.

[0837] If the score is high, create a positive message such as "Great! Your memory is well-established."

[0838] If the score is low, feedback is generated that includes study advice such as "Please review the following points."

[0839] Step 12:

[0840] The server sends a feedback message to the terminal.

[0841] The device displays feedback to the user.

[0842] Example 2

[0843] 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."

[0844] In conventional learning systems, there are limited ways for users to effectively check their understanding of an e-book after they have finished reading it, and the timing for reviewing the learning content is fixed, making it difficult to maximize the learning effect of each individual user. Furthermore, conventional systems do not take into account the user's emotional state, which creates the risk of the learning load becoming too high and lowering user motivation.

[0845] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for detecting the timing when the user finishes reading an e-book, means for generating a quiz based on a specific period after the completion of reading (2 days, 14 days, or 60 days), means for notifying the user terminal of the generated quiz, means for collecting and evaluating quiz answer results, means for providing feedback to the user based on the evaluation results, emotion recognition means for recognizing the user's emotion, and means for adjusting the quiz content and notification timing based on the emotion recognition data. This enables review at the optimal timing and content according to each user's emotional state, thereby improving learning effectiveness and motivation.

[0846] "User" refers to an individual who operates this system to read e-books and answer quizzes.

[0847] "Device" refers to any computer system used by a user that can run an e-book app, including, for example, a smartphone, tablet, or PC.

[0848] "Server" refers to a computer system that receives data from the terminal, processes it, and generates appropriate feedback and quizzes.

[0849] The "timing of completion of reading" refers to the time when the user has finished reading all the pages of the electronic book.

[0850] "Quiz generation" refers to the process of analyzing the content of an e-book and creating questions based on a specific period after reading.

[0851] "Notification" refers to the process of sending a push notification or alert to the user's device when the generated quiz is ready.

[0852] "Answer result" refers to the answer entered by the user to the quiz.

[0853] "Evaluation" refers to the process of analyzing the user's answers and measuring the percentage of correct answers and learning progress.

[0854] "Feedback" refers to specific advice or messages provided to users based on the evaluation results to improve their learning effectiveness.

[0855] "Emotion recognition" refers to the process of analyzing a user's facial expressions and voice data collected using the device's camera and microphone to determine the user's emotional state.

[0856] "Emotion recognition data" refers to data obtained through an emotion recognition process that indicates a user's emotional state.

[0857] "Adjustment" refers to the process of changing the content of the quiz or the timing of notifications based on emotion recognition data.

[0858] This invention is a system that detects when a user has finished reading an e-book, generates and notifies a user of a quiz after a specific period of time, evaluates the results of the quiz and provides feedback, and combines it with an emotion recognition engine that recognizes the user's emotions. This system operates based on the roles of the server, terminal, and user.

[0859] Specific hardware includes devices such as smartphones, tablets, and PCs. Servers are built as cloud servers or dedicated servers. Software includes e-book apps, emotion recognition engines, generative AI models, etc.

[0860] 1. User registration and reading record

[0861] A user opens an e-book app and creates an account. Specifically, the user enters their name, email address, and password, and the device sends that information to the server. The server saves the account information in a database and notifies the user when the account is complete. When the user selects an e-book and starts reading, the device records the reading start time and sends it to the server. The server starts the reading session and saves the progress in a database.

[0862] 2. Reading Completion and Quiz Generation

[0863] When a user finishes reading an e-book, the device records the time the user has finished reading and sends it to the server. The server then stores this information in a database and generates a quiz for a specific period of time after the user has finished reading (for example, 2 days, 14 days, or 60 days later). The generative AI model analyzes the content of the e-book, extracts key points, and creates the quiz.

[0864] 3. Emotional engine for recognizing user emotions

[0865] When a user receives a quiz notification and starts the quiz, the device's camera and microphone collect the user's facial expressions and voice data, which are then analyzed by an emotion recognition engine. The emotion recognition engine determines the user's emotional state (e.g., relaxed, tired) and sends the data to the server.

[0866] 4. Quiz Notifications and Adjustments

[0867] The server adjusts the content of the quiz and the timing of notifications based on emotion recognition data. For example, if the server determines that the user is tired, it will select less difficult questions or postpone notifications. When the quiz is ready, the server sends a push notification to the user's device. For example, it could send a message saying, "It's time for a review quiz!"

[0868] 5. Quiz

[0869] The user confirms the notification and starts the quiz. The device displays the quiz screen and the user enters their answers. Questions are presented in multiple choice or free-form format, and the appropriate content is selected based on the analysis results of the emotion recognition engine.

[0870] 6. Recording and feedback of results

[0871] The user answers the quiz, and the device sends the results to the server. The server evaluates the answer (for example, "80% correct") and records it in a database. Based on the evaluation results, the server provides feedback to the user. For example, if the user answers correctly, the server may generate a message such as "Great! Your memory is well-established. Keep up the good work!", adjusting the tone and content of the feedback based on the results of the emotion recognition engine. The feedback message is sent to the user's device, where it is displayed to the user.

[0872] Example prompt sentence:

[0873] "Detect when a user has finished reading a specific e-book and generate a quiz based on a specific period after reading. Also, recognize the user's emotional state and adjust the optimal quiz content and notification timing."

[0874] The above system provides personalized learning that takes into account the user's emotional state, and is expected to significantly improve the efficiency and enjoyment of learning.

[0875] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0876] Step 1:

[0877] Create an account

[0878] A user opens an e-book app and enters their name, email address, and password.

[0879] Enter your name, email address, and password.

[0880] Output: The user's account information.

[0881] The terminal sends the input information to the server.

[0882] The server saves the account information to the database, performs a database update operation, and logs the completion of the save.

[0883] Step 2:

[0884] Select an e-book and start reading

[0885] The user selects an e-book in the app (e.g., "Study Guide").

[0886] Input: Information about the selected e-book.

[0887] Output: Triggers the reading start event.

[0888] The terminal records the user's reading start time and sends that information to the server.

[0889] The server starts a reading session and saves the progress to a database, writes the start time to the database, and generates a session ID.

[0890] Step 3:

[0891] Record reading time

[0892] The user reads the e-book to the end.

[0893] Input: Information on the page you have read.

[0894] Output: Triggers a read event.

[0895] The device records the time it takes to finish reading and sends that information to the server.

[0896] The server saves the completion information to a database, records the completion time, and updates the relevant session data.

[0897] Step 4:

[0898] Quiz Generation

[0899] The server sets a specific period after reading (e.g., 2 days, 14 days, or 60 days).

[0900] Input: Reading information, specific period.

[0901] Output:Quiz schedule.

[0902] The server uses a generative AI model to analyze the contents of the e-book, extract key points, and create quiz questions.

[0903] Input: E-book text data.

[0904] Output: A set of quiz questions.

[0905] The server stores the generated quiz in a database.

[0906] Step 5:

[0907] Quiz Notifications

[0908] When the server is ready for the quiz based on the specified quiz notification timing, it sends a push notification to the user terminal.

[0909] Input: Quiz schedule, user's device information.

[0910] Output: Push notification (e.g. "Time for a review quiz!").

[0911] The server records the notification content and timing and sets retransmission logic.

[0912] Step 6:

[0913] Emotion recognition and quiz start

[0914] The user receives the quiz notification and starts the quiz.

[0915] Input: Acknowledgement of notification receipt.

[0916] Output: Quiz screen display.

[0917] The device's camera and microphone collect the user's facial expressions and voice data, which is then analyzed by an emotion recognition engine.

[0918] Input: User's facial expressions and voice data.

[0919] Output: Emotion recognition result (e.g. "Relaxed" or "Tired").

[0920] The emotion recognition engine sends the analysis results to the server.

[0921] Step 7:

[0922] Adjustment and implementation of quiz content

[0923] The server adjusts the content and difficulty of the quiz based on the emotion recognition data.

[0924] Input: Emotion recognition data, generated quiz questions.

[0925] Output: The adjusted quiz questions.

[0926] The terminal displays the adjusted quiz questions and the user inputs the answers.

[0927] Input: The user's answer.

[0928] Output: Response data.

[0929] Step 8:

[0930] Submitting and evaluating answer results

[0931] The terminal transmits the user's answer results to the server.

[0932] Input: Response data.

[0933] Output: Sending data to the server.

[0934] The server evaluates the answer results and stores the evaluation results in a database.

[0935] Input: Response data.

[0936] Output: Evaluation results such as accuracy rate.

[0937] Based on the evaluation results, the server generates feedback.

[0938] Step 9:

[0939] Providing Feedback

[0940] The server provides feedback to the user based on the evaluation results.

[0941] Input: Evaluation results, emotion recognition data.

[0942] Output: A feedback message (e.g., "Great! Your memory is solid. Keep it up!").

[0943] The terminal displays a feedback message to the user.

[0944] (Application example 2)

[0945] 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."

[0946] Conventional learning systems using e-books provide quizzes uniformly without considering the user's emotions, which means that they are unable to provide optimal review timing or difficulty for each individual user. Furthermore, to maximize learning efficiency, it is important to adjust the timing and content according to the user's emotional state, but no such system has existed. Furthermore, when using e-payment services, users have had the problem of not receiving appropriate feedback after selecting a product.

[0947] 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.

[0948] In this invention, the server includes a means for detecting when a user has finished reading an e-book, a means for generating a quiz based on a specific period of time since the user finished reading, and a means for recognizing the user's emotions using an emotion engine. This makes it possible to adjust the content of the quiz and the timing of notifications according to the user's emotional state and provide personalized feedback. Furthermore, emotion recognition can be utilized when using electronic payment services, providing appropriate feedback and recommendations to the user to increase their motivation to purchase.

[0949] The "means for detecting when the user has finished reading the e-book" is a mechanism that automatically detects when the user has read to the last page of the e-book and records that point in time.

[0950] The "means for generating quizzes" is a function that analyzes the contents of an e-book and creates multiple questions based on a specific algorithm.

[0951] "Means for notifying the user terminal" refers to a method for sending quizzes and other information to the user's device as alerts or push notifications.

[0952] "Means for collecting and evaluating quiz answer results" refers to a system for collecting data on users' answers to quizzes and analyzing and evaluating their accuracy and completeness.

[0953] The "means for providing feedback" is a system that returns appropriate advice and comments to the user based on the evaluation results of the quiz.

[0954] The "means for recognizing a user's emotions using an emotion engine" is a device equipped with an algorithm that analyzes a user's facial expressions, voice, and other biometric data to determine their psychological state.

[0955] The "means for adjusting the quiz content and notification timing according to the user's emotions" is a mechanism for optimizing the difficulty of the quiz and the timing of sending notifications based on the user's current emotional state.

[0956] This invention is a system that detects when a user has finished reading an e-book, generates a quiz after a specific period of time has passed, notifies the user of the quiz, evaluates the answers, and provides feedback.The system is characterized by using an emotion engine to recognize the user's emotions and adjusts the quiz content and notification timing accordingly.

[0957] System Configuration

[0958] The system consists of the following major hardware and software components:

[0959] Server: Contains the database, quiz generation algorithm, and emotion engine.

[0960] User device: A device such as a smartphone that is equipped with a camera and microphone.

[0961] Database: Stores user reading records, emotion data, and quiz results.

[0962] Emotion engine: A software module that recognizes emotions by analyzing the user's facial expressions and voice.

[0963] Quiz generation module: Analyzes the content of the e-book and generates quizzes based on key points.

[0964] System Operation

[0965] 1. User registration and reading record

[0966] Users create an account using a smartphone app, select an e-book, and begin reading. The device records the start time and sends it to the server, which then starts the reading session and stores the progress in a database.

[0967] 2. Reading Completion and Quiz Generation

[0968] When a user finishes reading an e-book, the device records the reading time and sends it to the server. The server receives the reading completion information and stores it in a database. A quiz is then generated and prepared based on a specific period after the reading (2 days, 14 days, or 60 days later). A generative AI model is used to analyze the content of the e-book, extract key points, and generate the quiz.

[0969] 3. Emotional engine for recognizing user emotions

[0970] When a user starts a quiz, the device's camera and microphone are used to recognize the user's emotions. The emotion engine analyzes the user's emotional data and sends this data to the server.

[0971] 4. Quiz Notifications and Adjustments

[0972] The server adjusts the quiz content and notification timing based on the emotion data. For example, if it determines that the user is tired, it can present easier questions or postpone notifications. When the quiz is ready, the server sends a push notification to the user's device. The notification reads, "Time for a review quiz!"

[0973] 5. Quiz and feedback

[0974] The user confirms the notification and begins the quiz. The quiz screen displays questions tailored to the user's emotional state, and the user enters their answers. The answers are sent from the device to the server, which evaluates them and provides feedback. For example, if the user answers correctly, a positive message such as "your memory is firmly established" is sent.

