system

Abstract

We provide the system. [Solution] A means of receiving book data and converting it to text format, A method for creating a summary using generative AI based on the converted text, A means to adjust the length of the summary according to the time set by the user, A means of displaying the summary on the user's device, A means of receiving questions related to the summary and generating answers, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern busy lives, the need to acquire a wide range of knowledge within limited time is increasing. However, it is difficult to quickly understand the content of books, especially to read books with hundreds of pages in a short time. For people who do not have enough time to read, there is a need for a means to efficiently understand the content and gain deeper learning. In addition, there is a problem that there is no effective method to immediately solve questions and unclear points related to books.

Means for Solving the Problems

[0005] To solve this problem, the present invention provides a means for receiving book data and converting it into text format. Based on the converted text, it utilizes generative AI technology to create a summary, and includes a function to adjust the length of the summary to fit the time frame set by the user. Furthermore, it is possible to display the generated summary on the user's device, and it also provides a function to accept questions related to the summary and generate corresponding answers. In this way, a system has been realized that allows users to grasp the content of a book efficiently in a short time and gain a deeper understanding as needed.

[0006] "Book data" refers to the content of a book provided in electronic file format, such as PDF or EPUB.

[0007] "Text format" refers to the representation format of pure string data extracted from book data, a format that can be used for subsequent processing and analysis.

[0008] "Generative AI" refers to artificial intelligence technology that learns from large amounts of data to generate and summarize text, and is used in the field of natural language processing.

[0009] A "summary" refers to a concise written overview of the entire content of a book, and is used to understand the content within a limited time.

[0010] "Device" refers to electronic devices such as computers, smartphones, and tablets that users use to view book summaries.

[0011] "Optical character recognition technology" refers to technology that extracts character information from image data such as PDFs and converts it into text data. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2]This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0013] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0016] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0018] In the following embodiments, a labeled communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), and the like.

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0023] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0032] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0033] To implement this invention, the server first receives book data and converts it into text format. Since the book data is provided by the user in formats such as PDF or EPUB, in the case of PDF, optical character recognition technology is used to extract character information, and in the case of EPUB and other formats, a dedicated library is used to obtain text data.

[0034] Next, the server inputs the converted text into a generating AI to produce a summary. The AI ​​is instructed to generate summaries of a length corresponding to a user-defined time limit (e.g., 5 minutes, 10 minutes, 30 minutes). Because the summarized text contains only concise and essential information, users can grasp the main points of the book within a limited time.

[0035] Next, the terminal displays the summary received from the server on the user interface. The user can view the summary and, if they have any questions to deepen their understanding, they can enter them through the terminal. The terminal is equipped with a question input form and a submit button, which the user uses to send questions of interest to the server.

[0036] The server uses AI to construct a detailed answer based on the received question. During this process, it extracts relevant information by referring to the original text data and summary, generating a specific and user-friendly response. Once the answer is complete, the server sends it back to the user's device, which then displays the received answer on the user's screen.

[0037] As a concrete example, consider a situation where a user wants to read the latest scientific journals but doesn't have the time. Using this system, the user can quickly understand the main topics and then ask more detailed questions about what they've already understood, thus acquiring knowledge efficiently. This method makes it possible to efficiently acquire necessary knowledge in today's information-saturated world.

[0038] The following describes the processing flow.

[0039] Step 1:

[0040] The user uploads book data using their device. After selecting the file, it is sent to the server via the device's interface.

[0041] Step 2:

[0042] The server analyzes the book data received from the user. If the data is in PDF format, it uses OCR technology to extract text information from the image data. If the data is in formats such as EPUB, it extracts text data via a dedicated library.

[0043] Step 3:

[0044] The server extracts text data and sends it to the AI. The AI ​​generates an optimal summary according to the specified summarization time (5 minutes, 10 minutes, 30 minutes). The summarized content is structured around the most important points.

[0045] Step 4:

[0046] The server sends the generated summary to the terminal. The terminal displays the summary on its screen, which the user can then review. The user interface includes a summary display and a text box for entering questions.

[0047] Step 5:

[0048] If a user has questions about the content while referring to the summary, they can use the terminal interface to enter their questions and send them to the server.

[0049] Step 6:

[0050] The server receives a question from the user, uses a generative AI to analyze the text data, and generates relevant answers. The answers are constructed based on the original text data and the generated summary, and address the user's question.

[0051] Step 7:

[0052] The server returns the generated answer to the terminal. The terminal displays this to the user, allowing the user to confirm the specific answer to the question.

[0053] By following these steps, users can quickly understand the content of the book and obtain additional information as needed.

[0054] (Example 1)

[0055] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0056] In today's world, the sheer volume of information is overwhelming, and there is a demand for efficient and time-efficient acquisition of important information. Furthermore, busy users often find it difficult to efficiently summarize vast amounts of book information and obtain more detailed information on topics of interest. Therefore, it is necessary to efficiently process book data and provide summaries and information tailored to user needs.

[0057] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0058] In this invention, the server includes means for receiving book information and converting it into text format, means for creating a summary using AI generated based on the converted text, and means for adjusting the length of the summary according to a time set by the user. This allows the user to efficiently check the necessary information in a short time and gain a deeper understanding through questions to acquire further knowledge.

[0059] "Means for receiving information from books and converting it into text format" refers to a device or method that receives data from books or documents in various formats and converts it into readable string information.

[0060] "Means for creating summaries using generated AI" refers to a device or method that utilizes artificial intelligence algorithms to extract only the important content from a large amount of text data and summarize it concisely.

[0061] "Means for adjusting the length of a summary according to a user-set time" refers to a device or method that dynamically changes the volume and level of detail of a summary to match a time frame specified in advance by the user.

[0062] "Means for displaying a summary on a user's terminal" refers to a device or method that transfers a generated summary to a user's device via a network and presents it in a visually verifiable format.

[0063] "Means by which a terminal receives a query related to a summary and a server generates a detailed response" refers to a device or method that receives a question via a user interface and derives an answer by retrieving or generating further information in response to that question.

[0064] "Means for converting to text data using optical character recognition technology" refers to a technology or device for mechanically reading characters from image data and converting them into digital text.

[0065] The embodiments for carrying out this invention will be described below.

[0066] The server first receives book information from the user. This information is often provided in electronic document format such as PDF or EPUB. In the case of PDF, the server uses optical character recognition (OCR) tools, such as Tesseract, to extract character information from the image data and convert it into text format. In the case of EPUB, the server directly obtains the text data using a dedicated library such as epub.js.

[0067] The converted text data is summarized by the generated AI. The server sends a prompt to the generating AI, instructing it to "summarize the following text in 5 minutes." This generating AI model uses natural language processing techniques to extract important information from the input text and create a summary of a specified length.

[0068] After the server generates a summary, the terminal receives this summary and displays it to the user through the user interface. The user can view this summary and, if they need more detailed information, can use the question input function on the terminal to make specific inquiries.

[0069] The server receives a user inquiry and uses the generated AI again to create a more detailed response. In this process, the server refers to the original text and summarized text, searches for relevant information, and generates the answer. The generated answer is then sent to the terminal, which displays it.

[0070] For example, if a user wants to efficiently understand the contents of the latest scientific journal, this system allows them to quickly obtain summaries of key topics and then gain a deeper understanding by asking more detailed questions about areas of interest. This approach makes it possible to efficiently acquire the necessary information in an age of information overload.

[0071] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0072] Step 1:

[0073] The server receives book information from the user. The server directly receives PDF and EPUB files uploaded by the user and prepares them for the next processing step. The input is the electronic document data provided by the user, and the output is the original data stored internally. This data is used in subsequent processing steps.

[0074] Step 2:

[0075] The server converts book information into text format. For PDF files, it extracts text data from image data using an OCR tool such as Tesseract. For EPUB files, it directly extracts text using a dedicated library (such as epub.js). The input is electronic document data, and the output is text format data. This conversion is performed as preparation for AI processing.

[0076] Step 3:

[0077] The server inputs text data into a generative AI to create a summary. The server sends a prompt to the generative AI saying, "Summarize this text within the specified time." The generative AI uses natural language processing techniques to generate a summary from the text. The input is text data and a prompt, and the output is the summarized text.

[0078] Step 4:

[0079] The server sends the generated summary to the terminal. The summary is sent from the server to the terminal via the network, making it available for user review. The input is the summary text, and the output is the data displayed on the terminal.

[0080] Step 5:

[0081] The device displays a summary to the user. The device visualizes the received summary on the user interface, allowing the user to review its contents. Specifically, the device includes a function that automatically displays the summary on its screen.

[0082] Step 6:

[0083] The user reviews the displayed summary and enters questions from their device if they want more detailed information. The user sends questions about points of interest to the server using the device's question input function. The input is the user's question text, and the output is the query sent to the server.

[0084] Step 7:

[0085] The server receives a question from the user and generates a detailed response using generative AI. In this process, relevant information is extracted from the original text or summary, and specific answers are constructed using the power of AI. The input is the user's question text, and the output is the generated response text.

[0086] Step 8:

[0087] The server sends the generated response to the terminal, which then displays it to the user. The user interface receives the response data and visualizes it in a way that the user can understand. The input is the generated response text, and the output is the response information displayed on the terminal.

[0088] (Application Example 1)

[0089] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0090] In today's world, the sheer volume of content is overwhelming, making it difficult for users to view everything due to time constraints. Furthermore, there is a need for efficient ways for users to understand the content they select beforehand and then delve deeper into it based on their interests.

[0091] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0092] In this invention, the server includes means for receiving content data and converting it into text format, means for creating a summary using a generative AI based on the converted text, and means for summarizing the main scenes and storyline of the content selected by the user. This allows the user to quickly understand the main points of the content and efficiently obtain more detailed information on areas of interest.

[0093] "Content" refers to a collection of information provided to a user, either visually or audibly.

[0094] "Data" refers to a sequence of numbers or strings that represent information, and is the subject of processing and transformation.

[0095] "Text format" refers to a state where data is represented as a string of characters and can be read by machines or humans.

[0096] "Generative AI" is a system that utilizes artificial intelligence technology to generate new information based on given data.

[0097] A "summary" is a short compilation of the main points or important content of information.

[0098] An "information terminal" is a physical device used to display, process, or communicate information electronically.

[0099] A "main scene" refers to an important or central moment or event within the content.

[0100] "Storyline" refers to the progression or plot of a story within a piece of content.

[0101] "Optical character recognition technology" is a technology that detects characters within an image and converts them into text data.

[0102] An "electronic document format" is a format for documents that are stored, displayed, or transmitted electronically on a computer.

[0103] To implement this invention, the server first receives content data and converts it into text format. Since the content data is provided in electronic document format, for example, in the case of a PDF, optical character recognition technology is used to extract the text information. The converted text is input into a generative AI model to generate a summary. The length of the summary is adjusted according to the time setting selected by the user.

[0104] The generated summary is sent from the server to the user's information terminal and displayed. The user can view the summary and enter questions as needed. Questions are sent to the server through an input form in the user interface. Based on the received questions, the server uses a generative AI model to find relevant information and construct specific answers. In doing so, the content is refined based on key scenes and storylines, and presented in a way that is easy for the user to understand.

[0105] As a concrete example, consider a user who doesn't have time to watch the latest movie using this system. The user can quickly obtain a movie summary, grasp the main scenes, and then input questions about specific scenes or settings to learn more detailed information. By setting prompts such as "Please provide a summary of the movie 'XX' that can be understood in 3 minutes" in the generating AI model, it is possible to provide specific and appropriate information.

[0106] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0107] Step 1:

[0108] The server receives content data from the user. The input is data in electronic document format, and the output is that data ready for conversion. Specifically, the server saves the PDF or EPUB files sent by the user to a database.

[0109] Step 2:

[0110] The server converts the received content data into text format. The input is stored electronic document data, and the output is text data. Specifically, for PDFs, OCR technology is used, and for EPUBs, a dedicated library is used to extract the text.

[0111] Step 3:

[0112] The server inputs the converted text data into an AI model to generate a summary. The input is text data, and the output is a summarized text. Specifically, it calls the AI ​​model's API and creates a summary using the prompt "Please summarize the text in a way that can be understood in X minutes."

