System

Abstract

A system is provided.SOLUTION: A system comprising: means for obtaining book information; means for presenting a question to a user; means for obtaining a user's answer; means for analyzing the user's answer to generate a next question; means for generating a draft of a reading opinion based on the user's answer; and means for displaying the draft to the user for modification or addition.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In the past, writing book reports was difficult for children to express their impressions well, and it took a lot of time, so many children avoided this homework. Furthermore, it was not realistic for teachers or parents to give individual advice to each child, which meant that children's creativity and thinking skills were not sufficiently developed. [Means for solving the problem]

[0005] To solve the above-mentioned problems, the present invention provides the following means. Specifically, the present invention provides a system including means for acquiring book information, means for presenting questions to a user, means for acquiring the user's answers, means for analyzing the user's answers and generating subsequent questions, means for generating a draft of a book review based on the user's answers, and means for displaying the draft to the user and allowing the user to make corrections or additions. This system allows children to be drawn out in an interview format to gradually elicit their thoughts, allowing them to complete their book review in a natural way. This lowers the barrier to writing a book review and also contributes to training children's imagination and thinking skills.

[0006] "Means for obtaining book information" refers to the function of searching and obtaining detailed information about a book (e.g., author, summary, main characters, etc.) from a book information database based on the title of the book entered by the user.

[0007] "Means for presenting questions to the user" refers to the function of generating the next question based on detailed information about the book and the user's answers and displaying it to the user.

[0008] "Means for obtaining a user's answer" refers to the function of the system receiving the answer entered by the user through the interface.

[0009] "Means for analyzing the user's response and generating the next question" refers to a function that analyzes the user's response using a natural language processing engine or the like, and generates the next question to ask based on the results.

[0010] "Means for generating a draft of a book review based on the user's responses" refers to a function for organizing multiple responses obtained from the user and constructing a consistent draft of a book review.

[0011] "Means for displaying the draft to the user and making corrections or additions" refers to an interface that provides the user with a generated draft of the book review, allowing the user to review it and make corrections or additions as necessary.

[0012] "Book information database" refers to a database that stores information about books (e.g., title, author, summary, main characters, etc.).

[0013] A "natural language processing engine" refers to an algorithm for analyzing and understanding a user's text and the system that executes it. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram illustrating a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0018] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0019] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] ---

[0036] The present invention is a system that helps children write book reports efficiently and effectively. This system acquires information about the book that the user has read, presents questions in an interview format, and generates a draft of the book report based on the user's answers. A specific embodiment of this system is described below.

[0037] First, the user (child) accesses the system using a terminal. The terminal provides an interface for the user to input the title of the book they have finished reading. The book title entered by the user is sent to the server via the terminal.

[0038] The server searches for and retrieves information about the book from a book information database based on the received book title. This book information includes basic information such as the author, summary, and main characters. Next, the server generates initial interview questions based on the book's detailed information. For example, a question such as "Why did you choose this book?" is generated.

[0039] The generated question is sent to the terminal, which displays the question to the user. The user then inputs their thoughts and impressions about the question and submits their answer.

[0040] The device sends the user's answer to the server, which uses a natural language processing engine to analyze the answer and generate the next question based on its content. This process is repeated, digging deeper into the user's answer. For example, more specific questions are generated, such as, "Which part of Harry resonated with you most?"

[0041] Based on the collected responses, the server generates a draft of the book report, which organizes the user's responses into a coherent text. The draft is then sent to the terminal and displayed to the user.

[0042] The user can review the displayed draft and make corrections or additions as needed, and finally the device will give the user the option to save or print the completed book report.

[0043] For example, if a user reads "Harry Potter and the Philosopher's Stone," the first question presented to them is, "Why did you choose this book?" If the user answers, "Because I love the magical world," the next question presented is, "What did you think of Harry?" The user answers, "Harry is very brave, and I was impressed by his adventurous spirit," and then delves deeper with, "Which part of him do you most identify with?" This process elicits the user's thoughts, ultimately resulting in a completed review that reads, "The book I read was 'Harry Potter and the Philosopher's Stone.' I chose this book because I love the magical world. Harry is very brave, and I was impressed by his adventurous spirit. I especially empathized with how he faced challenges together with his friends. Reading this book made me want to have the courage to face challenges myself."

[0044] As described above, the present invention is a system for drawing out the user's thoughts one by one and creating a book review in a natural way. This reduces the burden of writing a book review and also contributes to training children's imagination and thinking skills.

[0045] ---

[0046] The processing flow will be explained below.

[0047] Step 1:

[0048] The terminal provides the user with an interface for inputting the book title.

[0049] Step 2:

[0050] The user inputs the title of the book they have finished reading into the terminal and transmits it.

[0051] Step 3:

[0052] The terminal transmits the entered book title to the server.