[0975] Examples of specific examples and prompts

[0976] For example, if a user starts reading the e-book "Study Guide" and finishes it, and the emotion engine determines that they are in a "Relaxed" state, the quiz notification will look like this:

[0977] Quiz notification example

[0978] "Time for a review quiz!"

[0979] Prompt Sentence Examples

[0980] Feedback when the user is relaxed:

[0981] Feedback message: "Amazing! I recommend you buy this product."

[0982] This allows for personalized quizzes and feedback that take into account the user's emotional state.

[0983] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0984] Step 1:

[0985] User registration and reading log

[0986] A user creates an account using a smartphone app and enters their name, email address, and password. The device sends this information to the server, which stores the account information in a database. When the user selects an e-book and begins reading, the device records the start time of the reading and sends it to the server. The server starts the reading session and stores the progress in a database.

[0987] Input: User information (name, email address, password) and e-book selection information

[0988] Data processing and calculation: User information verification and storage, recording of reading start time

[0989] Output: User account created, reading session started

[0990] Step 2:

[0991] Reading Completion and Quiz Generation

[0992] When a user finishes reading an e-book, the device records the reading time and sends it to the server. The server receives the reading completion information and stores it in a database. It then generates a quiz based on a specific period after reading (e.g., 2 days, 14 days, or 60 days). A generative AI model is used to analyze the content of the e-book, extract key points, and create a quiz.

[0993] Input: Reading time, e-book content

[0994] Data processing and calculation: saving reading completion information, generating quizzes

[0995] Output:Quiz preparation

[0996] Step 3:

[0997] Recognizing user emotions with an emotion engine

[0998] When a user starts a quiz, the device's camera and microphone capture the user's facial expressions and voice, and send them to the emotion engine, which analyzes them, determines the user's emotional state, and sends the results to the server.

[0999] Input: User's facial expression and voice data

[1000] Data processing and calculation: Analysis of emotional data

[1001] Output: User's emotional state

[1002] Step 4:

[1003] Quiz Notifications and Adjustments

[1004] The server adjusts the quiz content and notification timing based on the emotion data. For example, if the server determines that the user is "tired," it can lower the difficulty of the questions or postpone the notification. The server sends a push notification to the user's device when the quiz is ready. It also sends a message saying, "It's time for a review quiz!"

[1005] Input: User's emotional state, prepared quiz

[1006] Data processing and calculation: Adjustment of quiz content and notification timing

[1007] Output: Adjusted quiz and notifications

[1008] Step 5:

[1009] Quiz and feedback

[1010] The user confirms the quiz notification and starts the quiz. The device displays the quiz screen, and the user answers the questions. The answers are sent from the device to the server, which evaluates them. Based on the evaluation, personalized feedback is generated; for example, if the user answers correctly, a message such as "Your memory is firmly established" is sent to the user.

[1011] Input: User's quiz answer

[1012] Data processing and calculation: Evaluation of quiz answers, generation of feedback

[1013] Output: Feedback message

[1014] By clarifying the specific operations and inputs / outputs, the overall flow of the system becomes easier to understand and implement. The above step-by-step process allows users to have a more personalized and effective learning experience.

[1015] 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.

[1016] 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.

[1017] 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.

[1018] [Third embodiment]

[1019] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1020] 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.

[1021] 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).

[1022] 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.

[1023] 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.

[1024] 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).

[1025] 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.

[1026] 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.

[1027] 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.

[1028] 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.

[1029] 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.

[1030] 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."

[1031] This invention is a system that generates and notifies a user of a quiz after a certain period of time based on when the user finishes reading an e-book, evaluates the answers, and provides feedback. This system operates based on the roles of the server, terminal, and user.

[1032] Program processing explanation

[1033] 1. User registration and reading record

[1034] The user opens an e-book app on their device.

[1035] Users create an account and enter basic information.

[1036] The server stores user account information in a database.

[1037] When a user selects an e-book and starts reading, the device records and transmits the reading start time.

[1038] The server initiates the reading session and tracks its progress.

[1039] 2. Reading Completion and Quiz Generation

[1040] The user finishes reading the e-book.

[1041] The device records and transmits the reading time.

[1042] The server receives the read completion information and stores it in a database.

[1043] The server generates and prepares quizzes based on a specific period after completion of reading (2 days, 14 days, 60 days).

[1044] Analyze the contents of e-books, extract important points, and generate quizzes.

[1045] 3. Quiz Notifications

[1046] When the server reaches the quiz timing, it sends a notification to the device.

[1047] A push notification will be sent to the user's device containing a message that the quiz is ready and a link.

[1048] 4. Quiz

[1049] The user confirms the notification and starts the quiz.

[1050] The terminal displays a quiz screen and the user inputs an answer.

[1051] The quizzes are presented in multiple choice or free-form format, making them fun to play like a game.

[1052] 5. Recording and feedback of results

[1053] The terminal transmits the user's answers to the quiz to the server.

[1054] The server evaluates the answers and records them in a database.

[1055] Based on the evaluation results, feedback is provided to the user. For example, if the accuracy rate is high, a positive message such as "Your memory is firmly established" is sent.

[1056] Specific examples

[1057] Example of a user selecting the e-book "Study Guide" and starting to read

[1058] 1. The user selects an e-book

[1059] I choose the e-book "Study Guide" and start reading.

[1060] The device records the reading start time (e.g., 10:00 on October 1, 2023) and sends it to the server.

[1061] The server starts the reading session and stores the progress in a database.

[1062] 2. The user finishes reading the book

[1063] The user completes the Study Guide.

[1064] The device records the time of completion of reading (e.g., 18:00 on October 2, 2023) and sends it to the server.

[1065] The server receives the reading completion information and generates and schedules the quiz.

[1066] The quiz timings will be set for 2 days (October 4th), 14 days (October 16th), and 60 days (December 1st) after the reading is completed.

[1067] Generative AI analyzes the contents of the book and creates quiz questions.

[1068] 3. Quiz Notification and Implementation

[1069] When the time comes for the quiz, the server will send a notification.

[1070] Example: On October 4th, a push notification will be sent saying "It's time for a review quiz!"

[1071] The user confirms the notification and starts the quiz screen.

[1072] The terminal displays a quiz screen and the user inputs an answer.

[1073] 4. Evaluation results and feedback

[1074] The user answers the quiz, and the terminal transmits the answer to the server.

[1075] The server evaluates the answer and gives an 80% correct answer rate.

[1076] The server generates feedback and sends the message "Great! Your memory is firmly established" to the device.

[1077] The terminal displays a feedback message to the user.

[1078] This invention provides a system that effectively solidifies the contents of e-books into memory through the timing and content of quiz notifications, as well as a mechanism for evaluation and feedback, aiming to make learning more enjoyable and efficient for users.

[1079] The processing flow will be explained below.

[1080] Step 1:

[1081] The user downloads an e-book app on their device and creates an account.

[1082] The user enters their name, email address, and password.

[1083] The device sends the input information to the server, which then stores the account in a database.

[1084] Step 2:

[1085] The user selects an e-book.

[1086] The device displays a list of e-books, and the user selects the book they want to read.

[1087] The user selects the Study Guide and begins reading.

[1088] The device records the reading start time and sends it to the server.

[1089] The server initiates the reading session and stores it in a database.

[1090] Step 3:

[1091] The user finishes reading the e-book.

[1092] When the user finishes reading the last page, the device records the time it took to finish reading.

[1093] The device sends the reading time to the server, which stores it in a database.

[1094] Step 4:

[1095] The server sets the timing for generating the quiz based on the reading completion information.

[1096] The server calculates the timing of 2 days (48 hours), 14 days, and 60 days after the end of reading and sets the schedule for generating the quiz.

[1097] Step 5:

[1098] The server uses generated AI to analyze the contents of the book that has been read.

[1099] Generative AI extracts key points from text and converts them into quizzes.

[1100] Quizzes are created in multiple choice or free-form format.

[1101] Step 6:

[1102] When the quiz timing is reached, the server will send a push notification to the device.

[1103] Example: On the second day after finishing reading, you will receive a notification saying "It's time for a review quiz."

[1104] Step 7:

[1105] The user confirms the notification and starts the quiz.

[1106] The user clicks the link in the notification message, and the device displays the quiz screen.

[1107] The user answers the quiz.

[1108] Step 8:

[1109] The terminal sends the user's answer to the server.

[1110] The server receives the response data and evaluates the accuracy rate, etc.

[1111] The evaluation results are recorded in a database.

[1112] Step 9:

[1113] The server generates feedback based on the evaluation results.

[1114] If the score is high, create a positive message such as "Great! Your memory is well-established."

[1115] If the score is low, feedback is generated that includes study advice such as "Please review the following points."

[1116] Step 10:

[1117] The server sends a feedback message to the terminal.

[1118] The device displays the feedback to the user.

[1119] Example 1

[1120] 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."

[1121] Conventional e-book learning systems lack mechanisms for helping users effectively solidify the contents of e-books in their memories, making it difficult to fully utilize the learning benefits after reading. Specifically, it is difficult to review the content at an appropriate time after reading, or to extract important points and turn them into quizzes, making it difficult to maintain users' motivation to learn.

[1122] 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.

[1123] In this invention, the server includes a means for detecting when the user has finished reading the e-book, a means for generating a quiz based on a specific period after the user has finished reading (2 days, 14 days, or 60 days), and a means for sending prompts to the generation AI model, analyzing the contents of the e-book, and extracting important points. This allows for the provision of quizzes at appropriate times and for reviewing the contents.

[1124] A "user" is an individual who uses the system to read an electronic book.

[1125] A "terminal" is an electronic device that a user uses to read an e-book, such as a smartphone, tablet, or e-book reader.

[1126] A "server" is a central device that manages the operation of the entire system and communicates with users and terminals.

[1127] The "reading record" is data on the time when the user started reading an electronic book and the time when the user finished reading it.

[1128] A "reading session" is a record of a single e-book reading activity, including the start and end times of that activity.

[1129] A "database" is a storage system connected to a server for storing user account information and reading records.

[1130] A "generative AI model" is an artificial intelligence model that analyzes the contents of e-books and generates quizzes.

[1131] A "prompt" is an instruction given to a generative AI model, which serves as a guide for generating a quiz.

[1132] A "quiz" is a question-based test based on the content of an e-book, and is provided for the purpose of measuring the user's level of comprehension of the content.

[1133] A "push notification" is a real-time message sent from a server to a user device. An example is a quiz notification.

[1134] "Evaluation" refers to analyzing the percentage of correct answers and the level of comprehension of the content based on the answers entered by the user to the quiz.

[1135] "Feedback" refers to results reports and advice provided based on the user's answers to the quiz.

[1136] This invention is a system that generates and notifies a user of a quiz after a certain period of time based on when the user finishes reading an e-book, evaluates the answers, and provides feedback. This system operates based on the roles of the server, terminal, and user.

[1137] The server is the central device that manages the operation of the entire system and communicates with users and their devices. The server notifies the users of the generated quizzes, collects and evaluates the answers to the quizzes, and provides feedback based on the evaluation results.

[1138] A device is an electronic device used by a user to read e-books, such as a smartphone, tablet, or e-reader. The device records the user's start and end times and sends them to a server. It also has the ability to receive push notifications.

[1139] A user is an individual who uses the system to read an e-book and answer the subsequent quiz. The user creates an account, selects an e-book, and begins reading. After finishing the reading, the user answers the quiz sent by the server and receives feedback based on the results.

[1140] Specifically, the user first opens an e-book on their device, creates an account, and enters basic information. The device then sends this information to the server, which then stores it in a database. When the user selects an e-book and begins reading, the device records the start time of reading and sends it to the server.

[1141] When a user finishes reading an e-book, the device records the reading time and sends it to the server. The server stores the received information in a database and generates quizzes based on specific time periods (2 days, 14 days, or 60 days later). The AI ​​model then sends prompts to analyze the e-book's content, extracting key points and generating appropriate quizzes.

[1142] As a specific example, consider the case where a user selects the e-book "Study Guide" and begins reading. If the reading start time is, for example, 10:00 on October 1, 2023, the device records this information and sends it to the server. Later, when the user finishes reading at 18:00 on October 2, 2023, the device records the information again and sends it to the server. Based on this reading completion information, the server sets the timing of three quiz notifications for October 4, October 16, and December 1.

[1143] The server generates a quiz by sending the following prompt to the generative AI model: "For a user who has finished reading the e-book 'Study Guide', after two days, please generate four multiple-choice quiz questions based on the following content: The key points of Chapter 1 are..."

