System

Abstract

A system is provided.SOLUTION: A system comprising: means for obtaining text data from a user; means for obtaining knowledge level information of the user from a database; means for using generative artificial intelligence to convert the text data into a simplified expression or a summary according to the knowledge level of the user; means for obtaining a question from the user and generating an answer to the question using the generative artificial intelligence; and means for transmitting the converted simplified expression or summary text and the generated answer to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] While the usefulness of reading is widely recognized, many people are unable to read books thoroughly due to a lack of time, difficult content, or a lack of prior knowledge. In particular, when it comes to books containing specialized content, it is difficult to provide information appropriately tailored to the reader's comprehension level and interests, which impedes the reading experience. This can result in a decline in individual learning efficiency, which could lead to a shrinking publishing market and a decline in writers' motivation. [Means for solving the problem]

[0005] To address the above-mentioned issues, this invention provides a reading support system using generative AI technology. Specifically, we propose a system in which a user inputs the text data they want to read, and a server converts that data into simplified expressions or summaries appropriate to the user's knowledge level. In this system, the user's knowledge level is retrieved from a database, and the generative AI generates a summary of the text and answers to any questions. It also provides quizzes and surveys to assess the user's level of comprehension, allowing the reading content to be further customized based on the results. This supports the reader's comprehension while maintaining the quality of the information, lowering the barrier to reading.

[0006] "User" refers to an individual or organization that uses this system to read.

[0007] "Text data" refers to digital data containing text or content to be read.

[0008] "Database" refers to a collection of digital information that stores information such as a user's knowledge level and makes it accessible as needed.

[0009] "Knowledge level" refers to an indicator that evaluates the depth and scope of knowledge a user has in a particular field.

[0010] "Generative artificial intelligence" refers to a system that uses AI technology, including natural language processing, to generate simplified expressions of text and answers to questions.

[0011] "Simplified expression" refers to sentences in which complex text is converted into an easily understandable format according to the user's level of knowledge and understanding.

[0012] A "summary" refers to a short sentence that extracts only the core parts of text data.

[0013] "Quiz or Survey" refers to a question-based approach to assessing a user's level of knowledge.

[0014] "Packaging" refers to the process of preparing user-input data or system-generated data in a format that can be sent in bulk.

[0015] "Server" refers to the computer system that processes data from users and operates generative AI models to provide the necessary information.

[0016] "Interface" refers to the screen and input format that users use to operate the system. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11]FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] 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.

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

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

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

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

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

[0032] 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.

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

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] This invention provides a system that utilizes generative AI to improve a user's reading experience. Specific embodiments of this system are described below.

[0039] System Overview

[0040] This system is mainly composed of three elements: a server, a terminal, and a user. The user operates the system using a terminal, and the server uses a generative AI to process the necessary text and generate answers.

[0041] Server-side behavior

[0042] Acquiring and processing text data

[0043] The server receives text data sent by the user. For example, consider the case where the text data received is, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems." The server retrieves the user's knowledge level from a database and uses generative AI to convert this text data into a simplified expression or summary that is easy for the user to understand. For example, a beginner user would be provided with the simplified expression, "This technology is difficult, but simply applying the basics will make the system run more efficiently."

[0044] Generating answers to user questions

[0045] The server also receives questions sent by users and generates answers to those questions using the same generative AI. For example, in response to the question, "What does it mean to improve efficiency?", the server generates the answer, "Improved efficiency means that the system can run faster or get the job done using fewer resources."

[0046] Creating and Sending a Response

[0047] The generated shorthand and answers are packaged and sent to the user, who receives this information to improve their reading comprehension.

[0048] Operation on the terminal side

[0049] Providing a user interface

[0050] The terminal provides an interface for the user to input text data and questions, including a field for entering the reading passage and a field for entering questions.

[0051] Sending and Displaying Data

[0052] After the user enters text data and a question, the device sends this information to the server. After receiving a response from the server, the device displays the received simplified expression and answer to the user, allowing the user to obtain information in an easy-to-understand format.

[0053] User behavior

[0054] Enter text data and questions

[0055] The user inputs part of the book they are reading as text data into the terminal, as well as any questions that arise while reading the book.

[0056] Verify the information

[0057] The user can check the simple expressions and answers sent from the server to confirm that their understanding has deepened. This allows the user to efficiently read through even difficult content, improving learning efficiency.

[0058] Specific examples

[0059] For example, a user might be reading a technical book and come across the following paragraph:

[0060] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[0061] The user inputs this paragraph into the system, and also inputs the question, "What does it mean to improve efficiency?" The server confirms that the user's knowledge level is beginner level, and converts the paragraph into a simple expression, "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question, "Improved efficiency means that the system will run faster and be able to complete tasks using fewer resources," and provides this to the user via their terminal.

[0062] In this way, users can obtain technical information in an easy-to-understand format, improving their reading experience.

[0063] The processing flow will be explained below.

[0064] Step 1:

[0065] Users log in to their device and select a book to begin reading. After the book is loaded, users copy and paste the portion of the text they want to read into the device's interface.

[0066] Step 2:

[0067] The user inputs the paragraph of text he is reading into an input field on the terminal, and at the same time inputs any questions he has into the input field.

[0068] Step 3:

[0069] The terminal receives the text data and question input by the user, and after verifying that the data has been received correctly, generates package data including the user's identification information.

[0070] Step 4:

[0071] The terminal sends this package data, which includes the user ID, text data, and questions, to the server.

[0072] Step 5:

[0073] The server receives the package data sent from the terminal, and then retrieves the user's knowledge level information from the database based on the user ID.

[0074] Step 6:

[0075] Based on the acquired knowledge level information, the server uses a generation AI to convert the text data into a format that is easy for the user to understand (for example, simple expressions or summaries).

[0076] Step 7:

[0077] The server uses AI to generate answers to questions entered by users, creating appropriate answers based on text data related to the question.

[0078] Step 8:

[0079] The server packages the converted shorthand or summary text and the generated answer to create response data.

[0080] Step 9:

[0081] The server then sends the response data to the terminal, which includes a simplified expression or summary text to help the user understand, and the answer to the question.

[0082] Step 10:

[0083] The terminal receives the response data from the server, analyzes the contents of the response data, and prepares to display it to the user.

[0084] Step 11:

[0085] The terminal displays the simplified expressions or summary text sent from the server and the answers to the questions to the user, allowing the user to confirm the displayed content and deepen their understanding.

[0086] Example 1

[0087] 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."

[0088] Currently, many people struggle to understand the content of specialized books and technical documents. Beginners and users with little prior knowledge find technical terminology and complex explanations particularly difficult to understand. Furthermore, the inability to quickly find answers to questions that arise while reading leads to a decline in learning efficiency. In these circumstances, there is a need for a system that can convert text into an easy-to-understand format and provide appropriate answers to questions.

[0089] 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.

[0090] In this invention, the server includes means for acquiring text data and questions from a user, means for a terminal to transmit the text data and questions to the server, means for the server to receive the text data and acquire user knowledge level information from a database, means for converting the text data into a simplified expression or a summary using a generative AI model, means for generating an answer to the user's question using the generative AI model, means for transmitting the converted simplified expression or summary text and the generated answer to the user, and means for the terminal to display the simplified expression and the answer to the user. This allows users to obtain specialized content in an easy-to-understand format and quickly find answers to questions that arise while reading.

[0091] The "server" is a central system that receives data from users, retrieves information from a database, processes and generates data using generative AI models, and sends the results to users.

[0092] A "terminal" is a device operated by a user, which inputs text data and questions, transmits them to a server, and receives and displays responses from the server.

[0093] A "user" is a person who uses the system to input text data, ask questions, and receive information from the server.

[0094] "Text data" refers to a portion of a book or document that a user is reading, and is text information that is input into the system.

[0095] "Questions" refer to questions or unclear points that arise when the user is reading the text data.

[0096] "Knowledge level information" is information that indicates the user's knowledge and level of understanding, and is stored in a database.

[0097] A "generative AI model" is an AI system used to convert text data into simple expressions or summaries and generate answers to questions.

[0098] "Simplified expressions" are sentences that convert specialized or complex text data into easy-to-understand sentences that suit the user's level of knowledge.

[0099] A "summary" is a piece of text that provides the main points or content of text data in an abbreviated form.

[0100] An "answer" is a generated answer to a question posed by a user.

[0101] A "database" is a storage device that stores user knowledge level information and other necessary information.

[0102] "Packaging" is the process of formatting data sent from a user or a server into a format suitable for transmission.

[0103] The present invention provides a system for improving a user's reading experience by utilizing generative artificial intelligence. A specific embodiment of this system will be described below.

[0104] System Overview

[0105] This system is mainly composed of three elements: a server, a terminal, and a user. The user operates the system using a terminal, and the server uses generative artificial intelligence to process the necessary text and generate answers.

[0106] Server-side behavior

[0107] Acquiring and processing text data

[0108] The server receives text data sent by a user. For example, consider the case where the text data received is, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems." The server obtains the user's knowledge level information from the database and uses generative artificial intelligence to convert this text data into a simplified expression or summary that is easy for the user to understand. For example, a beginner user would be provided with the simplified expression, "This technology is difficult, but simply applying the basics will make the system run more efficiently."

[0109] Generating answers to user questions

[0110] The server also receives questions sent by users and generates answers to those questions using generative AI. For example, in response to the question "What does it mean to improve efficiency?", the server generates the answer "Improved efficiency means that the system can run faster or perform its work using fewer resources."

[0111] Creating and Sending a Response

[0112] The server packages the generated shorthand and answers and sends the content to the user, who receives this information to improve their reading comprehension.

[0113] Operation on the terminal side

[0114] Providing a user interface

[0115] The terminal provides an interface for the user to input text data and questions, including a field for entering the reading passage and a field for entering questions.

[0116] Sending and Displaying Data

[0117] After the user enters text data and a question, the device sends this information to the server. After receiving a response from the server, the device displays the received simplified expression and answer to the user, allowing the user to obtain information in an easy-to-understand format.

[0118] User behavior

[0119] Enter text data and questions

[0120] The user inputs part of the book they are reading as text data into the terminal, as well as any questions that arise while reading the book.

[0121] Verify the information

[0122] The user can check the simple expressions and answers sent from the server to confirm that their understanding has deepened. This allows the user to efficiently read through even difficult content, improving learning efficiency.

[0123] Specific examples

[0124] For example, a user might be reading a technical book and come across the following paragraph:

[0125] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[0126] The user inputs this paragraph into the system, and also inputs the question, "What does it mean to improve efficiency?" The server confirms that the user's knowledge level is beginner level and converts the paragraph into a simple expression: "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question: "Improved efficiency means that the system will run faster or be able to complete tasks using fewer resources," and provides this to the user via their device. In this way, the user can obtain information, even if it is technical, in an easy-to-understand format, improving their reading experience.

[0127] Prompt Sentence Examples

[0128] "Please summarize the following text in a way that is easy for a beginner to understand:

[0129] "This technology is highly complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[0130] Please answer the following questions:

[0131] "What does it mean to be more efficient?"

[0132] The above is an embodiment of the present invention.

[0133] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0134] Step 1:

[0135] The user inputs text data and a question.

[0136] How it works: The user accesses a dedicated interface on the device and enters part of the book they are reading as text data. They also enter any questions they may have while reading the book into a separate field in the same interface.

[0137] Input: The user types, for example, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large systems," and then types in a question, "What does it mean to improve efficiency?"

[0138] Output: The input text data and questions.

[0139] Step 2:

[0140] The terminal transmits the text data and the question to the server.

[0141] Specific operation: The device acquires the text data and questions entered by the user and sends this information to the server. The device sends the data using an HTTP POST request.

[0142] Input: Text data and questions entered by the user.

[0143] Output: Text data and questions sent to the server.

[0144] Step 3:

[0145] The server receives the text data and retrieves the user's knowledge level information from a database.

[0146] Specific operation: The server analyzes the text data and questions received from the terminal, then retrieves the user's profile information from the database and checks the user's knowledge level.

[0147] Input: Text data and questions sent from the terminal.

[0148] Output: Parsed text data, user knowledge level information.

[0149] Step 4:

[0150] The server uses a generative artificial intelligence model to convert the text data into a simplified representation.

[0151] Specific operation: The server inputs text data into the generative AI model and generates a simplified representation based on the user's knowledge level. The specific prompt is passed to the generative AI model in the form of "Please summarize the following text in a form that is easy for beginners to understand: 'This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems.'"

[0152] Input: Parsed text data, user knowledge level information.

[0153] Output: Simplified text data.

[0154] Step 5:

[0155] The server uses a generative artificial intelligence model to generate answers to the user's questions.

[0156] Specific operation: The server passes the user's question to the generative AI model to generate an answer. The specific prompt is "Please answer the following question: 'What does it mean to improve efficiency?'"

[0157] Input: User's question.

[0158] Output: The generated answer.

[0159] Step 6:

[0160] The server transmits the generated simple expressions and answers to the terminal.

[0161] Specific operation: The server packages the generated simple representation and answer and sends them to the terminal. Here, the data is again packaged in JSON format and sent using an HTTP POST request.

[0162] Input: Simplified text data, generated answers.

[0163] Output: Shorthands and answers sent to the device.

[0164] Step 7:

[0165] The terminal displays the shorthand and the answer to the user.

[0166] Specific operation: The terminal analyzes the simple expressions and answers received from the server and displays them on the user interface. Specifically, a dedicated display area displays the simple expression "This technology is difficult, but by simply applying the basics, the system can run more efficiently" and the answer to the question "Improved efficiency means that the system will be able to run faster and complete tasks using fewer resources than before."

[0167] Input: Shorthands and answers sent to the device.

[0168] Output: The shorthand and answers that are displayed to the user.

[0169] Step 8:

[0170] Users review shorthand and answers to deepen their understanding.

[0171] Specific actions: The user checks the simple expressions and answers displayed on the device to confirm that their understanding has improved.

[0172] Input: The shorthand and answer displayed on the terminal.

[0173] Output: A user with a better understanding.

[0174] (Application example 1)

[0175] 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."

[0176] Currently, when reading, readers often encounter difficult content that is difficult to understand. In such cases, readers are unable to enjoy the reading experience and their learning efficiency decreases. Furthermore, when selecting a book in a store, they often end up purchasing it without understanding the details of the book, making it difficult to choose the right book. There is a need for a solution to this problem, making reading and selecting books in a store more efficient and effective.

[0177] 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.

[0178] In this invention, the server includes means for acquiring text data from a user, means for acquiring user knowledge level information from a database, means for using a generation AI to convert the text data into simplified expressions or summaries according to the user's knowledge level, means for acquiring questions from the user and generating answers to the questions using the generation AI, means for sending the converted simplified expressions or summary text and the generated answers to the user, and means for having a smart device as the terminal to visually provide the simplified expressions and answers to the user in real time while reading, thereby providing easy-to-understand information in real time while reading and improving the reading experience.

[0179] "User" means an individual who utilizes the system to input text data and receive shorthand or responses.

[0180] "Text data" refers to the text information entered from the book or text the user is reading.

[0181] "Knowledge level information" is information that indicates the user's level of understanding and is stored in a database.

[0182] A "database" is a system that organizes, stores, and manages data such as user knowledge level information.

[0183] "Simplified expression" refers to a sentence that has been converted from the original text data into a form that is easier to understand.

[0184] A "summary" is a sentence that summarizes the main points of the original text data in an abbreviated form.

[0185] "Generative AI" refers to AI that uses generative techniques to generate simplified representations, summaries, and answers to text.

[0186] A "question" is a question or uncertainty that a user has while reading the text.

[0187] An "answer" is a generated answer or explanation to a question.

[0188] "Smart device" means an electronic device that a user can wear or use to receive information in real time.

[0189] The "system" refers to the entire set of mechanisms that receives text data and questions from users, processes them, and generates simplified expressions and answers to provide to users.

[0190] This invention is a system that uses generative AI to improve the user's reading experience. Specific embodiments of this system are described below.

[0191] System Configuration

[0192] The system consists of three elements: the user, the device, and the server. The user inputs text data and questions via the device, and the server processes this data using generative AI and sends the results to the device.

[0193] Server Roles

[0194] The server has the following means:

[0195] 1. How to get text data from the user:

[0196] The server receives text data provided by the user through the terminal.

[0197] 2. How to get user knowledge level information from the database:

[0198] The server retrieves the user's knowledge level information from the database.

[0199] 3. Using generative artificial intelligence to convert text data into simplified representations or summaries:

[0200] The server uses a generative AI model (e.g., OpenAI's GPT model) to convert text data into simplified representations or summaries depending on the user's level of knowledge.

[0201] 4. A means of obtaining questions from users and generating answers to those questions:

[0202] The server takes the question entered by the user and generates an answer to that question using a generative AI model.

[0203] 5. Means for sending the converted shorthand or summary text and generated answer to the user:

[0204] The server sends the generated simple expressions and answers to the terminal.

[0205] Device Role

[0206] The device includes the following features:

[0207] 1. Providing the user interface:

[0208] The terminal provides an interface where the user can enter text data and questions.

[0209] 2. Data transmission and display:

[0210] The user inputs text data and a question into the device, which is then sent to the server, which then receives a response and provides the user with a simple expression and a visual answer in real time.

[0211] Adding specific examples

[0212] For example, a user might be reading a technical book and come across the following paragraph:

[0213] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[0214] The user types this paragraph into their device, along with the question "What does it mean to be more efficient?" The server uses a generative AI model to translate it and generate the following simple phrase and answer:

[0215] Simple: "This technology is difficult, but applying the basics will make your system work more efficiently."

[0216] Answer: "Increased efficiency means that a system can run faster or do its job using fewer resources."

[0217] The results are sent to the terminal, where the user receives a visual summary and answer, and if they have further questions, they can ask them again using the following prompt:

[0218] Please briefly explain the following sentence: Elves have long lifespans and their knowledge has been accumulated over thousands of years. The user's knowledge level is beginner.

[0219]

[0220] A user asked the question: What is an elf? Please provide a clear answer.

[0221] In this way, users can obtain technical information in an easy-to-understand format, improving their reading experience.

[0222] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0223] Step 1:

[0224] The user inputs text data and questions into the terminal.

[0225] As input, the user enters the paragraph or sentence (text data) of the book they are reading and any questions they may have about that paragraph through the terminal. The terminal receives this data and prepares to proceed to the next step.

[0226] Step 2:

[0227] The text data and the question are sent to the server.

[0228] The terminal packages the received text data and question and transmits the packaged data to the server. The transmitted data includes the text data and question entered by the user.

[0229] Step 3:

[0230] The server retrieves the user's knowledge level information from the database.

[0231] The server retrieves information about the user's knowledge level from a database, using the user's identification information as input and obtaining the user's knowledge level information as output.

[0232] Step 4:

[0233] The server uses a generative AI model to convert the text data into a simplified representation or summary.

[0234] Based on the acquired user knowledge level information, the server inputs the text data into a generative AI model (e.g., OpenAI's GPT model) and converts it into a simplified representation or summary. The text data and knowledge level are used as input, and a simplified representation or summary is generated as output.

[0235] Step 5:

[0236] The server uses a generative AI model to generate answers to questions.

[0237] The server inputs the question into a generative AI model to generate the corresponding answer. The question is used as input and the answer is generated as output.

[0238] Step 6:

[0239] The server transmits the converted shorthand or summary text and the generated answer to the terminal.

[0240] The server packages the generated simple expression or summary text and the answer, and transmits the packaged data to the terminal. The transmitted data includes the converted simple expression or summary and the answer to the question.

[0241] Step 7:

[0242] The terminal provides the user with visual shorthand and answers in real time.

[0243] The terminal displays the simple expressions and answers received from the server on the user's smart device and provides them visually. It uses the data sent from the server as input and presents information to the user in real time.

[0244] 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.

[0245] This invention utilizes a system that combines generative AI and an emotion engine to improve the user's reading experience. A specific embodiment of this system is described below.

[0246] System Overview

[0247] This system is mainly composed of three elements: a server, a terminal, and a user. The user operates the system using a terminal, and the server provides the necessary processing using a generative AI and emotion engine.