[0053] Step 4:

[0054] The server searches for and obtains detailed information about the book from the book information database based on the received book title.

[0055] Step 5:

[0056] The server generates initial interview questions for writing a book review based on the collected book information, such as "Please tell us why you chose this book."

[0057] Step 6:

[0058] The server sends the generated question to the terminal.

[0059] Step 7:

[0060] The terminal displays an initial question to the user.

[0061] Step 8:

[0062] The user answers the questions displayed on the terminal and sends them.

[0063] Step 9:

[0064] The terminal transmits the user's answer to the server.

[0065] Step 10:

[0066] The server analyzes the received user response using a natural language processing engine and considers and generates the next question based on the content.

[0067] Step 11:

[0068] The server sends the newly generated question to the terminal.

[0069] Step 12:

[0070] The terminal displays the new question to the user.

[0071] Step 13:

[0072] The user again answers the questions and transmits the answers via the terminal.

[0073] Step 14:

[0074] The terminal transmits the user's answer to the server.

[0075] Step 15:

[0076] The server repeats this process, accumulating multiple answers, and in the process, analyzes the user's answers sequentially and generates the next question appropriately.

[0077] Step 16:

[0078] The server generates a draft of the book report based on the collected series of user responses. The draft organizes the user responses and forms a coherent sentence.

[0079] Step 17:

[0080] The server transmits the generated draft to the terminal.

[0081] Step 18:

[0082] The terminal displays the generated draft of the book review to the user.

[0083] Step 19:

[0084] The user checks the displayed draft and makes corrections or additions as necessary.

[0085] Step 20:

[0086] The terminal sends any modifications or additions made by the user to the server (if necessary).

[0087] Step 21:

[0088] The server receives corrections and additions and prepares the final draft.

[0089] Step 22:

[0090] The server saves the final book report and exports it in the required format (e.g. PDF).

[0091] Step 23:

[0092] The device displays the completed book report to the user and offers the option to save or print it.

[0093] The above are the specific processing steps and operations of the system.

[0094] Example 1

[0095] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0096] Conventional book review writing support systems often rely solely on user input, requiring users to think up all the content from scratch. This makes it difficult for children, especially, to write book reviews effectively and efficiently. Furthermore, some systems are unable to adequately analyze user responses, resulting in inappropriate generation of the next question. As a result, the content of the book review can be shallow, preventing users from deepening their thoughts.

[0097] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0098] In this invention, the server includes means for providing an interface for users to access using multiple communication devices, means for searching and retrieving book titles obtained from the user via the communication devices from a database on the network, means for generating an initial question based on book information and presenting it to the user, means for obtaining the user's answers via the communication devices, means for analyzing the user's answers and generating a next question, means for presenting the next question to the user via the communication devices, means for generating a draft of a book review based on all of the user's answers, and means for displaying the generated draft to the user via the communication devices and providing an interface for corrections or additions. This enables the user to write a book review efficiently and effectively, and supports the process of deepening one's thinking.

[0099] A "communication device" is a device used by a user for access and has the ability to input and display data through an interface.

[0100] A "network" is a communication system that interconnects multiple information terminals and transmits and receives data.

[0101] A "database" is a system for organizing and storing specific information, and is designed with a structure that allows for efficient searching and retrieval of that information.

[0102] An "initial question" is a question that is first generated based on input from the user, and serves as a starting point for the system to elicit the user's thoughts.

[0103] "User answers" are the content entered by the user in response to the questions presented, and are important data for the system to generate the next question or draft of the feedback.

[0104] A "natural language processing engine" refers to software technology that analyzes text entered by a user and understands its meaning and intent.

[0105] A "draft" is an early version of the final document, before users can make any corrections or additions.

[0106] An "interface" refers to elements such as an operation screen and input form that enable interaction between a user and a system.

[0107] The present invention is a system for efficiently and effectively writing book reviews. The system allows a user to input the title of a book they have read, retrieves detailed information about the book based on the title, presents the user with a series of questions, and ultimately generates a draft of the book review.

[0108] First, a user accesses the system using a communication device. The communication device provides an interface for the user to input the title of the book they have just read. For example, the user inputs "Harry Potter and the Philosopher's Stone." This input title is sent to the server via the communication device.

[0109] The server searches for and retrieves information about the book from a database on the network based on the received book title. This database uses, for example, the Google® Books API. This book information includes the author's name, summary, main characters, etc.

[0110] Next, the server generates initial interview questions based on the acquired book information. The initial questions are general, such as "Why did you choose this book?". A generative AI model is used to create prompt sentences and generate initial questions like these.

[0111] The generated question is presented to the user via a communication device. The user inputs their thoughts and impressions about the question and sends the answer to the server. For example, the user might answer, "Because I like the world of magic."