[1144] When it's time for a quiz notification, the server sends an appropriate push notification to the device. For example, on October 4th, a message saying "It's time for a review quiz!" is sent, and the user confirms the notification and opens the quiz screen on the device. The user answers the quiz and the results are sent from the device to the server. The server evaluates the results, generates a feedback message, and sends it to the device. The device displays the feedback to the user, allowing them to confirm the results.

[1145] Through the quizzes and feedback provided by this system, users can effectively solidify the contents of e-books into their memories.

[1146] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1147] Step 1: User registration and reading log

[1148] A user opens an e-book app on their device. First, the user creates an account and enters basic information such as their name and email address. The device sends this information to the server, which stores it in a database. Next, the user selects an e-book and begins reading. The device records the reading start time and sends the reading start information to the server. The server starts a reading session based on this information and stores it in a database. It also tracks the progress in real time. The input data is the user's basic information and reading start time, and the output data is the reading session information stored in the database.

[1149] Step 2: Reading and creating a quiz

[1150] The user finishes reading an e-book. The device records the completion time and sends that information to the server. The server stores the received completion information in a database. Next, it schedules quizzes to be given two days, 14 days, and 60 days after completion. The server sends prompts to the generative AI model, which analyzes the content of the e-book, extracts key points, and generates a quiz. For example, it creates a quiz question such as, "What are the key points of Chapter 1?" The input data is the reading time and the content of the e-book, and the output data is the generated quiz.

[1151] Step 3: Quiz Notification

[1152] The quiz notification timing arrives. Based on the configured timing, the server sends a push notification to the user device that the quiz is ready. The notification includes the message "It's time for a review quiz!" and a link to the quiz screen. This allows the user to start the quiz smoothly. The input data is the quiz notification schedule, and the output data is the sent notification message.

[1153] Step 4: Take the quiz

[1154] The user confirms the notification and starts the quiz. The device displays the quiz screen, and the user enters their answers. The quiz questions are presented in multiple choice or free description format, and the user answers according to the format. The input data are the quiz questions and the user's answers, and the output data are the user's answers.

[1155] Step 5: Recording and feedback

[1156] Once the quiz is complete, the device sends the user's answers to the server. The server evaluates the received answers and analyzes the accuracy rate and comprehension level. Based on this evaluation result, a feedback message is generated, such as "Excellent! Your memory is firmly established." The server sends this feedback message to the device, which then displays it to the user. The input data is the user's answers, and the output data is the feedback message.

[1157] (Application example 1)

[1158] 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."

[1159] Simply viewing conventional e-books or learning content is often insufficient to retain what has been learned. Another issue is the lack of appropriate review methods that allow users to review what they have viewed later and improve their learning effectiveness. Therefore, a support system is needed to effectively review and retain what has been viewed.

[1160] 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.

[1161] In this invention, the server includes a means for detecting when a user has finished viewing an e-book or learning content, a means for generating a quiz based on a specific period (2 days, 14 days, or 60 days) after the completion of the reading or viewing, a means for notifying the generated quiz to the user terminal, a means for collecting and evaluating the quiz answers, and a means for providing feedback to the user based on the evaluation results, thereby effectively helping the user to solidify the content they have viewed.

[1162] "User" refers to an individual who uses the system to read e-books or view learning content.

[1163] An "e-book" is a book that is distributed in digital form and is read using an electronic device.

[1164] "Learning content" refers to educational videos and materials designed to improve knowledge and skills.

[1165] "Viewing" refers to the act of a user reading an e-book or viewing learning content.

[1166] The "means for detecting timing" refers to a technique or device for identifying the point in time at which a user has finished viewing an e-book and learning content.

[1167] A "specific period" refers to a predetermined period, such as 2 days, 14 days, or 60 days after viewing.

[1168] "Quiz generating means" refers to a technique or device for creating a quiz based on the content viewed.

[1169] A "user terminal" is an electronic device used by a user, such as a computer, smartphone, or tablet.

[1170] The "notification means" refers to a technique or device for notifying the user terminal of the generated quiz.

[1171] The "means for collecting answer results" refers to a technique or device for obtaining the results of users' answers to the quiz.

[1172] "Means for evaluation" refers to technology or equipment for analyzing collected answers and measuring the user's level of understanding.

[1173] The "means for providing feedback" refers to a technology or device for sending advice or comments to the user based on the evaluation results.

[1174] In order to implement the present invention, it is necessary to construct the following system.

[1175] First, a user uses a device (such as a smartphone or tablet) to view e-books and learning content. After installing a dedicated application on the device, the user registers and begins viewing. When the user starts viewing, the device records the start time and sends it to the server.

[1176] Platform configuration:

[1177] Hardware: Smartphones, tablets, computers, head-mounted displays (HMDs)

[1178] Software: Dedicated learning application, Flask (web application framework), SQLAlchemy (database management), OpenAI GPT-3 (quiz generation), Firebase Cloud Messaging (notification service)

[1179] The server tracks the user's progress from the start of the session, records the completion time when the user finishes the session, and then generates quizzes based on specific time periods (2 days, 14 days, 60 days).

[1180] To generate the quiz, the server analyzes the key points of the viewed content and creates the quiz using a generative AI model (e.g., OpenAI GPT-3). The generation process uses the following prompt sentence as input:

[1181] Example prompt sentence:

[1182] Generate a quiz with multiple choice questions based on the content of the documentary "Miracles of Earth". Include questions that test the viewer's understanding of key concepts discussed in the documentary.

[1183] The generated quiz is notified to the user's device using Firebase Cloud Messaging. The user receives the notification and answers the quiz. The user's answers are sent from the device to the server, which evaluates them. Based on the evaluation results, feedback is generated and sent to the user's device. This feedback allows the user to understand their level of understanding and obtain guidelines for further study.

[1184] For example, after a user finishes watching the science documentary "Miracles of the Earth," they are notified of different quizzes two days, 14 days, and 60 days later. Each quiz is based on the content viewed and is designed to help users retain their knowledge. Depending on the evaluation results, the user is given feedback such as "Excellent! Your memory is firmly established."

[1185] In this way, the present invention serves as a support system that effectively helps users to solidify their memory of what they have viewed and improves their learning effectiveness.

[1186] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1187] Step 1:

[1188] A dedicated application is installed on the device (such as a smartphone or tablet) on which the user will view the e-books and learning content.

[1189] Input: User basic information, installed apps.

[1190] Output: Initial setup completed, user account created.

[1191] Specific behavior: The user creates an account in the launched application and enters basic information.

[1192] Step 2:

[1193] Users view e-books and learning content.

[1194] Enter: Select the content you want to watch.

[1195] Output: Recording of viewing start time, viewing status tracking.

[1196] Specific operation: When a user starts watching, the device records the start time of watching and sends it to the server.

[1197] Step 3:

[1198] When viewing is finished, the time of completion of reading or viewing is recorded.

[1199] Input: End View action.

[1200] Output: Record of viewing end time.

[1201] Specific operation: When the user finishes watching, the device records the end time and sends it to the server.

[1202] Step 4:

[1203] Generate quizzes based on a specific time period (2 days, 14 days, 60 days).

[1204] Input: End time of viewing, content viewed.

[1205] Output: Generate a quiz.

[1206] Specific operation: The server sets the timing for generating the quiz based on the end time of viewing, and generates a quiz based on the viewing content using a generative AI model (OpenAI GPT-3).

[1207] Step 5:

[1208] The generated quiz is notified to the user terminal.

[1209] Input: The generated quiz.

[1210] Output: Push quiz notification.

[1211] Specific operation: The server uses Firebase Cloud Messaging to send a quiz notification to the user's device.

[1212] Step 6:

[1213] The user answers the quiz.

[1214] Input: Notified quiz.

[1215] Output: Quiz answer results.

[1216] Specific operation: The user receives a quiz notification, opens the quiz screen, enters the answer, and the device sends the answer to the server.

[1217] Step 7:

[1218] The server evaluates the quiz answers.

[1219] Input: The user's quiz answer result.

[1220] Output: Producing the evaluation results.

[1221] Specific operation: The server compiles the quiz answer results and evaluates the user's accuracy rate, etc.

[1222] Step 8:

[1223] Based on the evaluation results, feedback is provided to the user.

[1224] Input: Evaluation result.

[1225] Output: Generate and send feedback messages.

[1226] Specific operation: Based on the evaluation result, the server generates a feedback message and sends it to the user terminal.

[1227] In this way, the operation of the entire system is explained in detail at each step, linking the user's viewing experience to improved learning outcomes.

[1228] 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.

[1229] This invention combines a system that detects when a user has finished reading an e-book, generates and notifies a user of a quiz after a specific period of time, evaluates the results of the quiz, and provides feedback, with an emotion engine that recognizes the user's emotions. This system operates based on the roles of the server, the terminal, and the user.

[1230] Program processing explanation

[1231] 1. User registration and reading record

[1232] The user opens the e-book app on their device and creates an account.

[1233] The user enters their name, email address, and password, and the device sends the information to the server.

[1234] The server stores the account information in a database.

[1235] When a user selects an electronic book and starts reading, the terminal records the reading start time and transmits it to the server.

[1236] The server initiates the reading session and tracks its progress.

[1237] 2. Reading Completion and Quiz Generation

[1238] The user finishes reading the e-book.

[1239] The device records the reading time and sends it to the server.

[1240] The server receives the read completion information and stores it in a database.

[1241] The server generates and prepares quizzes based on specific time periods after completion of reading (2 days, 14 days, 60 days).

[1242] Analyze the contents of e-books, extract important points, and generate quizzes.

[1243] 3. Emotional engine for recognizing user emotions

[1244] When a user starts a quiz, the emotion engine kicks in.

[1245] The device's camera and microphone are used to analyze the user's facial expressions and voice to determine their emotional state.

[1246] The emotion engine sends the user's emotion data to the server.

[1247] 4. Quiz Notifications and Adjustments

[1248] The server adjusts the content and timing of the quiz based on the emotional data.

[1249] For example, if it is determined that the user is tired, it may present questions with lower difficulty or postpone notifications.

[1250] When the server is ready to quiz, it will send a push notification to the user's device. Example: "Time for a review quiz!"

[1251] 5. Quiz

[1252] The user confirms the notification and starts the quiz.

[1253] The terminal displays a quiz screen and the user inputs an answer.

[1254] The quizzes are presented in multiple choice or free-form format, with the appropriate content selected based on the analysis results of the emotion engine.

[1255] 6. Recording and feedback of results

[1256] The terminal transmits the user's answers to the quiz to the server.

[1257] The server evaluates the answers and records them in a database.

[1258] Based on the evaluation results, feedback is provided to the user. For example, if the accuracy rate is high, a positive message such as "Your memory is firmly established" is sent.

[1259] Consider the results of the emotion engine and adjust the tone and content of your feedback as needed.

[1260] Specific examples

[1261] Example of a user selecting the e-book "Study Guide" and starting to read

[1262] 1. The user selects an e-book

[1263] The user selects the e-book "Study Guide" and begins reading.

[1264] The device records the reading start time (e.g., 10:00 on October 1, 2023) and sends it to the server.

[1265] The server starts the reading session and stores the progress in a database.

[1266] 2. The user finishes reading the book

[1267] The user completes the Study Guide.

[1268] The device records the time of completion of reading (e.g., 18:00 on October 2, 2023) and sends it to the server.

[1269] The server receives the reading completion information and generates and schedules the quiz.

[1270] The quiz timings will be set for 2 days (October 4th), 14 days (October 16th), and 60 days (December 1st) after the reading is completed.

[1271] Generative AI analyzes the contents of the book and creates quiz questions.

[1272] 3. Emotional Engine Activation

[1273] When a user starts a quiz, the device's camera and microphone collect and analyze the user's emotions (e.g., the emotion engine determines that the user is relaxed).

[1274] The emotion engine sends the results to the server.

[1275] 4. Quiz Notifications and Coordination

[1276] When it's time for a quiz, the server takes into account the results of the emotion engine and adjusts the notification message.

[1277] Example: On October 4th, a push notification will be sent saying "It's time for a review quiz!"

[1278] 5. Conducting a quiz

[1279] The user confirms the notification and starts the quiz screen.

[1280] The terminal displays a quiz screen and the user inputs an answer.

[1281] The difficulty of the quiz is adjusted to suit the user's emotional state.

[1282] 6. Evaluation results and feedback

[1283] The user answers the quiz, and the terminal transmits the answer to the server.

[1284] The server evaluates the answer and gives an 80% correct answer rate.

[1285] The server generates feedback and, based on the results of the emotion engine, sends a message to the device saying, "Great! Your memory is well-established. Keep up the great work!"

[1286] The terminal displays a feedback message to the user.

[1287] This invention aims to provide more effective and personalized learning by taking into account the user's emotional state. By combining it with an emotion engine, it is possible to review at the most appropriate time and with the most appropriate content for the user, significantly improving the efficiency and enjoyment of learning.