[0248] Server-side behavior

[0249] Acquiring text data and emotional information

[0250] The server receives the text data and question sent by the user. For example, consider the case where the text data received is, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems." The server then uses an emotion engine to recognize the emotion the user is feeling when typing. The emotion engine analyzes, for example, the voice tone and typing speed to identify the user's emotional state (e.g., "confused," "interested," or "bored").

[0251] Text Processing Based on User Knowledge Level and Sentiment

[0252] The server retrieves the user's knowledge level from the database based on the user ID. Then, based on the retrieved emotion information and knowledge level, it uses generative AI to convert the text data into a format (simplified expression or summary) that is easy for the user to understand. For example, if the user is recognized as "confused," the simplified expression of the text is set to a more understandable level.

[0253] Generate answers to questions and sentiment-based feedback

[0254] The server uses generative AI to generate answers to questions entered by users, and also uses an emotion engine to generate feedback messages (e.g., "You're doing a good job," "You'll understand soon," etc.) based on the user's emotional state.

[0255] Creating and Sending a Response

[0256] The generated shorthand or summary text, the answer to the question, and the sentiment-based feedback are packaged and the response data is sent to the user.

[0257] Operation on the terminal side

[0258] Providing a user interface

[0259] The device provides an interface for users to input text data and questions. The interface includes a field for inputting the reading passage and a field for inputting questions. It also includes an interface (e.g., voice input or face recognition) for the emotion engine to recognize the user's emotions.

[0260] Sending and Displaying Data

[0261] After the user inputs text data and a question, the device sends this information to the server. After receiving a response from the server, the device displays the received simple expressions, answers, and emotion-based feedback messages to the user, allowing the user to obtain information in an easy-to-understand format.

[0262] User behavior

[0263] Enter text data and questions

[0264] The user inputs part of the book they are reading as text data into the device. They also input any questions they have while reading. Voice input and facial recognition functions are used as needed to enable the emotion engine to recognize emotions.

[0265] Verifying information and using emotional feedback

[0266] Users can check the simple expressions and answers sent from the server to confirm their understanding. Furthermore, they can receive emotional feedback messages to provide psychological support. This allows users to efficiently read through even difficult content, improving their learning efficiency.

[0267] Specific examples

[0268] For example, a user might be reading a technical book and come across the following paragraph:

[0269] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[0270] The user inputs this paragraph into the system, and also inputs the question "What does it mean to improve efficiency?" The emotion engine recognizes that the user is in a "confused" state. The server confirms that the user's knowledge level is beginner and that they are in a confused state, and converts the paragraph into a simple expression: "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question: "Improved efficiency means that the system can run faster or perform its work with fewer resources than before," and creates a feedback message saying, "You're doing well. There are some difficult parts, but you're almost there."

[0271] In this way, users can obtain technical information in an easy-to-understand format, improving their reading experience.

[0272] The processing flow will be explained below.

[0273] Step 1:

[0274] Users log in to their device and select a book to begin reading. After the book is loaded, users copy and paste the portion of the text they want to read into the device's interface.

[0275] Step 2:

[0276] The user inputs the paragraph of text he is reading into an input field on the terminal, and at the same time inputs any questions he has into the input field.

[0277] Step 3:

[0278] The device receives text data and questions entered by the user. After verifying that the data has been received correctly, it generates a data package containing the user's identification information. It also obtains the user's emotional information through voice input and facial recognition.

[0279] Step 4:

[0280] The terminal transmits the package data to the server, which includes the user ID, text data, questions, and emotion information.

[0281] Step 5:

[0282] The server receives the package data sent from the terminal, and then retrieves the user's knowledge level information from the database based on the user ID.

[0283] Step 6:

[0284] Based on the acquired knowledge level information and emotion information, the server uses a generation AI to convert the text data into a format (simplified expression or summary) that is easy for the user to understand. For example, if the user is recognized as "confused," the simplified expression of the text is set to a simpler level.

[0285] Step 7:

[0286] The server uses generative AI to generate answers to questions entered by users, and also uses an emotion engine to generate feedback messages (e.g., "You're doing a good job," "You'll understand soon," etc.) based on the user's emotional state.

[0287] Step 8:

[0288] The server packages the converted shorthand or summary text with the generated answers and sentiment-based feedback messages to create response data.

[0289] Step 9:

[0290] The server sends the response data to the terminal, which includes abbreviated or summarized text to aid the user's understanding, answers to questions, and sentiment-based feedback messages.

[0291] Step 10:

[0292] The terminal receives the response data from the server, analyzes the contents of the response data, and prepares to display it to the user.

[0293] Step 11:

[0294] The terminal displays the simplified or summarized text sent from the server, along with answers to questions and emotion-based feedback messages to the user. The user can confirm the displayed content and deepen their understanding. The emotion-based feedback also provides psychological support.

[0295] Example 2

[0296] 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."

[0297] Conventional reading assistance systems typically convert content based solely on the user's knowledge level. However, they do not provide appropriate feedback or text conversion that takes into account the user's emotional state, which can leave users feeling confused or bored, resulting in reduced learning efficiency. Furthermore, they often fail to provide appropriate answers to their questions. The present invention aims to solve these problems and provide a reading assistance system that is easier to understand and takes into account the user's emotional state.

[0298] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring text data and questions from a user, means for acquiring the user's knowledge level information and emotional information from a database and an emotional analysis engine, means for using a generation AI to convert the text data into a simplified expression or a summary according to the user's knowledge level and emotional information, means for acquiring the user's questions and generating an answer to the question using the generation AI, means for generating a feedback message based on the user's emotional information, and means for sending the converted simplified expression or summary text, the generated answer, and the feedback message to the user. This allows the user to receive appropriate feedback and text conversion tailored to their knowledge level and emotional state, thereby improving the efficiency of reading and learning.

[0299] "User" refers to any individual or entity that uses the System to convert text data or request answers to questions.

[0300] "Text data" refers to sentences or paragraphs of data that a user enters into a system.

[0301] "Questions" refer to questions or uncertainties that arise when a user is reading text data.

[0302] "Knowledge level" is information that indicates the user's level of expertise and understanding.

[0303] "Emotional information" refers to information that indicates the user's current emotional state (e.g., confusion, interest, boredom, etc.).

[0304] An "emotion analysis engine" refers to a program or system that analyzes a user's text data or voice data to identify emotional information.

[0305] "Database" refers to an information system for storing and managing user knowledge level information and other related information.

[0306] "Generative AI" refers to technology that uses machine learning and natural language processing to convert text data into simple expressions or summaries, or to generate answers to questions.

[0307] "Simplified expression" refers to a sentence that has been reconstructed from the original text data to make it easier to understand.

[0308] A "summary" refers to a short sentence summarizing the main points of the original text data.

[0309] A "feedback message" is a message generated based on the user's emotional information, and provides the user with a sense of psychological security and motivation.

[0310] "Packaging" refers to the process of bundling multiple pieces of data (e.g., shorthand, response, feedback message) into a format for transmission.

[0311] This invention provides a system that combines a generative AI model and a sentiment analysis engine to improve the user's reading experience. This system mainly consists of three elements: a server, a terminal, and a user.

[0312] Server-side behavior

[0313] The server performs the following process.

[0314] First, the server receives the text data and question sent by the user. Specifically, the text data and question entered by the user are sent to the server via an HTTP request. For example, the user might send the text data, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems."

[0315] Next, the server uses an emotion analysis engine to recognize the emotion the user is feeling when typing. For example, it analyzes the voice tone and typing speed to identify the user's emotional state (e.g., "confused," "interested," "bored"). For this purpose, a common emotion analysis engine (e.g., emotion analysis API) is used.

[0316] The server also retrieves the user's knowledge level from the database based on the user ID, and in this process, uses an SQL query to retrieve the user's knowledge level information from the database.

[0317] Based on the acquired emotional information and knowledge level, the server uses a generative AI model to convert the text data into a format that is easy for the user to understand (simple expressions or summary). For example, a general generative AI model (e.g., a generative AI model API) is used, and the prompt message sent is "Please convert the text into simple expressions that are easy for the user to understand."

[0318] Furthermore, the server uses the generative AI model to generate answers to questions entered by the user. This process also uses the generative AI model, sending the prompt "What does it mean to improve efficiency?"

[0319] Feedback messages based on emotional information are also generated on the server. Depending on the results of the emotion analysis engine, feedback messages such as "You're doing well" or "You'll understand soon" are generated.

[0320] Finally, the server packages the generated shorthand or summary text, the answer to the question, and the sentiment-based feedback message and sends it to the user. This response is packaged in JSON format and sent as an HTTP response.

[0321] Operation on the terminal side

[0322] The terminal operates as follows:

[0323] It provides an interface for users to input text data and questions. The interface includes a field for inputting the part being read and a field for inputting questions. It also includes an interface (voice input and facial recognition) that allows the emotion engine to recognize the user's emotions. After the user enters the necessary information in these fields, the device sends this information to the server.

[0324] The received response is analyzed and displayed to the user as a simple expression, an answer to the question, or an emotional feedback message. This data is then displayed appropriately in the UI, providing the user with information in an easy-to-understand format.

[0325] User behavior

[0326] The user follows the steps below:

[0327] First, users input part of the book they are reading into the device as text data. They also input any questions they have while reading. If necessary, voice input and facial recognition functions are used so that the emotion engine can recognize emotions.

[0328] Users can check the simple expressions and answers sent from the server to confirm their understanding. Furthermore, they can receive emotional feedback messages to provide psychological support. This allows users to efficiently read through even difficult content, improving their learning efficiency.

[0329] Specific examples

[0330] For example, if a user encounters the following paragraph:

[0331] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[0332] The user inputs this paragraph into the system, and also inputs the question "What does it mean to improve efficiency?" The emotion engine recognizes that the user is in a "confused" state. The server confirms that the user's knowledge level is beginner and that they are in a confused state, and converts the paragraph into a simple expression: "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question: "Improved efficiency means that the system will be able to run faster or perform its work with fewer resources than before," and also creates a feedback message saying, "You're doing well. There are some difficult parts, but you'll soon understand."

[0333] This allows users to obtain information in an easy-to-understand format, even for specialized content, improving their reading experience.

[0334] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0335] Step 1: Getting user-entered data

[0336] The user inputs the text data of the reading content and any questions that arise into the terminal. The terminal then sends this information to the server as an HTTP request. The input data consists of a text field and a question field, and examples include "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems" and "What do you mean by improved efficiency?"

[0337] Step 2: Receiving data on the server

[0338] The server receives the HTTP request sent from the terminal and obtains the text data and questions. Specifically, it extracts the text data and questions from the HTTP request body and prepares the data for subsequent processing. The input is the user's text data and questions, and the output is the prepared state of these data.

[0339] Step 3: Acquiring emotional information

[0340] The server uses a sentiment analysis engine to obtain the user's emotional information from the input text data and questions. Specifically, it sends the text data to the sentiment analysis API and receives the sentiment analysis results (confusion, interest, boredom, etc.). The input is the text data and questions, and the output is the user's emotional information.

[0341] Step 4: Gain a level of knowledge

[0342] The server retrieves the user's knowledge level information from the database based on the user ID. Specifically, it accesses the database using an SQL query to inquire about the user's knowledge level. The input is the user ID, and the output is the user's knowledge level information.

[0343] Step 5: Text conversion process

[0344] The server uses a generative AI model to convert text data into a simplified representation or summary based on emotion information and knowledge level information. Specifically, it provides a prompt to the generative AI model API to generate a simplified representation or summary. The input is text data, emotion information, knowledge level information, and a prompt, and the output is a simplified representation or summary text.

[0345] Step 6: Generate answers to your questions

[0346] The server uses the generative AI model to generate an answer to the user's question. Specifically, the question is sent as a prompt to the generative AI model API, and an appropriate answer is obtained. The input is the question and the prompt, and the output is the answer to the question.

[0347] Step 7: Generate feedback messages

[0348] The server generates a feedback message based on the emotion analysis results. Specifically, it selects and customizes a feedback message from a template according to the emotion information. The input is the emotion information, and the output is the customized feedback message.

[0349] Step 8: Packaging and Sending the Response

[0350] The server packages the generated simple expression or summary text, the answer to the question, and the feedback message, and sends them to the user. Specifically, it compiles this data in JSON format and sends it to the terminal as an HTTP response. The input is the simple expression or summary text, the answer to the question, and the feedback message, and the output is the packaged response data.

[0351] Step 9: Receive and display response data

[0352] The device receives the response data sent from the server, analyzes it, and displays a simple expression, an answer to the question, and a feedback message to the user. Specifically, it analyzes the received JSON data and displays each piece of information on the UI. The input is the response data, and the output is the displayed simple expression, answer, and feedback message.

[0353] Step 10: Verifying Information and Using Emotional Feedback

[0354] Users can check the displayed simple expressions and answers to confirm their understanding and receive emotional feedback messages to provide psychological support. By reading these messages, users can enhance their understanding and improve their reading experience.

[0355] (Application example 2)

[0356] 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."

[0357] Conventional reading assistance systems are limited to converting text according to the user's knowledge level and lack customization that takes into account the user's emotional state. This can lead to difficulties in reading comprehension and reduced learning efficiency. New methods are needed to solve this problem and improve the user's reading experience.

[0358] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring text data from a user, means for acquiring the user's knowledge level information and emotional information from a database, means for using a generation AI to convert the text data into a simplified expression or a summary according to the user's knowledge level and emotional information, means for using an emotion engine to analyze the user's emotional state, means for acquiring a question from the user and using the generation AI to generate an answer to the question and a feedback message based on the emotion, and means for sending the converted simplified expression or summary text and the generated answer and feedback message to the user. This enables individual optimization according to the user's emotional state, thereby providing more understandable information and psychological support.

[0359] "User" means an individual user of the system.

[0360] "Text data" is textual information that a user inputs into a system.

[0361] "Knowledge level information" is data regarding the user's level of understanding and depth of expertise.

[0362] "Emotion information" is data that indicates the user's emotional state.

[0363] A "database" is a storage device that stores data such as knowledge level information and emotion information.

[0364] A "simple phrase" is text that has been simplified to make it easier for users to understand.

[0365] A "summary" is a short summary of the original text.

[0366] "Generative AI" is an AI technology for converting text data and generating answers to questions.

[0367] An "emotion engine" is a technology for analyzing and identifying a user's emotional state.

[0368] "Questions" are questions or doubts that users have after reading the text data.

[0369] "Feedback messages" are messages of support or encouragement that correspond to the user's emotional state.

[0370] A "server" is a central computer that handles the overall processing of the system.

[0371] This invention uses a system that combines generative AI and an emotion engine to improve users' reading experience and understanding of product descriptions on online shopping sites. Specific embodiments for implementing this system are described below.

[0372] System Overview

[0373] This system consists of three elements: a server, a terminal, and a user. The server provides the necessary processing using a generative AI and emotion engine, and the terminal provides the interface to the user.

[0374] Server Operation

[0375] Acquiring text data and emotional information

[0376] The server receives text data sent by the user. For example, consider the case where the text data is "This product uses cutting-edge technology and is very effective." The server uses an emotion engine to identify the user's emotional state (e.g., "confused," "excited," "bored"). The emotion engine analyzes the voice tone, typing speed, etc. to recognize the emotional state.

[0377] Text processing based on user knowledge level and sentiment

[0378] The server retrieves knowledge level and emotion information from the database based on the user ID. Then, based on the retrieved emotion information and knowledge level, it uses generative AI to convert the text data into a format (simplified expression or summary) that is easy for the user to understand. For example, if the user is recognized as "confused," the text's simplified expression is set to a more understandable level.

[0379] Generate answers to questions and sentiment-based feedback

[0380] The server uses generative AI to generate answers to questions entered by the user, and also generates feedback messages based on the user's emotional state (e.g., "You're doing a great job").

[0381] Creating and Sending a Response

[0382] The generated simplified text, the answer to the question, and the feedback message based on the emotion are packaged and sent to the user's terminal as response data.

[0383] Device behavior

[0384] Providing a user interface

[0385] The device provides an interface for users to input text data and questions. The interface includes a field for inputting the reading passage and a field for inputting questions. It also includes an interface (e.g., voice input or facial recognition) for the emotion engine to recognize the user's emotions.

[0386] Sending and Displaying Data

[0387] After the user inputs text data and questions, the terminal sends this information to the server. After receiving a response from the server, the terminal displays the received simplified text, answers, and feedback messages to the user, allowing the user to obtain information in an easy-to-understand format.

[0388] User behavior

[0389] Enter text data and questions

[0390] Users input product descriptions and reviews as text data into the device. They also input any questions they may have while reading the text data. Voice input and facial recognition functions are used as needed to enable the emotion engine to recognize emotions.

[0391] Verifying information and using emotional feedback

[0392] The system checks the simplified text, answers, and feedback messages sent from the server to confirm that the user's understanding has improved. This allows the user to efficiently understand even complex content, improving the user's experience on the online shopping site.

[0393] Specific examples

[0394] For example, a user might read a product description and come across the following paragraph:

[0395] "This product uses cutting edge technology and is very effective."

[0396] The user inputs this paragraph into the system and then enters the question, "How exactly is it effective?" The emotion engine recognizes that the user is in a "confused" state. The server confirms that the user's knowledge level is beginner and that they are in a confused state, and converts the paragraph into a simplified expression, "This product uses new technology and is very useful." At the same time, it generates an answer to the question: "What I mean by effective is that using this product makes you more efficient than before," and creates a feedback message saying, "You're doing a great job."

[0397] Prompt Sentence Examples

[0398] User ID: User ID. Please describe this in simple terms: Original description.

[0399] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0400] Step 1: The user enters the product description text and question into the terminal.

[0401] Input: Product description text (e.g., "This product uses cutting-edge technology and is highly effective"), questions (e.g., "How exactly is it effective?")

[0402] How it works: The terminal provides fields to receive user-entered text and questions. The user enters text data and questions into these fields.

[0403] Output: Input text data and questions

[0404] Step 2: The device sends the text data, question, and user ID to the server.

[0405] Input: Text data, question, user ID

[0406] Operation: The terminal sends the text data and question entered by the user, as well as the user ID, to the server.

[0407] Output: Request data including text data, question, and user ID

[0408] Step 3: The server uses the emotion engine to analyze the user's emotional state.

[0409] Input: Request data

[0410] How it works: The server uses an emotion engine to analyze the text data in the request data, such as voice tone and typing speed, to determine the user's emotional state.

[0411] Output: Emotional state (e.g., "confused")

[0412] Step 4: The server retrieves the user's knowledge level information from the database.

[0413] Input: User ID

[0414] Operation: The server accesses the database and retrieves knowledge level information based on the user ID.

[0415] Output: Knowledge level information (e.g., "Beginner")

[0416] Step 5: The server uses generative AI to convert the text into simple expressions and summaries based on the emotional state and knowledge level.

[0417] Input: Text data, emotional state, knowledge level information

[0418] How it works: The server uses a generative AI to convert text data into simplified expressions appropriate for the knowledge level of "beginner," taking into account that the emotional state is "confused."

[0419] Output: Simple text (e.g. "This product uses new technology and is very useful.")

[0420] Step 6: The server uses AI to generate answers to the user's questions.

[0421] Input: Question, text data, knowledge level information, emotional state

[0422] How it works: The server uses generative AI to generate specific and understandable answers to questions based on your emotional state and knowledge level.

[0423] Output: Answer to the question (e.g., "Effective" means that using this product makes you more efficient than before.")

[0424] Step 7: The server generates a feedback message based on the emotional state.

[0425] Input: Emotional state

[0426] Behavior: The server considers the emotional state to be "confused" and generates an encouraging feedback message for the user.

[0427] Output: Feedback message (e.g. "Good job!")

[0428] Step 8: The server packages the generated simple text, the answer, and the feedback message and sends them to the terminal.

[0429] Input: Shorthand text, answer, feedback message

[0430] Operation: The server packages these data and sends them to the terminal as response data.

[0431] Output: Response data (simple text, answers, feedback messages)

[0432] Step 9: The device displays the received data to the user.