[0112] The server analyzes the user's answer using a natural language processing engine (e.g., GPT-3 (registered trademark)) and generates the next question based on the content. For example, if the user's answer is "Because I like the magical world," the next question generated will be "What did you think of Harry?" By repeating this process, the server collects a series of answers from the user.

[0113] Based on the collected answers, the server generates a draft of the book report, which is structured as a coherent sentence, such as, "The book I read was 'Harry Potter and the Philosopher's Stone.' I chose this book because I love the magical world. Harry is very brave, and I was impressed by his sense of adventure..."

[0114] The generated draft is displayed to the user via the communication device, where the user can review the displayed draft and make corrections or additions as needed. Finally, the communication device provides the user with the option to save or print the completed book report.

[0115] For example, here's a prompt that might appear if the user reads "Harry Potter and the Philosopher's Stone":

[0116] Prompt statement:

[0117] "Suppose a user has read "Harry Potter and the Philosopher's Stone." Please generate the next question based on the user's answers to the following questions:

[0118] Question 1: Why did you choose this book?

[0119] User Answer: Because I love the magical world.

[0120] Generate the following question: What did you think of Harry?”

[0121] In this way, the present invention gradually elicits the user's thoughts and ultimately supports them in writing a natural book review. This process reduces the burden of writing a book review and also contributes to training the user's imagination and thinking skills.

[0122] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0123] Step 1:

[0124] A user accesses the system using a communication device. The communication device provides an interface for the user to input the title of the book they have finished reading. The user inputs the title of the book they have finished reading, and the communication device sends the title to the server. The input is the book title, and the output is the book title data sent to the server. For example, the title "Harry Potter and the Philosopher's Stone" is input.

[0125] Step 2:

[0126] Based on the received book title, the server searches for and retrieves information about the corresponding book from a database on the network. The database uses the Google Books API, etc. The input is the book title data, and the output is book information such as the author name, summary, and main characters. The server retrieves the author name and summary of "Harry Potter and the Philosopher's Stone."

[0127] Step 3:

[0128] The server generates initial interview questions based on the acquired book information. It uses a generative AI model to generate appropriate questions. The input is the book information, and the output is the initial question. Specifically, the server generates the question, "Please tell us why you chose this book."

[0129] Step 4:

[0130] The generated initial question is sent from the server to the communication device, which then presents the question to the user. The input is the initial question, and the output is the question displayed on the communication device. The communication device displays to the user, "Please tell us why you chose this book."

[0131] Step 5:

[0132] The user inputs their thoughts in response to the questions presented, and the communication device sends the answer to the server. The input is the user's answer, and the output is the answer data sent to the server. For example, the user might answer, "Because I like the world of magic."

[0133] Step 6:

[0134] The server uses a natural language processing engine to analyze the received user response and generate the next question based on the content. The input is the user response data and the output is the next question. The server analyzes a response such as "Because I love the magical world" and then generates the question "What did you think of Harry?"

[0135] Step 7:

[0136] The generated next question is sent from the server to the communication device, which again presents the question to the user. The input is the next question and the output is the next question displayed on the communication device. The communication device displays to the user, "What did you think of Harry?"

[0137] Step 8:

[0138] This process is repeated until all of the user's answers are collected. The answer to each question is sent to the server, which generates the next question, maintaining a sequential interview format. The input is all of the user's answers, and the output is the collected answer data.

[0139] Step 9:

[0140] The server generates a draft of the book report based on all the answers. A generative AI model is used to synthesize the series of answers into a coherent sentence. The input is all the answer data, and the output is a draft of the book report. The server generates a draft with content such as, "The book I read was 'Harry Potter and the Philosopher's Stone.' I chose this book because I love the magical world. Harry is very brave, and I was impressed by his sense of adventure..."

[0141] Step 10:

[0142] The generated draft is sent from the server to the communication device, and the communication device displays the draft to the user. The input is the generated draft, and the output is the draft displayed on the communication device. The user can check the displayed draft and make corrections or additions as necessary.

[0143] Step 11:

[0144] Finally, the communication device provides the option to save or print the completed book review. The input is a revised draft and the output is the final book review that is saved or printed. The user can save the completed book review.

[0145] (Application example 1)

[0146] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0147] The process of writing a book report is a difficult and time-consuming task for many children. Many children find it particularly difficult to organize and summarize their impressions and opinions. For this reason, there is a need for a method that allows them to write book reports efficiently and effectively. Furthermore, there is a need for a method that generates questions based on the content entered by the user and naturally draws out the user's thoughts and feelings. A system that can solve these problems is highly anticipated.

[0148] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0149] In this invention, the server includes means for acquiring book information, means for presenting questions to the user, means for acquiring the user's answers, means for analyzing the user's answers and generating the next question, means for generating a draft of the book report based on the user's answers, means for displaying the draft to the user for correction or addition, means for using a generative AI model to generate the next question based on the user's input, and means for creating a prompt sentence to present the generated question. This makes it possible to create a book report efficiently and naturally, making it easier for children to organize and express their thoughts.