[0113] Step 4:

[0114] The server sends the generated summary to the user's device. The input is the summary text, and the output is the summary being displayed on the user's device. Specifically, the data is sent to the device as a push notification using a communication protocol.

[0115] Step 5:

[0116] The user views the displayed summary and enters questions if more information is needed. The input is the user's question, and the output is the question data sent to the server. Specifically, this involves entering a question through the terminal interface and pressing the submit button.

[0117] Step 6:

[0118] The server generates answers based on the received questions, utilizing a generative AI model. The input consists of the question data and the original text data, while the output is a detailed answer. Specifically, the AI ​​is given a question, extracts relevant information from the text data, and constructs an answer.

[0119] Step 7:

[0120] The server sends the generated response back to the user's terminal. The input is the detailed response, and the output is the response being displayed on the user's terminal. Specifically, the response data is sent to the terminal using a communication protocol and displayed on the screen.

[0121] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0122] As an embodiment of this invention, a method of combining an emotion engine with a system that receives book data and summarizes and displays its contents will be described.

[0123] First, the user uploads book data to the server using their device. After receiving the book data, the server converts it to text format. In this process, optical character recognition technology is used to extract text information from PDF data, and a dedicated library is used to obtain text data for ebook formats such as EPUB.

[0124] Next, the server feeds the converted text data into a generating AI to produce a summary. This summary is adjusted according to the time frame set by the user. The generated summary is presented in a format that aggregates important information and allows for quick understanding.

[0125] Furthermore, a key feature of this system is the incorporation of an emotion engine. The terminal uses cameras and sensors to analyze the user's emotions from their facial expressions and voice, and sends the emotion data to the server. The server evaluates this emotion data and uses generative AI to provide a response tailored to the user's emotional state. For example, if the user is confused, the generative AI adjusts to provide additional explanations or a different summarizing style.

[0126] The introduction of an emotion engine makes it possible to provide the appropriate amount and content of information according to the user's state. For example, if stress or confusion is detected when a user is trying to understand a particular academic paper, the system will improve learning efficiency by presenting explanations in simpler language and easy-to-understand examples.

[0127] As described above, the system configuration, which incorporates an emotion engine, goes beyond mere information provision to provide flexible support tailored to the user's emotions and understanding.

[0128] The following describes the processing flow.

[0129] Step 1:

[0130] The user imports book data into their device and uploads it to the server. After selecting the files, the device sends the data to the server.

[0131] Step 2:

[0132] The server analyzes the received book data. At this stage, if it's a PDF, text is extracted using optical character recognition technology; if it's in a format like EPUB, text data is extracted using a dedicated analysis library.

[0133] Step 3:

[0134] The server sends the converted text data to the generating AI and issues a command to generate a summary that fits the time specified by the user. The generating AI extracts key concepts and creates a summary that is appropriate for the specified time frame.

[0135] Step 4:

[0136] The terminal receives a summary from the server and displays it on the screen. The user can review this summary and understand its content. A user interface is also provided that includes fields for entering questions along with the summary.

[0137] Step 5:

[0138] The device collects the user's facial expressions and voice through its built-in camera and microphone. This data is sent to the emotion engine in real time and used to analyze the user's emotional state.

[0139] Step 6:

[0140] The server receives feedback from the emotion engine and determines the user's emotional state. If the user is showing emotions such as confusion or surprise, the server instructs the generating AI to make adjustments accordingly.

[0141] Step 7:

[0142] The generating AI adjusts or modifies responses based on the user's emotional state. For example, it might change the wording to something simpler and easier to understand, or include additional detailed explanations.

[0143] Step 8:

[0144] The server sends the adjusted results to the terminal, which then displays them to the user. This allows the user to receive information that corresponds to their emotional feedback, leading to a better understanding.

[0145] Step 9:

[0146] Users can ask additional questions as needed, and the system repeats the same process, using generated AI to respond as appropriate.

[0147] This process allows users to have a flexible learning experience tailored to their individual emotional state.

[0148] (Example 2)

[0149] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0150] Conventional book summarization systems have faced challenges in providing flexible information tailored to the user's emotional state, thus failing to enhance user understanding and satisfaction. Furthermore, they have limited ability to respond to specific user questions regarding the summarized information, resulting in a lack of in-depth information tailored to user needs.

[0151] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0152] In this invention, the server includes means for receiving data and converting it into an information format, means for creating a summary using a generative model based on the converted information, and means for acquiring emotional states and generating summaries and explanations corresponding to those emotions. This enables the provision of accurate information tailored to the user's emotional state. Furthermore, it enables the generation of flexible responses based on the user's questions, which is expected to improve the user's understanding and satisfaction.

[0153] "Data" refers to electronic material used to represent information.

[0154] "Information format" refers to the conversion of data into a recognizable form such as text or numbers.

[0155] A "generative model" is an algorithm or system that learns patterns from a large amount of data and generates new data.

[0156] A "summary" is a concise version of the original text, extracting the most important parts.

[0157] A "user" refers to a person who uses a system, and is an entity that operates the system through its interface.

[0158] "Device" refers to hardware that has a specific function and is used for operation or information processing.

[0159] "Emotional state" refers to the user's psychological state or mood, and is usually detected from facial expressions and voice.

[0160] "Explanation" means describing information or knowledge in detail so that others can understand it.

[0161] A "response" is information or feedback provided in response to a question or request.

[0162] As an embodiment of this invention, a system that consistently performs tasks from receiving book data to generating summaries and providing responses tailored to emotions will be described. First, the user uploads book data to a server using a terminal. Here, the terminal provides a user interface that allows data to be uploaded via drag-and-drop or a file selection dialog.

[0163] When the server receives book data, it determines its format and, if it is in PDF format, converts it into text data using Optical Character Recognition (OCR) technology. Open-source OCR engines are used for this purpose. For ebook formats such as EPUB, a dedicated ebook library is used to extract text information. The converted text data is then input into a generative AI model to generate a summary. For example, a large-scale language model using a multi-layer neural network is used as the generative AI model.

[0164] On the other hand, the device has sensors such as a camera and microphone to measure the user's emotional state in real time. Facial recognition and voice analysis technologies are used for emotion analysis. This emotion data is sent to a server, where a generative AI provides summaries and explanations appropriate to the user's emotional state.

[0165] The generated summary and additional information are displayed on the user's device, allowing the user to review the content. Furthermore, if the user enters a question related to the summary, the AI ​​model generates and provides an appropriate response to that question.

[0166] (Specific example)

[0167] For example, if a user wants to quickly understand a new science fiction novel, they could use a prompt like this: "Please read the summary of this novel in 10 minutes." Furthermore, if the user finds the summary difficult to understand after reading it and is deemed to be in a state of emotional confusion, the system could automatically provide additional information or a different style of summary with a prompt such as, "Please explain this part in more detail." This allows the user to receive information tailored to their level of understanding and emotional state.

[0168] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0169] Step 1:

[0170] The user uploads book data to the server using a terminal. The input is a file selected by the user (e.g., book data in PDF or EPUB format). The terminal provides the functionality to upload the file, and after transmission, the server saves the received data. The output is the book data stored on the server.

[0171] Step 2:

[0172] The server determines the format of the received book data and, if it is in PDF format, converts it to text data using Optical Character Recognition (OCR) technology. The input is the book data stored on the server. After determining the data format, the OCR engine is activated and the operation to extract characters from the image data is performed. The output is the converted text data.

[0173] Step 3:

[0174] The server inputs the converted text data into a generative AI model to generate a summary. The input is book data converted into text format. The generative AI model performs data calculations that extract the important parts of the input text and create a shortened summary. The output is the generated summary text.

[0175] Step 4:

[0176] The device uses a camera and microphone to collect the user's facial expressions and voice, and analyzes their emotional state. The input consists of real-time collected facial images and voice data of the user. The image and voice analysis engine is activated, and the system performs an emotional determination. The output is the user's emotional state data.

[0177] Step 5:

[0178] The server analyzes emotional state data transmitted from the terminal and provides summaries and additional explanations tailored to the user's emotions using a generative AI model. The input consists of emotional state data and the generated summary text. The generative AI model processes the data to output summaries and explanations in a format appropriate to the emotions. The output is the adjusted summary or additional explanation text.

[0179] Step 6:

[0180] The terminal displays the generated summary and response to the user. The input is the final generated summary or additional explanatory text. The information is displayed through the user interface. The user can review and understand the displayed content. The output is the information provided to the user visually.

[0181] (Application Example 2)

[0182] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0183] There is a need to efficiently summarize information in ebooks and provide appropriate information according to the user's emotional state. However, conventional systems lack the ability to adequately respond to the confusion and stress that users experience. In particular, there is a need for more specific and flexible means of responding when users feel anxious or confused during payment procedures or purchases.

[0184] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0185] In this invention, the server includes means for receiving book information and converting it into a string format, means for creating a summary using a generative AI based on the converted string, and means for using sensory organs to analyze the user's emotional state. This makes it possible not only to provide a summary according to the time set by the user, but also to provide optimal information based on the user's emotional state.

[0186] "Book information" refers to the content of a book represented as digital data in a format that can be processed electronically.

[0187] "Methods for converting to string format" refers to techniques for converting information from books, which exist in various formats, into string data that is easy for machines to process.

[0188] "Converted string" refers to data that has been converted from book information into a string format, and is the target of processing by the generation AI.

[0189] "Generative AI" is a type of artificial intelligence that models human knowledge and skills, analyzes data, and generates new information and insights.

[0190] "Methods for creating summaries" refer to the process of extracting key elements from a vast amount of original information data and automatically generating a document in a shortened format.

[0191] "User emotional state" refers to the psychological and sensory reactions a user exhibits when using the system, and the system analyzes this to determine appropriate responses.

[0192] "Methods using sensory organs" refer to technologies that use devices such as cameras and sensors to detect a user's facial expressions and voice, and analyze their emotional state.

[0193] The system for implementing this invention consists of a user terminal, a server, and a generative AI model. The user terminal is a device such as a smartphone or smart glasses, equipped with a camera and microphone. When the user selects information from a book on the device, that information is sent to the server.

[0194] The server runs a program that converts book information into a string format. For PDF data, it extracts text information using optical character recognition technology, and for ebook formats such as EPUB, it obtains string data using a dedicated library. The converted strings are fed into a generative AI model, and a summary is created.

[0195] This summary is adjusted according to the time frame set by the user and displayed on the user's device. Furthermore, the device's camera and sensors are used to analyze the user's emotional state from their facial expressions and voice. This emotional data is sent to a server, and the generative AI generates a response that corresponds to the user's emotional state. For example, if the user is confused, the generative AI will provide additional explanations or a different summarizing style.

[0196] As a concrete example, suppose a user using an electronic payment service is trying to purchase a new product using their smartphone, but is confused because entering the promotion code is complicated. In this case, the system analyzes the user's emotional state and uses a generative AI model to provide specific guidance such as, "Having trouble? You can check the promotion codes you can currently enter from the options in the upper right corner of the screen."

[0197] The software used will include TENSORFLOW® for the generative AI model and Flask for the server-side implementation. An example of a prompt message would be: "Generate a support message based on the user's emotional state. The user is confused. Provide a simple and concrete solution."

[0198] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0199] Step 1:

[0200] The user's terminal sends the entered book information to the server. This information is represented in various digital formats. The server receives this information and prepares for the next processing step.

[0201] Step 2:

[0202] The server converts the information from received books into a string format. For PDF data, optical character recognition (OCR) technology is used to extract the character information. For EPUB format, a dedicated library is used to obtain the string data. This converted string is then used in the subsequent summarization process.

[0203] Step 3:

[0204] The server inputs the converted string into a generating AI model to generate a summary of the book's content. The generating AI extracts key information from the input text and creates a shortened summary. This summary is then adjusted to a length corresponding to the time frame specified by the user and sent to the terminal.

[0205] Step 4:

[0206] The user's terminal displays the generated summary. The user can enter questions related to the summary as needed. These questions are sent back to the server, initiating the process of generating appropriate responses.

[0207] Step 5:

[0208] The device uses its camera and sensors to capture the user's facial expressions and voice, and analyzes their emotional state. By sending this emotional data to a server, it prepares to generate appropriate feedback based on the user's psychological response.

[0209] Step 6:

[0210] The server receives emotion data and uses generative AI to generate responses tailored to the user's emotional state. For example, if the user is confused, the system adjusts to provide additional explanations or a different summarizing style. The generated feedback is then sent back to the terminal and presented to the user.