[0433] Input: Response data

[0434] Behavior: The device displays received shorthand text, responses, and feedback messages to the user.

[0435] Output: Information displayed to the user (simple text, answers, feedback messages)

[0436] This allows users to obtain information in an easy-to-understand format, deepening their understanding of the product and providing psychological support.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] [Second embodiment]

[0441] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0442] 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.

[0443] 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).

[0444] 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.

[0445] 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.

[0446] 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).

[0447] 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.

[0448] 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.

[0449] 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.

[0450] 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.

[0451] In the smart glasses 214, 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.

[0452] 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."

[0453] This invention provides a system that utilizes generative AI to improve a user's reading experience. Specific embodiments of this system are described below.

[0454] System Overview

[0455] This system is mainly composed of three elements: a server, a terminal, and a user. The user operates the system using a terminal, and the server uses a generative AI to process the necessary text and generate answers.

[0456] Server-side behavior

[0457] Acquiring and processing text data

[0458] The server receives text data sent by the user. For example, consider the case where the text data received is, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems." The server retrieves the user's knowledge level from a database and uses generative AI to convert this text data into a simplified expression or summary that is easy for the user to understand. For example, a beginner user would be provided with the simplified expression, "This technology is difficult, but simply applying the basics will make the system run more efficiently."

[0459] Generating answers to user questions

[0460] The server also receives questions sent by users and generates answers to those questions using the same generative AI. For example, in response to the question, "What does it mean to improve efficiency?", the server generates the answer, "Improved efficiency means that the system can run faster or get the job done using fewer resources."

[0461] Creating and Sending a Response

[0462] The generated shorthand and answers are packaged and sent to the user, who receives this information to improve their reading comprehension.

[0463] Operation on the terminal side

[0464] Providing a user interface

[0465] The terminal provides an interface for the user to input text data and questions, including a field for entering the reading passage and a field for entering questions.

[0466] Sending and Displaying Data

[0467] After the user enters text data and a question, the device sends this information to the server. After receiving a response from the server, the device displays the received simplified expression and answer to the user, allowing the user to obtain information in an easy-to-understand format.

[0468] User behavior

[0469] Enter text data and questions

[0470] The user inputs part of the book they are reading as text data into the terminal, and also inputs any questions that arise while reading the book.

[0471] Verify the information

[0472] The user can check the simple expressions and answers sent from the server to confirm that their understanding has deepened. This allows the user to efficiently read through even difficult content, improving learning efficiency.

[0473] Specific examples

[0474] For example, a user might be reading a technical book and come across the following paragraph:

[0475] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[0476] The user inputs this paragraph into the system, and also inputs the question, "What does it mean to improve efficiency?" The server confirms that the user's knowledge level is beginner level, and converts the paragraph into a simple expression, "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question, "Improved efficiency means that the system will run faster and be able to complete tasks using fewer resources," and provides this to the user via their terminal.

[0477] In this way, users can obtain technical information in an easy-to-understand format, improving their reading experience.

[0478] The processing flow will be explained below.

[0479] Step 1:

[0480] Users log in to their device and select a book to begin reading. After the book is loaded, users copy and paste the portion of the text they want to read into the device's interface.

[0481] Step 2:

[0482] The user inputs the paragraph of text he is reading into an input field on the terminal, and at the same time inputs any questions he has into the input field.

[0483] Step 3:

[0484] The terminal receives the text data and question input by the user, and after verifying that the data has been received correctly, generates package data including the user's identification information.

[0485] Step 4:

[0486] The terminal sends this package data, which includes the user ID, text data, and questions, to the server.

[0487] Step 5:

[0488] The server receives the package data sent from the terminal, and then retrieves the user's knowledge level information from the database based on the user ID.

[0489] Step 6:

[0490] Based on the acquired knowledge level information, the server uses a generation AI to convert the text data into a format that is easy for the user to understand (for example, simple expressions or summaries).

[0491] Step 7:

[0492] The server uses AI to generate answers to questions entered by users, creating appropriate answers based on text data related to the question.

[0493] Step 8:

[0494] The server packages the converted shorthand or summary text and the generated answer to create response data.

[0495] Step 9:

[0496] The server then sends the response data to the terminal, which includes a simplified expression or summary text to help the user understand, and the answer to the question.

[0497] Step 10:

[0498] The terminal receives the response data from the server, analyzes the contents of the response data, and prepares to display it to the user.

[0499] Step 11:

[0500] The terminal displays the simplified expressions or summary text sent from the server and the answers to the questions to the user, allowing the user to confirm the displayed content and deepen their understanding.

[0501] Example 1

[0502] 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."

[0503] Currently, many people struggle to understand the content of specialized books and technical documents. Beginners and users with little prior knowledge find technical terminology and complex explanations particularly difficult to understand. Furthermore, the inability to quickly find answers to questions that arise while reading leads to a decline in learning efficiency. In these circumstances, there is a need for a system that can convert text into an easy-to-understand format and provide appropriate answers to questions.

[0504] 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.

[0505] In this invention, the server includes means for acquiring text data and questions from a user, means for a terminal to transmit the text data and questions to the server, means for the server to receive the text data and acquire user knowledge level information from a database, means for converting the text data into a simplified expression or a summary using a generative AI model, means for generating an answer to the user's question using the generative AI model, means for transmitting the converted simplified expression or summary text and the generated answer to the user, and means for the terminal to display the simplified expression and the answer to the user. This allows users to obtain specialized content in an easy-to-understand format and quickly find answers to questions that arise while reading.

[0506] The "server" is a central system that receives data from users, retrieves information from a database, processes and generates data using generative AI models, and sends the results to users.

[0507] A "terminal" is a device operated by a user, which inputs text data and questions, transmits them to a server, and receives and displays responses from the server.

[0508] A "user" is a person who uses the system to input text data, ask questions, and receive information from the server.

[0509] "Text data" refers to a portion of a book or document that a user is reading, and is text information that is input into the system.

[0510] "Questions" refer to questions or unclear points that arise when the user is reading the text data.

[0511] "Knowledge level information" is information that indicates the user's knowledge and level of understanding, and is stored in a database.

[0512] A "generative AI model" is an AI system used to convert text data into simple expressions or summaries and generate answers to questions.

[0513] "Simplified expressions" are sentences that convert specialized or complex text data into easy-to-understand sentences that suit the user's level of knowledge.

[0514] A "summary" is a piece of text that provides the main points or content of text data in an abbreviated form.

[0515] An "answer" is a generated answer to a question posed by a user.

[0516] A "database" is a storage device that stores user knowledge level information and other necessary information.

[0517] "Packaging" is the process of formatting data sent from a user or a server into a format suitable for transmission.

[0518] The present invention provides a system for improving a user's reading experience by utilizing generative artificial intelligence. A specific embodiment of this system will be described below.

[0519] System Overview

[0520] This system is mainly composed of three elements: a server, a terminal, and a user. The user operates the system using a terminal, and the server uses generative artificial intelligence to process the necessary text and generate answers.

[0521] Server-side behavior

[0522] Acquiring and processing text data

[0523] The server receives text data sent by a user. For example, consider the case where the text data received is, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems." The server obtains the user's knowledge level information from the database and uses generative artificial intelligence to convert this text data into a simplified expression or summary that is easy for the user to understand. For example, a beginner user would be provided with the simplified expression, "This technology is difficult, but simply applying the basics will make the system run more efficiently."

[0524] Generating answers to user questions

[0525] The server also receives questions sent by users and generates answers to those questions using generative AI. For example, in response to the question "What does it mean to improve efficiency?", the server generates the answer "Improved efficiency means that the system can run faster or perform its work using fewer resources."

[0526] Creating and Sending a Response

[0527] The server packages the generated shorthand and answers and sends the content to the user, who receives this information to improve their reading comprehension.

[0528] Operation on the terminal side

[0529] Providing a user interface

[0530] The terminal provides an interface for the user to input text data and questions, including a field for entering the reading passage and a field for entering questions.

[0531] Sending and Displaying Data

[0532] After the user enters text data and a question, the device sends this information to the server. After receiving a response from the server, the device displays the received simplified expression and answer to the user, allowing the user to obtain information in an easy-to-understand format.

[0533] User behavior

[0534] Enter text data and questions

[0535] The user inputs part of the book they are reading as text data into the terminal, as well as any questions that arise while reading the book.

[0536] Verify the information

[0537] The user can check the simple expressions and answers sent from the server to confirm that their understanding has deepened. This allows the user to efficiently read through even difficult content, improving learning efficiency.

[0538] Specific examples

[0539] For example, a user might be reading a technical book and come across the following paragraph:

[0540] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[0541] The user inputs this paragraph into the system, and also inputs the question, "What does it mean to improve efficiency?" The server confirms that the user's knowledge level is beginner level and converts the paragraph into a simple expression: "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question: "Improved efficiency means that the system can run faster or perform its tasks with fewer resources than before," and provides this to the user via their device. In this way, the user can obtain information, even if it is technical, in an easy-to-understand format, improving their reading experience.

[0542] Prompt Sentence Examples

[0543] "Please summarize the following text in a way that is easy for a beginner to understand:

[0544] "This technology is highly complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[0545] Please answer the following questions:

[0546] "What does it mean to be more efficient?"

[0547] The above is an embodiment of the present invention.

[0548] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0549] Step 1:

[0550] The user inputs text data and a question.

[0551] How it works: The user accesses a dedicated interface on the device and enters part of the book they are reading as text data. They also enter any questions they may have while reading the book into a separate field in the same interface.

[0552] Input: The user types, for example, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large systems," and then types in a question, "What does it mean to improve efficiency?"

[0553] Output: The input text data and questions.

[0554] Step 2:

[0555] The terminal transmits the text data and the question to the server.

[0556] Specific operation: The device acquires the text data and questions entered by the user and sends this information to the server. The device sends the data using an HTTP POST request.

[0557] Input: Text data and questions entered by the user.

[0558] Output: Text data and questions sent to the server.

[0559] Step 3:

[0560] The server receives the text data and retrieves the user's knowledge level information from a database.

[0561] Specific operation: The server analyzes the text data and questions received from the terminal, then retrieves the user's profile information from the database and checks the user's knowledge level.

[0562] Input: Text data and questions sent from the terminal.

[0563] Output: Parsed text data, user knowledge level information.

[0564] Step 4:

[0565] The server uses a generative artificial intelligence model to convert the text data into a simplified representation.

[0566] Specific operation: The server inputs text data into the generative AI model and generates a simplified representation based on the user's knowledge level. The specific prompt is passed to the generative AI model in the form of "Please summarize the following text in a form that is easy for beginners to understand: 'This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems.'"

[0567] Input: Parsed text data, user knowledge level information.

[0568] Output: Simplified text data.

[0569] Step 5:

[0570] The server uses a generative artificial intelligence model to generate answers to the user's questions.

[0571] Specific operation: The server passes the user's question to the generative AI model to generate an answer. The specific prompt is "Please answer the following question: 'What does it mean to improve efficiency?'"

[0572] Input: User's question.

[0573] Output: The generated answer.

[0574] Step 6:

[0575] The server transmits the generated simple expressions and answers to the terminal.

[0576] Specific operation: The server packages the generated simple representation and answer and sends them to the terminal. Here, the data is again packaged in JSON format and sent using an HTTP POST request.

[0577] Input: Simplified text data, generated answers.

[0578] Output: Shorthands and answers sent to the device.

[0579] Step 7:

[0580] The terminal displays the shorthand and the answer to the user.

[0581] Specific operation: The terminal analyzes the simple expressions and answers received from the server and displays them on the user interface. Specifically, a dedicated display area displays the simple expression "This technology is difficult, but by simply applying the basics, the system can run more efficiently" and the answer to the question "Improved efficiency means that the system will be able to run faster and complete tasks using fewer resources than before."

[0582] Input: Shorthands and answers sent to the device.

[0583] Output: The shorthand and answers that are displayed to the user.

[0584] Step 8:

[0585] Users review shorthand and answers to deepen their understanding.

[0586] Specific actions: The user checks the simple expressions and answers displayed on the device to confirm that their understanding has improved.

[0587] Input: The shorthand and answer displayed on the terminal.

[0588] Output: A user with a better understanding.

[0589] (Application example 1)

[0590] 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."

[0591] Currently, when reading, readers often encounter difficult content that is difficult to understand. In such cases, readers are unable to enjoy the reading experience and their learning efficiency decreases. Furthermore, when selecting a book in a store, they often end up purchasing it without understanding the details of the book, making it difficult to choose the right book. There is a need for a solution to this problem, making reading and selecting books in a store more efficient and effective.

[0592] 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.

[0593] In this invention, the server includes means for acquiring text data from a user, means for acquiring user knowledge level information from a database, means for using a generation AI to convert the text data into simplified expressions or summaries according to the user's knowledge level, means for acquiring questions from the user and generating answers to the questions using the generation AI, means for sending the converted simplified expressions or summary text and the generated answers to the user, and means for having a smart device as the terminal to visually provide the simplified expressions and answers to the user in real time while reading, thereby providing easy-to-understand information in real time while reading and improving the reading experience.

[0594] "User" means an individual who utilizes the system to input text data and receive shorthand or responses.

[0595] "Text data" refers to the text information entered from the book or text the user is reading.

[0596] "Knowledge level information" is information that indicates the user's level of understanding and is stored in a database.

[0597] A "database" is a system that organizes, stores, and manages data such as user knowledge level information.

[0598] "Simplified expression" refers to a sentence that has been converted from the original text data into a form that is easier to understand.

[0599] A "summary" is a sentence that summarizes the main points of the original text data in an abbreviated form.

[0600] "Generative AI" refers to AI that uses generative techniques to generate simplified representations, summaries, and answers to text.

[0601] A "question" is a question or uncertainty that a user has while reading the text.

[0602] An "answer" is a generated answer or explanation to a question.

[0603] "Smart device" means an electronic device that a user can wear or use to receive information in real time.

[0604] The "system" refers to the entire set of mechanisms that receives text data and questions from users, processes them, and generates simplified expressions and answers to provide to users.

[0605] This invention is a system that uses generative AI to improve the user's reading experience. Specific embodiments of this system are described below.

[0606] System Configuration

[0607] The system consists of three elements: the user, the device, and the server. The user inputs text data and questions via the device, and the server processes this data using generative AI and sends the results to the device.

[0608] Server Roles

[0609] The server has the following means:

[0610] 1. How to get text data from the user:

[0611] The server receives text data provided by the user through the terminal.

[0612] 2. How to get user knowledge level information from the database:

[0613] The server retrieves the user's knowledge level information from the database.

[0614] 3. Using generative artificial intelligence to convert text data into simplified representations or summaries:

[0615] The server uses a generative AI model (e.g., OpenAI's GPT model) to convert text data into simplified representations or summaries depending on the user's level of knowledge.

[0616] 4. A means of obtaining questions from users and generating answers to those questions:

[0617] The server takes the question entered by the user and generates an answer to that question using a generative AI model.

[0618] 5. Means for sending the converted shorthand or summary text and generated answer to the user:

[0619] The server sends the generated simple expressions and answers to the terminal.

[0620] Device Role

[0621] The device includes the following features:

[0622] 1. Providing the user interface:

[0623] The terminal provides an interface where the user can enter text data and questions.

[0624] 2. Data transmission and display:

[0625] The user inputs text data and a question into the device, which is then sent to the server, which then receives a response and provides the user with a simple expression and a visual answer in real time.

[0626] Adding specific examples

[0627] For example, a user might be reading a technical book and come across the following paragraph:

[0628] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[0629] The user types this paragraph into their device, along with the question "What does it mean to be more efficient?" The server uses a generative AI model to translate it and generate the following simple phrase and answer:

[0630] Simple: "This technology is difficult, but applying the basics will make your system work more efficiently."

[0631] Answer: "Increased efficiency means that a system can run faster or do its job using fewer resources."

[0632] The results are sent to the terminal, where the user receives a visual summary and answer, and if they have further questions, they can ask them again using the following prompt:

[0633] Please briefly explain the following sentence: Elves have long lifespans and their knowledge has been accumulated over thousands of years. The user's knowledge level is beginner.

[0634]

[0635] A user asked the question: What is an elf? Please provide a clear answer.

[0636] In this way, users can obtain technical information in an easy-to-understand format, improving their reading experience.

[0637] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0638] Step 1:

[0639] The user inputs text data and questions into the terminal.

[0640] As input, the user enters the paragraph or sentence (text data) of the book they are reading and any questions they may have about that paragraph through the terminal. The terminal receives this data and prepares to proceed to the next step.

[0641] Step 2:

[0642] The text data and the question are sent to the server.

[0643] The terminal packages the received text data and question and transmits the packaged data to the server. The transmitted data includes the text data and question entered by the user.

[0644] Step 3:

[0645] The server retrieves the user's knowledge level information from the database.

[0646] The server retrieves information about the user's knowledge level from a database, using the user's identification information as input and obtaining the user's knowledge level information as output.

[0647] Step 4:

[0648] The server uses a generative AI model to convert the text data into a simplified representation or summary.

[0649] Based on the acquired user knowledge level information, the server inputs the text data into a generative AI model (e.g., OpenAI's GPT model) and converts it into a simplified representation or summary. The text data and knowledge level are used as input, and a simplified representation or summary is generated as output.

[0650] Step 5:

[0651] The server uses a generative AI model to generate answers to questions.

[0652] The server inputs the question into a generative AI model to generate the corresponding answer. The question is used as input and the answer is generated as output.

[0653] Step 6:

[0654] The server transmits the converted shorthand or summary text and the generated answer to the terminal.

[0655] The server packages the generated simple expression or summary text and the answer, and transmits the packaged data to the terminal. The transmitted data includes the converted simple expression or summary and the answer to the question.

[0656] Step 7:

[0657] The terminal provides the user with visual shorthand and answers in real time.

[0658] The terminal displays the simple expressions and answers received from the server on the user's smart device and provides them visually. It uses the data sent from the server as input and presents information to the user in real time.

[0659] 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.

[0660] This invention utilizes a system that combines generative AI and an emotion engine to improve the user's reading experience. A specific embodiment of this system is described below.

[0661] System Overview

[0662] This system is mainly composed of three elements: a server, a terminal, and a user. The user operates the system using a terminal, and the server provides the necessary processing using a generative AI and emotion engine.

[0663] Server-side behavior

[0664] Acquiring text data and emotional information

[0665] The server receives the text data and question sent by the user. For example, consider the case where the text data received is, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems." The server then uses an emotion engine to recognize the emotion the user is feeling when typing. The emotion engine analyzes, for example, the voice tone and typing speed to identify the user's emotional state (e.g., "confused," "interested," or "bored").

[0666] Text Processing Based on User Knowledge Level and Sentiment

[0667] The server retrieves the user's knowledge level from the database based on the user ID. Then, based on the retrieved emotion information and knowledge level, it uses generative AI to convert the text data into a format (simplified expression or summary) that is easy for the user to understand. For example, if the user is recognized as "confused," the simplified expression of the text is set to a more understandable level.

[0668] Generate answers to questions and sentiment-based feedback

[0669] The server uses generative AI to generate answers to questions entered by users, and also uses an emotion engine to generate feedback messages (e.g., "You're doing a good job," "You'll understand soon," etc.) based on the user's emotional state.

[0670] Creating and Sending a Response

[0671] The generated shorthand or summary text, the answer to the question, and the sentiment-based feedback are packaged and the response data is sent to the user.

[0672] Operation on the terminal side

[0673] Providing a user interface

[0674] The device provides an interface for users to input text data and questions. The interface includes a field for inputting the reading passage and a field for inputting questions. It also includes an interface (e.g., voice input or face recognition) for the emotion engine to recognize the user's emotions.

[0675] Sending and Displaying Data

[0676] After the user inputs text data and a question, the device sends this information to the server. After receiving a response from the server, the device displays the received simple expressions, answers, and emotion-based feedback messages to the user, allowing the user to obtain information in an easy-to-understand format.

[0677] User behavior

[0678] Enter text data and questions

[0679] The user inputs part of the book they are reading as text data into the device. They also input any questions they have while reading. Voice input and facial recognition functions are used as needed to enable the emotion engine to recognize emotions.