[0150] "Means for obtaining book information" refers to a function that obtains information about books entered by users through a database or API.

[0151] "Means of presenting questions to the user" refers to a function that displays or presents questions on a screen or via voice for the user to answer.

[0152] The "means for acquiring the user's answer" refers to an interface or input device for recording the answer entered by the user and transmitting it to the server.

[0153] The "means for analyzing the user's answer and generating the next question" is a function that uses natural language processing technology to analyze the answer entered by the user and automatically generates the next appropriate question based on that.

[0154] "Means for generating a draft of a book review based on the user's answers" refers to a function that organizes and consolidates the answers provided by the user to create a consistent draft of a book review.

[0155] The "means for displaying the draft to the user and making corrections or additions" is a function that provides an interface for the user to check the generated draft and make any necessary corrections or additions.

[0156] "Means for using a generative AI model to generate the next question based on user input" refers to a function that uses a generative AI model to automatically generate the next question based on the user's input.

[0157] The "means for creating a prompt sentence to present the generated question" is a function for creating an appropriate prompt sentence to display to the user the question generated by the generative AI model.

[0158] This invention is a system for efficiently and effectively creating book reviews. This system acquires information about a book that a user has read, presents questions in an interview format, and generates a draft of the review based on the user's answers. A specific embodiment of this system is described below.

[0159] The overall system configuration mainly includes the following hardware and software:

[0160] User device (smartphone or tablet)

[0161] server

[0162] Book information database (e.g. Google Books API)

[0163] Natural language processing engine (e.g., OpenAI (registered trademark) GPT-3)

[0164] First, users access the system using a terminal, which provides an interface for inputting the title of the book they have finished reading, and also provides a function for scanning ISBN codes, which can automatically obtain book information.

[0165] The book title entered by the user is sent to the server via the terminal. The server searches and retrieves the corresponding book information from the book information database based on the received book title. This book information includes basic information such as the author, summary, and main characters.

[0166] The server then uses the book details to generate initial interview questions, using a generative AI model to present the questions that best fit the user's input, such as a specific question like, "Why did you choose this book?"

[0167] The generated question is sent to the terminal, which displays it to the user. The user answers the question by inputting their thoughts and impressions. Answers can be entered either by voice or text.

[0168] The device sends the user's answer to the server, which uses a natural language processing engine to analyze the answer and generate the next question based on its content. This process is repeated, digging deeper into the user's answer. For example, if the user answers, "Because I like magical worlds," the next question generated might be more specific, such as, "Which part of this book impressed you the most?"

[0169] Based on the collected responses, the server generates a draft of the book report, which organizes the user's responses into a coherent text. The draft is then sent to the terminal and displayed to the user.

[0170] The user can review the displayed draft and make corrections or additions as needed, and finally the device will give the user the option to save or print the completed book report.

[0171] For example, if a user answers "Because I like the world of magic," the next question generated based on that answer is "Which part of this book impressed you the most?" Through this process, the user's thoughts are drawn out one after another, and ultimately the review is completed efficiently and naturally.

[0172] An example of a prompt sentence would be, "Generate the next question based on the user's answer: 'Because I like magical worlds.' Next question:" and would be input to the generative AI model.

[0173] As described above, this system reduces the burden of writing a book review and provides a concrete means for users to easily express themselves.

[0174] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0175] Step 1:

[0176] A user uses a terminal to input the book title or ISBN code, and the terminal receives this input and sends a request to a book information database to obtain detailed information about the book (author, synopsis, main characters, etc.).

[0177] Step 2:

[0178] The device sends the acquired book information to the server, which uses a generative AI model to generate initial interview questions to present to the user based on this book information. For example, a question like, "Please tell us why you chose this book."

[0179] Step 3:

[0180] The generated question is sent to the device and displayed to the user, who then uses voice or text input to enter an answer to the question, which the device then captures and sends to the server.

[0181] Step 4:

[0182] The server receives the user's answer and analyzes it using a natural language processing engine. Based on this analysis, the generative AI model generates the next question. For example, if the user's answer is "Because I like magical worlds," the next question generated would be "Which part of this book impressed you the most?"

[0183] Step 5:

[0184] The next question generated by the server is sent to the device and displayed to the user. The user answers the question again, and the device sends the answer to the server. This process is repeated, digging deeper into the user's answers.

[0185] Step 6:

[0186] The server generates a draft of the book report based on the collected responses from the user. The generated draft logically organizes the user's responses and forms a coherent sentence.

[0187] Step 7:

[0188] The generated draft is sent to the terminal and displayed to the user. The user checks the draft and makes corrections or additions as necessary. The terminal then sends the user's corrections to the server.