[1288] The processing flow will be explained below.

[1289] Step 1:

[1290] The user downloads an e-book app on their device and creates an account.

[1291] The user enters their name, email address, and password.

[1292] The device sends the input information to the server, which then stores the account in a database.

[1293] Step 2:

[1294] The user selects an e-book.

[1295] The device displays a list of e-books, and the user selects the book they want to read.

[1296] The user selects the Study Guide and begins reading.

[1297] The device records the reading start time and sends it to the server.

[1298] The server initiates the reading session and stores it in a database.

[1299] Step 3:

[1300] The user finishes reading the e-book.

[1301] When the user finishes reading the last page, the device records the time it took to finish reading.

[1302] The device sends the reading time to the server, which stores it in a database.

[1303] Step 4:

[1304] The server sets the timing for generating the quiz based on the reading completion information.

[1305] The server calculates the timing of 2 days (48 hours), 14 days, and 60 days after the end of reading and sets the schedule for generating the quiz.

[1306] Step 5:

[1307] The server uses generated AI to analyze the contents of the book that has been read.

[1308] Generative AI extracts key points from text and creates quizzes.

[1309] The quiz will consist of multiple choice and free-form questions.

[1310] Step 6:

[1311] When the quiz timing is reached, the server will send a push notification to the device.

[1312] For example, you will receive a notification saying, "Take the quiz two days after you finish reading."

[1313] Step 7:

[1314] The user confirms the notification and starts the quiz.

[1315] The user clicks the link in the notification message, and the device displays the quiz screen.

[1316] The user answers the quiz.

[1317] Step 8:

[1318] The terminal transmits the user's response data to the server.

[1319] The server evaluates the answers and calculates the accuracy rate, etc.

[1320] The evaluation results are recorded in the user's database.

[1321] Step 9:

[1322] When a user starts a quiz, the emotion engine kicks in.

[1323] The device's camera and microphone are used to analyze the user's facial expressions and voice to determine their emotional state.

[1324] The emotion engine sends the user's emotion data to the server.

[1325] Step 10:

[1326] The server adjusts the quiz content and the timing of the next notification based on the emotional data.

[1327] For example, if it is determined that the user is tired, it may present questions with lower difficulty or postpone notifications.

[1328] When the server is ready for the quiz, it will send the following push notification to the user's device:

[1329] Step 11:

[1330] The server generates feedback based on the evaluation results.

[1331] If the score is high, create a positive message such as "Great! Your memory is well-established."

[1332] If the score is low, feedback is generated that includes study advice such as "Please review the following points."

[1333] Step 12:

[1334] The server sends a feedback message to the terminal.

[1335] The device displays feedback to the user.

[1336] Example 2

[1337] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1338] In conventional learning systems, there are limited ways for users to effectively check their understanding of an e-book after they have finished reading it, and the timing for reviewing the learning content is fixed, making it difficult to maximize the learning effect of each individual user. Furthermore, conventional systems do not take into account the user's emotional state, which creates the risk of the learning load becoming too high and lowering user motivation.

[1339] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for detecting the timing when the user finishes reading an e-book, means for generating a quiz based on a specific period after the completion of reading (2 days, 14 days, or 60 days), means for notifying the user terminal of the generated quiz, means for collecting and evaluating quiz answer results, means for providing feedback to the user based on the evaluation results, emotion recognition means for recognizing the user's emotion, and means for adjusting the quiz content and notification timing based on the emotion recognition data. This enables review at the optimal timing and content according to each user's emotional state, thereby improving learning effectiveness and motivation.

[1340] "User" refers to an individual who operates this system to read e-books and answer quizzes.

[1341] "Device" refers to any computer system used by a user that can run an e-book app, including, for example, a smartphone, tablet, or PC.

[1342] "Server" refers to a computer system that receives data from the terminal, processes it, and generates appropriate feedback and quizzes.

[1343] The "timing of completion of reading" refers to the time when the user has finished reading all the pages of the electronic book.

[1344] "Quiz generation" refers to the process of analyzing the content of an e-book and creating questions based on a specific period after reading.

[1345] "Notification" refers to the process of sending a push notification or alert to the user's device when the generated quiz is ready.

[1346] "Answer result" refers to the answer entered by the user to the quiz.

[1347] "Evaluation" refers to the process of analyzing the user's answers and measuring the percentage of correct answers and learning progress.

[1348] "Feedback" refers to specific advice or messages provided to users based on the evaluation results to improve their learning effectiveness.

[1349] "Emotion recognition" refers to the process of analyzing a user's facial expressions and voice data collected using the device's camera and microphone to determine the user's emotional state.

[1350] "Emotion recognition data" refers to data obtained through an emotion recognition process that indicates a user's emotional state.

[1351] "Adjustment" refers to the process of changing the content of the quiz or the timing of notifications based on emotion recognition data.

[1352] This invention is a system that detects when a user has finished reading an e-book, generates and notifies a user of a quiz after a specific period of time, evaluates the results of the quiz and provides feedback, and combines it with an emotion recognition engine that recognizes the user's emotions. This system operates based on the roles of the server, terminal, and user.

[1353] Specific hardware includes devices such as smartphones, tablets, and PCs. Servers are built as cloud servers or dedicated servers. Software includes e-book apps, emotion recognition engines, generative AI models, etc.

[1354] 1. User registration and reading record

[1355] A user opens an e-book app and creates an account. Specifically, the user enters their name, email address, and password, and the device sends that information to the server. The server saves the account information in a database and notifies the user when the account is complete. When the user selects an e-book and starts reading, the device records the reading start time and sends it to the server. The server starts the reading session and saves the progress in a database.

[1356] 2. Reading Completion and Quiz Generation

[1357] When a user finishes reading an e-book, the device records the time the user has finished reading and sends it to the server. The server then stores this information in a database and generates a quiz for a specific period of time after the user has finished reading (for example, 2 days, 14 days, or 60 days later). The generative AI model analyzes the content of the e-book, extracts key points, and creates the quiz.

[1358] 3. Emotional engine for recognizing user emotions

[1359] When a user receives a quiz notification and starts the quiz, the device's camera and microphone collect the user's facial expressions and voice data, which are then analyzed by an emotion recognition engine. The emotion recognition engine determines the user's emotional state (e.g., relaxed, tired) and sends the data to the server.

[1360] 4. Quiz Notifications and Adjustments

[1361] The server adjusts the content of the quiz and the timing of notifications based on emotion recognition data. For example, if the server determines that the user is tired, it will select less difficult questions or postpone notifications. When the quiz is ready, the server sends a push notification to the user's device. For example, it could send a message saying, "It's time for a review quiz!"

[1362] 5. Quiz

[1363] The user confirms the notification and starts the quiz. The device displays the quiz screen and the user enters their answers. Questions are presented in multiple choice or free-form format, and the appropriate content is selected based on the analysis results of the emotion recognition engine.

[1364] 6. Recording and feedback of results

[1365] The user answers the quiz, and the device sends the results to the server. The server evaluates the answer (for example, "80% correct") and records it in a database. Based on the evaluation results, the server provides feedback to the user. For example, if the user answers correctly, the server may generate a message such as "Great! Your memory is well-established. Keep up the good work!", adjusting the tone and content of the feedback based on the results of the emotion recognition engine. The feedback message is sent to the user's device, where it is displayed to the user.

[1366] Example prompt sentence:

[1367] "Detect when a user has finished reading a specific e-book and generate a quiz based on a specific period after reading. Also, recognize the user's emotional state and adjust the optimal quiz content and notification timing."

[1368] The above system provides personalized learning that takes into account the user's emotional state, and is expected to significantly improve the efficiency and enjoyment of learning.

[1369] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1370] Step 1:

[1371] Create an account

[1372] A user opens an e-book app and enters their name, email address, and password.

[1373] Enter your name, email address, and password.

[1374] Output: The user's account information.

[1375] The terminal sends the input information to the server.

[1376] The server saves the account information to the database, performs a database update operation, and logs the completion of the save.

[1377] Step 2:

[1378] Select an e-book and start reading

[1379] The user selects an e-book in the app (e.g., "Study Guide").

[1380] Input: Information about the selected e-book.

[1381] Output: Triggers the reading start event.

[1382] The terminal records the user's reading start time and sends that information to the server.

[1383] The server starts a reading session and saves the progress to a database, writes the start time to the database, and generates a session ID.

[1384] Step 3:

[1385] Record reading time

[1386] The user reads the e-book to the end.

[1387] Input: Information on the page you have read.

[1388] Output: Triggers a read event.

[1389] The device records the time it takes to finish reading and sends that information to the server.

[1390] The server saves the completion information to a database, records the completion time, and updates the relevant session data.

[1391] Step 4:

[1392] Quiz Generation

[1393] The server sets a specific period after reading (e.g., 2 days, 14 days, or 60 days).

[1394] Input: Reading information, specific period.

[1395] Output:Quiz schedule.

[1396] The server uses a generative AI model to analyze the contents of the e-book, extract key points, and create quiz questions.

[1397] Input: E-book text data.

[1398] Output: A set of quiz questions.

[1399] The server stores the generated quiz in a database.

[1400] Step 5:

[1401] Quiz Notifications

[1402] When the server is ready for the quiz based on the specified quiz notification timing, it sends a push notification to the user terminal.

[1403] Input: Quiz schedule, user's device information.

[1404] Output: Push notification (e.g. "Time for a review quiz!").

[1405] The server records the notification content and timing and sets retransmission logic.

[1406] Step 6:

[1407] Emotion recognition and quiz start

[1408] The user receives the quiz notification and starts the quiz.

[1409] Input: Acknowledgement of notification receipt.

[1410] Output: Quiz screen display.

[1411] The device's camera and microphone collect the user's facial expressions and voice data, which is then analyzed by an emotion recognition engine.

[1412] Input: User's facial expressions and voice data.

[1413] Output: Emotion recognition result (e.g. "Relaxed" or "Tired").

[1414] The emotion recognition engine sends the analysis results to the server.

[1415] Step 7:

[1416] Adjustment and implementation of quiz content

[1417] The server adjusts the content and difficulty of the quiz based on the emotion recognition data.

[1418] Input: Emotion recognition data, generated quiz questions.

[1419] Output: The adjusted quiz questions.

[1420] The terminal displays the adjusted quiz questions and the user inputs the answers.

[1421] Input: The user's answer.

[1422] Output: Response data.

[1423] Step 8:

[1424] Submitting and evaluating answer results

[1425] The terminal transmits the user's answer results to the server.

[1426] Input: Response data.

[1427] Output: Sending data to the server.

[1428] The server evaluates the answer results and stores the evaluation results in a database.

[1429] Input: Response data.

[1430] Output: Evaluation results such as accuracy rate.

[1431] Based on the evaluation results, the server generates feedback.

[1432] Step 9:

[1433] Providing Feedback

[1434] The server provides feedback to the user based on the evaluation results.

[1435] Input: Evaluation results, emotion recognition data.

[1436] Output: A feedback message (e.g., "Great! Your memory is solid. Keep it up!").

[1437] The terminal displays a feedback message to the user.

[1438] (Application example 2)

[1439] 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."

[1440] Conventional learning systems using e-books provide quizzes uniformly without considering the user's emotions, which means that they are unable to provide optimal review timing or difficulty for each individual user. Furthermore, to maximize learning efficiency, it is important to adjust the timing and content according to the user's emotional state, but no such system has existed. Furthermore, when using e-payment services, users have had the problem of not receiving appropriate feedback after selecting a product.

[1441] 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.

[1442] In this invention, the server includes a means for detecting when a user has finished reading an e-book, a means for generating a quiz based on a specific period of time since the user finished reading, and a means for recognizing the user's emotions using an emotion engine. This makes it possible to adjust the content of the quiz and the timing of notifications according to the user's emotional state and provide personalized feedback. Furthermore, emotion recognition can be utilized when using electronic payment services, providing appropriate feedback and recommendations to the user to increase their motivation to purchase.

[1443] The "means for detecting when the user has finished reading the e-book" is a mechanism that automatically detects when the user has read to the last page of the e-book and records that point in time.

[1444] The "means for generating quizzes" is a function that analyzes the contents of an e-book and creates multiple questions based on a specific algorithm.

[1445] "Means for notifying the user terminal" refers to a method for sending quizzes and other information to the user's device as alerts or push notifications.

[1446] "Means for collecting and evaluating quiz answer results" refers to a system for collecting data on users' answers to quizzes and analyzing and evaluating their accuracy and completeness.

[1447] The "means for providing feedback" is a system that returns appropriate advice and comments to the user based on the evaluation results of the quiz.

[1448] The "means for recognizing a user's emotions using an emotion engine" is a device equipped with an algorithm that analyzes a user's facial expressions, voice, and other biometric data to determine their psychological state.