[0680] Verifying information and using emotional feedback

[0681] Users can check the simple expressions and answers sent from the server to confirm their understanding. Furthermore, they can receive emotional feedback messages to provide psychological support. This allows users to efficiently read through even difficult content, improving their learning efficiency.

[0682] Specific examples

[0683] For example, a user might be reading a technical book and come across the following paragraph:

[0684] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[0685] The user inputs this paragraph into the system, and also inputs the question "What does it mean to improve efficiency?" The emotion engine recognizes that the user is in a "confused" state. The server confirms that the user's knowledge level is beginner and that they are in a confused state, and converts the paragraph into a simple expression: "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question: "Improved efficiency means that the system can run faster or perform its work with fewer resources than before," and creates a feedback message saying, "You're doing well. There are some difficult parts, but you're almost there."

[0686] In this way, users can obtain technical information in an easy-to-understand format, improving their reading experience.

[0687] The processing flow will be explained below.

[0688] Step 1:

[0689] Users log in to their device and select a book to begin reading. After the book is loaded, users copy and paste the portion of the text they want to read into the device's interface.

[0690] Step 2:

[0691] The user inputs the paragraph of text he is reading into an input field on the terminal, and at the same time inputs any questions he has into the input field.

[0692] Step 3:

[0693] The device receives text data and questions entered by the user. After verifying that the data has been received correctly, it generates a data package containing the user's identification information. It also obtains the user's emotional information through voice input and facial recognition.

[0694] Step 4:

[0695] The terminal transmits the package data to the server, which includes the user ID, text data, questions, and emotion information.

[0696] Step 5:

[0697] The server receives the package data sent from the terminal, and then retrieves the user's knowledge level information from the database based on the user ID.

[0698] Step 6:

[0699] Based on the acquired knowledge level information and emotion information, the server uses a generation AI to convert the text data into a format (simplified expression or summary) that is easy for the user to understand. For example, if the user is recognized as "confused," the simplified expression of the text is set to a simpler level.

[0700] Step 7:

[0701] The server uses generative AI to generate answers to questions entered by users, and also uses an emotion engine to generate feedback messages (e.g., "You're doing a good job," "You'll understand soon," etc.) based on the user's emotional state.

[0702] Step 8:

[0703] The server packages the converted shorthand or summary text with the generated answers and sentiment-based feedback messages to create response data.

[0704] Step 9:

[0705] The server sends the response data to the terminal, which includes abbreviated or summarized text to aid the user's understanding, answers to questions, and sentiment-based feedback messages.

[0706] Step 10:

[0707] The terminal receives the response data from the server, analyzes the contents of the response data, and prepares to display it to the user.

[0708] Step 11:

[0709] The terminal displays the simplified or summarized text sent from the server, along with answers to questions and emotion-based feedback messages to the user. The user can confirm the displayed content and deepen their understanding. The emotion-based feedback also provides psychological support.

[0710] Example 2

[0711] 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."

[0712] Conventional reading assistance systems typically convert content based solely on the user's knowledge level. However, they do not provide appropriate feedback or text conversion that takes into account the user's emotional state, which can leave users feeling confused or bored, resulting in reduced learning efficiency. Furthermore, they often fail to provide appropriate answers to their questions. The present invention aims to solve these problems and provide a reading assistance system that is easier to understand and takes into account the user's emotional state.

[0713] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring text data and questions from a user, means for acquiring the user's knowledge level information and emotional information from a database and an emotional analysis engine, means for using a generation AI to convert the text data into a simplified expression or a summary according to the user's knowledge level and emotional information, means for acquiring the user's questions and generating an answer to the question using the generation AI, means for generating a feedback message based on the user's emotional information, and means for sending the converted simplified expression or summary text, the generated answer, and the feedback message to the user. This allows the user to receive appropriate feedback and text conversion tailored to their knowledge level and emotional state, thereby improving the efficiency of reading and learning.

[0714] "User" refers to any individual or entity that uses the System to convert text data or request answers to questions.

[0715] "Text data" refers to sentences or paragraphs of data that a user enters into a system.

[0716] "Questions" refer to questions or uncertainties that arise when a user is reading text data.

[0717] "Knowledge level" is information that indicates the user's level of expertise and understanding.

[0718] "Emotional information" refers to information that indicates the user's current emotional state (e.g., confusion, interest, boredom, etc.).

[0719] An "emotion analysis engine" refers to a program or system that analyzes a user's text data or voice data to identify emotional information.

[0720] "Database" refers to an information system for storing and managing user knowledge level information and other related information.

[0721] "Generative AI" refers to technology that uses machine learning and natural language processing to convert text data into simple expressions or summaries, or to generate answers to questions.

[0722] "Simplified expression" refers to a sentence that has been reconstructed from the original text data to make it easier to understand.

[0723] A "summary" refers to a short sentence summarizing the main points of the original text data.

[0724] A "feedback message" is a message generated based on the user's emotional information, and provides the user with a sense of psychological security and motivation.

[0725] "Packaging" refers to the process of bundling multiple pieces of data (e.g., shorthand, response, feedback message) into a format for transmission.

[0726] This invention provides a system that combines a generative AI model and a sentiment analysis engine to improve the user's reading experience. This system mainly consists of three elements: a server, a terminal, and a user.

[0727] Server-side behavior

[0728] The server performs the following process.

[0729] First, the server receives the text data and question sent by the user. Specifically, the text data and question entered by the user are sent to the server via an HTTP request. For example, the user might send the text data, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems."

[0730] Next, the server uses an emotion analysis engine to recognize the emotion the user is feeling when typing. For example, it analyzes the voice tone and typing speed to identify the user's emotional state (e.g., "confused," "interested," "bored"). For this purpose, a common emotion analysis engine (e.g., emotion analysis API) is used.

[0731] The server also retrieves the user's knowledge level from the database based on the user ID, and in this process, uses an SQL query to retrieve the user's knowledge level information from the database.

[0732] Based on the acquired emotional information and knowledge level, the server uses a generative AI model to convert the text data into a format that is easy for the user to understand (simple expressions or summary). For example, a general generative AI model (e.g., a generative AI model API) is used, and the prompt message sent is "Please convert the text into simple expressions that are easy for the user to understand."

[0733] Furthermore, the server uses the generative AI model to generate answers to questions entered by the user. This process also uses the generative AI model, sending the prompt "What does it mean to improve efficiency?"

[0734] Feedback messages based on emotional information are also generated on the server. Depending on the results of the emotion analysis engine, feedback messages such as "You're doing well" or "You'll understand soon" are generated.

[0735] Finally, the server packages the generated shorthand or summary text, the answer to the question, and the sentiment-based feedback message and sends it to the user. This response is packaged in JSON format and sent as an HTTP response.

[0736] Operation on the terminal side

[0737] The terminal operates as follows:

[0738] It provides an interface for users to input text data and questions. The interface includes a field for inputting the part being read and a field for inputting questions. It also includes an interface (voice input and facial recognition) that allows the emotion engine to recognize the user's emotions. After the user enters the necessary information in these fields, the device sends this information to the server.

[0739] The received response is analyzed and displayed to the user as a simple expression, an answer to the question, or an emotional feedback message. This data is then displayed appropriately in the UI, providing the user with information in an easy-to-understand format.

[0740] User behavior

[0741] The user follows the steps below:

[0742] First, users input part of the book they are reading into the device as text data. They also input any questions they have while reading. If necessary, voice input and facial recognition functions are used so that the emotion engine can recognize emotions.

[0743] Users can check the simple expressions and answers sent from the server to confirm their understanding. Furthermore, they can receive emotional feedback messages to provide psychological support. This allows users to efficiently read through even difficult content, improving their learning efficiency.

[0744] Specific examples

[0745] For example, if a user encounters the following paragraph:

[0746] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[0747] The user inputs this paragraph into the system, and also inputs the question "What does it mean to improve efficiency?" The emotion engine recognizes that the user is in a "confused" state. The server confirms that the user's knowledge level is beginner and that they are in a confused state, and converts the paragraph into a simple expression: "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question: "Improved efficiency means that the system will be able to run faster or perform its work with fewer resources than before," and also creates a feedback message saying, "You're doing well. There are some difficult parts, but you'll soon understand."

[0748] This allows users to obtain information in an easy-to-understand format, even for specialized content, improving their reading experience.

[0749] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0750] Step 1: Getting user-entered data

[0751] The user inputs the text data of the reading content and any questions that arise into the terminal. The terminal then sends this information to the server as an HTTP request. The input data consists of a text field and a question field, and examples include "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems" and "What do you mean by improved efficiency?"

[0752] Step 2: Receiving data on the server

[0753] The server receives the HTTP request sent from the terminal and obtains the text data and questions. Specifically, it extracts the text data and questions from the HTTP request body and prepares the data for subsequent processing. The input is the user's text data and questions, and the output is the prepared state of these data.

[0754] Step 3: Acquiring emotional information

[0755] The server uses a sentiment analysis engine to obtain the user's emotional information from the input text data and questions. Specifically, it sends the text data to the sentiment analysis API and receives the sentiment analysis results (confusion, interest, boredom, etc.). The input is the text data and questions, and the output is the user's emotional information.

[0756] Step 4: Gain a level of knowledge

[0757] The server retrieves the user's knowledge level information from the database based on the user ID. Specifically, it accesses the database using an SQL query to inquire about the user's knowledge level. The input is the user ID, and the output is the user's knowledge level information.

[0758] Step 5: Text conversion process

[0759] The server uses a generative AI model to convert text data into a simplified representation or summary based on emotion information and knowledge level information. Specifically, it provides a prompt to the generative AI model API to generate a simplified representation or summary. The input is text data, emotion information, knowledge level information, and a prompt, and the output is a simplified representation or summary text.

[0760] Step 6: Generate answers to your questions

[0761] The server uses the generative AI model to generate an answer to the user's question. Specifically, the question is sent as a prompt to the generative AI model API, and an appropriate answer is obtained. The input is the question and the prompt, and the output is the answer to the question.

[0762] Step 7: Generate feedback messages

[0763] The server generates a feedback message based on the emotion analysis results. Specifically, it selects and customizes a feedback message from a template according to the emotion information. The input is the emotion information, and the output is the customized feedback message.

[0764] Step 8: Packaging and Sending the Response

[0765] The server packages the generated simple expression or summary text, the answer to the question, and the feedback message, and sends them to the user. Specifically, it compiles this data in JSON format and sends it to the terminal as an HTTP response. The input is the simple expression or summary text, the answer to the question, and the feedback message, and the output is the packaged response data.

[0766] Step 9: Receive and display response data

[0767] The device receives the response data sent from the server, analyzes it, and displays a simple expression, an answer to the question, and a feedback message to the user. Specifically, it analyzes the received JSON data and displays each piece of information on the UI. The input is the response data, and the output is the displayed simple expression, answer, and feedback message.

[0768] Step 10: Verifying Information and Using Emotional Feedback

[0769] Users can check the displayed simple expressions and answers to confirm their understanding and receive emotional feedback messages to provide psychological support. By reading these messages, users can enhance their understanding and improve their reading experience.

[0770] (Application example 2)

[0771] 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."

[0772] Conventional reading assistance systems are limited to converting text according to the user's knowledge level and lack customization that takes into account the user's emotional state. This can lead to difficulties in reading comprehension and reduced learning efficiency. New methods are needed to solve this problem and improve the user's reading experience.

[0773] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring text data from a user, means for acquiring the user's knowledge level information and emotional information from a database, means for using a generation AI to convert the text data into a simplified expression or a summary according to the user's knowledge level and emotional information, means for using an emotion engine to analyze the user's emotional state, means for acquiring a question from the user and using the generation AI to generate an answer to the question and a feedback message based on the emotion, and means for sending the converted simplified expression or summary text and the generated answer and feedback message to the user. This enables individual optimization according to the user's emotional state, thereby providing more understandable information and psychological support.

[0774] "User" means an individual user of the system.

[0775] "Text data" is textual information that a user inputs into a system.

[0776] "Knowledge level information" is data regarding the user's level of understanding and depth of expertise.

[0777] "Emotion information" is data that indicates the user's emotional state.

[0778] A "database" is a storage device that stores data such as knowledge level information and emotion information.

[0779] A "simple phrase" is text that has been simplified to make it easier for users to understand.

[0780] A "summary" is a short summary of the original text.

[0781] "Generative AI" is an AI technology for converting text data and generating answers to questions.

[0782] An "emotion engine" is a technology for analyzing and identifying a user's emotional state.

[0783] "Questions" are questions or doubts that users have after reading the text data.

[0784] "Feedback messages" are messages of support or encouragement that correspond to the user's emotional state.

[0785] A "server" is a central computer that handles the overall processing of the system.

[0786] This invention uses a system that combines generative AI and an emotion engine to improve users' reading experience and understanding of product descriptions on online shopping sites. Specific embodiments for implementing this system are described below.

[0787] System Overview

[0788] This system consists of three elements: a server, a terminal, and a user. The server provides the necessary processing using a generative AI and emotion engine, and the terminal provides the interface to the user.

[0789] Server Operation

[0790] Acquiring text data and emotional information

[0791] The server receives text data sent by the user. For example, consider the case where the text data is "This product uses cutting-edge technology and is very effective." The server uses an emotion engine to identify the user's emotional state (e.g., "confused," "excited," "bored"). The emotion engine analyzes the voice tone, typing speed, etc. to recognize the emotional state.

[0792] Text processing based on user knowledge level and sentiment

[0793] The server retrieves knowledge level and emotion information from the database based on the user ID. Then, based on the retrieved emotion information and knowledge level, it uses generative AI to convert the text data into a format (simplified expression or summary) that is easy for the user to understand. For example, if the user is recognized as "confused," the text's simplified expression is set to a more understandable level.

[0794] Generate answers to questions and sentiment-based feedback

[0795] The server uses generative AI to generate answers to questions entered by the user, and also generates feedback messages based on the user's emotional state (e.g., "You're doing a great job").

[0796] Creating and Sending a Response

[0797] The generated simplified text, the answer to the question, and the feedback message based on the emotion are packaged and sent to the user's terminal as response data.

[0798] Device behavior

[0799] Providing a user interface

[0800] The device provides an interface for users to input text data and questions. The interface includes a field for inputting the reading passage and a field for inputting questions. It also includes an interface (e.g., voice input or facial recognition) for the emotion engine to recognize the user's emotions.

[0801] Sending and Displaying Data

[0802] After the user inputs text data and questions, the terminal sends this information to the server. After receiving a response from the server, the terminal displays the received simplified text, answers, and feedback messages to the user, allowing the user to obtain information in an easy-to-understand format.

[0803] User behavior

[0804] Enter text data and questions

[0805] Users input product descriptions and reviews as text data into the device. They also input any questions they may have while reading the text data. Voice input and facial recognition functions are used as needed to enable the emotion engine to recognize emotions.

[0806] Verifying information and using emotional feedback

[0807] The system checks the simplified text, answers, and feedback messages sent from the server to confirm that the user's understanding has improved. This allows the user to efficiently understand even complex content, improving the user's experience on the online shopping site.

[0808] Specific examples

[0809] For example, a user might read a product description and come across the following paragraph:

[0810] "This product uses cutting edge technology and is very effective."

[0811] The user inputs this paragraph into the system and then enters the question, "How exactly is it effective?" The emotion engine recognizes that the user is in a "confused" state. The server confirms that the user's knowledge level is beginner and that they are in a confused state, and converts the paragraph into a simplified expression, "This product uses new technology and is very useful." At the same time, it generates an answer to the question: "What I mean by effective is that using this product makes you more efficient than before," and creates a feedback message saying, "You're doing a great job."

[0812] Prompt Sentence Examples

[0813] User ID: User ID. Please describe this in simple terms: Original description.

[0814] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0815] Step 1: The user enters the product description text and question into the terminal.

[0816] Input: Product description text (e.g., "This product uses cutting-edge technology and is highly effective"), questions (e.g., "How exactly is it effective?")

[0817] How it works: The terminal provides fields to receive user-entered text and questions. The user enters text data and questions into these fields.

[0818] Output: Input text data and questions

[0819] Step 2: The device sends the text data, question, and user ID to the server.

[0820] Input: Text data, question, user ID

[0821] Operation: The terminal sends the text data and question entered by the user, as well as the user ID, to the server.

[0822] Output: Request data including text data, question, and user ID

[0823] Step 3: The server uses the emotion engine to analyze the user's emotional state.

[0824] Input: Request data

[0825] How it works: The server uses an emotion engine to analyze the text data in the request data, such as voice tone and typing speed, to determine the user's emotional state.

[0826] Output: Emotional state (e.g., "confused")

[0827] Step 4: The server retrieves the user's knowledge level information from the database.

[0828] Input: User ID

[0829] Operation: The server accesses the database and retrieves knowledge level information based on the user ID.

[0830] Output: Knowledge level information (e.g., "Beginner")

[0831] Step 5: The server uses generative AI to convert the text into simple expressions and summaries based on the emotional state and knowledge level.

[0832] Input: Text data, emotional state, knowledge level information

[0833] How it works: The server uses a generative AI to convert text data into simplified expressions appropriate for the knowledge level of "beginner," taking into account that the emotional state is "confused."

[0834] Output: Simple text (e.g. "This product uses new technology and is very useful.")

[0835] Step 6: The server uses AI to generate answers to the user's questions.

[0836] Input: Question, text data, knowledge level information, emotional state

[0837] How it works: The server uses generative AI to generate specific and understandable answers to questions based on your emotional state and knowledge level.

[0838] Output: Answer to the question (e.g., "Effective" means that using this product makes you more efficient than before.")

[0839] Step 7: The server generates a feedback message based on the emotional state.

[0840] Input: Emotional state

[0841] Behavior: The server considers the emotional state to be "confused" and generates an encouraging feedback message for the user.

[0842] Output: Feedback message (e.g. "Good job!")

[0843] Step 8: The server packages the generated simple text, the answer, and the feedback message and sends them to the terminal.

[0844] Input: Shorthand text, answer, feedback message

[0845] Operation: The server packages these data and sends them to the terminal as response data.

[0846] Output: Response data (simple text, answers, feedback messages)

[0847] Step 9: The device displays the received data to the user.

[0848] Input: Response data

[0849] Behavior: The device displays received shorthand text, responses, and feedback messages to the user.

[0850] Output: Information displayed to the user (simple text, answers, feedback messages)

[0851] This allows users to obtain information in an easy-to-understand format, deepening their understanding of the product and providing psychological support.

[0852] 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.

[0853] 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.

[0854] 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.

[0855] [Third embodiment]

[0856] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0857] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0858] 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).

[0859] 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.

[0860] 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.

[0861] 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).

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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.

[0867] 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."

[0868] This invention provides a system that utilizes generative AI to improve a user's reading experience. Specific embodiments of this system are described below.

[0869] System Overview

[0870] This system is mainly composed of three elements: a server, a terminal, and a user. The user operates the system using a terminal, and the server uses a generative AI to process the necessary text and generate answers.

[0871] Server-side behavior

[0872] Acquiring and processing text data

[0873] The server receives text data sent by the user. For example, consider the case where the text data received is, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems." The server retrieves the user's knowledge level from a database and uses generative AI to convert this text data into a simplified expression or summary that is easy for the user to understand. For example, a beginner user would be provided with the simplified expression, "This technology is difficult, but simply applying the basics will make the system run more efficiently."

[0874] Generating answers to user questions

[0875] The server also receives questions sent by users and generates answers to those questions using the same generative AI. For example, in response to the question, "What does it mean to improve efficiency?", the server generates the answer, "Improved efficiency means that the system can run faster or get the job done using fewer resources."

[0876] Creating and Sending a Response

[0877] The generated shorthand and answers are packaged and sent to the user, who receives this information to improve their reading comprehension.

[0878] Operation on the terminal side

[0879] Providing a user interface

[0880] The terminal provides an interface for the user to input text data and questions, including a field for entering the reading passage and a field for entering questions.

[0881] Sending and Displaying Data

[0882] After the user enters text data and a question, the device sends this information to the server. After receiving a response from the server, the device displays the received simplified expression and answer to the user, allowing the user to obtain information in an easy-to-understand format.