[0189] Step 8:

[0190] Finally, the user has the option to save or print the completed book report. The device also provides the ability to save the completed book report in PDF format or send it via email.

[0191] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0192] ---

[0193] This invention is a system that helps children write book reports efficiently and effectively. This system acquires information about the book the user has read, presents questions in an interview format, and generates a draft of the book report based on the user's answers. In addition, by combining it with an emotion engine that analyzes the user's emotions, the system generates questions and writes the book report while taking the user's emotions into consideration.

[0194] First, the user (child) accesses the system using a terminal. The terminal provides an interface for the user to input the title of the book they have finished reading. The book title entered by the user is sent to the server via the terminal.

[0195] The server searches for and retrieves information about the book from a book information database based on the received book title. This book information includes basic information such as the author, summary, and main characters. Next, the server generates initial interview questions based on the book's detailed information. For example, a question such as "Why did you choose this book?" is generated.

[0196] The generated question is sent to the terminal, which displays the question to the user. The user then inputs their thoughts and impressions about the question and submits their answer.

[0197] The device sends the user's answer to the server, which then analyzes the received answer using a natural language processing engine and an emotion engine. The natural language processing engine analyzes the user's text grammatically and semantically, and the emotion engine recognizes the emotional state (e.g., joy, sadness, surprise, etc.) contained in the user's answer.

[0198] Based on the results of this analysis, the server generates the next question. At this time, the analysis results of the emotion engine are also taken into consideration, and a question is presented that corresponds to the user's emotions. For example, if the user answers that they were moved, a question is generated that draws out the details of that emotion. For example, a question such as "Which part of Harry most moved you?" may be generated.

[0199] This process is repeated, digging deeper into the user's answers and taking into account their emotional state. Based on the collected responses, the server generates a draft of the book review. This draft organizes the user's answers and reflects the emotional nuances analyzed by the emotion engine.

[0200] The generated draft is sent to the device and displayed to the user, who can review the displayed draft and make corrections or additions as needed. Finally, the device provides the option to save or print the completed book report.

[0201] For example, if a user reads "Harry Potter and the Philosopher's Stone," the first question presented to them is, "Why did you choose this book?" If the user answers, "Because I love the magical world," the next question generated is, "What did you think of Harry?" If the user answers, "Harry is very brave, and I was moved by his adventurous spirit," the emotion engine recognizes the emotional state of "moved," and generates the next question, "What about him moved you the most?" This completes a detailed review that reflects the user's emotional state.

[0202] As described above, the present invention is a system for drawing out the user's thoughts and feelings in a natural way and writing a book review. This reduces the burden of writing a book review and also contributes to training children's imagination, thinking skills, and emotional expression.

[0203] ---

[0204] The processing flow will be explained below.

[0205] Step 1:

[0206] The terminal provides the user with an interface for inputting the book title.

[0207] Step 2:

[0208] The user inputs the title of the book they have finished reading into the terminal and transmits it.

[0209] Step 3:

[0210] The terminal transmits the entered book title to the server.

[0211] Step 4:

[0212] The server searches for and obtains detailed information about the book from the book information database based on the received book title.

[0213] Step 5:

[0214] The server generates initial interview questions for writing a book review based on the collected book information, such as "Please tell us why you chose this book."

[0215] Step 6:

[0216] The server sends the generated question to the terminal.

[0217] Step 7:

[0218] The terminal displays an initial question to the user.

[0219] Step 8:

[0220] The user answers the questions displayed on the terminal and sends them.

[0221] Step 9:

[0222] The terminal transmits the user's answer to the server.

[0223] Step 10:

[0224] The server analyzes the received user response using a natural language processing engine.

[0225] Step 11:

[0226] The server also uses an emotion engine to recognize the emotional state contained in the user's response.

[0227] Step 12:

[0228] The server generates the next question based on the analysis results of the natural language processing engine and the recognition results of the emotion engine. For example, if the user answers "I was moved," it generates a question according to the emotion, such as "Which scene moved you the most?"

[0229] Step 13:

[0230] The server sends the newly generated question to the terminal.

[0231] Step 14:

[0232] The terminal displays the new question to the user.

[0233] Step 15:

[0234] The user again answers the questions and transmits the answers via the terminal.

[0235] Step 16:

[0236] The terminal transmits the user's answer to the server.

[0237] Step 17:

[0238] The server repeats this process, analyzing each user's answers and generating multiple questions, each of which is analyzed and refined using natural language processing and an emotion engine.

[0239] Step 18:

[0240] The server generates a draft of the book report based on the collected series of user responses. The draft organizes the user responses and reflects the emotional nuances based on the analysis results of the emotion engine.

[0241] Step 19:

[0242] The server transmits the generated draft to the terminal.

[0243] Step 20:

[0244] The terminal displays the generated draft of the book review to the user.