[0211] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0212] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0213] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0214] [Second Embodiment]

[0215] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0216] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0217] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0218] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0219] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0220] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0221] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0222] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0223] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0224] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0225] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0226] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0227] To implement this invention, the server first receives book data and converts it into text format. Since the book data is provided by the user in formats such as PDF or EPUB, in the case of PDF, optical character recognition technology is used to extract character information, and in the case of EPUB and other formats, a dedicated library is used to obtain text data.

[0228] Next, the server inputs the converted text into a generating AI to produce a summary. The AI ​​is instructed to generate summaries of a length corresponding to a user-defined time limit (e.g., 5 minutes, 10 minutes, 30 minutes). Because the summarized text contains only concise and essential information, users can grasp the main points of the book within a limited time.

[0229] Next, the terminal displays the summary received from the server on the user interface. The user can view the summary and, if they have any questions to deepen their understanding, they can enter them through the terminal. The terminal is equipped with a question input form and a submit button, which the user uses to send questions of interest to the server.

[0230] The server uses AI to construct a detailed answer based on the received question. During this process, it extracts relevant information by referring to the original text data and summary, generating a specific and user-friendly response. Once the answer is complete, the server sends it back to the user's device, which then displays the received answer on the user's screen.

[0231] As a concrete example, consider a situation where a user wants to read the latest scientific journals but doesn't have the time. Using this system, the user can quickly understand the main topics and then ask more detailed questions about what they've already understood, thus acquiring knowledge efficiently. This method makes it possible to efficiently acquire necessary knowledge in today's information-saturated world.

[0232] The following describes the processing flow.

[0233] Step 1:

[0234] The user uploads book data using their device. After selecting the file, it is sent to the server via the device's interface.

[0235] Step 2:

[0236] The server analyzes the book data received from the user. If the data is in PDF format, it uses OCR technology to extract text information from the image data. If the data is in formats such as EPUB, it extracts text data via a dedicated library.

[0237] Step 3:

[0238] The server extracts text data and sends it to the AI. The AI ​​generates an optimal summary according to the specified summarization time (5 minutes, 10 minutes, 30 minutes). The summarized content is structured around the most important points.

[0239] Step 4:

[0240] The server sends the generated summary to the terminal. The terminal displays the summary on its screen, which the user can then review. The user interface includes a summary display and a text box for entering questions.

[0241] Step 5:

[0242] If a user has questions about the content while referring to the summary, they can use the terminal interface to enter their questions and send them to the server.

[0243] Step 6:

[0244] The server receives a question from the user, uses a generative AI to analyze the text data, and generates relevant answers. The answers are constructed based on the original text data and the generated summary, and address the user's question.

[0245] Step 7:

[0246] The server returns the generated answer to the terminal. The terminal displays this to the user, allowing the user to confirm the specific answer to the question.

[0247] By following these steps, users can quickly understand the content of the book and obtain additional information as needed.

[0248] (Example 1)

[0249] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0250] In today's world, the sheer volume of information is overwhelming, and there is a demand for efficient and time-efficient acquisition of important information. Furthermore, busy users often find it difficult to efficiently summarize vast amounts of book information and obtain more detailed information on topics of interest. Therefore, it is necessary to efficiently process book data and provide summaries and information tailored to user needs.

[0251] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0252] In this invention, the server includes means for receiving book information and converting it into text format, means for creating a summary using AI generated based on the converted text, and means for adjusting the length of the summary according to a time set by the user. This allows the user to efficiently check the necessary information in a short time and gain a deeper understanding through questions to acquire further knowledge.

[0253] "Means for receiving information from books and converting it into text format" refers to a device or method that receives data from books or documents in various formats and converts it into readable string information.

[0254] "Means for creating summaries using generated AI" refers to a device or method that utilizes artificial intelligence algorithms to extract only the important content from a large amount of text data and summarize it concisely.

[0255] "Means for adjusting the length of a summary according to a user-set time" refers to a device or method that dynamically changes the volume and level of detail of a summary to match a time frame specified in advance by the user.

[0256] "Means for displaying a summary on a user's terminal" refers to a device or method that transfers a generated summary to a user's device via a network and presents it in a visually verifiable format.

[0257] "Means by which a terminal receives a query related to a summary and a server generates a detailed response" refers to a device or method that receives a question via a user interface and derives an answer by retrieving or generating further information in response to that question.

[0258] "Means for converting to text data using optical character recognition technology" refers to a technology or device for mechanically reading characters from image data and converting them into digital text.

[0259] The embodiments for carrying out this invention will be described below.

[0260] The server first receives book information from the user. This information is often provided in electronic document format such as PDF or EPUB. In the case of PDF, the server uses optical character recognition (OCR) tools, such as Tesseract, to extract character information from the image data and convert it into text format. In the case of EPUB, the server directly obtains the text data using a dedicated library such as epub.js.

[0261] The converted text data is summarized by the generated AI. The server sends a prompt to the generating AI, instructing it to "summarize the following text in 5 minutes." This generating AI model uses natural language processing techniques to extract important information from the input text and create a summary of a specified length.

[0262] After the server generates a summary, the terminal receives this summary and displays it to the user through the user interface. The user can view this summary and, if they need more detailed information, can use the question input function on the terminal to make specific inquiries.

[0263] The server receives a user inquiry and uses the generated AI again to create a more detailed response. In this process, the server refers to the original text and summarized text, searches for relevant information, and generates the answer. The generated answer is then sent to the terminal, which displays it.

[0264] For example, if a user wants to efficiently understand the contents of the latest scientific journal, this system allows them to quickly obtain summaries of key topics and then gain a deeper understanding by asking more detailed questions about areas of interest. This approach makes it possible to efficiently acquire the necessary information in an age of information overload.

[0265] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0266] Step 1:

[0267] The server receives book information from the user. The server directly receives PDF and EPUB files uploaded by the user and prepares them for the next processing step. The input is the electronic document data provided by the user, and the output is the original data stored internally. This data is used in subsequent processing steps.

[0268] Step 2:

[0269] The server converts book information into text format. For PDF files, it extracts text data from image data using an OCR tool such as Tesseract. For EPUB files, it directly extracts text using a dedicated library (such as epub.js). The input is electronic document data, and the output is text format data. This conversion is performed as preparation for AI processing.

[0270] Step 3:

[0271] The server inputs text data into a generative AI to create a summary. The server sends a prompt to the generative AI saying, "Summarize this text within the specified time." The generative AI uses natural language processing techniques to generate a summary from the text. The input is text data and a prompt, and the output is the summarized text.

[0272] Step 4:

[0273] The server sends the generated summary to the terminal. The summary is sent from the server to the terminal via the network, making it available for user review. The input is the summary text, and the output is the data displayed on the terminal.

[0274] Step 5:

[0275] The device displays a summary to the user. The device visualizes the received summary on the user interface, allowing the user to review its contents. Specifically, the device includes a function that automatically displays the summary on its screen.

[0276] Step 6:

[0277] The user reviews the displayed summary and enters questions from their device if they want more detailed information. The user sends questions about points of interest to the server using the device's question input function. The input is the user's question text, and the output is the query sent to the server.

[0278] Step 7:

[0279] The server receives a question from the user and generates a detailed response using a generative AI. In this process, relevant information is extracted from the original text or summary, and a specific answer is constructed with the power of the AI. The input is the user's question text, and the output is the generated response text.

[0280] Step 8:

[0281] The server sends the generated response to the terminal, and the terminal displays it to the user. The response data is received by the user interface and visualized in a form understandable to the user. The input is the generated response text, and the output is the response information displayed on the terminal.

[0282] (Application Example 1)

[0283] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0284] In modern times, the amount of content is extremely large, and it is difficult for users to view all of it due to time constraints. Also, an efficient means is required to pre-understand the content of the content selected by the user and further deeply understand it based on interest.

[0285] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0286] In this invention, the server includes means for receiving content data and converting it into text format, means for creating a summary using a generative AI based on the converted text, and means for summarizing the main scenes and storylines of the content selected by the user. Thereby, the user can understand the key points of the content in a short time and can efficiently obtain detailed information regarding the parts of interest.

[0287] "Content" refers to a collection of information provided to a user, either visually or audibly.

[0288] "Data" refers to a sequence of numbers or strings that represent information, and is the subject of processing and transformation.

[0289] "Text format" refers to a state where data is represented as a string of characters and can be read by machines or humans.

[0290] "Generative AI" is a system that utilizes artificial intelligence technology to generate new information based on given data.

[0291] A "summary" is a short compilation of the main points or important content of information.

[0292] An "information terminal" is a physical device used to display, process, or communicate information electronically.

[0293] A "main scene" refers to an important or central moment or event within the content.

[0294] "Storyline" refers to the progression or plot of a story within a piece of content.

[0295] "Optical character recognition technology" is a technology that detects characters within an image and converts them into text data.

[0296] An "electronic document format" is a format for documents that are stored, displayed, or transmitted electronically on a computer.

[0297] To implement this invention, the server first receives content data and converts it into text format. Since the content data is provided in electronic document format, for example, in the case of a PDF, optical character recognition technology is used to extract the text information. The converted text is input into a generative AI model to generate a summary. The length of the summary is adjusted according to the time setting selected by the user.

[0298] The generated summary is sent from the server to the user's information terminal and displayed. The user can view the summary and enter questions as needed. Questions are sent to the server through an input form in the user interface. Based on the received questions, the server uses a generative AI model to find relevant information and construct specific answers. In doing so, the content is refined based on key scenes and storylines, and presented in a way that is easy for the user to understand.

[0299] As a concrete example, consider a user who doesn't have time to watch the latest movie using this system. The user can quickly obtain a movie summary, grasp the main scenes, and then input questions about specific scenes or settings to learn more detailed information. By setting prompts such as "Please provide a summary of the movie 'XX' that can be understood in 3 minutes" in the generating AI model, it is possible to provide specific and appropriate information.

[0300] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0301] Step 1:

[0302] The server receives content data from the user. The input is data in electronic document format, and the output is that data ready for conversion. Specifically, the server saves the PDF or EPUB files sent by the user to a database.

[0303] Step 2:

[0304] The server converts the received content data into text format. The input is stored electronic document data, and the output is text data. Specifically, for PDFs, OCR technology is used, and for EPUBs, a dedicated library is used to extract the text.

[0305] Step 3:

[0306] The server inputs the converted text data into the generative AI model to generate a summary. The input is the text data, and the output is the summary text. Specifically, it calls the API of the AI model and creates a summary using the prompt sentence "Please summarize the text so that it can be understood in X minutes."

[0307] Step 4:

[0308] The server sends the generated summary to the user's terminal. The input is the summary text, and the output is that the summary is displayed on the user terminal. Specifically, it uses the communication protocol to push and send the data to the terminal as a push notification.

[0309] Step 5:

[0310] The user views the displayed summary and enters a question if more detailed information is needed. The input is the user's question, and the output is the question data to the server. Specifically, it is the operation of entering a question through the terminal interface and pressing the send button.

[0311] Step 6:

[0312] Based on the received question, the server utilizes the generative AI model to generate an answer. The input is the question data and the original text data, and the output is a detailed answer. Specifically, it poses the question to the AI, extracts relevant information from the text data, and constructs an answer.

[0313] Step 7:

[0314] The server replies with the generated answer to the user's terminal. The input is the detailed answer, and the output is that the answer is displayed on the user terminal. Specifically, it uses the communication protocol to send the answer data to the terminal and display it on the screen.

[0315] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0316] As an embodiment of this invention, a method of combining an emotion engine with a system that receives book data and summarizes and displays its contents will be described.

[0317] First, the user uploads book data to the server using their device. After receiving the book data, the server converts it to text format. In this process, optical character recognition technology is used to extract text information from PDF data, and a dedicated library is used to obtain text data for ebook formats such as EPUB.

[0318] Next, the server feeds the converted text data into a generating AI to produce a summary. This summary is adjusted according to the time frame set by the user. The generated summary is presented in a format that aggregates important information and allows for quick understanding.