[0883] User behavior

[0884] Enter text data and questions

[0885] The user inputs part of the book they are reading as text data into the terminal, as well as any questions that arise while reading the book.

[0886] Verify the information

[0887] The user can check the simple expressions and answers sent from the server to confirm that their understanding has deepened. This allows the user to efficiently read through even difficult content, improving learning efficiency.

[0888] Specific examples

[0889] For example, a user might be reading a technical book and come across the following paragraph:

[0890] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[0891] The user inputs this paragraph into the system, and also inputs the question, "What does it mean to improve efficiency?" The server confirms that the user's knowledge level is beginner level, and converts the paragraph into a simple expression, "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question, "Improved efficiency means that the system will run faster and be able to complete tasks using fewer resources," and provides this to the user via their terminal.

[0892] In this way, users can obtain technical information in an easy-to-understand format, improving their reading experience.

[0893] The processing flow will be explained below.

[0894] Step 1:

[0895] Users log in to their device and select a book to begin reading. After the book is loaded, users copy and paste the portion of the text they want to read into the device's interface.

[0896] Step 2:

[0897] The user inputs the paragraph of text he is reading into an input field on the terminal, and at the same time inputs any questions he has into the input field.

[0898] Step 3:

[0899] The terminal receives the text data and question input by the user, and after verifying that the data has been received correctly, generates package data including the user's identification information.

[0900] Step 4:

[0901] The terminal sends this package data, which includes the user ID, text data, and questions, to the server.

[0902] Step 5:

[0903] The server receives the package data sent from the terminal, and then retrieves the user's knowledge level information from the database based on the user ID.

[0904] Step 6:

[0905] Based on the acquired knowledge level information, the server uses a generation AI to convert the text data into a format that is easy for the user to understand (for example, simple expressions or summaries).

[0906] Step 7:

[0907] The server uses AI to generate answers to questions entered by users, creating appropriate answers based on text data related to the question.

[0908] Step 8:

[0909] The server packages the converted shorthand or summary text and the generated answer to create response data.

[0910] Step 9:

[0911] The server then sends the response data to the terminal, which includes a simplified expression or summary text to help the user understand, and the answer to the question.

[0912] Step 10:

[0913] The terminal receives the response data from the server, analyzes the contents of the response data, and prepares to display it to the user.

[0914] Step 11:

[0915] The terminal displays the simplified expressions or summary text sent from the server and the answers to the questions to the user, allowing the user to confirm the displayed content and deepen their understanding.

[0916] Example 1

[0917] 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."

[0918] Currently, many people struggle to understand the content of specialized books and technical documents. Beginners and users with little prior knowledge find technical terminology and complex explanations particularly difficult to understand. Furthermore, the inability to quickly find answers to questions that arise while reading leads to a decline in learning efficiency. In these circumstances, there is a need for a system that can convert text into an easy-to-understand format and provide appropriate answers to questions.

[0919] 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.

[0920] In this invention, the server includes means for acquiring text data and questions from a user, means for a terminal to transmit the text data and questions to the server, means for the server to receive the text data and acquire user knowledge level information from a database, means for converting the text data into a simplified expression or a summary using a generative AI model, means for generating an answer to the user's question using the generative AI model, means for transmitting the converted simplified expression or summary text and the generated answer to the user, and means for the terminal to display the simplified expression and the answer to the user. This allows users to obtain specialized content in an easy-to-understand format and quickly find answers to questions that arise while reading.

[0921] The "server" is a central system that receives data from users, retrieves information from a database, processes and generates data using generative AI models, and sends the results to users.

[0922] A "terminal" is a device operated by a user, which inputs text data and questions, transmits them to a server, and receives and displays responses from the server.

[0923] A "user" is a person who uses the system to input text data, ask questions, and receive information from the server.

[0924] "Text data" refers to a portion of a book or document that a user is reading, and is text information that is input into the system.

[0925] "Questions" refer to questions or unclear points that arise when the user is reading the text data.

[0926] "Knowledge level information" is information that indicates the user's knowledge and level of understanding, and is stored in a database.

[0927] A "generative AI model" is an AI system used to convert text data into simple expressions or summaries and generate answers to questions.

[0928] "Simplified expressions" are sentences that convert specialized or complex text data into easy-to-understand sentences that suit the user's level of knowledge.

[0929] A "summary" is a piece of text that provides the main points or content of text data in an abbreviated form.

[0930] An "answer" is a generated answer to a question posed by a user.

[0931] A "database" is a storage device that stores user knowledge level information and other necessary information.

[0932] "Packaging" is the process of formatting data sent from a user or a server into a format suitable for transmission.

[0933] The present invention provides a system for improving a user's reading experience by utilizing generative artificial intelligence. A specific embodiment of this system will be described below.

[0934] System Overview

[0935] This system is mainly composed of three elements: a server, a terminal, and a user. The user operates the system using a terminal, and the server uses generative artificial intelligence to process the necessary text and generate answers.

[0936] Server-side behavior

[0937] Acquiring and processing text data

[0938] The server receives text data sent by a user. For example, consider the case where the text data received is, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems." The server obtains the user's knowledge level information from the database and uses generative artificial intelligence to convert this text data into a simplified expression or summary that is easy for the user to understand. For example, a beginner user would be provided with the simplified expression, "This technology is difficult, but simply applying the basics will make the system run more efficiently."

[0939] Generating answers to user questions

[0940] The server also receives questions sent by users and generates answers to those questions using generative AI. For example, in response to the question "What does it mean to improve efficiency?", the server generates the answer "Improved efficiency means that the system can run faster or perform its work using fewer resources."

[0941] Creating and Sending a Response

[0942] The server packages the generated shorthand and answers and sends the content to the user, who receives this information to improve their reading comprehension.

[0943] Operation on the terminal side

[0944] Providing a user interface

[0945] The terminal provides an interface for the user to input text data and questions, including a field for entering the reading passage and a field for entering questions.

[0946] Sending and Displaying Data

[0947] After the user enters text data and a question, the device sends this information to the server. After receiving a response from the server, the device displays the received simplified expression and answer to the user, allowing the user to obtain information in an easy-to-understand format.

[0948] User behavior

[0949] Enter text data and questions

[0950] The user inputs part of the book they are reading as text data into the terminal, as well as any questions that arise while reading the book.

[0951] Verify the information

[0952] The user can check the simple expressions and answers sent from the server to confirm that their understanding has deepened. This allows the user to efficiently read through even difficult content, improving learning efficiency.

[0953] Specific examples

[0954] For example, a user might be reading a technical book and come across the following paragraph:

[0955] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[0956] The user inputs this paragraph into the system, and also inputs the question, "What does it mean to improve efficiency?" The server confirms that the user's knowledge level is beginner level and converts the paragraph into a simple expression: "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question: "Improved efficiency means that the system will run faster or be able to complete tasks using fewer resources," and provides this to the user via their device. In this way, the user can obtain information, even if it is technical, in an easy-to-understand format, improving their reading experience.

[0957] Prompt Sentence Examples

[0958] "Please summarize the following text in a way that is easy for a beginner to understand:

[0959] "This technology is highly complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[0960] Please answer the following questions:

[0961] "What does it mean to be more efficient?"

[0962] The above is an embodiment of the present invention.

[0963] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0964] Step 1:

[0965] The user inputs text data and a question.

[0966] How it works: The user accesses a dedicated interface on the device and enters part of the book they are reading as text data. They also enter any questions they may have while reading the book into a separate field in the same interface.

[0967] Input: The user types, for example, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large systems," and then types in a question, "What does it mean to improve efficiency?"

[0968] Output: The input text data and questions.

[0969] Step 2:

[0970] The terminal transmits the text data and the question to the server.

[0971] Specific operation: The device acquires the text data and questions entered by the user and sends this information to the server. The device sends the data using an HTTP POST request.

[0972] Input: Text data and questions entered by the user.

[0973] Output: Text data and questions sent to the server.

[0974] Step 3:

[0975] The server receives the text data and retrieves the user's knowledge level information from a database.

[0976] Specific operation: The server analyzes the text data and questions received from the terminal, then retrieves the user's profile information from the database and checks the user's knowledge level.

[0977] Input: Text data and questions sent from the terminal.

[0978] Output: Parsed text data, user knowledge level information.

[0979] Step 4:

[0980] The server uses a generative artificial intelligence model to convert the text data into a simplified representation.

[0981] Specific operation: The server inputs text data into the generative AI model and generates a simplified representation based on the user's knowledge level. The specific prompt is passed to the generative AI model in the form of "Please summarize the following text in a form that is easy for beginners to understand: 'This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems.'"

[0982] Input: Parsed text data, user knowledge level information.

[0983] Output: Simplified text data.

[0984] Step 5:

[0985] The server uses a generative artificial intelligence model to generate answers to the user's questions.

[0986] Specific operation: The server passes the user's question to the generative AI model to generate an answer. The specific prompt is "Please answer the following question: 'What does it mean to improve efficiency?'"

[0987] Input: User's question.

[0988] Output: The generated answer.

[0989] Step 6:

[0990] The server transmits the generated simple expressions and answers to the terminal.

[0991] Specific operation: The server packages the generated simple representation and answer and sends them to the terminal. Here, the data is again packaged in JSON format and sent using an HTTP POST request.

[0992] Input: Simplified text data, generated answers.

[0993] Output: Shorthands and answers sent to the device.

[0994] Step 7:

[0995] The terminal displays the shorthand and the answer to the user.

[0996] Specific operation: The terminal analyzes the simple expressions and answers received from the server and displays them on the user interface. Specifically, a dedicated display area displays the simple expression "This technology is difficult, but by simply applying the basics, the system can run more efficiently" and the answer to the question "Improved efficiency means that the system will be able to run faster and complete tasks using fewer resources than before."

[0997] Input: Shorthands and answers sent to the device.

[0998] Output: The shorthand and answers that are displayed to the user.

[0999] Step 8:

[1000] Users review shorthand and answers to deepen their understanding.

[1001] Specific actions: The user checks the simple expressions and answers displayed on the device to confirm that their understanding has improved.

[1002] Input: The shorthand and answer displayed on the terminal.

[1003] Output: A user with a better understanding.

[1004] (Application example 1)

[1005] 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."

[1006] Currently, when reading, readers often encounter difficult content that is difficult to understand. In such cases, readers are unable to enjoy the reading experience and their learning efficiency decreases. Furthermore, when selecting a book in a store, they often end up purchasing it without understanding the details of the book, making it difficult to choose the right book. There is a need for a solution to this problem, making reading and selecting books in a store more efficient and effective.

[1007] 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.

[1008] In this invention, the server includes means for acquiring text data from a user, means for acquiring user knowledge level information from a database, means for using a generation AI to convert the text data into simplified expressions or summaries according to the user's knowledge level, means for acquiring questions from the user and generating answers to the questions using the generation AI, means for sending the converted simplified expressions or summary text and the generated answers to the user, and means for having a smart device as the terminal to visually provide the simplified expressions and answers to the user in real time while reading, thereby providing easy-to-understand information in real time while reading and improving the reading experience.

[1009] "User" means an individual who utilizes the system to input text data and receive shorthand or responses.

[1010] "Text data" refers to the text information entered from the book or text the user is reading.

[1011] "Knowledge level information" is information that indicates the user's level of understanding and is stored in a database.

[1012] A "database" is a system that organizes, stores, and manages data such as user knowledge level information.

[1013] "Simplified expression" refers to a sentence that has been converted from the original text data into a form that is easier to understand.

[1014] A "summary" is a sentence that summarizes the main points of the original text data in an abbreviated form.

[1015] "Generative AI" refers to AI that uses generative techniques to generate simplified representations, summaries, and answers to text.

[1016] A "question" is a question or uncertainty that a user has while reading the text.

[1017] An "answer" is a generated answer or explanation to a question.

[1018] "Smart device" means an electronic device that a user can wear or use to receive information in real time.

[1019] The "system" refers to the entire set of mechanisms that receives text data and questions from users, processes them, and generates simplified expressions and answers to provide to users.

[1020] This invention is a system that uses generative AI to improve the user's reading experience. Specific embodiments of this system are described below.

[1021] System Configuration

[1022] The system consists of three elements: the user, the device, and the server. The user inputs text data and questions via the device, and the server processes this data using generative AI and sends the results to the device.

[1023] Server Roles

[1024] The server has the following means:

[1025] 1. How to get text data from the user:

[1026] The server receives text data provided by the user through the terminal.

[1027] 2. How to get user knowledge level information from the database:

[1028] The server retrieves the user's knowledge level information from the database.

[1029] 3. Using generative artificial intelligence to convert text data into simplified representations or summaries:

[1030] The server uses a generative AI model (e.g., OpenAI's GPT model) to convert text data into simplified representations or summaries depending on the user's level of knowledge.

[1031] 4. A means of obtaining questions from users and generating answers to those questions:

[1032] The server takes the question entered by the user and generates an answer to that question using a generative AI model.

[1033] 5. Means for sending the converted shorthand or summary text and generated answer to the user:

[1034] The server sends the generated simple expressions and answers to the terminal.

[1035] Device Role

[1036] The device includes the following features:

[1037] 1. Providing the user interface:

[1038] The terminal provides an interface where the user can enter text data and questions.

[1039] 2. Data transmission and display:

[1040] The user inputs text data and a question into the device, which is then sent to the server, which then receives a response and provides the user with a simple expression and a visual answer in real time.

[1041] Adding specific examples

[1042] For example, a user might be reading a technical book and come across the following paragraph:

[1043] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[1044] The user types this paragraph into their device, along with the question "What does it mean to be more efficient?" The server uses a generative AI model to translate it and generate the following simple phrase and answer:

[1045] Simple: "This technology is difficult, but applying the basics will make your system work more efficiently."

[1046] Answer: "Increased efficiency means that a system can run faster or do its job using fewer resources."

[1047] The results are sent to the terminal, where the user receives a visual summary and answer, and if they have further questions, they can ask them again using the following prompt:

[1048] Please briefly explain the following sentence: Elves have long lifespans and their knowledge has been accumulated over thousands of years. The user's knowledge level is beginner.

[1049]

[1050] A user asked the question: What is an elf? Please provide a clear answer.

[1051] In this way, users can obtain technical information in an easy-to-understand format, improving their reading experience.

[1052] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1053] Step 1:

[1054] The user inputs text data and questions into the terminal.

[1055] As input, the user enters the paragraph or sentence (text data) of the book they are reading and any questions they may have about that paragraph through the terminal. The terminal receives this data and prepares to proceed to the next step.

[1056] Step 2:

[1057] The text data and the question are sent to the server.

[1058] The terminal packages the received text data and question and transmits the packaged data to the server. The transmitted data includes the text data and question entered by the user.

[1059] Step 3:

[1060] The server retrieves the user's knowledge level information from the database.

[1061] The server retrieves information about the user's knowledge level from a database, using the user's identification information as input and obtaining the user's knowledge level information as output.

[1062] Step 4:

[1063] The server uses a generative AI model to convert the text data into a simplified representation or summary.

[1064] Based on the acquired user knowledge level information, the server inputs the text data into a generative AI model (e.g., OpenAI's GPT model) and converts it into a simplified representation or summary. The text data and knowledge level are used as input, and a simplified representation or summary is generated as output.

[1065] Step 5:

[1066] The server uses a generative AI model to generate answers to questions.

[1067] The server inputs the question into a generative AI model to generate the corresponding answer. The question is used as input and the answer is generated as output.

[1068] Step 6:

[1069] The server transmits the converted shorthand or summary text and the generated answer to the terminal.

[1070] The server packages the generated simple expression or summary text and the answer, and transmits the packaged data to the terminal. The transmitted data includes the converted simple expression or summary and the answer to the question.

[1071] Step 7:

[1072] The terminal provides the user with visual shorthand and answers in real time.

[1073] The terminal displays the simple expressions and answers received from the server on the user's smart device and provides them visually. It uses the data sent from the server as input and presents information to the user in real time.

[1074] 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.

[1075] This invention utilizes a system that combines generative AI and an emotion engine to improve the user's reading experience. A specific embodiment of this system is described below.

[1076] System Overview

[1077] This system is mainly composed of three elements: a server, a terminal, and a user. The user operates the system using a terminal, and the server provides the necessary processing using a generative AI and emotion engine.

[1078] Server-side behavior

[1079] Acquiring text data and emotional information

[1080] The server receives the text data and question sent by the user. For example, consider the case where the text data received is, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems." The server then uses an emotion engine to recognize the emotion the user is feeling when typing. The emotion engine analyzes, for example, the voice tone and typing speed to identify the user's emotional state (e.g., "confused," "interested," or "bored").

[1081] Text Processing Based on User Knowledge Level and Sentiment

[1082] The server retrieves the user's knowledge level from the database based on the user ID. Then, based on the retrieved emotional information and knowledge level, it uses generative AI to convert the text data into a format (simplified expression or summary) that is easy for the user to understand. For example, if the user is recognized as "confused," the simplified expression of the text is set to a more understandable level.

[1083] Generate answers to questions and sentiment-based feedback

[1084] The server uses generative AI to generate answers to questions entered by users, and also uses an emotion engine to generate feedback messages (e.g., "You're doing a good job," "You'll understand soon," etc.) based on the user's emotional state.

[1085] Creating and Sending a Response

[1086] The generated shorthand or summary text, the answer to the question, and the sentiment-based feedback are packaged and the response data is sent to the user.

[1087] Operation on the terminal side

[1088] Providing a user interface

[1089] The device provides an interface for users to input text data and questions. The interface includes a field for inputting the reading passage and a field for inputting questions. It also includes an interface (e.g., voice input or face recognition) for the emotion engine to recognize the user's emotions.

[1090] Sending and Displaying Data

[1091] After the user inputs text data and a question, the device sends this information to the server. After receiving a response from the server, the device displays the received simple expressions, answers, and emotion-based feedback messages to the user, allowing the user to obtain information in an easy-to-understand format.

[1092] User behavior

[1093] Enter text data and questions

[1094] The user inputs part of the book they are reading as text data into the device. They also input any questions they have while reading. Voice input and facial recognition functions are used as needed to enable the emotion engine to recognize emotions.

[1095] Verifying information and using emotional feedback

[1096] Users can check the simple expressions and answers sent from the server to confirm their understanding. Furthermore, they can receive emotional feedback messages to provide psychological support. This allows users to efficiently read through even difficult content, improving their learning efficiency.

[1097] Specific examples

[1098] For example, a user might be reading a technical book and come across the following paragraph:

[1099] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[1100] The user inputs this paragraph into the system, and also inputs the question "What does it mean to improve efficiency?" The emotion engine recognizes that the user is in a "confused" state. The server confirms that the user's knowledge level is beginner and that they are in a confused state, and converts the paragraph into a simple expression: "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question: "Improved efficiency means that the system can run faster or perform its work with fewer resources than before," and creates a feedback message saying, "You're doing well. There are some difficult parts, but you're almost there."

[1101] In this way, users can obtain technical information in an easy-to-understand format, improving their reading experience.

[1102] The processing flow will be explained below.

[1103] Step 1:

[1104] Users log in to their device and select a book to begin reading. After the book is loaded, users copy and paste the portion of the text they want to read into the device's interface.

[1105] Step 2:

[1106] The user inputs the paragraph of text he is reading into an input field on the terminal, and at the same time inputs any questions he has into the input field.

[1107] Step 3:

[1108] The device receives text data and questions entered by the user. After verifying that the data has been received correctly, it generates a data package containing the user's identification information. It also obtains the user's emotional information through voice input and facial recognition.

[1109] Step 4:

[1110] The terminal transmits the package data to the server, which includes the user ID, text data, questions, and emotion information.

[1111] Step 5:

[1112] The server receives the package data sent from the terminal, and then retrieves the user's knowledge level information from the database based on the user ID.

[1113] Step 6:

[1114] Based on the acquired knowledge level information and emotion information, the server uses a generation AI to convert the text data into a format (simplified expression or summary) that is easy for the user to understand. For example, if the user is recognized as "confused," the simplified expression of the text is set to a simpler level.