[0245] Step 21:

[0246] The user checks the displayed draft and makes corrections or additions as necessary.

[0247] Step 22:

[0248] The terminal sends any modifications or additions made by the user to the server (if necessary).

[0249] Step 23:

[0250] The server receives corrections and additions and prepares the final draft.

[0251] Step 24:

[0252] The server saves the final book report and exports it in the required format (e.g. PDF).

[0253] Step 25:

[0254] The device displays the completed book report to the user and offers the option to save or print it.

[0255] The above are the specific processing steps and operations of the system that combines the emotion engine.

[0256] Example 2

[0257] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0258] Conventional book review writing support systems are unable to take the user's emotions into account when writing a book review, making it difficult for the user to write a book review that reflects their true feelings. Furthermore, because the questions are uniform, it is not possible to elicit individual impressions from each user, resulting in variations in the quality of the book reviews. This makes writing a book review a heavy burden, especially for users who require advanced support, such as children.

[0259] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0260] In this invention, the server includes means for acquiring book information, means for presenting questions to the user, means for acquiring the user's answers, means for analyzing the user's answers and generating the next question, means for analyzing the user's emotions, means for generating a draft of a book review based on the user's answers, and means for displaying the draft to the user and allowing the user to make corrections or additions. This makes it possible to generate questions and draft reviews that reflect the user's emotions, and to efficiently create interesting reviews that are suitable for each user.

[0261] The "means for obtaining book information" is a function for searching and obtaining information on the corresponding book from the book information database based on the book title entered by the user.

[0262] The "means for presenting questions to the user" is a function for displaying to the user questions generated based on the book information and the user's answers.

[0263] The "means for acquiring the user's answer" is a function that receives the answer entered by the user to the question and sends it to the server.

[0264] The "means for analyzing the user's response and generating the next question" is a function that analyzes the user's response using a natural language processing engine and generates the next question based on the results.

[0265] The "emotion analysis means for analyzing the user's emotions" is a function for recognizing and analyzing the emotional state (for example, joy, sadness, surprise, etc.) contained in the user's response.

[0266] The "means for generating a draft of a book review based on the user's answers" is a function for generating a draft of a book review based on the analyzed answers and emotional state of the user.

[0267] "Means for displaying the draft to the user and making corrections or additions" is a function that displays the generated draft of the book review to the user and provides an interface for the user to make corrections or additions.

[0268] A "book information database" refers to a database that stores basic information about a book, such as its author, summary, and main characters.

[0269] A "natural language processing engine" is an engine (software component) for grammatically and semantically analyzing a user's response.

[0270] This invention is a system for making the creation of book reviews more efficient. This system acquires information about the book the user has read, presents questions in an interview format, and generates a draft of the review based on the user's answers. In addition, by combining it with an emotion analysis engine that analyzes the user's emotions, the system generates questions and creates a review that takes the user's emotions into consideration.

[0271] System configuration

[0272] The main components of the system include the following hardware and software:

[0273] Terminal (user side): A device used by the user to input and confirm data. This terminal can be a PC, tablet, smartphone, etc.

[0274] Server: A central processing unit that manages the processing of the entire system. The server integrates the book information database, natural language processing engine, and sentiment analysis engine, and processes various data according to user input.

[0275] Book information database: Contains basic information such as the book title, author, summary, and main characters.

[0276] Natural language processing engine: An engine for analyzing user responses grammatically and semantically. This engine can use technologies such as GPT-3.

[0277] Sentiment analysis engine: An engine for analyzing the emotional state contained in the user's answers.

[0278] System Operation

[0279] The user (child) uses a terminal to access the system, which incorporates a sentiment analysis engine. The terminal provides an interface for the user to input the title of the book they have finished reading. The book title entered by the user is sent to the server via the terminal.

[0280] Get book information

[0281] The server searches for and retrieves information about the book from the book information database based on the received book title, including basic information such as the author, summary, and main characters.

[0282] Question Generation

[0283] The server generates initial interview questions based on the book information, such as "Please tell us why you chose this book." The generated questions are sent to the terminal and displayed to the user.

[0284] User responses and their analysis

[0285] Users input their thoughts and feelings in response to the displayed questions and send their answers from their devices to the server. The server then analyzes the received answers using a natural language processing engine and a sentiment analysis engine. The natural language processing engine analyzes the user's text grammatically and semantically, and the sentiment analysis engine recognizes the emotional state contained in the user's answer.

[0286] Question generation and emotion consideration

[0287] Based on the analysis results, the server generates the next question. At this time, the results of the emotion analysis are also taken into consideration, and a question is presented that corresponds to the user's emotions. For example, if the user answers "I was moved," the next question generated would be "Which part of Harry impressed you the most?"

[0288] Generate a draft of your review

[0289] The server then digs deeper into the user's answers, collecting them in a way that takes into account their emotional state, and generates a draft of the book review. This draft organizes the user's answers and reflects the emotional nuances resulting from the emotion analysis.