[1449] The "means for adjusting the quiz content and notification timing according to the user's emotions" is a mechanism for optimizing the difficulty of the quiz and the timing of sending notifications based on the user's current emotional state.

[1450] This invention is a system that detects when a user has finished reading an e-book, generates a quiz after a specific period of time has passed, notifies the user of the quiz, evaluates the answers, and provides feedback.The system is characterized by using an emotion engine to recognize the user's emotions and adjusts the quiz content and notification timing accordingly.

[1451] System Configuration

[1452] The system consists of the following major hardware and software components:

[1453] Server: Contains the database, quiz generation algorithm, and emotion engine.

[1454] User device: A device such as a smartphone that is equipped with a camera and microphone.

[1455] Database: Stores user reading records, emotion data, and quiz results.

[1456] Emotion engine: A software module that recognizes emotions by analyzing the user's facial expressions and voice.

[1457] Quiz generation module: Analyzes the content of the e-book and generates quizzes based on key points.

[1458] System Operation

[1459] 1. User registration and reading record

[1460] Users create an account using a smartphone app, select an e-book, and begin reading. The device records the start time and sends it to the server, which then starts the reading session and stores the progress in a database.

[1461] 2. Reading Completion and Quiz Generation

[1462] When a user finishes reading an e-book, the device records the reading time and sends it to the server. The server receives the reading completion information and stores it in a database. A quiz is then generated and prepared based on a specific period after the reading (2 days, 14 days, or 60 days later). A generative AI model is used to analyze the content of the e-book, extract key points, and generate the quiz.

[1463] 3. Emotional engine for recognizing user emotions

[1464] When a user starts a quiz, the device's camera and microphone are used to recognize the user's emotions. The emotion engine analyzes the user's emotional data and sends this data to the server.

[1465] 4. Quiz Notifications and Adjustments

[1466] The server adjusts the quiz content and notification timing based on the emotion data. For example, if it determines that the user is tired, it can present easier questions or postpone notifications. When the quiz is ready, the server sends a push notification to the user's device. The notification reads, "Time for a review quiz!"

[1467] 5. Quiz and feedback

[1468] The user confirms the notification and begins the quiz. The quiz screen displays questions tailored to the user's emotional state, and the user enters their answers. The answers are sent from the device to the server, which evaluates them and provides feedback. For example, if the user answers correctly, a positive message such as "your memory is firmly established" is sent.

[1469] Examples of specific examples and prompts

[1470] For example, if a user starts reading the e-book "Study Guide" and finishes it, and the emotion engine determines that they are in a "Relaxed" state, the quiz notification will look like this:

[1471] Quiz notification example

[1472] "Time for a review quiz!"

[1473] Prompt Sentence Examples

[1474] Feedback when the user is relaxed:

[1475] Feedback message: "Amazing! I recommend you buy this product."

[1476] This allows for personalized quizzes and feedback that take into account the user's emotional state.

[1477] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1478] Step 1:

[1479] User registration and reading log

[1480] A user creates an account using a smartphone app and enters their name, email address, and password. The device sends this information to the server, which stores the account information in a database. When the user selects an e-book and begins reading, the device records the start time of the reading and sends it to the server. The server starts the reading session and stores the progress in a database.

[1481] Input: User information (name, email address, password) and e-book selection information

[1482] Data processing and calculation: User information verification and storage, recording of reading start time

[1483] Output: User account created, reading session started

[1484] Step 2:

[1485] Reading Completion and Quiz Generation

[1486] When a user finishes reading an e-book, the device records the reading time and sends it to the server. The server receives the reading completion information and stores it in a database. It then generates a quiz based on a specific period after reading (e.g., 2 days, 14 days, or 60 days). A generative AI model is used to analyze the content of the e-book, extract key points, and create a quiz.

[1487] Input: Reading time, e-book content

[1488] Data processing and calculation: saving reading completion information, generating quizzes

[1489] Output:Quiz preparation

[1490] Step 3:

[1491] Recognizing user emotions with an emotion engine

[1492] When a user starts a quiz, the device's camera and microphone capture the user's facial expressions and voice, and send them to the emotion engine, which analyzes them, determines the user's emotional state, and sends the results to the server.

[1493] Input: User's facial expression and voice data

[1494] Data processing and calculation: Analysis of emotional data

[1495] Output: User's emotional state

[1496] Step 4:

[1497] Quiz Notifications and Adjustments

[1498] The server adjusts the quiz content and notification timing based on the emotion data. For example, if the server determines that the user is "tired," it can lower the difficulty of the questions or postpone the notification. The server sends a push notification to the user's device when the quiz is ready. It also sends a message saying, "It's time for a review quiz!"

[1499] Input: User's emotional state, prepared quiz

[1500] Data processing and calculation: Adjustment of quiz content and notification timing

[1501] Output: Adjusted quiz and notifications

[1502] Step 5:

[1503] Quiz and feedback

[1504] The user confirms the quiz notification and starts the quiz. The device displays the quiz screen, and the user answers the questions. The answers are sent from the device to the server, which evaluates them. Based on the evaluation, personalized feedback is generated; for example, if the user answers correctly, a message such as "Your memory is firmly established" is sent to the user.

[1505] Input: User's quiz answer

[1506] Data processing and calculation: Evaluation of quiz answers, generation of feedback

[1507] Output: Feedback message

[1508] By clarifying the specific operations and inputs / outputs, the overall flow of the system becomes easier to understand and implement. The above step-by-step process allows users to have a more personalized and effective learning experience.

[1509] 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.

[1510] 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.

[1511] 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.

[1512] [Fourth embodiment]

[1513] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1514] 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.

[1515] 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).

[1516] 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.

[1517] 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.

[1518] 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).

[1519] 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.

[1520] 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.

[1521] 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.

[1522] 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.

[1523] 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.

[1524] 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.

[1525] 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."

[1526] This invention is a system that generates and notifies a user of a quiz after a certain period of time based on when the user finishes reading an e-book, evaluates the answers, and provides feedback. This system operates based on the roles of the server, terminal, and user.

[1527] Program processing explanation

[1528] 1. User registration and reading record

[1529] The user opens an e-book app on their device.

[1530] Users create an account and enter basic information.

[1531] The server stores user account information in a database.

[1532] When a user selects an e-book and starts reading, the device records and transmits the reading start time.

[1533] The server initiates the reading session and tracks its progress.

[1534] 2. Reading Completion and Quiz Generation

[1535] The user finishes reading the e-book.

[1536] The device records and transmits the reading time.

[1537] The server receives the read completion information and stores it in a database.

[1538] The server generates and prepares quizzes based on a specific period after completion of reading (2 days, 14 days, 60 days).

[1539] Analyze the contents of e-books, extract important points, and generate quizzes.

[1540] 3. Quiz Notifications

[1541] When the server reaches the quiz timing, it sends a notification to the device.

[1542] A push notification will be sent to the user's device containing a message that the quiz is ready and a link.

[1543] 4. Quiz

[1544] The user confirms the notification and starts the quiz.

[1545] The terminal displays a quiz screen and the user inputs an answer.

[1546] The quizzes are presented in multiple choice or free-form format, making them fun to play like a game.

[1547] 5. Recording and feedback of results

[1548] The terminal transmits the user's answers to the quiz to the server.

[1549] The server evaluates the answers and records them in a database.

[1550] Based on the evaluation results, feedback is provided to the user. For example, if the accuracy rate is high, a positive message such as "Your memory is firmly established" is sent.

[1551] Specific examples

[1552] Example of a user selecting the e-book "Study Guide" and starting to read

[1553] 1. The user selects an e-book

[1554] I choose the e-book "Study Guide" and start reading.

[1555] The device records the reading start time (e.g., 10:00 on October 1, 2023) and sends it to the server.

[1556] The server starts the reading session and stores the progress in a database.

[1557] 2. The user finishes reading the book

[1558] The user completes the Study Guide.

[1559] The device records the time of completion of reading (e.g., 18:00 on October 2, 2023) and sends it to the server.

[1560] The server receives the reading completion information and generates and schedules the quiz.

[1561] The quiz timings will be set for 2 days (October 4th), 14 days (October 16th), and 60 days (December 1st) after the reading is completed.

[1562] Generative AI analyzes the contents of the book and creates quiz questions.

[1563] 3. Quiz Notification and Implementation

[1564] When the time comes for the quiz, the server will send a notification.

[1565] Example: On October 4th, a push notification will be sent saying "It's time for a review quiz!"

[1566] The user confirms the notification and starts the quiz screen.

[1567] The terminal displays a quiz screen and the user inputs an answer.

[1568] 4. Evaluation results and feedback

[1569] The user answers the quiz, and the terminal transmits the answer to the server.

[1570] The server evaluates the answer and gives an 80% correct answer rate.

[1571] The server generates feedback and sends the message "Great! Your memory is firmly established" to the device.

[1572] The terminal displays a feedback message to the user.

[1573] This invention provides a system that effectively solidifies the contents of e-books into memory through the timing and content of quiz notifications, as well as a mechanism for evaluation and feedback, aiming to make learning more enjoyable and efficient for users.

[1574] The processing flow will be explained below.

[1575] Step 1:

[1576] The user downloads an e-book app on their device and creates an account.

[1577] The user enters their name, email address, and password.

[1578] The device sends the input information to the server, which then stores the account in a database.

[1579] Step 2:

[1580] The user selects an e-book.

[1581] The device displays a list of e-books, and the user selects the book they want to read.

[1582] The user selects the Study Guide and begins reading.

[1583] The device records the reading start time and sends it to the server.

[1584] The server initiates the reading session and stores it in a database.

[1585] Step 3:

[1586] The user finishes reading the e-book.

[1587] When the user finishes reading the last page, the device records the time it took to finish reading.

[1588] The device sends the reading time to the server, which stores it in a database.

[1589] Step 4:

[1590] The server sets the timing for generating the quiz based on the reading completion information.

[1591] The server calculates the timing of 2 days (48 hours), 14 days, and 60 days after the end of reading and sets the schedule for generating the quiz.

[1592] Step 5:

[1593] The server uses generated AI to analyze the contents of the book that has been read.

[1594] Generative AI extracts key points from text and converts them into quizzes.

[1595] Quizzes are created in multiple choice or free-form format.

[1596] Step 6:

[1597] When the quiz timing is reached, the server will send a push notification to the device.

[1598] Example: On the second day after finishing reading, you will receive a notification saying "It's time for a review quiz."

[1599] Step 7:

[1600] The user confirms the notification and starts the quiz.

[1601] The user clicks the link in the notification message, and the device displays the quiz screen.

[1602] The user answers the quiz.

[1603] Step 8:

[1604] The terminal sends the user's answer to the server.

[1605] The server receives the response data and evaluates the accuracy rate, etc.

[1606] The evaluation results are recorded in a database.

[1607] Step 9:

[1608] The server generates feedback based on the evaluation results.

[1609] If the score is high, create a positive message such as "Great! Your memory is well-established."

[1610] If the score is low, feedback is generated that includes study advice such as "Please review the following points."

[1611] Step 10:

[1612] The server sends a feedback message to the terminal.

[1613] The device displays the feedback to the user.

[1614] Example 1

[1615] 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."

[1616] Conventional e-book learning systems lack mechanisms for helping users effectively solidify the contents of e-books in their memories, making it difficult to fully utilize the learning benefits after reading. Specifically, it is difficult to review the content at an appropriate time after reading, or to extract important points and turn them into quizzes, making it difficult to maintain users' motivation to learn.

[1617] 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.

[1618] In this invention, the server includes a means for detecting when the user has finished reading the e-book, a means for generating a quiz based on a specific period after the user has finished reading (2 days, 14 days, or 60 days), and a means for sending prompts to the generation AI model, analyzing the contents of the e-book, and extracting important points. This allows for the provision of quizzes at appropriate times and for reviewing the contents.

[1619] A "user" is an individual who uses the system to read an electronic book.

[1620] A "terminal" is an electronic device that a user uses to read an e-book, such as a smartphone, tablet, or e-book reader.

[1621] A "server" is a central device that manages the operation of the entire system and communicates with users and terminals.

[1622] The "reading record" is data on the time when the user started reading an electronic book and the time when the user finished reading it.

[1623] A "reading session" is a record of a single e-book reading activity, including the start and end times of that activity.

[1624] A "database" is a storage system connected to a server for storing user account information and reading records.

[1625] A "generative AI model" is an artificial intelligence model that analyzes the contents of e-books and generates quizzes.

[1626] A "prompt" is an instruction given to a generative AI model, which serves as a guide for generating a quiz.

[1627] A "quiz" is a question-based test based on the content of an e-book, and is provided for the purpose of measuring the user's level of comprehension of the content.