[0319] Furthermore, a key feature of this system is the incorporation of an emotion engine. The terminal uses cameras and sensors to analyze the user's emotions from their facial expressions and voice, and sends the emotion data to the server. The server evaluates this emotion data and uses generative AI to provide a response tailored to the user's emotional state. For example, if the user is confused, the generative AI adjusts to provide additional explanations or a different summarizing style.

[0320] The introduction of an emotion engine makes it possible to provide the appropriate amount and content of information according to the user's state. For example, if stress or confusion is detected when a user is trying to understand a particular academic paper, the system will improve learning efficiency by presenting explanations in simpler language and easy-to-understand examples.

[0321] As described above, the system configuration, which incorporates an emotion engine, goes beyond mere information provision to provide flexible support tailored to the user's emotions and understanding.

[0322] The following describes the processing flow.

[0323] Step 1:

[0324] The user imports book data into their device and uploads it to the server. After selecting the files, the device sends the data to the server.

[0325] Step 2:

[0326] The server analyzes the received book data. At this stage, if it's a PDF, text is extracted using optical character recognition technology; if it's in a format like EPUB, text data is extracted using a dedicated analysis library.

[0327] Step 3:

[0328] The server sends the converted text data to the generating AI and issues a command to generate a summary that fits the time specified by the user. The generating AI extracts key concepts and creates a summary that is appropriate for the specified time frame.

[0329] Step 4:

[0330] The terminal receives a summary from the server and displays it on the screen. The user can review this summary and understand its content. A user interface is also provided that includes fields for entering questions along with the summary.

[0331] Step 5:

[0332] The device collects the user's facial expressions and voice through its built-in camera and microphone. This data is sent to the emotion engine in real time and used to analyze the user's emotional state.

[0333] Step 6:

[0334] The server receives feedback from the emotion engine and determines the user's emotional state. If the user is showing emotions such as confusion or surprise, the server instructs the generating AI to make adjustments accordingly.

[0335] Step 7:

[0336] The generating AI adjusts or modifies responses based on the user's emotional state. For example, it might change the wording to something simpler and easier to understand, or include additional detailed explanations.

[0337] Step 8:

[0338] The server sends the adjusted results to the terminal, which then displays them to the user. This allows the user to receive information that corresponds to their emotional feedback, leading to a better understanding.

[0339] Step 9:

[0340] Users can ask additional questions as needed, and the system repeats the same process, using generated AI to respond as appropriate.

[0341] This process allows users to have a flexible learning experience tailored to their individual emotional state.

[0342] (Example 2)

[0343] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0344] Conventional book summarization systems have faced challenges in providing flexible information tailored to the user's emotional state, thus failing to enhance user understanding and satisfaction. Furthermore, they have limited ability to respond to specific user questions regarding the summarized information, resulting in a lack of in-depth information tailored to user needs.

[0345] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0346] In this invention, the server includes means for receiving data and converting it into an information format, means for creating a summary using a generative model based on the converted information, and means for acquiring emotional states and generating summaries and explanations corresponding to those emotions. This enables the provision of accurate information tailored to the user's emotional state. Furthermore, it enables the generation of flexible responses based on the user's questions, which is expected to improve the user's understanding and satisfaction.

[0347] "Data" refers to electronic material used to represent information.

[0348] "Information format" refers to the conversion of data into a recognizable form such as text or numbers.

[0349] A "generative model" is an algorithm or system that learns patterns from a large amount of data and generates new data.

[0350] A "summary" is a concise version of the original text, extracting the most important parts.

[0351] A "user" refers to a person who uses a system, and is an entity that operates the system through its interface.

[0352] "Device" refers to hardware that has a specific function and is used for operation or information processing.

[0353] "Emotional state" refers to the user's psychological state or mood, and is usually detected from facial expressions and voice.

[0354] "Explanation" means describing information or knowledge in detail so that others can understand it.

[0355] A "response" is information or feedback provided in response to a question or request.

[0356] As an embodiment of this invention, a system that consistently performs tasks from receiving book data to generating summaries and providing responses tailored to emotions will be described. First, the user uploads book data to a server using a terminal. Here, the terminal provides a user interface that allows data to be uploaded via drag-and-drop or a file selection dialog.

[0357] When the server receives book data, it determines its format and, if it is in PDF format, converts it into text data using Optical Character Recognition (OCR) technology. Open-source OCR engines are used for this purpose. For ebook formats such as EPUB, a dedicated ebook library is used to extract text information. The converted text data is then input into a generative AI model to generate a summary. For example, a large-scale language model using a multi-layer neural network is used as the generative AI model.

[0358] On the other hand, the device has sensors such as a camera and microphone to measure the user's emotional state in real time. Facial recognition and voice analysis technologies are used for emotion analysis. This emotion data is sent to a server, where a generative AI provides summaries and explanations appropriate to the user's emotional state.

[0359] The generated summary and additional information are displayed on the user's device, allowing the user to review the content. Furthermore, if the user enters a question related to the summary, the AI ​​model generates and provides an appropriate response to that question.

[0360] (Specific example)

[0361] For example, if a user wants to quickly understand a new science fiction novel, they could use a prompt like this: "Please read the summary of this novel in 10 minutes." Furthermore, if the user finds the summary difficult to understand after reading it and is deemed to be in a state of emotional confusion, the system could automatically provide additional information or a different style of summary with a prompt such as, "Please explain this part in more detail." This allows the user to receive information tailored to their level of understanding and emotional state.

[0362] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0363] Step 1:

[0364] The user uploads book data to the server using a terminal. The input is a file selected by the user (e.g., book data in PDF or EPUB format). The terminal provides the functionality to upload the file, and after transmission, the server saves the received data. The output is the book data stored on the server.

[0365] Step 2:

[0366] The server determines the format of the received book data and, if it is in PDF format, converts it to text data using Optical Character Recognition (OCR) technology. The input is the book data stored on the server. After determining the data format, the OCR engine is activated and the operation to extract characters from the image data is performed. The output is the converted text data.

[0367] Step 3:

[0368] The server inputs the converted text data into a generative AI model to generate a summary. The input is book data converted into text format. The generative AI model performs data calculations that extract the important parts of the input text and create a shortened summary. The output is the generated summary text.

[0369] Step 4:

[0370] The device uses a camera and microphone to collect the user's facial expressions and voice, and analyzes their emotional state. The input consists of real-time collected facial images and voice data of the user. The image and voice analysis engine is activated, and the system performs an emotional determination. The output is the user's emotional state data.

[0371] Step 5:

[0372] The server analyzes emotional state data transmitted from the terminal and provides summaries and additional explanations tailored to the user's emotions using a generative AI model. The input consists of emotional state data and the generated summary text. The generative AI model processes the data to output summaries and explanations in a format appropriate to the emotions. The output is the adjusted summary or additional explanation text.

[0373] Step 6:

[0374] The terminal displays the generated summary and response to the user. The input is the final generated summary or additional explanatory text. The information is displayed through the user interface. The user can review and understand the displayed content. The output is the information provided to the user visually.

[0375] (Application Example 2)

[0376] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0377] There is a need to efficiently summarize information in ebooks and provide appropriate information according to the user's emotional state. However, conventional systems lack the ability to adequately respond to the confusion and stress that users experience. In particular, there is a need for more specific and flexible means of responding when users feel anxious or confused during payment procedures or purchases.

[0378] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0379] In this invention, the server includes means for receiving book information and converting it into a string format, means for creating a summary using a generative AI based on the converted string, and means for using sensory organs to analyze the user's emotional state. This makes it possible not only to provide a summary according to the time set by the user, but also to provide optimal information based on the user's emotional state.

[0380] "Book information" refers to the content of a book represented as digital data in a format that can be processed electronically.

[0381] "Methods for converting to string format" refers to techniques for converting information from books, which exist in various formats, into string data that is easy for machines to process.

[0382] "Converted string" refers to data that has been converted from book information into a string format, and is the target of processing by the generation AI.

[0383] "Generative AI" is a type of artificial intelligence that models human knowledge and skills, analyzes data, and generates new information and insights.

[0384] "Methods for creating summaries" refer to the process of extracting key elements from a vast amount of original information data and automatically generating a document in a shortened format.

[0385] "User emotional state" refers to the psychological and sensory reactions a user exhibits when using the system, and the system analyzes this to determine appropriate responses.

[0386] "Methods using sensory organs" refer to technologies that use devices such as cameras and sensors to detect a user's facial expressions and voice, and analyze their emotional state.

[0387] The system for implementing this invention consists of a user terminal, a server, and a generative AI model. The user terminal is a device such as a smartphone or smart glasses, equipped with a camera and microphone. When the user selects information from a book on the device, that information is sent to the server.

[0388] The server runs a program that converts book information into a string format. For PDF data, it extracts text information using optical character recognition technology, and for ebook formats such as EPUB, it obtains string data using a dedicated library. The converted strings are fed into a generative AI model, and a summary is created.

[0389] This summary is adjusted according to the time frame set by the user and displayed on the user's device. Furthermore, the device's camera and sensors are used to analyze the user's emotional state from their facial expressions and voice. This emotional data is sent to a server, and the generative AI generates a response that corresponds to the user's emotional state. For example, if the user is confused, the generative AI will provide additional explanations or a different summarizing style.

[0390] As a concrete example, suppose a user using an electronic payment service is trying to purchase a new product using their smartphone, but is confused because entering the promotion code is complicated. In this case, the system analyzes the user's emotional state and uses a generative AI model to provide specific guidance such as, "Having trouble? You can check the promotion codes you can currently enter from the options in the upper right corner of the screen."

[0391] The software used will be TensorFlow for the generative AI model and Flask for the server-side implementation. An example of a prompt would be: "Generate a support message based on the user's emotional state. The user is confused. Provide a simple and concrete solution."

[0392] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0393] Step 1:

[0394] The user's terminal sends the entered book information to the server. This information is represented in various digital formats. The server receives this information and prepares for the next processing step.

[0395] Step 2:

[0396] The server converts the information from received books into a string format. For PDF data, optical character recognition (OCR) technology is used to extract the character information. For EPUB format, a dedicated library is used to obtain the string data. This converted string is then used in the subsequent summarization process.

[0397] Step 3:

[0398] The server inputs the converted string into a generating AI model to generate a summary of the book's content. The generating AI extracts key information from the input text and creates a shortened summary. This summary is then adjusted to a length corresponding to the time frame specified by the user and sent to the terminal.

[0399] Step 4:

[0400] The user's terminal displays the generated summary. The user can enter questions related to the summary as needed. These questions are sent back to the server, initiating the process of generating appropriate responses.

[0401] Step 5:

[0402] The device uses its camera and sensors to capture the user's facial expressions and voice, and analyzes their emotional state. By sending this emotional data to a server, it prepares to generate appropriate feedback based on the user's psychological response.

[0403] Step 6:

[0404] The server receives emotion data and uses generative AI to generate responses tailored to the user's emotional state. For example, if the user is confused, the system adjusts to provide additional explanations or a different summarizing style. The generated feedback is then sent back to the terminal and presented to the user.

[0405] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0406] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0407] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0408] [Third Embodiment]

[0409] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0410] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0411] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0412] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0413] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0414] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0415] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0416] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0417] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0418] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0419] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0420] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0421] To implement this invention, the server first receives book data and converts it into text format. Since the book data is provided by the user in formats such as PDF or EPUB, in the case of PDF, optical character recognition technology is used to extract character information, and in the case of EPUB and other formats, a dedicated library is used to obtain text data.

[0422] Next, the server inputs the converted text into a generating AI to produce a summary. The AI ​​is instructed to generate summaries of a length corresponding to a user-defined time limit (e.g., 5 minutes, 10 minutes, 30 minutes). Because the summarized text contains only concise and essential information, users can grasp the main points of the book within a limited time.

[0423] Next, the terminal displays the summary received from the server on the user interface. The user can view the summary and, if they have any questions to deepen their understanding, they can enter them through the terminal. The terminal is equipped with a question input form and a submit button, which the user uses to send questions of interest to the server.

[0424] The server uses AI to construct a detailed answer based on the received question. During this process, it extracts relevant information by referring to the original text data and summary, generating a specific and user-friendly response. Once the answer is complete, the server sends it back to the user's device, which then displays the received answer on the user's screen.

[0425] As a concrete example, consider a situation where a user wants to read the latest scientific journals but doesn't have the time. Using this system, the user can quickly understand the main topics and then ask more detailed questions about what they've already understood, thus acquiring knowledge efficiently. This method makes it possible to efficiently acquire necessary knowledge in today's information-saturated world.