[1115] Step 7:

[1116] The server uses generative AI to generate answers to questions entered by users, and also uses an emotion engine to generate feedback messages (e.g., "You're doing a good job," "You'll understand soon," etc.) based on the user's emotional state.

[1117] Step 8:

[1118] The server packages the converted shorthand or summary text with the generated answers and sentiment-based feedback messages to create response data.

[1119] Step 9:

[1120] The server sends the response data to the terminal, which includes abbreviated or summarized text to aid the user's understanding, answers to questions, and sentiment-based feedback messages.

[1121] Step 10:

[1122] The terminal receives the response data from the server, analyzes the contents of the response data, and prepares to display it to the user.

[1123] Step 11:

[1124] The terminal displays the simplified or summarized text sent from the server, along with answers to questions and emotion-based feedback messages to the user. The user can confirm the displayed content and deepen their understanding. The emotion-based feedback also provides psychological support.

[1125] Example 2

[1126] 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."

[1127] Conventional reading assistance systems typically convert content based solely on the user's knowledge level. However, they do not provide appropriate feedback or text conversion that takes into account the user's emotional state, which can leave users feeling confused or bored, resulting in reduced learning efficiency. Furthermore, they often fail to provide appropriate answers to their questions. The present invention aims to solve these problems and provide a reading assistance system that is easier to understand and takes into account the user's emotional state.

[1128] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring text data and questions from a user, means for acquiring the user's knowledge level information and emotional information from a database and an emotional analysis engine, means for using a generation AI to convert the text data into a simplified expression or a summary according to the user's knowledge level and emotional information, means for acquiring the user's questions and generating an answer to the question using the generation AI, means for generating a feedback message based on the user's emotional information, and means for sending the converted simplified expression or summary text, the generated answer, and the feedback message to the user. This allows the user to receive appropriate feedback and text conversion tailored to their knowledge level and emotional state, thereby improving the efficiency of reading and learning.

[1129] "User" refers to any individual or entity that uses the System to convert text data or request answers to questions.

[1130] "Text data" refers to sentences or paragraphs of data that a user enters into a system.

[1131] "Questions" refer to questions or uncertainties that arise when a user is reading text data.

[1132] "Knowledge level" is information that indicates the user's level of expertise and understanding.

[1133] "Emotional information" refers to information that indicates the user's current emotional state (e.g., confusion, interest, boredom, etc.).

[1134] An "emotion analysis engine" refers to a program or system that analyzes a user's text data or voice data to identify emotional information.

[1135] "Database" refers to an information system for storing and managing user knowledge level information and other related information.

[1136] "Generative AI" refers to technology that uses machine learning and natural language processing to convert text data into simple expressions or summaries, or to generate answers to questions.

[1137] "Simplified expression" refers to a sentence that has been reconstructed from the original text data to make it easier to understand.

[1138] A "summary" refers to a short sentence summarizing the main points of the original text data.

[1139] A "feedback message" is a message generated based on the user's emotional information, and provides the user with a sense of psychological security and motivation.

[1140] "Packaging" refers to the process of bundling multiple pieces of data (e.g., shorthand, response, feedback message) into a format for transmission.

[1141] This invention provides a system that combines a generative AI model and a sentiment analysis engine to improve the user's reading experience. This system mainly consists of three elements: a server, a terminal, and a user.

[1142] Server-side behavior

[1143] The server performs the following process.

[1144] First, the server receives the text data and question sent by the user. Specifically, the text data and question entered by the user are sent to the server via an HTTP request. For example, the user might send the text data, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems."

[1145] Next, the server uses an emotion analysis engine to recognize the emotion the user is feeling when typing. For example, it analyzes the voice tone and typing speed to identify the user's emotional state (e.g., "confused," "interested," "bored"). For this purpose, a common emotion analysis engine (e.g., emotion analysis API) is used.

[1146] The server also retrieves the user's knowledge level from the database based on the user ID, and in this process, uses an SQL query to retrieve the user's knowledge level information from the database.

[1147] Based on the acquired emotional information and knowledge level, the server uses a generative AI model to convert the text data into a format that is easy for the user to understand (simple expressions or summary). For example, a general generative AI model (e.g., a generative AI model API) is used, and the prompt message sent is "Please convert the text into simple expressions that are easy for the user to understand."

[1148] Furthermore, the server uses the generative AI model to generate answers to questions entered by the user. This process also uses the generative AI model, sending the prompt "What does it mean to improve efficiency?"

[1149] Feedback messages based on emotional information are also generated on the server. Depending on the results of the emotion analysis engine, feedback messages such as "You're doing well" or "You'll understand soon" are generated.

[1150] Finally, the server packages the generated shorthand or summary text, the answer to the question, and the sentiment-based feedback message and sends it to the user. This response is packaged in JSON format and sent as an HTTP response.

[1151] Operation on the terminal side

[1152] The terminal operates as follows:

[1153] It provides an interface for users to input text data and questions. The interface includes a field for inputting the part being read and a field for inputting questions. It also includes an interface (voice input and facial recognition) that allows the emotion engine to recognize the user's emotions. After the user enters the necessary information in these fields, the device sends this information to the server.

[1154] The received response is analyzed and displayed to the user as a simple expression, an answer to the question, or an emotional feedback message. This data is then displayed appropriately in the UI, providing the user with information in an easy-to-understand format.

[1155] User behavior

[1156] The user follows the steps below:

[1157] First, users input part of the book they are reading into the device as text data. They also input any questions they have while reading. If necessary, voice input and facial recognition functions are used so that the emotion engine can recognize emotions.

[1158] Users can check the simple expressions and answers sent from the server to confirm their understanding. Furthermore, they can receive emotional feedback messages to provide psychological support. This allows users to efficiently read through even difficult content, improving their learning efficiency.

[1159] Specific examples

[1160] For example, if a user encounters the following paragraph:

[1161] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[1162] The user inputs this paragraph into the system, and also inputs the question "What does it mean to improve efficiency?" The emotion engine recognizes that the user is in a "confused" state. The server confirms that the user's knowledge level is beginner and that they are in a confused state, and converts the paragraph into a simple expression: "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question: "Improved efficiency means that the system will be able to run faster or perform its work with fewer resources than before," and also creates a feedback message saying, "You're doing well. There are some difficult parts, but you'll soon understand."

[1163] This allows users to obtain information in an easy-to-understand format, even for specialized content, improving their reading experience.

[1164] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1165] Step 1: Getting user-entered data

[1166] The user inputs the text data of the reading content and any questions that arise into the terminal. The terminal then sends this information to the server as an HTTP request. The input data consists of a text field and a question field, and examples include "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems" and "What do you mean by improved efficiency?"

[1167] Step 2: Receiving data on the server

[1168] The server receives the HTTP request sent from the terminal and obtains the text data and questions. Specifically, it extracts the text data and questions from the HTTP request body and prepares the data for subsequent processing. The input is the user's text data and questions, and the output is the prepared state of these data.

[1169] Step 3: Acquiring emotional information

[1170] The server uses a sentiment analysis engine to obtain the user's emotional information from the input text data and questions. Specifically, it sends the text data to the sentiment analysis API and receives the sentiment analysis results (confusion, interest, boredom, etc.). The input is the text data and questions, and the output is the user's emotional information.

[1171] Step 4: Gain a level of knowledge

[1172] The server retrieves the user's knowledge level information from the database based on the user ID. Specifically, it accesses the database using an SQL query to inquire about the user's knowledge level. The input is the user ID, and the output is the user's knowledge level information.

[1173] Step 5: Text conversion process

[1174] The server uses a generative AI model to convert text data into a simplified representation or summary based on emotion information and knowledge level information. Specifically, it provides a prompt to the generative AI model API to generate a simplified representation or summary. The input is text data, emotion information, knowledge level information, and a prompt, and the output is a simplified representation or summary text.

[1175] Step 6: Generate answers to your questions

[1176] The server uses the generative AI model to generate an answer to the user's question. Specifically, the question is sent as a prompt to the generative AI model API, and an appropriate answer is obtained. The input is the question and the prompt, and the output is the answer to the question.

[1177] Step 7: Generate feedback messages

[1178] The server generates a feedback message based on the emotion analysis results. Specifically, it selects and customizes a feedback message from a template according to the emotion information. The input is the emotion information, and the output is the customized feedback message.

[1179] Step 8: Packaging and Sending the Response

[1180] The server packages the generated simple expression or summary text, the answer to the question, and the feedback message, and sends them to the user. Specifically, it compiles this data in JSON format and sends it to the terminal as an HTTP response. The input is the simple expression or summary text, the answer to the question, and the feedback message, and the output is the packaged response data.

[1181] Step 9: Receive and display response data

[1182] The device receives the response data sent from the server, analyzes it, and displays a simple expression, an answer to the question, and a feedback message to the user. Specifically, it analyzes the received JSON data and displays each piece of information on the UI. The input is the response data, and the output is the displayed simple expression, answer, and feedback message.

[1183] Step 10: Verifying Information and Using Emotional Feedback

[1184] Users can check the displayed simple expressions and answers to confirm their understanding and receive emotional feedback messages to provide psychological support. By reading these messages, users can enhance their understanding and improve their reading experience.

[1185] (Application example 2)

[1186] 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."

[1187] Conventional reading assistance systems are limited to converting text according to the user's knowledge level and lack customization that takes into account the user's emotional state. This can lead to difficulties in reading comprehension and reduced learning efficiency. New methods are needed to solve this problem and improve the user's reading experience.

[1188] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring text data from a user, means for acquiring the user's knowledge level information and emotional information from a database, means for using a generation AI to convert the text data into a simplified expression or a summary according to the user's knowledge level and emotional information, means for using an emotion engine to analyze the user's emotional state, means for acquiring a question from the user and using the generation AI to generate an answer to the question and a feedback message based on the emotion, and means for sending the converted simplified expression or summary text and the generated answer and feedback message to the user. This enables individual optimization according to the user's emotional state, thereby providing more understandable information and psychological support.

[1189] "User" means an individual user of the system.

[1190] "Text data" is textual information that a user inputs into a system.

[1191] "Knowledge level information" is data regarding the user's level of understanding and depth of expertise.

[1192] "Emotion information" is data that indicates the user's emotional state.

[1193] A "database" is a storage device that stores data such as knowledge level information and emotion information.

[1194] A "simple phrase" is text that has been simplified to make it easier for users to understand.

[1195] A "summary" is a short summary of the original text.

[1196] "Generative AI" is an AI technology for converting text data and generating answers to questions.

[1197] An "emotion engine" is a technology for analyzing and identifying a user's emotional state.

[1198] "Questions" are questions or doubts that users have after reading the text data.

[1199] "Feedback messages" are messages of support or encouragement that correspond to the user's emotional state.

[1200] A "server" is a central computer that handles the overall processing of the system.

[1201] This invention uses a system that combines generative AI and an emotion engine to improve users' reading experience and understanding of product descriptions on online shopping sites. Specific embodiments for implementing this system are described below.

[1202] System Overview

[1203] This system consists of three elements: a server, a terminal, and a user. The server provides the necessary processing using a generative AI and emotion engine, and the terminal provides the interface to the user.

[1204] Server Operation

[1205] Acquiring text data and emotional information

[1206] The server receives text data sent by the user. For example, consider the case where the text data is "This product uses cutting-edge technology and is very effective." The server uses an emotion engine to identify the user's emotional state (e.g., "confused," "excited," "bored"). The emotion engine analyzes the voice tone, typing speed, etc. to recognize the emotional state.

[1207] Text processing based on user knowledge level and sentiment

[1208] The server retrieves knowledge level and emotion information from the database based on the user ID. Then, based on the retrieved emotion information and knowledge level, it uses generative AI to convert the text data into a format (simplified expression or summary) that is easy for the user to understand. For example, if the user is recognized as "confused," the text's simplified expression is set to a more understandable level.

[1209] Generate answers to questions and sentiment-based feedback

[1210] The server uses generative AI to generate answers to questions entered by the user, and also generates feedback messages based on the user's emotional state (e.g., "You're doing a great job").

[1211] Creating and Sending a Response

[1212] The generated simplified text, the answer to the question, and the feedback message based on the emotion are packaged and sent to the user's terminal as response data.

[1213] Device behavior

[1214] Providing a user interface

[1215] The device provides an interface for users to input text data and questions. The interface includes a field for inputting the reading passage and a field for inputting questions. It also includes an interface (e.g., voice input or facial recognition) for the emotion engine to recognize the user's emotions.

[1216] Sending and Displaying Data

[1217] After the user inputs text data and questions, the terminal sends this information to the server. After receiving a response from the server, the terminal displays the received simplified text, answers, and feedback messages to the user, allowing the user to obtain information in an easy-to-understand format.

[1218] User behavior

[1219] Enter text data and questions

[1220] Users input product descriptions and reviews as text data into the device. They also input any questions they may have while reading the text data. Voice input and facial recognition functions are used as needed to enable the emotion engine to recognize emotions.

[1221] Verifying information and using emotional feedback

[1222] The system checks the simplified text, answers, and feedback messages sent from the server to confirm that the user's understanding has improved. This allows the user to efficiently understand even complex content, improving the user's experience on the online shopping site.

[1223] Specific examples

[1224] For example, a user might read a product description and come across the following paragraph:

[1225] "This product uses cutting edge technology and is very effective."

[1226] The user inputs this paragraph into the system and then enters the question, "How exactly is it effective?" The emotion engine recognizes that the user is in a "confused" state. The server confirms that the user's knowledge level is beginner and that they are in a confused state, and converts the paragraph into a simplified expression, "This product uses new technology and is very useful." At the same time, it generates an answer to the question: "What I mean by effective is that using this product makes you more efficient than before," and creates a feedback message saying, "You're doing a great job."

[1227] Prompt Sentence Examples

[1228] User ID: User ID. Please describe this in simple terms: Original description.

[1229] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1230] Step 1: The user enters the product description text and question into the terminal.

[1231] Input: Product description text (e.g., "This product uses cutting-edge technology and is highly effective"), questions (e.g., "How exactly is it effective?")

[1232] How it works: The terminal provides fields to receive user-entered text and questions. The user enters text data and questions into these fields.

[1233] Output: Input text data and questions

[1234] Step 2: The device sends the text data, question, and user ID to the server.

[1235] Input: Text data, question, user ID

[1236] Operation: The terminal sends the text data and question entered by the user, as well as the user ID, to the server.

[1237] Output: Request data including text data, question, and user ID

[1238] Step 3: The server uses the emotion engine to analyze the user's emotional state.

[1239] Input: Request data

[1240] How it works: The server uses an emotion engine to analyze the text data in the request data, such as voice tone and typing speed, to determine the user's emotional state.

[1241] Output: Emotional state (e.g., "confused")

[1242] Step 4: The server retrieves the user's knowledge level information from the database.

[1243] Input: User ID

[1244] Operation: The server accesses the database and retrieves knowledge level information based on the user ID.

[1245] Output: Knowledge level information (e.g., "Beginner")

[1246] Step 5: The server uses generative AI to convert the text into simple expressions and summaries based on the emotional state and knowledge level.

[1247] Input: Text data, emotional state, knowledge level information

[1248] How it works: The server uses a generative AI to convert text data into simplified expressions appropriate for the knowledge level of "beginner," taking into account that the emotional state is "confused."

[1249] Output: Simple text (e.g. "This product uses new technology and is very useful.")

[1250] Step 6: The server uses AI to generate answers to the user's questions.

[1251] Input: Question, text data, knowledge level information, emotional state

[1252] How it works: The server uses generative AI to generate specific and understandable answers to questions based on your emotional state and knowledge level.

[1253] Output: Answer to the question (e.g., "Effective" means that using this product makes you more efficient than before.")

[1254] Step 7: The server generates a feedback message based on the emotional state.

[1255] Input: Emotional state

[1256] Behavior: The server considers the emotional state to be "confused" and generates an encouraging feedback message for the user.

[1257] Output: Feedback message (e.g. "Good job!")

[1258] Step 8: The server packages the generated simple text, the answer, and the feedback message and sends them to the terminal.

[1259] Input: Shorthand text, answer, feedback message

[1260] Operation: The server packages these data and sends them to the terminal as response data.

[1261] Output: Response data (simple text, answers, feedback messages)

[1262] Step 9: The device displays the received data to the user.

[1263] Input: Response data

[1264] Behavior: The device displays received shorthand text, responses, and feedback messages to the user.

[1265] Output: Information displayed to the user (simple text, answers, feedback messages)

[1266] This allows users to obtain information in an easy-to-understand format, deepening their understanding of the product and providing psychological support.

[1267] 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.

[1268] 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.

[1269] 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.

[1270] [Fourth embodiment]

[1271] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1272] 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.

[1273] 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).

[1274] 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.

[1275] 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.

[1276] 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).

[1277] 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.

[1278] 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.

[1279] 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.

[1280] 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.

[1281] 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.

[1282] 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.

[1283] 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."

[1284] This invention provides a system that utilizes generative AI to improve a user's reading experience. Specific embodiments of this system are described below.

[1285] System Overview

[1286] This system is mainly composed of three elements: a server, a terminal, and a user. The user operates the system using a terminal, and the server uses a generative AI to process the necessary text and generate answers.

[1287] Server-side behavior

[1288] Acquiring and processing text data

[1289] The server receives text data sent by the user. For example, consider the case where the text data received is, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems." The server retrieves the user's knowledge level from a database and uses generative AI to convert this text data into a simplified expression or summary that is easy for the user to understand. For example, a beginner user would be provided with the simplified expression, "This technology is difficult, but simply applying the basics will make the system run more efficiently."

[1290] Generating answers to user questions

[1291] The server also receives questions sent by users and generates answers to those questions using the same generative AI. For example, in response to the question, "What does it mean to improve efficiency?", the server generates the answer, "Improved efficiency means that the system can run faster or get the job done using fewer resources."

[1292] Creating and Sending a Response

[1293] The generated shorthand and answers are packaged and sent to the user, who receives this information to improve their reading comprehension.

[1294] Operation on the terminal side

[1295] Providing a user interface

[1296] The terminal provides an interface for the user to input text data and questions, including a field for entering the reading passage and a field for entering questions.

[1297] Sending and Displaying Data

[1298] After the user enters text data and a question, the device sends this information to the server. After receiving a response from the server, the device displays the received simplified expression and answer to the user, allowing the user to obtain information in an easy-to-understand format.

[1299] User behavior

[1300] Enter text data and questions

[1301] The user inputs part of the book they are reading as text data into the terminal, as well as any questions that arise while reading the book.

[1302] Verify the information

[1303] The user can check the simple expressions and answers sent from the server to confirm that their understanding has deepened. This allows the user to efficiently read through even difficult content, improving learning efficiency.

[1304] Specific examples

[1305] For example, a user might be reading a technical book and come across the following paragraph:

[1306] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[1307] The user inputs this paragraph into the system, and also inputs the question, "What does it mean to improve efficiency?" The server confirms that the user's knowledge level is beginner level, and converts the paragraph into a simple expression, "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question, "Improved efficiency means that the system will run faster and be able to complete tasks using fewer resources," and provides this to the user via their terminal.

[1308] In this way, users can obtain technical information in an easy-to-understand format, improving their reading experience.

[1309] The processing flow will be explained below.

[1310] Step 1:

[1311] Users log in to their device and select a book to begin reading. After the book is loaded, users copy and paste the portion of the text they want to read into the device's interface.

[1312] Step 2:

[1313] The user inputs the paragraph of text he is reading into an input field on the terminal, and at the same time inputs any questions he has into the input field.

[1314] Step 3:

[1315] The terminal receives the text data and question input by the user, and after verifying that the data has been received correctly, generates package data including the user's identification information.

[1316] Step 4:

[1317] The terminal sends this package data, which includes the user ID, text data, and questions, to the server.

[1318] Step 5:

[1319] The server receives the package data sent from the terminal, and then retrieves the user's knowledge level information from the database based on the user ID.

[1320] Step 6:

[1321] Based on the acquired knowledge level information, the server uses a generation AI to convert the text data into a format that is easy for the user to understand (for example, simple expressions or summaries).