[0290] Review and revise the draft

[0291] The generated draft is sent to the device and displayed to the user, who can review the displayed draft and make corrections or additions as needed. Finally, the device provides the option to save or print the completed book report.

[0292] Specific examples

[0293] When a user reads a "fantasy novel," the first question presented to them is, "Why did you choose this book?" If the user answers, "Because I like adventure," the next question generated is, "What did you think of the main character?" If the user answers, "I was moved by his bravery," the sentiment analysis engine recognizes the emotional state of "moved" and generates the next question, "What was it about his bravery that particularly impressed you?" This results in a detailed book review that reflects the user's emotional state.

[0294] Prompt Sentence Examples

[0295] User Answer: "Because I love adventure."

[0296] Generated question: Based on the answer "Because I love adventure" to the question "Why did you choose this book?", generate the following question taking into account the analysis results of the sentiment analysis engine.

[0297] User Answer: "I was impressed by his bravery."

[0298] Generated question: Based on the answer "I was moved by his bravery" to the question "What did you think of the main character?", generate the following question taking into account the analysis results of the sentiment analysis engine.

[0299] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0300] Step 1:

[0301] A user accesses the system and enters the title of a book.

[0302] Input: Title of the book the user has read

[0303] Specific actions: A user uses a device to access a web page or app on the system. The device interface displays a text box for entering the book title. The user enters the book title and presses the submit button.

[0304] Output: The book title is sent to the server.

[0305] Step 2:

[0306] The server retrieves information from the book information database.

[0307] Input: The book title entered by the user

[0308] Specific operation: The server searches the book information database based on the received book title, issues an SQL query to retrieve the corresponding book information, including the author name, summary, and main characters.

[0309] Output: Book information is retrieved and stored on the server.

[0310] Step 3:

[0311] The server generates the initial question

[0312] Input: Retrieved book information

[0313] Specific operation: The server generates the first interview questions based on the book information. For example, a question such as "Please tell us why you chose this book" is generated. The generated questions are sent to the terminal and displayed to the user.

[0314] Output: The initial question is sent to the terminal and displayed to the user.

[0315] Step 4:

[0316] The user answers the question

[0317] Input: Question sent by the server

[0318] Specific operation: The user inputs their thoughts and impressions in response to the questions displayed on the terminal. Once input is complete, they press the send button.

[0319] Output: The user's answer is sent from the device to the server.

[0320] Step 5:

[0321] The server analyzes the user's answers

[0322] Input: User's answer

[0323] Specific operation: The server passes the received user response to a natural language processing engine for grammatical and semantic analysis, and a sentiment analysis engine recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.) from the response.

[0324] Output: Analysis results (grammatical and semantic analysis results and emotional state) are obtained.

[0325] Step 6:

[0326] The server generates the next question

[0327] Input: Analysis results

[0328] Specific operation: The server generates the next question based on the analysis results. At this time, the results of the sentiment analysis are also taken into consideration. For example, if the user answers "I was moved," a question is generated to elicit more details about that emotion. For example, "Which part of him moved you the most?" The generated question is sent to the terminal and displayed to the user.

[0329] Output: The following question is sent to the terminal and displayed to the user.

[0330] Step 7:

[0331] Repeat steps 4-6

[0332] Input: The user's new answer

[0333] What happens: The user answers a new question, the server analyzes the answer, generates the next question, and the process repeats.

[0334] Output: Answers from multiple users are collected on the server.

[0335] Step 8:

[0336] The server generates a draft of the book report.

[0337] Input: Multiple user responses and sentiment analysis results

[0338] Specific operation: The server integrates all collected user responses and the results of sentiment analysis, and generates a draft book report using natural language processing. This draft organizes the user responses and reflects the emotional nuances.

[0339] Output: The generated draft of the book report is sent to the device.

[0340] Step 9:

[0341] User reviews and modifies draft

[0342] Input: A generated draft of the book report

[0343] Specific operation: The terminal displays the generated draft to the user. The user checks the draft and makes corrections or additions as necessary. After entering the corrections, the user presses the save button to confirm.

[0344] Output: The revised or finalized book report is finally saved.

[0345] Step 10:

[0346] Save and print your book report

[0347] Input: Revised or confirmed book report

[0348] Specific operation: The terminal finally provides the user with the option to save or print the completed review. The user saves or prints the review according to the selection.

[0349] Output: The user receives a saved file or a printed book report.

[0350] (Application example 2)

[0351] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0352] Conventional book review writing systems struggled to generate questions that took the user's emotional state into account, making it impossible to elicit effective feedback or detailed reviews. Furthermore, in factory work environments, it was difficult to efficiently collect and analyze feedback from workers and suggest areas for improvement in the next step. For these reasons, a system that could contribute to improving work efficiency and quality was needed.