[0426] The following describes the processing flow.

[0427] Step 1:

[0428] The user uploads book data using their device. After selecting the file, it is sent to the server via the device's interface.

[0429] Step 2:

[0430] The server analyzes the book data received from the user. If the data is in PDF format, it uses OCR technology to extract text information from the image data. If the data is in formats such as EPUB, it extracts text data via a dedicated library.

[0431] Step 3:

[0432] The server extracts text data and sends it to the AI. The AI ​​generates an optimal summary according to the specified summarization time (5 minutes, 10 minutes, 30 minutes). The summarized content is structured around the most important points.

[0433] Step 4:

[0434] The server sends the generated summary to the terminal. The terminal displays the summary on its screen, which the user can then review. The user interface includes a summary display and a text box for entering questions.

[0435] Step 5:

[0436] If a user has questions about the content while referring to the summary, they can use the terminal interface to enter their questions and send them to the server.

[0437] Step 6:

[0438] The server receives a question from the user, uses a generative AI to analyze the text data, and generates relevant answers. The answers are constructed based on the original text data and the generated summary, and address the user's question.

[0439] Step 7:

[0440] The server returns the generated answer to the terminal. The terminal displays this to the user, allowing the user to confirm the specific answer to the question.

[0441] By following these steps, users can quickly understand the content of the book and obtain additional information as needed.

[0442] (Example 1)

[0443] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0444] In today's world, the sheer volume of information is overwhelming, and there is a demand for efficient and time-efficient acquisition of important information. Furthermore, busy users often find it difficult to efficiently summarize vast amounts of book information and obtain more detailed information on topics of interest. Therefore, it is necessary to efficiently process book data and provide summaries and information tailored to user needs.

[0445] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0446] In this invention, the server includes means for receiving book information and converting it into text format, means for creating a summary using AI generated based on the converted text, and means for adjusting the length of the summary according to a time set by the user. This allows the user to efficiently check the necessary information in a short time and gain a deeper understanding through questions to acquire further knowledge.

[0447] "Means for receiving information from books and converting it into text format" refers to a device or method that receives data from books or documents in various formats and converts it into readable string information.

[0448] "Means for creating summaries using generated AI" refers to a device or method that utilizes artificial intelligence algorithms to extract only the important content from a large amount of text data and summarize it concisely.

[0449] "Means for adjusting the length of a summary according to a user-set time" refers to a device or method that dynamically changes the volume and level of detail of a summary to match a time frame specified in advance by the user.

[0450] "Means for displaying a summary on a user's terminal" refers to a device or method that transfers a generated summary to a user's device via a network and presents it in a visually verifiable format.

[0451] "Means by which a terminal receives a query related to a summary and a server generates a detailed response" refers to a device or method that receives a question via a user interface and derives an answer by retrieving or generating further information in response to that question.

[0452] "Means for converting to text data using optical character recognition technology" refers to a technology or device for mechanically reading characters from image data and converting them into digital text.

[0453] The embodiments for carrying out this invention will be described below.

[0454] The server first receives book information from the user. This information is often provided in electronic document format such as PDF or EPUB. In the case of PDF, the server uses optical character recognition (OCR) tools, such as Tesseract, to extract character information from the image data and convert it into text format. In the case of EPUB, the server directly obtains the text data using a dedicated library such as epub.js.

[0455] The converted text data is summarized by the generated AI. The server sends a prompt to the generating AI, instructing it to "summarize the following text in 5 minutes." This generating AI model uses natural language processing techniques to extract important information from the input text and create a summary of a specified length.

[0456] After the server generates a summary, the terminal receives this summary and displays it to the user through the user interface. The user can view this summary and, if they need more detailed information, can use the question input function on the terminal to make specific inquiries.

[0457] The server receives a user inquiry and uses the generated AI again to create a more detailed response. In this process, the server refers to the original text and summarized text, searches for relevant information, and generates the answer. The generated answer is then sent to the terminal, which displays it.

[0458] For example, if a user wants to efficiently understand the contents of the latest scientific journal, this system allows them to quickly obtain summaries of key topics and then gain a deeper understanding by asking more detailed questions about areas of interest. This approach makes it possible to efficiently acquire the necessary information in an age of information overload.

[0459] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0460] Step 1:

[0461] The server receives book information from the user. The server directly receives PDF and EPUB files uploaded by the user and prepares them for the next processing step. The input is the electronic document data provided by the user, and the output is the original data stored internally. This data is used in subsequent processing steps.

[0462] Step 2:

[0463] The server converts book information into text format. For PDF files, it extracts text data from image data using an OCR tool such as Tesseract. For EPUB files, it directly extracts text using a dedicated library (such as epub.js). The input is electronic document data, and the output is text format data. This conversion is performed as preparation for AI processing.

[0464] Step 3:

[0465] The server inputs text data into a generative AI to create a summary. The server sends a prompt to the generative AI saying, "Summarize this text within the specified time." The generative AI uses natural language processing techniques to generate a summary from the text. The input is text data and a prompt, and the output is the summarized text.

[0466] Step 4:

[0467] The server sends the generated summary to the terminal. The summary is sent from the server to the terminal via the network, making it available for user review. The input is the summary text, and the output is the data displayed on the terminal.

[0468] Step 5:

[0469] The device displays a summary to the user. The device visualizes the received summary on the user interface, allowing the user to review its contents. Specifically, the device includes a function that automatically displays the summary on its screen.

[0470] Step 6:

[0471] The user reviews the displayed summary and enters questions from their device if they want more detailed information. The user sends questions about points of interest to the server using the device's question input function. The input is the user's question text, and the output is the query sent to the server.

[0472] Step 7:

[0473] The server receives a question from the user and generates a detailed response using generative AI. In this process, relevant information is extracted from the original text or summary, and specific answers are constructed using the power of AI. The input is the user's question text, and the output is the generated response text.

[0474] Step 8:

[0475] The server sends the generated response to the terminal, which then displays it to the user. The user interface receives the response data and visualizes it in a way that the user can understand. The input is the generated response text, and the output is the response information displayed on the terminal.

[0476] (Application Example 1)

[0477] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0478] In today's world, the sheer volume of content is overwhelming, making it difficult for users to view everything due to time constraints. Furthermore, there is a need for efficient ways for users to understand the content they select beforehand and then delve deeper into it based on their interests.

[0479] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0480] In this invention, the server includes means for receiving content data and converting it into text format, means for creating a summary using a generative AI based on the converted text, and means for summarizing the main scenes and storyline of the content selected by the user. This allows the user to quickly understand the main points of the content and efficiently obtain more detailed information on areas of interest.

[0481] "Content" refers to a collection of information provided to a user, either visually or audibly.

[0482] "Data" refers to a sequence of numbers or strings that represent information, and is the subject of processing and transformation.

[0483] "Text format" refers to a state where data is represented as a string of characters and can be read by machines or humans.

[0484] "Generative AI" is a system that utilizes artificial intelligence technology to generate new information based on given data.

[0485] A "summary" is a short compilation of the main points or important content of information.

[0486] An "information terminal" is a physical device used to display, process, or communicate information electronically.

[0487] A "main scene" refers to an important or central moment or event within the content.

[0488] "Storyline" refers to the progression or plot of a story within a piece of content.

[0489] "Optical character recognition technology" is a technology that detects characters within an image and converts them into text data.

[0490] An "electronic document format" is a format for documents that are stored, displayed, or transmitted electronically on a computer.

[0491] To implement this invention, the server first receives content data and converts it into text format. Since the content data is provided in electronic document format, for example, in the case of a PDF, optical character recognition technology is used to extract the text information. The converted text is input into a generative AI model to generate a summary. The length of the summary is adjusted according to the time setting selected by the user.

[0492] The generated summary is sent from the server to the user's information terminal and displayed. The user can view the summary and enter questions as needed. Questions are sent to the server through an input form in the user interface. Based on the received questions, the server uses a generative AI model to find relevant information and construct specific answers. In doing so, the content is refined based on key scenes and storylines, and presented in a way that is easy for the user to understand.

[0493] As a concrete example, consider a user who doesn't have time to watch the latest movie using this system. The user can quickly obtain a movie summary, grasp the main scenes, and then input questions about specific scenes or settings to learn more detailed information. By setting prompts such as "Please provide a summary of the movie 'XX' that can be understood in 3 minutes" in the generating AI model, it is possible to provide specific and appropriate information.

[0494] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0495] Step 1:

[0496] The server receives content data from the user. The input is data in electronic document format, and the output is that data ready for conversion. Specifically, the server saves the PDF or EPUB files sent by the user to a database.

[0497] Step 2:

[0498] The server converts the received content data into text format. The input is stored electronic document data, and the output is text data. Specifically, for PDFs, OCR technology is used, and for EPUBs, a dedicated library is used to extract the text.

[0499] Step 3:

[0500] The server inputs the converted text data into an AI model to generate a summary. The input is text data, and the output is a summarized text. Specifically, it calls the AI ​​model's API and creates a summary using the prompt "Please summarize the text in a way that can be understood in X minutes."

[0501] Step 4:

[0502] The server sends the generated summary to the user's device. The input is the summary text, and the output is the summary being displayed on the user's device. Specifically, the data is sent to the device as a push notification using a communication protocol.

[0503] Step 5:

[0504] The user views the displayed summary and enters questions if more information is needed. The input is the user's question, and the output is the question data sent to the server. Specifically, this involves entering a question through the terminal interface and pressing the submit button.

[0505] Step 6:

[0506] The server generates answers based on the received questions, utilizing a generative AI model. The input consists of the question data and the original text data, while the output is a detailed answer. Specifically, the AI ​​is given a question, extracts relevant information from the text data, and constructs an answer.

[0507] Step 7:

[0508] The server sends the generated response back to the user's terminal. The input is the detailed response, and the output is the response being displayed on the user's terminal. Specifically, the response data is sent to the terminal using a communication protocol and displayed on the screen.

[0509] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0510] As an embodiment of this invention, a method of combining an emotion engine with a system that receives book data and summarizes and displays its contents will be described.

[0511] First, the user uploads book data to the server using their device. After receiving the book data, the server converts it to text format. In this process, optical character recognition technology is used to extract text information from PDF data, and a dedicated library is used to obtain text data for ebook formats such as EPUB.

[0512] Next, the server feeds the converted text data into a generating AI to produce a summary. This summary is adjusted according to the time frame set by the user. The generated summary is presented in a format that aggregates important information and allows for quick understanding.

[0513] Furthermore, a key feature of this system is the incorporation of an emotion engine. The terminal uses cameras and sensors to analyze the user's emotions from their facial expressions and voice, and sends the emotion data to the server. The server evaluates this emotion data and uses generative AI to provide a response tailored to the user's emotional state. For example, if the user is confused, the generative AI adjusts to provide additional explanations or a different summarizing style.

[0514] The introduction of an emotion engine makes it possible to provide the appropriate amount and content of information according to the user's state. For example, if stress or confusion is detected when a user is trying to understand a particular academic paper, the system will improve learning efficiency by presenting explanations in simpler language and easy-to-understand examples.

[0515] As described above, the system configuration, which incorporates an emotion engine, goes beyond mere information provision to provide flexible support tailored to the user's emotions and understanding.

[0516] The following describes the processing flow.

[0517] Step 1:

[0518] The user imports book data into their device and uploads it to the server. After selecting the files, the device sends the data to the server.

[0519] Step 2:

[0520] The server analyzes the received book data. At this stage, if it's a PDF, text is extracted using optical character recognition technology; if it's in a format like EPUB, text data is extracted using a dedicated analysis library.

[0521] Step 3:

[0522] The server sends the converted text data to the generating AI and issues a command to generate a summary that fits the time specified by the user. The generating AI extracts key concepts and creates a summary that is appropriate for the specified time frame.

[0523] Step 4:

[0524] The terminal receives a summary from the server and displays it on the screen. The user can review this summary and understand its content. A user interface is also provided that includes fields for entering questions along with the summary.

[0525] Step 5:

[0526] The device collects the user's facial expressions and voice through its built-in camera and microphone. This data is sent to the emotion engine in real time and used to analyze the user's emotional state.