[1322] Step 7:

[1323] The server uses AI to generate answers to questions entered by users, creating appropriate answers based on text data related to the question.

[1324] Step 8:

[1325] The server packages the converted shorthand or summary text and the generated answer to create response data.

[1326] Step 9:

[1327] The server then sends the response data to the terminal, which includes a simplified expression or summary text to help the user understand, and the answer to the question.

[1328] Step 10:

[1329] The terminal receives the response data from the server, analyzes the contents of the response data, and prepares to display it to the user.

[1330] Step 11:

[1331] The terminal displays the simplified expressions or summary text sent from the server and the answers to the questions to the user, allowing the user to confirm the displayed content and deepen their understanding.

[1332] Example 1

[1333] 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."

[1334] Currently, many people struggle to understand the content of specialized books and technical documents. Beginners and users with little prior knowledge find technical terminology and complex explanations particularly difficult to understand. Furthermore, the inability to quickly find answers to questions that arise while reading leads to a decline in learning efficiency. In these circumstances, there is a need for a system that can convert text into an easy-to-understand format and provide appropriate answers to questions.

[1335] 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.

[1336] In this invention, the server includes means for acquiring text data and questions from a user, means for a terminal to transmit the text data and questions to the server, means for the server to receive the text data and acquire user knowledge level information from a database, means for converting the text data into a simplified expression or a summary using a generative AI model, means for generating an answer to the user's question using the generative AI model, means for transmitting the converted simplified expression or summary text and the generated answer to the user, and means for the terminal to display the simplified expression and the answer to the user. This allows users to obtain specialized content in an easy-to-understand format and quickly find answers to questions that arise while reading.

[1337] The "server" is a central system that receives data from users, retrieves information from a database, processes and generates data using generative AI models, and sends the results to users.

[1338] A "terminal" is a device operated by a user, which inputs text data and questions, transmits them to a server, and receives and displays responses from the server.

[1339] A "user" is a person who uses the system to input text data, ask questions, and receive information from the server.

[1340] "Text data" refers to a portion of a book or document that a user is reading, and is text information that is input into the system.

[1341] "Questions" refer to questions or unclear points that arise when the user is reading the text data.

[1342] "Knowledge level information" is information that indicates the user's knowledge and level of understanding, and is stored in a database.

[1343] A "generative AI model" is an AI system used to convert text data into simple expressions or summaries and generate answers to questions.

[1344] "Simplified expressions" are sentences that convert specialized or complex text data into easy-to-understand sentences that suit the user's level of knowledge.

[1345] A "summary" is a piece of text that provides the main points or content of text data in an abbreviated form.

[1346] An "answer" is a generated answer to a question posed by a user.

[1347] A "database" is a storage device that stores user knowledge level information and other necessary information.

[1348] "Packaging" is the process of formatting data sent from a user or a server into a format suitable for transmission.

[1349] The present invention provides a system for improving a user's reading experience by utilizing generative artificial intelligence. A specific embodiment of this system will be described below.

[1350] System Overview

[1351] This system is mainly composed of three elements: a server, a terminal, and a user. The user operates the system using a terminal, and the server uses generative artificial intelligence to process the necessary text and generate answers.

[1352] Server-side behavior

[1353] Acquiring and processing text data

[1354] The server receives text data sent by a user. For example, consider the case where the text data received is, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems." The server obtains the user's knowledge level information from the database and uses generative artificial intelligence to convert this text data into a simplified expression or summary that is easy for the user to understand. For example, a beginner user would be provided with the simplified expression, "This technology is difficult, but simply applying the basics will make the system run more efficiently."

[1355] Generating answers to user questions

[1356] The server also receives questions sent by users and generates answers to those questions using generative AI. For example, in response to the question "What does it mean to improve efficiency?", the server generates the answer "Improved efficiency means that the system can run faster or perform its work using fewer resources."

[1357] Creating and Sending a Response

[1358] The server packages the generated shorthand and answers and sends the content to the user, who receives this information to improve their reading comprehension.

[1359] Operation on the terminal side

[1360] Providing a user interface

[1361] The terminal provides an interface for the user to input text data and questions, including a field for entering the reading passage and a field for entering questions.

[1362] Sending and Displaying Data

[1363] After the user enters text data and a question, the device sends this information to the server. After receiving a response from the server, the device displays the received simplified expression and answer to the user, allowing the user to obtain information in an easy-to-understand format.

[1364] User behavior

[1365] Enter text data and questions

[1366] The user inputs part of the book they are reading as text data into the terminal, as well as any questions that arise while reading the book.

[1367] Verify the information

[1368] The user can check the simple expressions and answers sent from the server to confirm that their understanding has deepened. This allows the user to efficiently read through even difficult content, improving learning efficiency.

[1369] Specific examples

[1370] For example, a user might be reading a technical book and come across the following paragraph:

[1371] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[1372] The user inputs this paragraph into the system, and also inputs the question, "What does it mean to improve efficiency?" The server confirms that the user's knowledge level is beginner level and converts the paragraph into a simple expression: "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question: "Improved efficiency means that the system will run faster or be able to complete tasks using fewer resources," and provides this to the user via their device. In this way, the user can obtain information, even if it is technical, in an easy-to-understand format, improving their reading experience.

[1373] Prompt Sentence Examples

[1374] "Please summarize the following text in a way that is easy for a beginner to understand:

[1375] "This technology is highly complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[1376] Please answer the following questions:

[1377] "What does it mean to be more efficient?"

[1378] The above is an embodiment of the present invention.

[1379] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1380] Step 1:

[1381] The user inputs text data and a question.

[1382] How it works: The user accesses a dedicated interface on the device and enters part of the book they are reading as text data. They also enter any questions they may have while reading the book into a separate field in the same interface.

[1383] Input: The user types, for example, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large systems," and then types in a question, "What does it mean to improve efficiency?"

[1384] Output: The input text data and questions.

[1385] Step 2:

[1386] The terminal transmits the text data and the question to the server.

[1387] Specific operation: The device acquires the text data and questions entered by the user and sends this information to the server. The device sends the data using an HTTP POST request.

[1388] Input: Text data and questions entered by the user.

[1389] Output: Text data and questions sent to the server.

[1390] Step 3:

[1391] The server receives the text data and retrieves the user's knowledge level information from a database.

[1392] Specific operation: The server analyzes the text data and questions received from the terminal, then retrieves the user's profile information from the database and checks the user's knowledge level.

[1393] Input: Text data and questions sent from the terminal.

[1394] Output: Parsed text data, user knowledge level information.

[1395] Step 4:

[1396] The server uses a generative artificial intelligence model to convert the text data into a simplified representation.

[1397] Specific operation: The server inputs text data into the generative AI model and generates a simplified representation based on the user's knowledge level. The specific prompt is passed to the generative AI model in the form of "Please summarize the following text in a form that is easy for beginners to understand: 'This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems.'"

[1398] Input: Parsed text data, user knowledge level information.

[1399] Output: Simplified text data.

[1400] Step 5:

[1401] The server uses a generative artificial intelligence model to generate answers to the user's questions.

[1402] Specific operation: The server passes the user's question to the generative AI model to generate an answer. The specific prompt is "Please answer the following question: 'What does it mean to improve efficiency?'"

[1403] Input: User's question.

[1404] Output: The generated answer.

[1405] Step 6:

[1406] The server transmits the generated simple expressions and answers to the terminal.

[1407] Specific operation: The server packages the generated simple representation and answer and sends them to the terminal. Here, the data is again packaged in JSON format and sent using an HTTP POST request.

[1408] Input: Simplified text data, generated answers.

[1409] Output: Shorthands and answers sent to the device.

[1410] Step 7:

[1411] The terminal displays the shorthand and the answer to the user.

[1412] Specific operation: The terminal analyzes the simple expressions and answers received from the server and displays them on the user interface. Specifically, a dedicated display area displays the simple expression "This technology is difficult, but by simply applying the basics, the system can run more efficiently" and the answer to the question "Improved efficiency means that the system will be able to run faster and complete tasks using fewer resources than before."

[1413] Input: Shorthands and answers sent to the device.

[1414] Output: The shorthand and answers that are displayed to the user.

[1415] Step 8:

[1416] Users review shorthand and answers to deepen their understanding.

[1417] Specific actions: The user checks the simple expressions and answers displayed on the device to confirm that their understanding has improved.

[1418] Input: The shorthand and answer displayed on the terminal.

[1419] Output: A user with a better understanding.

[1420] (Application example 1)

[1421] 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."

[1422] Currently, when reading, readers often encounter difficult content that is difficult to understand. In such cases, readers are unable to enjoy the reading experience and their learning efficiency decreases. Furthermore, when selecting a book in a store, they often end up purchasing it without understanding the details of the book, making it difficult to choose the right book. There is a need for a solution to this problem, making reading and selecting books in a store more efficient and effective.

[1423] 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.

[1424] In this invention, the server includes means for acquiring text data from a user, means for acquiring user knowledge level information from a database, means for using a generation AI to convert the text data into simplified expressions or summaries according to the user's knowledge level, means for acquiring questions from the user and generating answers to the questions using the generation AI, means for sending the converted simplified expressions or summary text and the generated answers to the user, and means for having a smart device as the terminal to visually provide the simplified expressions and answers to the user in real time while reading, thereby providing easy-to-understand information in real time while reading and improving the reading experience.

[1425] "User" means an individual who utilizes the system to input text data and receive shorthand or responses.

[1426] "Text data" refers to the text information entered from the book or text the user is reading.

[1427] "Knowledge level information" is information that indicates the user's level of understanding and is stored in a database.

[1428] A "database" is a system that organizes, stores, and manages data such as user knowledge level information.

[1429] "Simplified expression" refers to a sentence that has been converted from the original text data into a form that is easier to understand.

[1430] A "summary" is a sentence that summarizes the main points of the original text data in an abbreviated form.

[1431] "Generative AI" refers to AI that uses generative techniques to generate simplified representations, summaries, and answers to text.

[1432] A "question" is a question or uncertainty that a user has while reading the text.

[1433] An "answer" is a generated answer or explanation to a question.

[1434] "Smart device" means an electronic device that a user can wear or use to receive information in real time.

[1435] The "system" refers to the entire set of mechanisms that receives text data and questions from users, processes them, and generates simplified expressions and answers to provide to users.

[1436] This invention is a system that uses generative AI to improve the user's reading experience. Specific embodiments of this system are described below.

[1437] System Configuration

[1438] The system consists of three elements: the user, the device, and the server. The user inputs text data and questions via the device, and the server processes this data using generative AI and sends the results to the device.

[1439] Server Roles

[1440] The server has the following means:

[1441] 1. How to get text data from the user:

[1442] The server receives text data provided by the user through the terminal.

[1443] 2. How to get user knowledge level information from the database:

[1444] The server retrieves the user's knowledge level information from the database.

[1445] 3. Using generative artificial intelligence to convert text data into simplified representations or summaries:

[1446] The server uses a generative AI model (e.g., OpenAI's GPT model) to convert text data into simplified representations or summaries depending on the user's level of knowledge.

[1447] 4. A means of obtaining questions from users and generating answers to those questions:

[1448] The server takes the question entered by the user and generates an answer to that question using a generative AI model.

[1449] 5. Means for sending the converted shorthand or summary text and generated answer to the user:

[1450] The server sends the generated simple expressions and answers to the terminal.

[1451] Device Role

[1452] The device includes the following features:

[1453] 1. Providing the user interface:

[1454] The terminal provides an interface where the user can enter text data and questions.

[1455] 2. Data transmission and display:

[1456] The user inputs text data and a question into the device, which is then sent to the server, which then receives a response and provides the user with a simple expression and a visual answer in real time.

[1457] Adding specific examples

[1458] For example, a user might be reading a technical book and come across the following paragraph:

[1459] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[1460] The user types this paragraph into their device, along with the question "What does it mean to be more efficient?" The server uses a generative AI model to translate it and generate the following simple phrase and answer:

[1461] Simple: "This technology is difficult, but applying the basics will make your system work more efficiently."

[1462] Answer: "Increased efficiency means that a system can run faster or do its job using fewer resources."

[1463] The results are sent to the terminal, where the user receives a visual summary and answer, and if they have further questions, they can ask them again using the following prompt:

[1464] Please briefly explain the following sentence: Elves have long lifespans and their knowledge has been accumulated over thousands of years. The user's knowledge level is beginner.

[1465]

[1466] A user asked the question: What is an elf? Please provide a clear answer.

[1467] In this way, users can obtain technical information in an easy-to-understand format, improving their reading experience.

[1468] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1469] Step 1:

[1470] The user inputs text data and questions into the terminal.

[1471] As input, the user enters the paragraph or sentence (text data) of the book they are reading and any questions they may have about that paragraph through the terminal. The terminal receives this data and prepares to proceed to the next step.

[1472] Step 2:

[1473] The text data and the question are sent to the server.

[1474] The terminal packages the received text data and question and transmits the packaged data to the server. The transmitted data includes the text data and question entered by the user.

[1475] Step 3:

[1476] The server retrieves the user's knowledge level information from the database.

[1477] The server retrieves information about the user's knowledge level from a database, using the user's identification information as input and obtaining the user's knowledge level information as output.

[1478] Step 4:

[1479] The server uses a generative AI model to convert the text data into a simplified representation or summary.

[1480] Based on the acquired user knowledge level information, the server inputs the text data into a generative AI model (e.g., OpenAI's GPT model) and converts it into a simplified representation or summary. The text data and knowledge level are used as input, and a simplified representation or summary is generated as output.

[1481] Step 5:

[1482] The server uses a generative AI model to generate answers to questions.

[1483] The server inputs the question into a generative AI model to generate the corresponding answer. The question is used as input and the answer is generated as output.

[1484] Step 6:

[1485] The server transmits the converted shorthand or summary text and the generated answer to the terminal.

[1486] The server packages the generated simple expression or summary text and the answer, and transmits the packaged data to the terminal. The transmitted data includes the converted simple expression or summary and the answer to the question.

[1487] Step 7:

[1488] The terminal provides the user with visual shorthand and answers in real time.

[1489] The terminal displays the simple expressions and answers received from the server on the user's smart device and provides them visually. It uses the data sent from the server as input and presents information to the user in real time.

[1490] 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.

[1491] This invention utilizes a system that combines generative AI and an emotion engine to improve the user's reading experience. A specific embodiment of this system is described below.

[1492] System Overview

[1493] This system is mainly composed of three elements: a server, a terminal, and a user. The user operates the system using a terminal, and the server provides the necessary processing using a generative AI and emotion engine.

[1494] Server-side behavior

[1495] Acquiring text data and emotional information

[1496] The server receives the text data and question sent by the user. For example, consider the case where the text data received is, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems." The server then uses an emotion engine to recognize the emotion the user is feeling when typing. The emotion engine analyzes, for example, the voice tone and typing speed to identify the user's emotional state (e.g., "confused," "interested," or "bored").

[1497] Text Processing Based on User Knowledge Level and Sentiment

[1498] The server retrieves the user's knowledge level from the database based on the user ID. Then, based on the retrieved emotion information and knowledge level, it uses generative AI to convert the text data into a format (simplified expression or summary) that is easy for the user to understand. For example, if the user is recognized as "confused," the simplified expression of the text is set to a more understandable level.

[1499] Generate answers to questions and sentiment-based feedback

[1500] The server uses generative AI to generate answers to questions entered by users, and also uses an emotion engine to generate feedback messages (e.g., "You're doing a good job," "You'll understand soon," etc.) based on the user's emotional state.

[1501] Creating and Sending a Response

[1502] The generated shorthand or summary text, the answer to the question, and the sentiment-based feedback are packaged and the response data is sent to the user.

[1503] Operation on the terminal side

[1504] Providing a user interface

[1505] The device provides an interface for users to input text data and questions. The interface includes a field for inputting the reading passage and a field for inputting questions. It also includes an interface (e.g., voice input or face recognition) for the emotion engine to recognize the user's emotions.

[1506] Sending and Displaying Data

[1507] After the user inputs text data and a question, the device sends this information to the server. After receiving a response from the server, the device displays the received simple expressions, answers, and emotion-based feedback messages to the user, allowing the user to obtain information in an easy-to-understand format.

[1508] User behavior

[1509] Enter text data and questions

[1510] The user inputs part of the book they are reading as text data into the device. They also input any questions they have while reading. Voice input and facial recognition functions are used as needed to enable the emotion engine to recognize emotions.

[1511] Verifying information and using emotional feedback

[1512] Users can check the simple expressions and answers sent from the server to confirm their understanding. Furthermore, they can receive emotional feedback messages to provide psychological support. This allows users to efficiently read through even difficult content, improving their learning efficiency.

[1513] Specific examples

[1514] For example, a user might be reading a technical book and come across the following paragraph:

[1515] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[1516] The user inputs this paragraph into the system, and also inputs the question "What does it mean to improve efficiency?" The emotion engine recognizes that the user is in a "confused" state. The server confirms that the user's knowledge level is beginner and that they are in a confused state, and converts the paragraph into a simple expression: "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question: "Improved efficiency means that the system can run faster or perform its work with fewer resources than before," and creates a feedback message saying, "You're doing well. There are some difficult parts, but you're almost there."

[1517] In this way, users can obtain technical information in an easy-to-understand format, improving their reading experience.

[1518] The processing flow will be explained below.

[1519] Step 1:

[1520] Users log in to their device and select a book to begin reading. After the book is loaded, users copy and paste the portion of the text they want to read into the device's interface.

[1521] Step 2:

[1522] The user inputs the paragraph of text he is reading into an input field on the terminal, and at the same time inputs any questions he has into the input field.

[1523] Step 3:

[1524] The device receives text data and questions entered by the user. After verifying that the data has been received correctly, it generates a data package containing the user's identification information. It also obtains the user's emotional information through voice input and facial recognition.

[1525] Step 4:

[1526] The terminal transmits the package data to the server, which includes the user ID, text data, questions, and emotion information.

[1527] Step 5:

[1528] The server receives the package data sent from the terminal, and then retrieves the user's knowledge level information from the database based on the user ID.

[1529] Step 6:

[1530] Based on the acquired knowledge level information and emotion information, the server uses a generation AI to convert the text data into a format (simplified expression or summary) that is easy for the user to understand. For example, if the user is recognized as "confused," the simplified expression of the text is set to a simpler level.

[1531] Step 7:

[1532] The server uses generative AI to generate answers to questions entered by users, and also uses an emotion engine to generate feedback messages (e.g., "You're doing a good job," "You'll understand soon," etc.) based on the user's emotional state.

[1533] Step 8:

[1534] The server packages the converted shorthand or summary text with the generated answers and sentiment-based feedback messages to create response data.

[1535] Step 9:

[1536] The server sends the response data to the terminal, which includes abbreviated or summarized text to aid the user's understanding, answers to questions, and sentiment-based feedback messages.

[1537] Step 10:

[1538] The terminal receives the response data from the server, analyzes the contents of the response data, and prepares to display it to the user.

[1539] Step 11:

[1540] The terminal displays the simplified or summarized text sent from the server, along with answers to questions and emotion-based feedback messages to the user. The user can confirm the displayed content and deepen their understanding. The emotion-based feedback also provides psychological support.

[1541] Example 2

[1542] 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."

[1543] Conventional reading assistance systems typically convert content based solely on the user's knowledge level. However, they do not provide appropriate feedback or text conversion that takes into account the user's emotional state, which can leave users feeling confused or bored, resulting in reduced learning efficiency. Furthermore, they often fail to provide appropriate answers to their questions. The present invention aims to solve these problems and provide a reading assistance system that is easier to understand and takes into account the user's emotional state.

[1544] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring text data and questions from a user, means for acquiring the user's knowledge level information and emotional information from a database and an emotional analysis engine, means for using a generation AI to convert the text data into a simplified expression or a summary according to the user's knowledge level and emotional information, means for acquiring the user's questions and generating an answer to the question using the generation AI, means for generating a feedback message based on the user's emotional information, and means for sending the converted simplified expression or summary text, the generated answer, and the feedback message to the user. This allows the user to receive appropriate feedback and text conversion tailored to their knowledge level and emotional state, thereby improving the efficiency of reading and learning.