[1628] A "push notification" is a real-time message sent from a server to a user device. An example is a quiz notification.

[1629] "Evaluation" refers to analyzing the percentage of correct answers and the level of comprehension of the content based on the answers entered by the user to the quiz.

[1630] "Feedback" refers to results reports and advice provided based on the user's answers to the quiz.

[1631] This invention is a system that generates and notifies a user of a quiz after a certain period of time based on when the user finishes reading an e-book, evaluates the answers, and provides feedback. This system operates based on the roles of the server, terminal, and user.

[1632] The server is the central device that manages the operation of the entire system and communicates with users and their devices. The server notifies the users of the generated quizzes, collects and evaluates the answers to the quizzes, and provides feedback based on the evaluation results.

[1633] A device is an electronic device used by a user to read e-books, such as a smartphone, tablet, or e-reader. The device records the user's start and end times and sends them to a server. It also has the ability to receive push notifications.

[1634] A user is an individual who uses the system to read an e-book and answer the subsequent quiz. The user creates an account, selects an e-book, and begins reading. After finishing the reading, the user answers the quiz sent by the server and receives feedback based on the results.

[1635] Specifically, the user first opens an e-book on their device, creates an account, and enters basic information. The device then sends this information to the server, which then stores it in a database. When the user selects an e-book and begins reading, the device records the start time of reading and sends it to the server.

[1636] When a user finishes reading an e-book, the device records the reading time and sends it to the server. The server stores the received information in a database and generates quizzes based on specific time periods (2 days, 14 days, or 60 days later). The AI ​​model then sends prompts to analyze the e-book's content, extracting key points and generating appropriate quizzes.

[1637] As a specific example, consider the case where a user selects the e-book "Study Guide" and begins reading. If the reading start time is, for example, 10:00 on October 1, 2023, the device records this information and sends it to the server. Later, when the user finishes reading at 18:00 on October 2, 2023, the device records the information again and sends it to the server. Based on this reading completion information, the server sets the timing of three quiz notifications for October 4, October 16, and December 1.

[1638] The server generates a quiz by sending the following prompt to the generative AI model: "For a user who has finished reading the e-book 'Study Guide', after two days, please generate four multiple-choice quiz questions based on the following content: The key points of Chapter 1 are..."

[1639] When it's time for a quiz notification, the server sends an appropriate push notification to the device. For example, on October 4th, a message saying "It's time for a review quiz!" is sent, and the user confirms the notification and opens the quiz screen on the device. The user answers the quiz and the results are sent from the device to the server. The server evaluates the results, generates a feedback message, and sends it to the device. The device displays the feedback to the user, allowing them to confirm the results.

[1640] Through the quizzes and feedback provided by this system, users can effectively solidify the contents of e-books into their memories.

[1641] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1642] Step 1: User registration and reading log

[1643] A user opens an e-book app on their device. First, the user creates an account and enters basic information such as their name and email address. The device sends this information to the server, which stores it in a database. Next, the user selects an e-book and begins reading. The device records the reading start time and sends the reading start information to the server. The server starts a reading session based on this information and stores it in a database. It also tracks the progress in real time. The input data is the user's basic information and reading start time, and the output data is the reading session information stored in the database.

[1644] Step 2: Reading and creating a quiz

[1645] The user finishes reading an e-book. The device records the completion time and sends that information to the server. The server stores the received completion information in a database. Next, it schedules quizzes to be given two days, 14 days, and 60 days after completion. The server sends prompts to the generative AI model, which analyzes the content of the e-book, extracts key points, and generates a quiz. For example, it creates a quiz question such as, "What are the key points of Chapter 1?" The input data is the reading time and the content of the e-book, and the output data is the generated quiz.

[1646] Step 3: Quiz Notification

[1647] The quiz notification timing arrives. Based on the configured timing, the server sends a push notification to the user device that the quiz is ready. The notification includes the message "It's time for a review quiz!" and a link to the quiz screen. This allows the user to start the quiz smoothly. The input data is the quiz notification schedule, and the output data is the sent notification message.

[1648] Step 4: Take the quiz

[1649] The user confirms the notification and starts the quiz. The device displays the quiz screen, and the user enters their answers. The quiz questions are presented in multiple choice or free description format, and the user answers according to the format. The input data are the quiz questions and the user's answers, and the output data are the user's answers.

[1650] Step 5: Recording and feedback

[1651] Once the quiz is complete, the device sends the user's answers to the server. The server evaluates the received answers and analyzes the accuracy rate and comprehension level. Based on this evaluation result, a feedback message is generated, such as "Excellent! Your memory is firmly established." The server sends this feedback message to the device, which then displays it to the user. The input data is the user's answers, and the output data is the feedback message.

[1652] (Application example 1)

[1653] 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."

[1654] Simply viewing conventional e-books or learning content is often insufficient to retain what has been learned. Another issue is the lack of appropriate review methods that allow users to review what they have viewed later and improve their learning effectiveness. Therefore, a support system is needed to effectively review and retain what has been viewed.

[1655] 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.

[1656] In this invention, the server includes a means for detecting when a user has finished viewing an e-book or learning content, a means for generating a quiz based on a specific period (2 days, 14 days, or 60 days) after the completion of the reading or viewing, a means for notifying the generated quiz to the user terminal, a means for collecting and evaluating the quiz answers, and a means for providing feedback to the user based on the evaluation results, thereby effectively helping the user to solidify the content they have viewed.

[1657] "User" refers to an individual who uses the system to read e-books or view learning content.

[1658] An "e-book" is a book that is distributed in digital form and is read using an electronic device.

[1659] "Learning content" refers to educational videos and materials designed to improve knowledge and skills.

[1660] "Viewing" refers to the act of a user reading an e-book or viewing learning content.

[1661] The "means for detecting timing" refers to a technique or device for identifying the point in time at which a user has finished viewing an e-book and learning content.

[1662] A "specific period" refers to a predetermined period, such as 2 days, 14 days, or 60 days after viewing.

[1663] "Quiz generating means" refers to a technique or device for creating a quiz based on the content viewed.

[1664] A "user terminal" is an electronic device used by a user, such as a computer, smartphone, or tablet.

[1665] The "notification means" refers to a technique or device for notifying the user terminal of the generated quiz.

[1666] The "means for collecting answer results" refers to a technique or device for obtaining the results of users' answers to the quiz.

[1667] "Means for evaluation" refers to technology or equipment for analyzing collected answers and measuring the user's level of understanding.

[1668] The "means for providing feedback" refers to a technology or device for sending advice or comments to the user based on the evaluation results.

[1669] In order to implement the present invention, it is necessary to construct the following system.

[1670] First, a user uses a device (such as a smartphone or tablet) to view e-books and learning content. After installing a dedicated application on the device, the user registers and begins viewing. When the user starts viewing, the device records the start time and sends it to the server.

[1671] Platform configuration:

[1672] Hardware: Smartphones, tablets, computers, head-mounted displays (HMDs)

[1673] Software: Dedicated learning application, Flask (web application framework), SQLAlchemy (database management), OpenAI GPT-3 (quiz generation), Firebase Cloud Messaging (notification service)

[1674] The server tracks the user's progress from the start of the session, records the completion time when the user finishes the session, and then generates quizzes based on specific time periods (2 days, 14 days, 60 days).

[1675] To generate the quiz, the server analyzes the key points of the viewed content and creates the quiz using a generative AI model (e.g., OpenAI GPT-3). The generation process uses the following prompt sentence as input:

[1676] Example prompt sentence:

[1677] Generate a quiz with multiple choice questions based on the content of the documentary "Miracles of Earth". Include questions that test the viewer's understanding of key concepts discussed in the documentary.

[1678] The generated quiz is notified to the user's device using Firebase Cloud Messaging. The user receives the notification and answers the quiz. The user's answers are sent from the device to the server, which evaluates them. Based on the evaluation results, feedback is generated and sent to the user's device. This feedback allows the user to understand their level of understanding and obtain guidelines for further study.

[1679] For example, after a user finishes watching the science documentary "Miracles of the Earth," they are notified of different quizzes two days, 14 days, and 60 days later. Each quiz is based on the content viewed and is designed to help users retain their knowledge. Depending on the evaluation results, the user is given feedback such as "Excellent! Your memory is firmly established."

[1680] In this way, the present invention serves as a support system that effectively helps users to solidify their memory of what they have viewed and improves their learning effectiveness.

[1681] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1682] Step 1:

[1683] A dedicated application is installed on the device (such as a smartphone or tablet) on which the user will view the e-books and learning content.

[1684] Input: User basic information, installed apps.

[1685] Output: Initial setup completed, user account created.

[1686] Specific behavior: The user creates an account in the launched application and enters basic information.

[1687] Step 2:

[1688] Users view e-books and learning content.

[1689] Enter: Select the content you want to watch.

[1690] Output: Recording of viewing start time, viewing status tracking.

[1691] Specific operation: When a user starts watching, the device records the start time of watching and sends it to the server.

[1692] Step 3:

[1693] When viewing is finished, the time of completion of reading or viewing is recorded.

[1694] Input: End View action.

[1695] Output: Record of viewing end time.

[1696] Specific operation: When the user finishes watching, the device records the end time and sends it to the server.

[1697] Step 4:

[1698] Generate quizzes based on a specific time period (2 days, 14 days, 60 days).

[1699] Input: End time of viewing, content viewed.

[1700] Output: Generate a quiz.

[1701] Specific operation: The server sets the timing for generating the quiz based on the end time of viewing, and generates a quiz based on the viewing content using a generative AI model (OpenAI GPT-3).

[1702] Step 5:

[1703] The generated quiz is notified to the user terminal.

[1704] Input: The generated quiz.

[1705] Output: Push quiz notification.

[1706] Specific operation: The server uses Firebase Cloud Messaging to send a quiz notification to the user's device.

[1707] Step 6:

[1708] The user answers the quiz.

[1709] Input: Notified quiz.

[1710] Output: Quiz answer results.

[1711] Specific operation: The user receives a quiz notification, opens the quiz screen, enters the answer, and the device sends the answer to the server.

[1712] Step 7:

[1713] The server evaluates the quiz answers.

[1714] Input: The user's quiz answer result.

[1715] Output: Producing the evaluation results.

[1716] Specific operation: The server compiles the quiz answer results and evaluates the user's accuracy rate, etc.

[1717] Step 8:

[1718] Based on the evaluation results, feedback is provided to the user.

[1719] Input: Evaluation result.

[1720] Output: Generate and send feedback messages.

[1721] Specific operation: Based on the evaluation result, the server generates a feedback message and sends it to the user terminal.

[1722] In this way, the operation of the entire system is explained in detail at each step, linking the user's viewing experience to improved learning outcomes.

[1723] 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.

[1724] This invention combines a system that detects when a user has finished reading an e-book, generates and notifies a user of a quiz after a specific period of time, evaluates the results of the quiz, and provides feedback, with an emotion engine that recognizes the user's emotions. This system operates based on the roles of the server, the terminal, and the user.

[1725] Program processing explanation

[1726] 1. User registration and reading record

[1727] The user opens the e-book app on their device and creates an account.

[1728] The user enters their name, email address, and password, and the device sends the information to the server.

[1729] The server stores the account information in a database.

[1730] When a user selects an electronic book and starts reading, the terminal records the reading start time and transmits it to the server.

[1731] The server initiates the reading session and tracks its progress.

[1732] 2. Reading Completion and Quiz Generation

[1733] The user finishes reading the e-book.

[1734] The device records the reading time and sends it to the server.

[1735] The server receives the read completion information and stores it in a database.

[1736] The server generates and prepares quizzes based on specific time periods after completion of reading (2 days, 14 days, 60 days).

[1737] Analyze the contents of e-books, extract important points, and generate quizzes.

[1738] 3. Emotional engine for recognizing user emotions

[1739] When a user starts a quiz, the emotion engine kicks in.

[1740] The device's camera and microphone are used to analyze the user's facial expressions and voice to determine their emotional state.

[1741] The emotion engine sends the user's emotion data to the server.

[1742] 4. Quiz Notifications and Adjustments

[1743] The server adjusts the content and timing of the quiz based on the emotional data.

[1744] For example, if it is determined that the user is tired, it may present questions with lower difficulty or postpone notifications.

[1745] When the server is ready to quiz, it will send a push notification to the user's device. Example: "Time for a review quiz!"

[1746] 5. Quiz

[1747] The user confirms the notification and starts the quiz.

[1748] The terminal displays a quiz screen and the user inputs an answer.

[1749] The quizzes are presented in multiple choice or free-form format, with the appropriate content selected based on the analysis results of the emotion engine.

[1750] 6. Recording and feedback of results

[1751] The terminal transmits the user's answers to the quiz to the server.

[1752] The server evaluates the answers and records them in a database.