[0527] Step 6:

[0528] The server receives feedback from the emotion engine and determines the user's emotional state. If the user is showing emotions such as confusion or surprise, the server instructs the generating AI to make adjustments accordingly.

[0529] Step 7:

[0530] The generating AI adjusts or modifies responses based on the user's emotional state. For example, it might change the wording to something simpler and easier to understand, or include additional detailed explanations.

[0531] Step 8:

[0532] The server sends the adjusted results to the terminal, which then displays them to the user. This allows the user to receive information that corresponds to their emotional feedback, leading to a better understanding.

[0533] Step 9:

[0534] Users can ask additional questions as needed, and the system repeats the same process, using generated AI to respond as appropriate.

[0535] This process allows users to have a flexible learning experience tailored to their individual emotional state.

[0536] (Example 2)

[0537] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0538] Conventional book summarization systems have faced challenges in providing flexible information tailored to the user's emotional state, thus failing to enhance user understanding and satisfaction. Furthermore, they have limited ability to respond to specific user questions regarding the summarized information, resulting in a lack of in-depth information tailored to user needs.

[0539] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0540] In this invention, the server includes means for receiving data and converting it into an information format, means for creating a summary using a generative model based on the converted information, and means for acquiring emotional states and generating summaries and explanations corresponding to those emotions. This enables the provision of accurate information tailored to the user's emotional state. Furthermore, it enables the generation of flexible responses based on the user's questions, which is expected to improve the user's understanding and satisfaction.

[0541] "Data" refers to electronic material used to represent information.

[0542] "Information format" refers to the conversion of data into a recognizable form such as text or numbers.

[0543] A "generative model" is an algorithm or system that learns patterns from a large amount of data and generates new data.

[0544] A "summary" is a concise version of the original text, extracting the most important parts.

[0545] A "user" refers to a person who uses a system, and is an entity that operates the system through its interface.

[0546] "Device" refers to hardware that has a specific function and is used for operation or information processing.

[0547] "Emotional state" refers to the user's psychological state or mood, and is usually detected from facial expressions and voice.

[0548] "Explanation" means describing information or knowledge in detail so that others can understand it.

[0549] A "response" is information or feedback provided in response to a question or request.

[0550] As an embodiment of this invention, a system that consistently performs tasks from receiving book data to generating summaries and providing responses tailored to emotions will be described. First, the user uploads book data to a server using a terminal. Here, the terminal provides a user interface that allows data to be uploaded via drag-and-drop or a file selection dialog.

[0551] When the server receives book data, it determines its format and, if it is in PDF format, converts it into text data using Optical Character Recognition (OCR) technology. Open-source OCR engines are used for this purpose. For ebook formats such as EPUB, a dedicated ebook library is used to extract text information. The converted text data is then input into a generative AI model to generate a summary. For example, a large-scale language model using a multi-layer neural network is used as the generative AI model.

[0552] On the other hand, the device has sensors such as a camera and microphone to measure the user's emotional state in real time. Facial recognition and voice analysis technologies are used for emotion analysis. This emotion data is sent to a server, where a generative AI provides summaries and explanations appropriate to the user's emotional state.

[0553] The generated summary and additional information are displayed on the user's device, allowing the user to review the content. Furthermore, if the user enters a question related to the summary, the AI ​​model generates and provides an appropriate response to that question.

[0554] (Specific example)

[0555] For example, if a user wants to quickly understand a new science fiction novel, they could use a prompt like this: "Please read the summary of this novel in 10 minutes." Furthermore, if the user finds the summary difficult to understand after reading it and is deemed to be in a state of emotional confusion, the system could automatically provide additional information or a different style of summary with a prompt such as, "Please explain this part in more detail." This allows the user to receive information tailored to their level of understanding and emotional state.

[0556] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0557] Step 1:

[0558] The user uploads book data to the server using a terminal. The input is a file selected by the user (e.g., book data in PDF or EPUB format). The terminal provides the functionality to upload the file, and after transmission, the server saves the received data. The output is the book data stored on the server.

[0559] Step 2:

[0560] The server determines the format of the received book data and, if it is in PDF format, converts it to text data using Optical Character Recognition (OCR) technology. The input is the book data stored on the server. After determining the data format, the OCR engine is activated and the operation to extract characters from the image data is performed. The output is the converted text data.

[0561] Step 3:

[0562] The server inputs the converted text data into a generative AI model to generate a summary. The input is book data converted into text format. The generative AI model performs data calculations that extract the important parts of the input text and create a shortened summary. The output is the generated summary text.

[0563] Step 4:

[0564] The device uses a camera and microphone to collect the user's facial expressions and voice, and analyzes their emotional state. The input consists of real-time collected facial images and voice data of the user. The image and voice analysis engine is activated, and the system performs an emotional determination. The output is the user's emotional state data.

[0565] Step 5:

[0566] The server analyzes emotional state data transmitted from the terminal and provides summaries and additional explanations tailored to the user's emotions using a generative AI model. The input consists of emotional state data and the generated summary text. The generative AI model processes the data to output summaries and explanations in a format appropriate to the emotions. The output is the adjusted summary or additional explanation text.

[0567] Step 6:

[0568] The terminal displays the generated summary and response to the user. The input is the final generated summary or additional explanatory text. The information is displayed through the user interface. The user can review and understand the displayed content. The output is the information provided to the user visually.

[0569] (Application Example 2)

[0570] Next, we will explain Application Example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0571] There is a need to efficiently summarize information in ebooks and provide appropriate information according to the user's emotional state. However, conventional systems lack the ability to adequately respond to the confusion and stress that users experience. In particular, there is a need for more specific and flexible means of responding when users feel anxious or confused during payment procedures or purchases.

[0572] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0573] In this invention, the server includes means for receiving book information and converting it into a string format, means for creating a summary using a generative AI based on the converted string, and means for using sensory organs to analyze the user's emotional state. This makes it possible not only to provide a summary according to the time set by the user, but also to provide optimal information based on the user's emotional state.

[0574] "Book information" refers to the content of a book represented as digital data in a format that can be processed electronically.

[0575] "Methods for converting to string format" refers to techniques for converting information from books, which exist in various formats, into string data that is easy for machines to process.

[0576] "Converted string" refers to data that has been converted from book information into a string format, and is the target of processing by the generation AI.

[0577] "Generative AI" is a type of artificial intelligence that models human knowledge and skills, analyzes data, and generates new information and insights.

[0578] "Methods for creating summaries" refer to the process of extracting key elements from a vast amount of original information data and automatically generating a document in a shortened format.

[0579] "User emotional state" refers to the psychological and sensory reactions a user exhibits when using the system, and the system analyzes this to determine appropriate responses.

[0580] "Methods using sensory organs" refer to technologies that use devices such as cameras and sensors to detect a user's facial expressions and voice, and analyze their emotional state.

[0581] The system for implementing this invention consists of a user terminal, a server, and a generative AI model. The user terminal is a device such as a smartphone or smart glasses, equipped with a camera and microphone. When the user selects information from a book on the device, that information is sent to the server.

[0582] The server runs a program that converts book information into a string format. For PDF data, it extracts text information using optical character recognition technology, and for ebook formats such as EPUB, it obtains string data using a dedicated library. The converted strings are fed into a generative AI model, and a summary is created.

[0583] This summary is adjusted according to the time frame set by the user and displayed on the user's device. Furthermore, the device's camera and sensors are used to analyze the user's emotional state from their facial expressions and voice. This emotional data is sent to a server, and the generative AI generates a response that corresponds to the user's emotional state. For example, if the user is confused, the generative AI will provide additional explanations or a different summarizing style.

[0584] As a concrete example, suppose a user using an electronic payment service is trying to purchase a new product using their smartphone, but is confused because entering the promotion code is complicated. In this case, the system analyzes the user's emotional state and uses a generative AI model to provide specific guidance such as, "Having trouble? You can check the promotion codes you can currently enter from the options in the upper right corner of the screen."

[0585] The software used will be TensorFlow for the generative AI model and Flask for the server-side implementation. An example of a prompt would be: "Generate a support message based on the user's emotional state. The user is confused. Provide a simple and concrete solution."

[0586] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0587] Step 1:

[0588] The user's terminal sends the entered book information to the server. This information is represented in various digital formats. The server receives this information and prepares for the next processing step.

[0589] Step 2:

[0590] The server converts the information from received books into a string format. For PDF data, optical character recognition (OCR) technology is used to extract the character information. For EPUB format, a dedicated library is used to obtain the string data. This converted string is then used in the subsequent summarization process.

[0591] Step 3:

[0592] The server inputs the converted string into a generating AI model to generate a summary of the book's content. The generating AI extracts key information from the input text and creates a shortened summary. This summary is then adjusted to a length corresponding to the time frame specified by the user and sent to the terminal.

[0593] Step 4:

[0594] The user's terminal displays the generated summary. The user can enter questions related to the summary as needed. These questions are sent back to the server, initiating the process of generating appropriate responses.

[0595] Step 5:

[0596] The device uses its camera and sensors to capture the user's facial expressions and voice, and analyzes their emotional state. By sending this emotional data to a server, it prepares to generate appropriate feedback based on the user's psychological response.

[0597] Step 6:

[0598] The server receives emotion data and uses generative AI to generate responses tailored to the user's emotional state. For example, if the user is confused, the system adjusts to provide additional explanations or a different summarizing style. The generated feedback is then sent back to the terminal and presented to the user.

[0599] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0600] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0601] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0602] [Fourth Embodiment]

[0603] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0604] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0605] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0606] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0607] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0608] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0609] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0610] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0611] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0612] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0613] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0614] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0615] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0616] To implement this invention, the server first receives book data and converts it into text format. Since the book data is provided by the user in formats such as PDF or EPUB, in the case of PDF, optical character recognition technology is used to extract character information, and in the case of EPUB and other formats, a dedicated library is used to obtain text data.

[0617] Next, the server inputs the converted text into a generating AI to produce a summary. The AI ​​is instructed to generate summaries of a length corresponding to a user-defined time limit (e.g., 5 minutes, 10 minutes, 30 minutes). Because the summarized text contains only concise and essential information, users can grasp the main points of the book within a limited time.

[0618] Next, the terminal displays the summary received from the server on the user interface. The user can view the summary and, if they have any questions to deepen their understanding, they can enter them through the terminal. The terminal is equipped with a question input form and a submit button, which the user uses to send questions of interest to the server.

[0619] The server uses AI to construct a detailed answer based on the received question. During this process, it extracts relevant information by referring to the original text data and summary, generating a specific and user-friendly response. Once the answer is complete, the server sends it back to the user's device, which then displays the received answer on the user's screen.

[0620] As a concrete example, consider a situation where a user wants to read the latest scientific journals but doesn't have the time. Using this system, the user can quickly understand the main topics and then ask more detailed questions about what they've already understood, thus acquiring knowledge efficiently. This method makes it possible to efficiently acquire necessary knowledge in today's information-saturated world.

[0621] The following describes the processing flow.

[0622] Step 1:

[0623] The user uploads book data using their device. After selecting the file, it is sent to the server via the device's interface.

[0624] Step 2:

[0625] The server analyzes the book data received from the user. If the data is in PDF format, it uses OCR technology to extract text information from the image data. If the data is in formats such as EPUB, it extracts text data via a dedicated library.

[0626] Step 3:

[0627] The server extracts text data and sends it to the AI. The AI ​​generates an optimal summary according to the specified summarization time (5 minutes, 10 minutes, 30 minutes). The summarized content is structured around the most important points.

[0628] Step 4:

[0629] The server sends the generated summary to the terminal. The terminal displays the summary on its screen, which the user can then review. The user interface includes a summary display and a text box for entering questions.

[0630] Step 5:

[0631] If a user has questions about the content while referring to the summary, they can use the terminal interface to enter their questions and send them to the server.

[0632] Step 6:

[0633] The server receives a question from the user, uses a generative AI to analyze the text data, and generates relevant answers. The answers are constructed based on the original text data and the generated summary, and address the user's question.

[0634] Step 7:

[0635] The server returns the generated answer to the terminal. The terminal displays this to the user, allowing the user to confirm the specific answer to the question.

[0636] By following these steps, users can quickly understand the content of the book and obtain additional information as needed.