[1545] "User" refers to any individual or entity that uses the System to convert text data or request answers to questions.

[1546] "Text data" refers to sentences or paragraphs of data that a user enters into a system.

[1547] "Questions" refer to questions or uncertainties that arise when a user is reading text data.

[1548] "Knowledge level" is information that indicates the user's level of expertise and understanding.

[1549] "Emotional information" refers to information that indicates the user's current emotional state (e.g., confusion, interest, boredom, etc.).

[1550] An "emotion analysis engine" refers to a program or system that analyzes a user's text data or voice data to identify emotional information.

[1551] "Database" refers to an information system for storing and managing user knowledge level information and other related information.

[1552] "Generative AI" refers to technology that uses machine learning and natural language processing to convert text data into simple expressions or summaries, or to generate answers to questions.

[1553] "Simplified expression" refers to a sentence that has been reconstructed from the original text data to make it easier to understand.

[1554] A "summary" refers to a short sentence summarizing the main points of the original text data.

[1555] A "feedback message" is a message generated based on the user's emotional information, and provides the user with a sense of psychological security and motivation.

[1556] "Packaging" refers to the process of bundling multiple pieces of data (e.g., shorthand, response, feedback message) into a format for transmission.

[1557] This invention provides a system that combines a generative AI model and a sentiment analysis engine to improve the user's reading experience. This system mainly consists of three elements: a server, a terminal, and a user.

[1558] Server-side behavior

[1559] The server performs the following process.

[1560] First, the server receives the text data and question sent by the user. Specifically, the text data and question entered by the user are sent to the server via an HTTP request. For example, the user might send the text data, "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems."

[1561] Next, the server uses an emotion analysis engine to recognize the emotion the user is feeling when typing. For example, it analyzes the voice tone and typing speed to identify the user's emotional state (e.g., "confused," "interested," "bored"). For this purpose, a common emotion analysis engine (e.g., emotion analysis API) is used.

[1562] The server also retrieves the user's knowledge level from the database based on the user ID, and in this process, uses an SQL query to retrieve the user's knowledge level information from the database.

[1563] Based on the acquired emotional information and knowledge level, the server uses a generative AI model to convert the text data into a format that is easy for the user to understand (simple expressions or summary). For example, a general generative AI model (e.g., a generative AI model API) is used, and the prompt message sent is "Please convert the text into simple expressions that are easy for the user to understand."

[1564] Furthermore, the server uses the generative AI model to generate answers to questions entered by the user. This process also uses the generative AI model, sending the prompt "What does it mean to improve efficiency?"

[1565] Feedback messages based on emotional information are also generated on the server. Depending on the results of the emotion analysis engine, feedback messages such as "You're doing well" or "You'll understand soon" are generated.

[1566] Finally, the server packages the generated shorthand or summary text, the answer to the question, and the sentiment-based feedback message and sends it to the user. This response is packaged in JSON format and sent as an HTTP response.

[1567] Operation on the terminal side

[1568] The terminal operates as follows:

[1569] It provides an interface for users to input text data and questions. The interface includes a field for inputting the part being read and a field for inputting questions. It also includes an interface (voice input and facial recognition) that allows the emotion engine to recognize the user's emotions. After the user enters the necessary information in these fields, the device sends this information to the server.

[1570] The received response is analyzed and displayed to the user as a simple expression, an answer to the question, or an emotional feedback message. This data is then displayed appropriately in the UI, providing the user with information in an easy-to-understand format.

[1571] User behavior

[1572] The user follows the steps below:

[1573] First, users input part of the book they are reading into the device as text data. They also input any questions they have while reading. If necessary, voice input and facial recognition functions are used so that the emotion engine can recognize emotions.

[1574] Users can check the simple expressions and answers sent from the server to confirm their understanding. Furthermore, they can receive emotional feedback messages to provide psychological support. This allows users to efficiently read through even difficult content, improving their learning efficiency.

[1575] Specific examples

[1576] For example, if a user encounters the following paragraph:

[1577] "This technology is very complex and requires a lot of prior knowledge, but its basic applications can improve the efficiency of large-scale systems."

[1578] The user inputs this paragraph into the system, and also inputs the question "What does it mean to improve efficiency?" The emotion engine recognizes that the user is in a "confused" state. The server confirms that the user's knowledge level is beginner and that they are in a confused state, and converts the paragraph into a simple expression: "This technology is difficult, but by simply applying the basics, the system can run more efficiently." At the same time, it generates an answer to the question: "Improved efficiency means that the system will be able to run faster or perform its work with fewer resources than before," and also creates a feedback message saying, "You're doing well. There are some difficult parts, but you'll soon understand."

[1579] This allows users to obtain information in an easy-to-understand format, even for specialized content, improving their reading experience.

[1580] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1581] Step 1: Getting user-entered data

[1582] The user inputs the text data of the reading content and any questions that arise into the terminal. The terminal then sends this information to the server as an HTTP request. The input data consists of a text field and a question field, and examples include "This technology is very complex and requires a lot of prior knowledge, but basic applications can improve the efficiency of large-scale systems" and "What do you mean by improved efficiency?"

[1583] Step 2: Receiving data on the server

[1584] The server receives the HTTP request sent from the terminal and obtains the text data and questions. Specifically, it extracts the text data and questions from the HTTP request body and prepares the data for subsequent processing. The input is the user's text data and questions, and the output is the prepared state of these data.

[1585] Step 3: Acquiring emotional information

[1586] The server uses a sentiment analysis engine to obtain the user's emotional information from the input text data and questions. Specifically, it sends the text data to the sentiment analysis API and receives the sentiment analysis results (confusion, interest, boredom, etc.). The input is the text data and questions, and the output is the user's emotional information.

[1587] Step 4: Gain a level of knowledge

[1588] The server retrieves the user's knowledge level information from the database based on the user ID. Specifically, it accesses the database using an SQL query to inquire about the user's knowledge level. The input is the user ID, and the output is the user's knowledge level information.

[1589] Step 5: Text conversion process

[1590] The server uses a generative AI model to convert text data into a simplified representation or summary based on emotion information and knowledge level information. Specifically, it provides a prompt to the generative AI model API to generate a simplified representation or summary. The input is text data, emotion information, knowledge level information, and a prompt, and the output is a simplified representation or summary text.

[1591] Step 6: Generate answers to your questions

[1592] The server uses the generative AI model to generate an answer to the user's question. Specifically, the question is sent as a prompt to the generative AI model API, and an appropriate answer is obtained. The input is the question and the prompt, and the output is the answer to the question.

[1593] Step 7: Generate feedback messages

[1594] The server generates a feedback message based on the emotion analysis results. Specifically, it selects and customizes a feedback message from a template according to the emotion information. The input is the emotion information, and the output is the customized feedback message.

[1595] Step 8: Packaging and Sending the Response

[1596] The server packages the generated simple expression or summary text, the answer to the question, and the feedback message, and sends them to the user. Specifically, it compiles this data in JSON format and sends it to the terminal as an HTTP response. The input is the simple expression or summary text, the answer to the question, and the feedback message, and the output is the packaged response data.

[1597] Step 9: Receive and display response data

[1598] The device receives the response data sent from the server, analyzes it, and displays a simple expression, an answer to the question, and a feedback message to the user. Specifically, it analyzes the received JSON data and displays each piece of information on the UI. The input is the response data, and the output is the displayed simple expression, answer, and feedback message.

[1599] Step 10: Verifying Information and Using Emotional Feedback

[1600] Users can check the displayed simple expressions and answers to confirm their understanding and receive emotional feedback messages to provide psychological support. By reading these messages, users can enhance their understanding and improve their reading experience.

[1601] (Application example 2)

[1602] 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."

[1603] Conventional reading assistance systems are limited to converting text according to the user's knowledge level and lack customization that takes into account the user's emotional state. This can lead to difficulties in reading comprehension and reduced learning efficiency. New methods are needed to solve this problem and improve the user's reading experience.

[1604] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring text data from a user, means for acquiring the user's knowledge level information and emotional information from a database, means for using a generation AI to convert the text data into a simplified expression or a summary according to the user's knowledge level and emotional information, means for using an emotion engine to analyze the user's emotional state, means for acquiring a question from the user and using the generation AI to generate an answer to the question and a feedback message based on the emotion, and means for sending the converted simplified expression or summary text and the generated answer and feedback message to the user. This enables individual optimization according to the user's emotional state, thereby providing more understandable information and psychological support.

[1605] "User" means an individual user of the system.

[1606] "Text data" is textual information that a user inputs into a system.

[1607] "Knowledge level information" is data regarding the user's level of understanding and depth of expertise.

[1608] "Emotion information" is data that indicates the user's emotional state.

[1609] A "database" is a storage device that stores data such as knowledge level information and emotion information.

[1610] A "simple phrase" is text that has been simplified to make it easier for users to understand.

[1611] A "summary" is a short summary of the original text.

[1612] "Generative AI" is an AI technology for converting text data and generating answers to questions.

[1613] An "emotion engine" is a technology for analyzing and identifying a user's emotional state.

[1614] "Questions" are questions or doubts that users have after reading the text data.

[1615] "Feedback messages" are messages of support or encouragement that correspond to the user's emotional state.

[1616] A "server" is a central computer that handles the overall processing of the system.

[1617] This invention uses a system that combines generative AI and an emotion engine to improve users' reading experience and understanding of product descriptions on online shopping sites. Specific embodiments for implementing this system are described below.

[1618] System Overview

[1619] This system consists of three elements: a server, a terminal, and a user. The server provides the necessary processing using a generative AI and emotion engine, and the terminal provides the interface to the user.

[1620] Server Operation

[1621] Acquiring text data and emotional information

[1622] The server receives text data sent by the user. For example, consider the case where the text data is "This product uses cutting-edge technology and is very effective." The server uses an emotion engine to identify the user's emotional state (e.g., "confused," "excited," "bored"). The emotion engine analyzes the voice tone, typing speed, etc. to recognize the emotional state.

[1623] Text processing based on user knowledge level and sentiment

[1624] The server retrieves knowledge level and emotion information from the database based on the user ID. Then, based on the retrieved emotion information and knowledge level, it uses generative AI to convert the text data into a format (simplified expression or summary) that is easy for the user to understand. For example, if the user is recognized as "confused," the text's simplified expression is set to a more understandable level.

[1625] Generate answers to questions and sentiment-based feedback

[1626] The server uses generative AI to generate answers to questions entered by the user, and also generates feedback messages based on the user's emotional state (e.g., "You're doing a great job").

[1627] Creating and Sending a Response

[1628] The generated simplified text, the answer to the question, and the feedback message based on the emotion are packaged and sent to the user's terminal as response data.

[1629] Device behavior

[1630] Providing a user interface

[1631] The device provides an interface for users to input text data and questions. The interface includes a field for inputting the reading passage and a field for inputting questions. It also includes an interface (e.g., voice input or facial recognition) for the emotion engine to recognize the user's emotions.

[1632] Sending and Displaying Data

[1633] After the user inputs text data and questions, the terminal sends this information to the server. After receiving a response from the server, the terminal displays the received simplified text, answers, and feedback messages to the user, allowing the user to obtain information in an easy-to-understand format.

[1634] User behavior

[1635] Enter text data and questions

[1636] Users input product descriptions and reviews as text data into the device. They also input any questions they may have while reading the text data. Voice input and facial recognition functions are used as needed to enable the emotion engine to recognize emotions.

[1637] Verifying information and using emotional feedback

[1638] The system checks the simplified text, answers, and feedback messages sent from the server to confirm that the user's understanding has improved. This allows the user to efficiently understand even complex content, improving the user's experience on the online shopping site.

[1639] Specific examples

[1640] For example, a user might read a product description and come across the following paragraph:

[1641] "This product uses cutting edge technology and is very effective."

[1642] The user inputs this paragraph into the system and then enters the question, "How exactly is it effective?" The emotion engine recognizes that the user is in a "confused" state. The server confirms that the user's knowledge level is beginner and that they are in a confused state, and converts the paragraph into a simplified expression, "This product uses new technology and is very useful." At the same time, it generates an answer to the question: "What I mean by effective is that using this product makes you more efficient than before," and creates a feedback message saying, "You're doing a great job."

[1643] Prompt Sentence Examples

[1644] User ID: User ID. Please describe this in simple terms: Original description.

[1645] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1646] Step 1: The user enters the product description text and question into the terminal.

[1647] Input: Product description text (e.g., "This product uses cutting-edge technology and is highly effective"), questions (e.g., "How exactly is it effective?")

[1648] How it works: The terminal provides fields to receive user-entered text and questions. The user enters text data and questions into these fields.

[1649] Output: Input text data and questions

[1650] Step 2: The device sends the text data, question, and user ID to the server.

[1651] Input: Text data, question, user ID

[1652] Operation: The terminal sends the text data and question entered by the user, as well as the user ID, to the server.

[1653] Output: Request data including text data, question, and user ID

[1654] Step 3: The server uses the emotion engine to analyze the user's emotional state.

[1655] Input: Request data

[1656] How it works: The server uses an emotion engine to analyze the text data in the request data, such as voice tone and typing speed, to determine the user's emotional state.

[1657] Output: Emotional state (e.g., "confused")

[1658] Step 4: The server retrieves the user's knowledge level information from the database.

[1659] Input: User ID

[1660] Operation: The server accesses the database and retrieves knowledge level information based on the user ID.

[1661] Output: Knowledge level information (e.g., "Beginner")

[1662] Step 5: The server uses generative AI to convert the text into simple expressions and summaries based on the emotional state and knowledge level.

[1663] Input: Text data, emotional state, knowledge level information

[1664] How it works: The server uses a generative AI to convert text data into simplified expressions appropriate for the knowledge level of "beginner," taking into account that the emotional state is "confused."

[1665] Output: Simple text (e.g. "This product uses new technology and is very useful.")

[1666] Step 6: The server uses AI to generate answers to the user's questions.

[1667] Input: Question, text data, knowledge level information, emotional state

[1668] How it works: The server uses generative AI to generate specific and understandable answers to questions based on your emotional state and knowledge level.

[1669] Output: Answer to the question (e.g., "Effective" means that using this product makes you more efficient than before.")

[1670] Step 7: The server generates a feedback message based on the emotional state.

[1671] Input: Emotional state

[1672] Behavior: The server considers the emotional state to be "confused" and generates an encouraging feedback message for the user.

[1673] Output: Feedback message (e.g. "Good job!")

[1674] Step 8: The server packages the generated simple text, the answer, and the feedback message and sends them to the terminal.

[1675] Input: Shorthand text, answer, feedback message

[1676] Operation: The server packages these data and sends them to the terminal as response data.

[1677] Output: Response data (simple text, answers, feedback messages)

[1678] Step 9: The device displays the received data to the user.

[1679] Input: Response data

[1680] Behavior: The device displays received shorthand text, responses, and feedback messages to the user.

[1681] Output: Information displayed to the user (simple text, answers, feedback messages)

[1682] This allows users to obtain information in an easy-to-understand format, deepening their understanding of the product and providing psychological support.

[1683] 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.

[1684] 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.

[1685] 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.

[1686] 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.

[1687] 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.

[1688] 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.

[1689] 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).

[1690] 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.

[1691] 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."

[1692] 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.

[1693] 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).

[1694] 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.

[1695] 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.

[1696] 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.

[1697] 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.

[1698] 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.

[1699] 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.

[1700] 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.

[1701] 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.

[1702] 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.

[1703] 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.

[1704] The following is further disclosed regarding the above embodiment.

[1705] (Claim 1)

[1706] a means for obtaining text data from a user;

[1707] means for obtaining user knowledge level information from a database;

[1708] A means using a generative artificial intelligence to convert said text data into a simplified representation or summary depending on the user's knowledge level;

[1709] A means for acquiring a question from a user and generating an answer to the question using the generating artificial intelligence;

[1710] The system includes means for transmitting the converted shorthand or summary text and the generated answer to the user.

[1711] (Claim 2)

[1712] 2. The system of claim 1, wherein the user's text data and questions are packaged and transmitted to the server.

[1713] (Claim 3)

[1714] 10. The system of claim 1, further comprising providing a quiz or survey to assess a user's level of knowledge.

[1715] "Example 1"

[1716] (Claim 1)

[1717] means for obtaining text data and questions from a user;

[1718] A means for the terminal to transmit text data and questions to a server;

[1719] A server receives the text data and acquires the user's knowledge level information from the database;

[1720] means for converting said text data into a simplified representation or summary using a generative artificial intelligence model;

[1721] means for generating answers to user questions using a generative artificial intelligence model;

[1722] means for transmitting the converted shorthand or summary text and the generated answer to the user;

[1723] The system includes a terminal including means for displaying the shorthand and the answer to the user.

[1724] (Claim 2)

[1725] 2. The system according to claim 1, wherein the user's text data and questions are packaged and transmitted to the server.

[1726] (Claim 3)

[1727] 10. The system of claim 1, further comprising providing a quiz or survey to assess a user's knowledge level.

[1728] "Application Example 1"

[1729] (Claim 1)

[1730] a means for obtaining text data from a user;

[1731] means for obtaining user knowledge level information from a database;

[1732] A means using a generative artificial intelligence to convert said text data into a simplified representation or summary depending on the user's knowledge level;

[1733] A means for acquiring a question from a user and generating an answer to the question using the generating artificial intelligence;

[1734] means for transmitting the converted shorthand or summary text and the generated answer to the user;

[1735] A terminal has a smart device that visually provides simple expressions and answers to a user in real time while the user is reading;

[1736] A system including:

[1737] (Claim 2)

[1738] 2. The system of claim 1, wherein the user's text data and questions are packaged and transmitted to the server.

[1739] (Claim 3)

[1740] 10. The system of claim 1, further comprising providing a quiz or survey to assess a user's level of knowledge.

[1741] "Example 2: Combining Emotion Engines"

[1742] (Claim 1)

[1743] a means for obtaining text data and questions from a user;

[1744] means for obtaining user knowledge level information and emotion information from the database and the emotion analysis engine;

[1745] A means using a generative artificial intelligence to convert the text data into a simplified representation or summary according to the user's knowledge level and emotional information;

[1746] A means for acquiring a question from a user and generating an answer to the question using the generating artificial intelligence;

[1747] means for generating a feedback message based on the user's emotional information;

[1748] The system includes means for transmitting the converted shorthand or summary text and the generated answers and feedback messages to the user.

[1749] (Claim 2)

[1750] 2. The system of claim 1, wherein the user's text data and questions are packaged and transmitted to the server.

[1751] (Claim 3)

[1752] 10. The system of claim 1, further comprising providing a quiz or survey to assess a user's level of knowledge.

[1753] "Application example 2 when combining emotion engines"

[1754] (Claim 1)

[1755] a means for obtaining text data from a user;

[1756] means for obtaining user knowledge level information and emotion information from a database;

[1757] A means using a generative artificial intelligence to convert the text data into a simplified representation or summary according to the user's knowledge level and emotional information;

[1758] a means for using an emotion engine to analyze the user's emotional state;

[1759] A means for receiving a question from a user and generating an answer to the question and a feedback message based on the emotion using the generation artificial intelligence;

[1760] The system includes means for transmitting the converted shorthand or summary text and the generated answers and feedback messages to the user.

[1761] (Claim 2)

[1762] 10. The system of claim 1, wherein the user's text data and questions are packaged and sent to a server, and the converted text and answers are displayed.

[1763] (Claim 3)

[1764] 10. The system of claim 1, providing a quiz or survey to assess the user's knowledge level and emotional state. [Explanation of symbols]

[1765] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for obtaining text data from a user; means for obtaining user knowledge level information from a database; A means using a generative artificial intelligence to convert said text data into a simplified representation or summary depending on the user's knowledge level; A means for acquiring a question from a user and generating an answer to the question using the generating artificial intelligence; The system includes means for transmitting the converted shorthand or summary text and the generated answer to the user.

2. 2. The system according to claim 1, wherein the user's text data and questions are packaged and transmitted to the server.

3. The system of claim 1 , further comprising a quiz or survey to assess a user's knowledge level.

Images