[1753] Based on the evaluation results, feedback is provided to the user. For example, if the accuracy rate is high, a positive message such as "Your memory is firmly established" is sent.

[1754] Consider the results of the emotion engine and adjust the tone and content of your feedback as needed.

[1755] Specific examples

[1756] Example of a user selecting the e-book "Study Guide" and starting to read

[1757] 1. The user selects an e-book

[1758] The user selects the e-book "Study Guide" and begins reading.

[1759] The device records the reading start time (e.g., 10:00 on October 1, 2023) and sends it to the server.

[1760] The server starts the reading session and stores the progress in a database.

[1761] 2. The user finishes reading the book

[1762] The user completes the Study Guide.

[1763] The device records the time of completion of reading (e.g., 18:00 on October 2, 2023) and sends it to the server.

[1764] The server receives the reading completion information and generates and schedules the quiz.

[1765] The quiz timings will be set for 2 days (October 4th), 14 days (October 16th), and 60 days (December 1st) after the reading is completed.

[1766] Generative AI analyzes the contents of the book and creates quiz questions.

[1767] 3. Emotional Engine Activation

[1768] When a user starts a quiz, the device's camera and microphone collect and analyze the user's emotions (e.g., the emotion engine determines that the user is relaxed).

[1769] The emotion engine sends the results to the server.

[1770] 4. Quiz Notifications and Coordination

[1771] When it's time for a quiz, the server takes into account the results of the emotion engine and adjusts the notification message.

[1772] Example: On October 4th, a push notification will be sent saying "It's time for a review quiz!"

[1773] 5. Conducting a quiz

[1774] The user confirms the notification and starts the quiz screen.

[1775] The terminal displays a quiz screen and the user inputs an answer.

[1776] The difficulty of the quiz is adjusted to suit the user's emotional state.

[1777] 6. Evaluation results and feedback

[1778] The user answers the quiz, and the terminal transmits the answer to the server.

[1779] The server evaluates the answer and gives an 80% correct answer rate.

[1780] The server generates feedback and, based on the results of the emotion engine, sends a message to the device saying, "Great! Your memory is well-established. Keep up the great work!"

[1781] The terminal displays a feedback message to the user.

[1782] This invention aims to provide more effective and personalized learning by taking into account the user's emotional state. By combining it with an emotion engine, it is possible to review at the most appropriate time and with the most appropriate content for the user, significantly improving the efficiency and enjoyment of learning.

[1783] The processing flow will be explained below.

[1784] Step 1:

[1785] The user downloads an e-book app on their device and creates an account.

[1786] The user enters their name, email address, and password.

[1787] The device sends the input information to the server, which then stores the account in a database.

[1788] Step 2:

[1789] The user selects an e-book.

[1790] The device displays a list of e-books, and the user selects the book they want to read.

[1791] The user selects the Study Guide and begins reading.

[1792] The device records the reading start time and sends it to the server.

[1793] The server initiates the reading session and stores it in a database.

[1794] Step 3:

[1795] The user finishes reading the e-book.

[1796] When the user finishes reading the last page, the device records the time it took to finish reading.

[1797] The device sends the reading time to the server, which stores it in a database.

[1798] Step 4:

[1799] The server sets the timing for generating the quiz based on the reading completion information.

[1800] The server calculates the timing of 2 days (48 hours), 14 days, and 60 days after the end of reading and sets the schedule for generating the quiz.

[1801] Step 5:

[1802] The server uses generated AI to analyze the contents of the book that has been read.

[1803] Generative AI extracts key points from text and creates quizzes.

[1804] The quiz will consist of multiple choice and free-form questions.

[1805] Step 6:

[1806] When the quiz timing is reached, the server will send a push notification to the device.

[1807] For example, you will receive a notification saying, "Take the quiz two days after you finish reading."

[1808] Step 7:

[1809] The user confirms the notification and starts the quiz.

[1810] The user clicks the link in the notification message, and the device displays the quiz screen.

[1811] The user answers the quiz.

[1812] Step 8:

[1813] The terminal transmits the user's response data to the server.

[1814] The server evaluates the answers and calculates the accuracy rate, etc.

[1815] The evaluation results are recorded in the user's database.

[1816] Step 9:

[1817] When a user starts a quiz, the emotion engine kicks in.

[1818] The device's camera and microphone are used to analyze the user's facial expressions and voice to determine their emotional state.

[1819] The emotion engine sends the user's emotion data to the server.

[1820] Step 10:

[1821] The server adjusts the quiz content and the timing of the next notification based on the emotional data.

[1822] For example, if it is determined that the user is tired, it may present questions with lower difficulty or postpone notifications.

[1823] When the server is ready for the quiz, it will send the following push notification to the user's device:

[1824] Step 11:

[1825] The server generates feedback based on the evaluation results.

[1826] If the score is high, create a positive message such as "Great! Your memory is well-established."

[1827] If the score is low, feedback is generated that includes study advice such as "Please review the following points."

[1828] Step 12:

[1829] The server sends a feedback message to the terminal.

[1830] The device displays feedback to the user.

[1831] Example 2

[1832] 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."

[1833] In conventional learning systems, there are limited ways for users to effectively check their understanding of an e-book after they have finished reading it, and the timing for reviewing the learning content is fixed, making it difficult to maximize the learning effect of each individual user. Furthermore, conventional systems do not take into account the user's emotional state, which creates the risk of the learning load becoming too high and lowering user motivation.

[1834] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for detecting the timing when the user finishes reading an e-book, means for generating a quiz based on a specific period after the completion of reading (2 days, 14 days, or 60 days), means for notifying the user terminal of the generated quiz, means for collecting and evaluating quiz answer results, means for providing feedback to the user based on the evaluation results, emotion recognition means for recognizing the user's emotion, and means for adjusting the quiz content and notification timing based on the emotion recognition data. This enables review at the optimal timing and content according to each user's emotional state, thereby improving learning effectiveness and motivation.

[1835] "User" refers to an individual who operates this system to read e-books and answer quizzes.

[1836] "Device" refers to any computer system used by a user that can run an e-book app, including, for example, a smartphone, tablet, or PC.

[1837] "Server" refers to a computer system that receives data from the terminal, processes it, and generates appropriate feedback and quizzes.

[1838] The "timing of completion of reading" refers to the time when the user has finished reading all the pages of the electronic book.

[1839] "Quiz generation" refers to the process of analyzing the content of an e-book and creating questions based on a specific period after reading.

[1840] "Notification" refers to the process of sending a push notification or alert to the user's device when the generated quiz is ready.

[1841] "Answer result" refers to the answer entered by the user to the quiz.

[1842] "Evaluation" refers to the process of analyzing the user's answers and measuring the percentage of correct answers and learning progress.

[1843] "Feedback" refers to specific advice or messages provided to users based on the evaluation results to improve their learning effectiveness.

[1844] "Emotion recognition" refers to the process of analyzing a user's facial expressions and voice data collected using the device's camera and microphone to determine the user's emotional state.

[1845] "Emotion recognition data" refers to data obtained through an emotion recognition process that indicates a user's emotional state.

[1846] "Adjustment" refers to the process of changing the content of the quiz or the timing of notifications based on emotion recognition data.

[1847] This invention is a system that detects when a user has finished reading an e-book, generates and notifies a user of a quiz after a specific period of time, evaluates the results of the quiz and provides feedback, and combines it with an emotion recognition engine that recognizes the user's emotions. This system operates based on the roles of the server, terminal, and user.

[1848] Specific hardware includes devices such as smartphones, tablets, and PCs. Servers are built as cloud servers or dedicated servers. Software includes e-book apps, emotion recognition engines, generative AI models, etc.

[1849] 1. User registration and reading record

[1850] A user opens an e-book app and creates an account. Specifically, the user enters their name, email address, and password, and the device sends that information to the server. The server saves the account information in a database and notifies the user when the account is complete. When the user selects an e-book and starts reading, the device records the reading start time and sends it to the server. The server starts the reading session and saves the progress in a database.

[1851] 2. Reading Completion and Quiz Generation

[1852] When a user finishes reading an e-book, the device records the time the user has finished reading and sends it to the server. The server then stores this information in a database and generates a quiz for a specific period of time after the user has finished reading (for example, 2 days, 14 days, or 60 days later). The generative AI model analyzes the content of the e-book, extracts key points, and creates the quiz.

[1853] 3. Emotional engine for recognizing user emotions

[1854] When a user receives a quiz notification and starts the quiz, the device's camera and microphone collect the user's facial expressions and voice data, which are then analyzed by an emotion recognition engine. The emotion recognition engine determines the user's emotional state (e.g., relaxed, tired) and sends the data to the server.

[1855] 4. Quiz Notifications and Adjustments

[1856] The server adjusts the content of the quiz and the timing of notifications based on emotion recognition data. For example, if the server determines that the user is tired, it will select less difficult questions or postpone notifications. When the quiz is ready, the server sends a push notification to the user's device. For example, it could send a message saying, "It's time for a review quiz!"

[1857] 5. Quiz

[1858] The user confirms the notification and starts the quiz. The device displays the quiz screen and the user enters their answers. Questions are presented in multiple choice or free-form format, and the appropriate content is selected based on the analysis results of the emotion recognition engine.

[1859] 6. Recording and feedback of results

[1860] The user answers the quiz, and the device sends the results to the server. The server evaluates the answer (for example, "80% correct") and records it in a database. Based on the evaluation results, the server provides feedback to the user. For example, if the user answers correctly, the server may generate a message such as "Great! Your memory is well-established. Keep up the good work!", adjusting the tone and content of the feedback based on the results of the emotion recognition engine. The feedback message is sent to the user's device, where it is displayed to the user.

[1861] Example prompt sentence:

[1862] "Detect when a user has finished reading a specific e-book and generate a quiz based on a specific period after reading. Also, recognize the user's emotional state and adjust the optimal quiz content and notification timing."

[1863] The above system provides personalized learning that takes into account the user's emotional state, and is expected to significantly improve the efficiency and enjoyment of learning.

[1864] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1865] Step 1:

[1866] Create an account

[1867] A user opens an e-book app and enters their name, email address, and password.

[1868] Enter your name, email address, and password.

[1869] Output: The user's account information.

[1870] The terminal sends the input information to the server.

[1871] The server saves the account information to the database, performs a database update operation, and logs the completion of the save.

[1872] Step 2:

[1873] Select an e-book and start reading

[1874] The user selects an e-book in the app (e.g., "Study Guide").

[1875] Input: Information about the selected e-book.

[1876] Output: Triggers the reading start event.

[1877] The terminal records the user's reading start time and sends that information to the server.

[1878] The server starts a reading session and saves the progress to a database, writes the start time to the database, and generates a session ID.

[1879] Step 3:

[1880] Record reading time

[1881] The user reads the e-book to the end.

[1882] Input: Information on the page you have read.

[1883] Output: Triggers a read event.

[1884] The device records the time it takes to finish reading and sends that information to the server.

[1885] The server saves the completion information to a database, records the completion time, and updates the relevant session data.

[1886] Step 4:

[1887] Quiz Generation

[1888] The server sets a specific period after reading (e.g., 2 days, 14 days, or 60 days).

[1889] Input: Reading information, specific period.

[1890] Output:Quiz schedule.

[1891] The server uses a generative AI model to analyze the contents of the e-book, extract key points, and create quiz questions.

[1892] Input: E-book text data.

[1893] Output: A set of quiz questions.

[1894] The server stores the generated quiz in a database.

[1895] Step 5:

[1896] Quiz Notifications

[1897] When the server is ready for the quiz based on the specified quiz notification timing, it sends a push notification to the user terminal.

[1898] Input: Quiz schedule, user's device information.

[1899] Output: Push notification (e.g. "Time for a review quiz!").

[1900] The server records the notification content and timing and sets retransmission logic.

[1901] Step 6:

[1902] Emotion recognition and quiz start

[1903] The user receives the quiz notification and starts the quiz.

[1904] Input: Acknowledgement of notification receipt.

[1905] Output: Quiz screen display.

[1906] The device's camera and microphone collect the user's facial expressions and voice data, which is then analyzed by an emotion recognition engine.

[1907] Input: User's facial expressions and voice data.

[1908] Output: Emotion recognition result (e.g. "Relaxed" or "Tired").

[1909] The emotion recognition engine sends the analysis results to the server.

[1910] Step 7:

[1911] Adjustment and implementation of quiz content

[1912] The server adjusts the content and difficulty of the quiz based on the emotion recognition data.

[1913] Input: Emotion recognition data, generated quiz questions.

[1914] Output: The adjusted quiz questions.

[1915] The terminal displays the adjusted quiz questions and the user inputs the answers.

[1916] Input: The user's answer.

[1917] Output: Response data.