[0637] (Example 1)

[0638] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0639] In today's world, the sheer volume of information is overwhelming, and there is a demand for efficient and time-efficient acquisition of important information. Furthermore, busy users often find it difficult to efficiently summarize vast amounts of book information and obtain more detailed information on topics of interest. Therefore, it is necessary to efficiently process book data and provide summaries and information tailored to user needs.

[0640] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0641] In this invention, the server includes means for receiving book information and converting it into text format, means for creating a summary using AI generated based on the converted text, and means for adjusting the length of the summary according to a time set by the user. This allows the user to efficiently check the necessary information in a short time and gain a deeper understanding through questions to acquire further knowledge.

[0642] "Means for receiving information from books and converting it into text format" refers to a device or method that receives data from books or documents in various formats and converts it into readable string information.

[0643] "Means for creating summaries using generated AI" refers to a device or method that utilizes artificial intelligence algorithms to extract only the important content from a large amount of text data and summarize it concisely.

[0644] "Means for adjusting the length of a summary according to a user-set time" refers to a device or method that dynamically changes the volume and level of detail of a summary to match a time frame specified in advance by the user.

[0645] "Means for displaying a summary on a user's terminal" refers to a device or method that transfers a generated summary to a user's device via a network and presents it in a visually verifiable format.

[0646] "Means by which a terminal receives a query related to a summary and a server generates a detailed response" refers to a device or method that receives a question via a user interface and derives an answer by retrieving or generating further information in response to that question.

[0647] "Means for converting to text data using optical character recognition technology" refers to a technology or device for mechanically reading characters from image data and converting them into digital text.

[0648] The embodiments for carrying out this invention will be described below.

[0649] The server first receives book information from the user. This information is often provided in electronic document format such as PDF or EPUB. In the case of PDF, the server uses optical character recognition (OCR) tools, such as Tesseract, to extract character information from the image data and convert it into text format. In the case of EPUB, the server directly obtains the text data using a dedicated library such as epub.js.

[0650] The converted text data is summarized by the generated AI. The server sends a prompt to the generating AI, instructing it to "summarize the following text in 5 minutes." This generating AI model uses natural language processing techniques to extract important information from the input text and create a summary of a specified length.

[0651] After the server generates a summary, the terminal receives this summary and displays it to the user through the user interface. The user can view this summary and, if they need more detailed information, can use the question input function on the terminal to make specific inquiries.

[0652] The server receives a user inquiry and uses the generated AI again to create a more detailed response. In this process, the server refers to the original text and summarized text, searches for relevant information, and generates the answer. The generated answer is then sent to the terminal, which displays it.

[0653] For example, if a user wants to efficiently understand the contents of the latest scientific journal, this system allows them to quickly obtain summaries of key topics and then gain a deeper understanding by asking more detailed questions about areas of interest. This approach makes it possible to efficiently acquire the necessary information in an age of information overload.

[0654] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0655] Step 1:

[0656] The server receives book information from the user. The server directly receives PDF and EPUB files uploaded by the user and prepares them for the next processing step. The input is the electronic document data provided by the user, and the output is the original data stored internally. This data is used in subsequent processing steps.

[0657] Step 2:

[0658] The server converts book information into text format. For PDF files, it extracts text data from image data using an OCR tool such as Tesseract. For EPUB files, it directly extracts text using a dedicated library (such as epub.js). The input is electronic document data, and the output is text format data. This conversion is performed as preparation for AI processing.

[0659] Step 3:

[0660] The server inputs text data into a generative AI to create a summary. The server sends a prompt to the generative AI saying, "Summarize this text within the specified time." The generative AI uses natural language processing techniques to generate a summary from the text. The input is text data and a prompt, and the output is the summarized text.

[0661] Step 4:

[0662] The server sends the generated summary to the terminal. The summary is sent from the server to the terminal via the network, making it available for user review. The input is the summary text, and the output is the data displayed on the terminal.

[0663] Step 5:

[0664] The device displays a summary to the user. The device visualizes the received summary on the user interface, allowing the user to review its contents. Specifically, the device includes a function that automatically displays the summary on its screen.

[0665] Step 6:

[0666] The user reviews the displayed summary and enters questions from their device if they want more detailed information. The user sends questions about points of interest to the server using the device's question input function. The input is the user's question text, and the output is the query sent to the server.

[0667] Step 7:

[0668] The server receives a question from the user and generates a detailed response using generative AI. In this process, relevant information is extracted from the original text or summary, and specific answers are constructed using the power of AI. The input is the user's question text, and the output is the generated response text.

[0669] Step 8:

[0670] The server sends the generated response to the terminal, which then displays it to the user. The user interface receives the response data and visualizes it in a way that the user can understand. The input is the generated response text, and the output is the response information displayed on the terminal.

[0671] (Application Example 1)

[0672] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0673] In today's world, the sheer volume of content is overwhelming, making it difficult for users to view everything due to time constraints. Furthermore, there is a need for efficient ways for users to understand the content they select beforehand and then delve deeper into it based on their interests.

[0674] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0675] In this invention, the server includes means for receiving content data and converting it into text format, means for creating a summary using a generative AI based on the converted text, and means for summarizing the main scenes and storyline of the content selected by the user. This allows the user to quickly understand the main points of the content and efficiently obtain more detailed information on areas of interest.

[0676] "Content" refers to a collection of information provided to a user, either visually or audibly.

[0677] "Data" refers to a sequence of numbers or strings that represent information, and is the subject of processing and transformation.

[0678] "Text format" refers to a state where data is represented as a string of characters and can be read by machines or humans.

[0679] "Generative AI" is a system that utilizes artificial intelligence technology to generate new information based on given data.

[0680] A "summary" is a short compilation of the main points or important content of information.

[0681] An "information terminal" is a physical device used to display, process, or communicate information electronically.

[0682] A "main scene" refers to an important or central moment or event within the content.

[0683] "Storyline" refers to the progression or plot of a story within a piece of content.

[0684] "Optical character recognition technology" is a technology that detects characters within an image and converts them into text data.

[0685] An "electronic document format" is a format for documents that are stored, displayed, or transmitted electronically on a computer.

[0686] To implement this invention, the server first receives content data and converts it into text format. Since the content data is provided in electronic document format, for example, in the case of a PDF, optical character recognition technology is used to extract the text information. The converted text is input into a generative AI model to generate a summary. The length of the summary is adjusted according to the time setting selected by the user.

[0687] The generated summary is sent from the server to the user's information terminal and displayed. The user can view the summary and enter questions as needed. Questions are sent to the server through an input form in the user interface. Based on the received questions, the server uses a generative AI model to find relevant information and construct specific answers. In doing so, the content is refined based on key scenes and storylines, and presented in a way that is easy for the user to understand.

[0688] As a concrete example, consider a user who doesn't have time to watch the latest movie using this system. The user can quickly obtain a movie summary, grasp the main scenes, and then input questions about specific scenes or settings to learn more detailed information. By setting prompts such as "Please provide a summary of the movie 'XX' that can be understood in 3 minutes" in the generating AI model, it is possible to provide specific and appropriate information.

[0689] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0690] Step 1:

[0691] The server receives content data from the user. The input is data in electronic document format, and the output is that data ready for conversion. Specifically, the server saves the PDF or EPUB files sent by the user to a database.

[0692] Step 2:

[0693] The server converts the received content data into text format. The input is stored electronic document data, and the output is text data. Specifically, for PDFs, OCR technology is used, and for EPUBs, a dedicated library is used to extract the text.

[0694] Step 3:

[0695] The server inputs the converted text data into an AI model to generate a summary. The input is text data, and the output is a summarized text. Specifically, it calls the AI ​​model's API and creates a summary using the prompt "Please summarize the text in a way that can be understood in X minutes."

[0696] Step 4:

[0697] The server sends the generated summary to the user's device. The input is the summary text, and the output is the summary being displayed on the user's device. Specifically, the data is sent to the device as a push notification using a communication protocol.

[0698] Step 5:

[0699] The user views the displayed summary and enters questions if more information is needed. The input is the user's question, and the output is the question data sent to the server. Specifically, this involves entering a question through the terminal interface and pressing the submit button.

[0700] Step 6:

[0701] The server generates answers based on the received questions, utilizing a generative AI model. The input consists of the question data and the original text data, while the output is a detailed answer. Specifically, the AI ​​is given a question, extracts relevant information from the text data, and constructs an answer.

[0702] Step 7:

[0703] The server sends the generated response back to the user's terminal. The input is the detailed response, and the output is the response being displayed on the user's terminal. Specifically, the response data is sent to the terminal using a communication protocol and displayed on the screen.

[0704] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0705] As an embodiment of this invention, a method of combining an emotion engine with a system that receives book data and summarizes and displays its contents will be described.

[0706] First, the user uploads book data to the server using their device. After receiving the book data, the server converts it to text format. In this process, optical character recognition technology is used to extract text information from PDF data, and a dedicated library is used to obtain text data for ebook formats such as EPUB.

[0707] Next, the server feeds the converted text data into a generating AI to produce a summary. This summary is adjusted according to the time frame set by the user. The generated summary is presented in a format that aggregates important information and allows for quick understanding.

[0708] Furthermore, a key feature of this system is the incorporation of an emotion engine. The terminal uses cameras and sensors to analyze the user's emotions from their facial expressions and voice, and sends the emotion data to the server. The server evaluates this emotion data and uses generative AI to provide a response tailored to the user's emotional state. For example, if the user is confused, the generative AI adjusts to provide additional explanations or a different summarizing style.

[0709] The introduction of an emotion engine makes it possible to provide the appropriate amount and content of information according to the user's state. For example, if stress or confusion is detected when a user is trying to understand a particular academic paper, the system will improve learning efficiency by presenting explanations in simpler language and easy-to-understand examples.

[0710] As described above, the system configuration, which incorporates an emotion engine, goes beyond mere information provision to provide flexible support tailored to the user's emotions and understanding.

[0711] The following describes the processing flow.

[0712] Step 1:

[0713] The user imports book data into their device and uploads it to the server. After selecting the files, the device sends the data to the server.

[0714] Step 2:

[0715] The server analyzes the received book data. At this stage, if it's a PDF, text is extracted using optical character recognition technology; if it's in a format like EPUB, text data is extracted using a dedicated analysis library.

[0716] Step 3:

[0717] The server sends the converted text data to the generating AI and issues a command to generate a summary that fits the time specified by the user. The generating AI extracts key concepts and creates a summary that is appropriate for the specified time frame.

[0718] Step 4:

[0719] The terminal receives a summary from the server and displays it on the screen. The user can review this summary and understand its content. A user interface is also provided that includes fields for entering questions along with the summary.

[0720] Step 5:

[0721] The device collects the user's facial expressions and voice through its built-in camera and microphone. This data is sent to the emotion engine in real time and used to analyze the user's emotional state.

[0722] Step 6:

[0723] The server receives feedback from the emotion engine and determines the user's emotional state. If the user is showing emotions such as confusion or surprise, the server instructs the generating AI to make adjustments accordingly.

[0724] Step 7:

[0725] The generating AI adjusts or modifies responses based on the user's emotional state. For example, it might change the wording to something simpler and easier to understand, or include additional detailed explanations.

[0726] Step 8:

[0727] The server sends the adjusted results to the terminal, which then displays them to the user. This allows the user to receive information that corresponds to their emotional feedback, leading to a better understanding.

[0728] Step 9:

[0729] Users can ask additional questions as needed, and the system repeats the same process, using generated AI to respond as appropriate.

[0730] This process allows users to have a flexible learning experience tailored to their individual emotional state.

[0731] (Example 2)

[0732] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0733] Conventional book summarization systems have faced challenges in providing flexible information tailored to the user's emotional state, thus failing to enhance user understanding and satisfaction. Furthermore, they have limited ability to respond to specific user questions regarding the summarized information, resulting in a lack of in-depth information tailored to user needs.

[0734] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0735] In this invention, the server includes means for receiving data and converting it into an information format, means for creating a summary using a generative model based on the converted information, and means for acquiring emotional states and generating summaries and explanations corresponding to those emotions. This enables the provision of accurate information tailored to the user's emotional state. Furthermore, it enables the generation of flexible responses based on the user's questions, which is expected to improve the user's understanding and satisfaction.

[0736] "Data" refers to electronic material used to represent information.

[0737] "Information format" refers to the conversion of data into a recognizable form such as text or numbers.