[1918] Step 8:

[1919] Submitting and evaluating answer results

[1920] The terminal transmits the user's answer results to the server.

[1921] Input: Response data.

[1922] Output: Sending data to the server.

[1923] The server evaluates the answer results and stores the evaluation results in a database.

[1924] Input: Response data.

[1925] Output: Evaluation results such as accuracy rate.

[1926] Based on the evaluation results, the server generates feedback.

[1927] Step 9:

[1928] Providing Feedback

[1929] The server provides feedback to the user based on the evaluation results.

[1930] Input: Evaluation results, emotion recognition data.

[1931] Output: A feedback message (e.g., "Great! Your memory is solid. Keep it up!").

[1932] The terminal displays a feedback message to the user.

[1933] (Application example 2)

[1934] 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."

[1935] Conventional learning systems using e-books provide quizzes uniformly without considering the user's emotions, which means that they are unable to provide optimal review timing or difficulty for each individual user. Furthermore, to maximize learning efficiency, it is important to adjust the timing and content according to the user's emotional state, but no such system has existed. Furthermore, when using e-payment services, users have had the problem of not receiving appropriate feedback after selecting a product.

[1936] 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.

[1937] In this invention, the server includes a means for detecting when a user has finished reading an e-book, a means for generating a quiz based on a specific period of time since the user finished reading, and a means for recognizing the user's emotions using an emotion engine. This makes it possible to adjust the content of the quiz and the timing of notifications according to the user's emotional state and provide personalized feedback. Furthermore, emotion recognition can be utilized when using electronic payment services, providing appropriate feedback and recommendations to the user to increase their motivation to purchase.

[1938] The "means for detecting when the user has finished reading the e-book" is a mechanism that automatically detects when the user has read to the last page of the e-book and records that point in time.

[1939] The "means for generating quizzes" is a function that analyzes the contents of an e-book and creates multiple questions based on a specific algorithm.

[1940] "Means for notifying the user terminal" refers to a method for sending quizzes and other information to the user's device as alerts or push notifications.

[1941] "Means for collecting and evaluating quiz answer results" refers to a system for collecting data on users' answers to quizzes and analyzing and evaluating their accuracy and completeness.

[1942] The "means for providing feedback" is a system that returns appropriate advice and comments to the user based on the evaluation results of the quiz.

[1943] The "means for recognizing a user's emotions using an emotion engine" is a device equipped with an algorithm that analyzes a user's facial expressions, voice, and other biometric data to determine their psychological state.

[1944] The "means for adjusting the quiz content and notification timing according to the user's emotions" is a mechanism for optimizing the difficulty of the quiz and the timing of sending notifications based on the user's current emotional state.

[1945] This invention is a system that detects when a user has finished reading an e-book, generates a quiz after a specific period of time has passed, notifies the user of the quiz, evaluates the answers, and provides feedback.The system is characterized by using an emotion engine to recognize the user's emotions and adjusts the quiz content and notification timing accordingly.

[1946] System Configuration

[1947] The system consists of the following major hardware and software components:

[1948] Server: Contains the database, quiz generation algorithm, and emotion engine.

[1949] User device: A device such as a smartphone that is equipped with a camera and microphone.

[1950] Database: Stores user reading records, emotion data, and quiz results.

[1951] Emotion engine: A software module that recognizes emotions by analyzing the user's facial expressions and voice.

[1952] Quiz generation module: Analyzes the content of the e-book and generates quizzes based on key points.

[1953] System Operation

[1954] 1. User registration and reading record

[1955] Users create an account using a smartphone app, select an e-book, and begin reading. The device records the start time and sends it to the server, which then starts the reading session and stores the progress in a database.

[1956] 2. Reading Completion and Quiz Generation

[1957] When a user finishes reading an e-book, the device records the reading time and sends it to the server. The server receives the reading completion information and stores it in a database. A quiz is then generated and prepared based on a specific period after the reading (2 days, 14 days, or 60 days later). A generative AI model is used to analyze the content of the e-book, extract key points, and generate the quiz.

[1958] 3. Emotional engine for recognizing user emotions

[1959] When a user starts a quiz, the device's camera and microphone are used to recognize the user's emotions. The emotion engine analyzes the user's emotional data and sends this data to the server.

[1960] 4. Quiz Notifications and Adjustments

[1961] The server adjusts the quiz content and notification timing based on the emotion data. For example, if it determines that the user is tired, it can present easier questions or postpone notifications. When the quiz is ready, the server sends a push notification to the user's device. The notification reads, "Time for a review quiz!"

[1962] 5. Quiz and feedback

[1963] The user confirms the notification and begins the quiz. The quiz screen displays questions tailored to the user's emotional state, and the user enters their answers. The answers are sent from the device to the server, which evaluates them and provides feedback. For example, if the user answers correctly, a positive message such as "your memory is firmly established" is sent.

[1964] Examples of specific examples and prompts

[1965] For example, if a user starts reading the e-book "Study Guide" and finishes it, and the emotion engine determines that they are in a "Relaxed" state, the quiz notification will look like this:

[1966] Quiz notification example

[1967] "Time for a review quiz!"

[1968] Prompt Sentence Examples

[1969] Feedback when the user is relaxed:

[1970] Feedback message: "Amazing! I recommend you buy this product."

[1971] This allows for personalized quizzes and feedback that take into account the user's emotional state.

[1972] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1973] Step 1:

[1974] User registration and reading log

[1975] A user creates an account using a smartphone app and enters their name, email address, and password. The device sends this information to the server, which stores the account information in a database. When the user selects an e-book and begins reading, the device records the start time of the reading and sends it to the server. The server starts the reading session and stores the progress in a database.

[1976] Input: User information (name, email address, password) and e-book selection information

[1977] Data processing and calculation: User information verification and storage, recording of reading start time

[1978] Output: User account created, reading session started

[1979] Step 2:

[1980] Reading Completion and Quiz Generation

[1981] When a user finishes reading an e-book, the device records the reading time and sends it to the server. The server receives the reading completion information and stores it in a database. It then generates a quiz based on a specific period after reading (e.g., 2 days, 14 days, or 60 days). A generative AI model is used to analyze the content of the e-book, extract key points, and create a quiz.

[1982] Input: Reading time, e-book content

[1983] Data processing and calculation: saving reading completion information, generating quizzes

[1984] Output:Quiz preparation

[1985] Step 3:

[1986] Recognizing user emotions with an emotion engine

[1987] When a user starts a quiz, the device's camera and microphone capture the user's facial expressions and voice, and send them to the emotion engine, which analyzes them, determines the user's emotional state, and sends the results to the server.

[1988] Input: User's facial expression and voice data

[1989] Data processing and calculation: Analysis of emotional data

[1990] Output: User's emotional state

[1991] Step 4:

[1992] Quiz Notifications and Adjustments

[1993] The server adjusts the quiz content and notification timing based on the emotion data. For example, if the server determines that the user is "tired," it can lower the difficulty of the questions or postpone the notification. The server sends a push notification to the user's device when the quiz is ready. It also sends a message saying, "It's time for a review quiz!"

[1994] Input: User's emotional state, prepared quiz

[1995] Data processing and calculation: Adjustment of quiz content and notification timing

[1996] Output: Adjusted quiz and notifications

[1997] Step 5:

[1998] Quiz and feedback

[1999] The user confirms the quiz notification and starts the quiz. The device displays the quiz screen, and the user answers the questions. The answers are sent from the device to the server, which evaluates them. Based on the evaluation, personalized feedback is generated; for example, if the user answers correctly, a message such as "Your memory is firmly established" is sent to the user.

[2000] Input: User's quiz answer

[2001] Data processing and calculation: Evaluation of quiz answers, generation of feedback

[2002] Output: Feedback message

[2003] By clarifying the specific operations and inputs / outputs, the overall flow of the system becomes easier to understand and implement. The above step-by-step process allows users to have a more personalized and effective learning experience.

[2004] 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.

[2005] 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.

[2006] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2007] 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.

[2008] 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.

[2009] 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.

[2010] 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).

[2011] 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.

[2012] 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."

[2013] 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.

[2014] 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).

[2015] 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.

[2016] 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.

[2017] 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.

[2018] 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.

[2019] 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.

[2020] 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.

[2021] 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.

[2022] 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.

[2023] 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.

[2024] 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.

[2025] The following is further disclosed regarding the above embodiment.

[2026] (Claim 1)

[2027] means for detecting when a user has finished reading an electronic book;

[2028] A means for generating quizzes based on specific time periods after completion of the reading (2 days, 14 days, 60 days);

[2029] a means for notifying a user terminal of the generated quiz;

[2030] a means for collecting and evaluating quiz responses;

[2031] means for providing feedback to the user based on the evaluation results;

[2032] A system including:

[2033] (Claim 2)

[2034] 2. The system according to claim 1, which analyzes the contents of an e-book, extracts important points, and generates a quiz.

[2035] (Claim 3)

[2036] The system according to claim 1, wherein quizzes are presented in multiple choice or free description format, making learning fun and game-like.

[2037] "Example 1"

[2038] (Claim 1)

[2039] means for detecting when a user has finished reading an electronic book;

[2040] A means for generating quizzes based on specific time periods after completion of the reading (2 days, 14 days, 60 days);

[2041] A means to send prompts to a generative AI model, analyze the contents of the e-book, and extract important points.

[2042] a means for notifying a user terminal of the generated quiz;

[2043] a means for collecting and evaluating quiz responses;

[2044] means for providing feedback to the user based on the evaluation results;

[2045] A system including:

[2046] (Claim 2)

[2047] 2. The system according to claim 1, further comprising means for the server to set the timing of the quiz notification and to send a push notification to the user terminal.

[2048] (Claim 3)

[2049] 2. The system according to claim 1, further comprising means for providing quizzes in multiple choice or free description format, allowing users to enjoy the quiz as if it were a game.

[2050] "Application Example 1"

[2051] (Claim 1)

[2052] means for detecting when a user has finished viewing the e-book and the learning content;

[2053] A means for generating quizzes based on specific time periods after reading or viewing (2 days, 14 days, 60 days);

[2054] a means for notifying a user terminal of the generated quiz;

[2055] a means for collecting and evaluating quiz responses;

[2056] means for providing feedback to the user based on the evaluation results;

[2057] A system including:

[2058] (Claim 2)

[2059] The system according to claim 1, which analyzes the contents of e-books and learning content, extracts important points, and generates quizzes.

[2060] (Claim 3)

[2061] The system according to claim 1, wherein quizzes are presented in multiple choice or free description format, making learning fun and game-like.

[2062] "Example 2: Combining Emotion Engines"

[2063] (Claim 1)

[2064] means for detecting when a user has finished reading an electronic book;

[2065] A means for generating quizzes based on specific time periods after completion of the reading (2 days, 14 days, 60 days);

[2066] a means for notifying a user terminal of the generated quiz;

[2067] a means for collecting and evaluating quiz responses;

[2068] means for providing feedback to the user based on the evaluation results;

[2069] emotion recognition means for recognizing an emotion of a user;

[2070] A means for adjusting the content of the quiz and the timing of notifications based on emotion recognition data;

[2071] A system including:

[2072] (Claim 2)

[2073] 2. The system according to claim 1, which analyzes the contents of an e-book, extracts important points, and generates a quiz.

[2074] (Claim 3)

[2075] The system according to claim 1, wherein quizzes are presented in multiple choice or free description format, making learning fun and game-like.

[2076] "Application example 2 when combining emotion engines"

[2077] (Claim 1)

[2078] means for detecting when a user has finished reading an electronic book;

[2079] A means for generating quizzes based on specific time periods after completion of the reading (2 days, 14 days, 60 days);

[2080] a means for notifying a user terminal of the generated quiz;

[2081] a means for collecting and evaluating quiz responses;

[2082] means for providing feedback to the user based on the evaluation results;

[2083] means for recognizing a user's emotion using an emotion engine;

[2084] A means for adjusting the content of the quiz and the timing of notifications according to the user's emotions;

[2085] A system including:

[2086] (Claim 2)

[2087] 2. The system according to claim 1, which analyzes the contents of an e-book, extracts important points, and generates a quiz.

[2088] (Claim 3)

[2089] The system according to claim 1, wherein quizzes are presented in multiple choice or free description format, making learning fun and game-like. [Explanation of symbols]

[2090] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for detecting when a user has finished reading an electronic book; means for generating a quiz based on a predetermined period of time after completion of the reading; a means for notifying a user terminal of the generated quiz; a means for collecting and evaluating quiz responses; means for providing feedback to the user based on the evaluation results; A system including:

2. 2. The system according to claim 1, wherein the system analyzes the contents of an electronic book, extracts important points, and generates a quiz.

3. 2. The system according to claim 1, wherein quizzes are given in multiple choice or free description format, making learning fun and game-like.

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