[0738] A "generative model" is an algorithm or system that learns patterns from a large amount of data and generates new data.

[0739] A "summary" is a concise version of the original text, extracting the most important parts.

[0740] A "user" refers to a person who uses a system, and is an entity that operates the system through its interface.

[0741] "Device" refers to hardware that has a specific function and is used for operation or information processing.

[0742] "Emotional state" refers to the user's psychological state or mood, and is usually detected from facial expressions and voice.

[0743] "Explanation" means describing information or knowledge in detail so that others can understand it.

[0744] A "response" is information or feedback provided in response to a question or request.

[0745] As an embodiment of this invention, a system that consistently performs tasks from receiving book data to generating summaries and providing responses tailored to emotions will be described. First, the user uploads book data to a server using a terminal. Here, the terminal provides a user interface that allows data to be uploaded via drag-and-drop or a file selection dialog.

[0746] When the server receives book data, it determines its format and, if it is in PDF format, converts it into text data using Optical Character Recognition (OCR) technology. Open-source OCR engines are used for this purpose. For ebook formats such as EPUB, a dedicated ebook library is used to extract text information. The converted text data is then input into a generative AI model to generate a summary. For example, a large-scale language model using a multi-layer neural network is used as the generative AI model.

[0747] On the other hand, the device has sensors such as a camera and microphone to measure the user's emotional state in real time. Facial recognition and voice analysis technologies are used for emotion analysis. This emotion data is sent to a server, where a generative AI provides summaries and explanations appropriate to the user's emotional state.

[0748] The generated summary and additional information are displayed on the user's device, allowing the user to review the content. Furthermore, if the user enters a question related to the summary, the AI ​​model generates and provides an appropriate response to that question.

[0749] (Specific example)

[0750] For example, if a user wants to quickly understand a new science fiction novel, they could use a prompt like this: "Please read the summary of this novel in 10 minutes." Furthermore, if the user finds the summary difficult to understand after reading it and is deemed to be in a state of emotional confusion, the system could automatically provide additional information or a different style of summary with a prompt such as, "Please explain this part in more detail." This allows the user to receive information tailored to their level of understanding and emotional state.

[0751] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0752] Step 1:

[0753] The user uploads book data to the server using a terminal. The input is a file selected by the user (e.g., book data in PDF or EPUB format). The terminal provides the functionality to upload the file, and after transmission, the server saves the received data. The output is the book data stored on the server.

[0754] Step 2:

[0755] The server determines the format of the received book data and, if it is in PDF format, converts it to text data using Optical Character Recognition (OCR) technology. The input is the book data stored on the server. After determining the data format, the OCR engine is activated and the operation to extract characters from the image data is performed. The output is the converted text data.

[0756] Step 3:

[0757] The server inputs the converted text data into a generative AI model to generate a summary. The input is book data converted into text format. The generative AI model performs data calculations that extract the important parts of the input text and create a shortened summary. The output is the generated summary text.

[0758] Step 4:

[0759] The device uses a camera and microphone to collect the user's facial expressions and voice, and analyzes their emotional state. The input consists of real-time collected facial images and voice data of the user. The image and voice analysis engine is activated, and the system performs an emotional determination. The output is the user's emotional state data.

[0760] Step 5:

[0761] The server analyzes emotional state data transmitted from the terminal and provides summaries and additional explanations tailored to the user's emotions using a generative AI model. The input consists of emotional state data and the generated summary text. The generative AI model processes the data to output summaries and explanations in a format appropriate to the emotions. The output is the adjusted summary or additional explanation text.

[0762] Step 6:

[0763] The terminal displays the generated summary and response to the user. The input is the final generated summary or additional explanatory text. The information is displayed through the user interface. The user can review and understand the displayed content. The output is the information provided to the user visually.

[0764] (Application Example 2)

[0765] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0766] There is a need to efficiently summarize information in ebooks and provide appropriate information according to the user's emotional state. However, conventional systems lack the ability to adequately respond to the confusion and stress that users experience. In particular, there is a need for more specific and flexible means of responding when users feel anxious or confused during payment procedures or purchases.

[0767] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0768] In this invention, the server includes means for receiving book information and converting it into a string format, means for creating a summary using a generative AI based on the converted string, and means for using sensory organs to analyze the user's emotional state. This makes it possible not only to provide a summary according to the time set by the user, but also to provide optimal information based on the user's emotional state.

[0769] "Book information" refers to the content of a book represented as digital data in a format that can be processed electronically.

[0770] "Methods for converting to string format" refers to techniques for converting information from books, which exist in various formats, into string data that is easy for machines to process.

[0771] "Converted string" refers to data that has been converted from book information into a string format, and is the target of processing by the generation AI.

[0772] "Generative AI" is a type of artificial intelligence that models human knowledge and skills, analyzes data, and generates new information and insights.

[0773] "Methods for creating summaries" refer to the process of extracting key elements from a vast amount of original information data and automatically generating a document in a shortened format.

[0774] "User emotional state" refers to the psychological and sensory reactions a user exhibits when using the system, and the system analyzes this to determine appropriate responses.

[0775] "Methods using sensory organs" refer to technologies that use devices such as cameras and sensors to detect a user's facial expressions and voice, and analyze their emotional state.

[0776] The system for implementing this invention consists of a user terminal, a server, and a generative AI model. The user terminal is a device such as a smartphone or smart glasses, equipped with a camera and microphone. When the user selects information from a book on the device, that information is sent to the server.

[0777] The server runs a program that converts book information into a string format. For PDF data, it extracts text information using optical character recognition technology, and for ebook formats such as EPUB, it obtains string data using a dedicated library. The converted strings are fed into a generative AI model, and a summary is created.

[0778] This summary is adjusted according to the time frame set by the user and displayed on the user's device. Furthermore, the device's camera and sensors are used to analyze the user's emotional state from their facial expressions and voice. This emotional data is sent to a server, and the generative AI generates a response that corresponds to the user's emotional state. For example, if the user is confused, the generative AI will provide additional explanations or a different summarizing style.

[0779] As a concrete example, suppose a user using an electronic payment service is trying to purchase a new product using their smartphone, but is confused because entering the promotion code is complicated. In this case, the system analyzes the user's emotional state and uses a generative AI model to provide specific guidance such as, "Having trouble? You can check the promotion codes you can currently enter from the options in the upper right corner of the screen."

[0780] The software used will be TensorFlow for the generative AI model and Flask for the server-side implementation. An example of a prompt would be: "Generate a support message based on the user's emotional state. The user is confused. Provide a simple and concrete solution."

[0781] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0782] Step 1:

[0783] The user's terminal sends the entered book information to the server. This information is represented in various digital formats. The server receives this information and prepares for the next processing step.

[0784] Step 2:

[0785] The server converts the information from received books into a string format. For PDF data, optical character recognition (OCR) technology is used to extract the character information. For EPUB format, a dedicated library is used to obtain the string data. This converted string is then used in the subsequent summarization process.

[0786] Step 3:

[0787] The server inputs the converted string into a generating AI model to generate a summary of the book's content. The generating AI extracts key information from the input text and creates a shortened summary. This summary is then adjusted to a length corresponding to the time frame specified by the user and sent to the terminal.

[0788] Step 4:

[0789] The user's terminal displays the generated summary. The user can enter questions related to the summary as needed. These questions are sent back to the server, initiating the process of generating appropriate responses.

[0790] Step 5:

[0791] The device uses its camera and sensors to capture the user's facial expressions and voice, and analyzes their emotional state. By sending this emotional data to a server, it prepares to generate appropriate feedback based on the user's psychological response.

[0792] Step 6:

[0793] The server receives emotion data and uses generative AI to generate responses tailored to the user's emotional state. For example, if the user is confused, the system adjusts to provide additional explanations or a different summarizing style. The generated feedback is then sent back to the terminal and presented to the user.

[0794] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0795] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0796] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0797] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0798] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0799] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0800] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0801] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0802] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0803] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0804] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0805] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0806] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0807] 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.

[0808] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0809] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0810] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0811] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0812] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0813] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0814] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0815] The following is further disclosed regarding the embodiments described above.

[0816] (Claim 1)

[0817] A means of receiving book data and converting it to text format,

[0818] A method for creating a summary using generative AI based on the converted text,

[0819] A means to adjust the length of the summary according to the time set by the user,

[0820] A means of displaying the summary on the user's device,

[0821] A means of receiving questions related to the summary and generating answers,

[0822] A system that includes this.

[0823] (Claim 2)

[0824] The system according to claim 1, further comprising means for a generating AI to search for relevant information and generate an answer based on a question from a user.

[0825] (Claim 3)

[0826] The system according to claim 1, further comprising means for converting book data in PDF format into text data using optical character recognition technology.

[0827] "Example 1"

[0828] (Claim 1)

[0829] A means of receiving information from a book and converting it into text format,

[0830] A means of creating a summary using AI generated based on the converted text,

[0831] A means to adjust the length of the summary according to the time set by the user,

[0832] A means of displaying the summary on the user's terminal,

[0833] A means by which a terminal receives a query related to the summary and a server generates a detailed response,

[0834] A system that includes this.

[0835] (Claim 2)

[0836] The system according to claim 1, further comprising means for a generated AI to refer to relevant information and generate a response based on an inquiry from a user.

[0837] (Claim 3)

[0838] The system according to claim 1, further comprising means for converting book information in electronic document format into text data using optical character recognition technology.

[0839] "Application Example 1"

[0840] (Claim 1)

[0841] A means of receiving content data and converting it to text format,

[0842] A method for creating a summary using generative AI based on the converted text,

[0843] A means to adjust the length of the summary according to the time set by the user,

[0844] A means of displaying a summary on the user's information terminal,

[0845] A means of receiving questions about the summary and generating answers,

[0846] A means of summarizing the main scenes and storyline of the content selected by the user,

[0847] A means by which a generating AI searches for relevant information based on a user's question and generates a detailed answer,

[0848] A system that includes this.

[0849] (Claim 2)

[0850] The system according to claim 1, comprising means for analyzing converted text based on the script of a film or documentary to generate a summary.

[0851] (Claim 3)

[0852] The system according to claim 1, further comprising means for converting content data in electronic document format into text data using optical character recognition technology.

[0853] "Example 2 of combining an emotion engine"

[0854] (Claim 1)

[0855] A means of receiving data and converting it into an information format,

[0856] A means of creating a summary using a generative model based on the transformed information,

[0857] A means to adjust the length of the summary according to the time set by the user,

[0858] A means for displaying the summary on the user's device,

[0859] A means for acquiring emotional states and generating summaries and explanations corresponding to those emotions,

[0860] A means for receiving questions related to the summary and generating responses,

[0861] A system that includes this.

[0862] (Claim 2)

[0863] The system according to claim 1, further comprising means for a generative model to search for relevant information and generate a response based on a question from a user.

[0864] (Claim 3)

[0865] The system according to claim 1, further comprising means for converting data in PDF format into information using optical character recognition technology.

[0866] "Application example 2 when combining with an emotional engine"

[0867] (Claim 1)

[0868] A means of receiving information from a book and converting it into a string format,

[0869] A method for creating a summary using a generative AI based on the converted string,

[0870] A means to adjust the length of the summary according to the time set by the user,

[0871] A means of displaying the summary on the user's terminal,

[0872] A method of using sensory organs to analyze the emotional state of a user,

[0873] A means of adjusting responses using generative AI based on the user's emotional state,

[0874] A means of receiving questions related to the summary and generating answers,

[0875] A system that includes this.

[0876] (Claim 2)

[0877] The system according to claim 1, further comprising means for a generating AI to search for relevant information and generate an answer based on a question from a user.

[0878] (Claim 3)

[0879] The system according to claim 1, further comprising means for converting book data in PDF format into string data using optical character recognition technology. [Explanation of Symbols]

[0880] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving book data and converting it to text format, A method for creating a summary using generative AI based on the converted text, A means to adjust the length of the summary according to the time set by the user, A means of displaying the summary on the user's device, A means of receiving questions related to the summary and generating answers, A system that includes this.

2. The system according to claim 1, further comprising means for a generating AI to search for relevant information and generate an answer based on a question from a user.

3. The system according to claim 1, further comprising means for converting book data in PDF format into text data using optical character recognition technology.

Images