[0353] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0354] In this invention, the server includes means for acquiring book information, means for presenting questions to the user, means for acquiring the user's answers, means for analyzing the user's answers and generating the next question, means for generating a draft of a book review based on the user's answers, means for displaying the draft to the user and for corrections or additions, means for collecting work content and impressions input by workers, means for analyzing the input work content and impressions with a natural language processing engine and recognizing the emotional state using an emotion analysis engine, means for generating questions to draw out improvements for the next work based on the work content and emotions, and means for organizing the collected feedback data and creating a report containing the improvements. This makes it possible to collect detailed feedback and present impressions and improvements while taking into consideration the emotional states of the user and workers.

[0355] The "means for acquiring book information" is a means for searching and acquiring information on the corresponding book from a book information database based on the title of the book entered by the user.

[0356] The "means for presenting questions to the user" is an interface that displays questions to assist the user in writing a book review based on the acquired book information.

[0357] The "means for acquiring user answers" refers to a means for collecting and saving answers entered by users in response to questions presented to them.

[0358] The "means for analyzing the user's answers and generating the next question" is a means for analyzing the collected answers using a natural language processing and sentiment analysis engine, and generating the next question based on the analysis results.

[0359] The "means for generating a draft of a book review based on the user's responses" is a means for automatically generating an initial draft of a book review based on the analyzed user's response data.

[0360] The "means for displaying the draft to the user and for making corrections or additions" is an interface for displaying the generated draft of the book review to the user and for the user to make corrections or additions.

[0361] The "means for collecting work details and feedback entered by workers" is an interface for collecting work details and feedback from workers in the factory.

[0362] "Means for analyzing input work details and impressions using a natural language processing engine and recognizing emotional states using an emotion analysis engine" refers to means for analyzing work details and impressions collected from workers using a natural language processing engine and further recognizing their emotional states using an emotion analysis engine.

[0363] The "means for generating questions to draw out improvements to the next task based on the task content and emotions" refers to a means for creating questions to draw out improvements to the next task based on the analyzed data and presenting them to the worker.

[0364] "Means for organizing collected feedback data and creating a report listing areas for improvement" refers to means for systematically organizing collected feedback data and automatically generating a report listing areas for improvement.

[0365] This invention provides a system that allows users to write book reports efficiently and effectively. This system can also collect feedback from factory workers and use it to improve future operations. The system consists of the following main components:

[0366] System Configuration

[0367] 1. Hardware Configuration

[0368] Terminal: A device on which a user writes a book report or writes about their work. The terminal in question can be a tablet or a PC.

[0369] Server: A computer with a database and analytical capabilities that runs a natural language processing engine and a sentiment analysis engine.

[0370] 2. Software Configuration

[0371] Natural language processing engines (e.g. SpaCy)

[0372] Sentiment analysis engine (e.g., IBM Watson® Tone Analyzer)

[0373] Feedback management interface (frontend: React, backend: Node.js)

[0374] Data processing and calculation flow

[0375] 1. Data Acquisition

[0376] The user inputs the book title, work content, and impressions through the terminal and sends them to the server.

[0377] The server receives the data entered by the user and retrieves information about the book from a book information database based on the book title.

[0378] 2. Question generation

[0379] Based on the book information and the initial task, the server generates the initial interview questions. For example, for a book, the server generates an initial question such as "Why did you choose this book?". For the task, the server generates an initial question such as "What were the particular difficulties you had while working?".

[0380] 3. Analysis of user responses

[0381] The terminal presents the generated question to the user and transmits the user's answer to the server.

[0382] The server analyzes the received user responses using a natural language processing engine and a sentiment analysis engine.

[0383] 4. Generate the next question

[0384] Based on the analysis results, the server generates the next question according to the user's emotions and the content of the task. For example, if the user answers "I was moved," it generates a follow-up question such as "Which part moved you?"

[0385] 5. Draft and Report Generation

[0386] The server collects all questions and answers and generates a feedback report for drafting impressions and improving work.

[0387] The generated drafts and reports are sent to the terminal, where the user can make final confirmations and make corrections or additions.

[0388] Examples of concrete examples and prompts

[0389] For example, if a user answers, "I chose this book because I love the magical world," the server uses a natural language processing engine to analyze the text and a sentiment analysis engine to recognize the emotion of "joy."Then, the server generates the next question, "Which of Harry's adventures did you like best?"

[0390] Prompt sentence format example

[0391] "Which part of the task did you find difficult?"

[0392] “What support did you feel you needed to overcome that challenge?”

[0393] In this way, it is possible to collect detailed feedback and provide written impressions and suggestions for work improvement, while taking into consideration the emotional state of the user or worker.

[0394] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0395] Step 1:

[0396] Users access the system through their terminals and input the book title, work content, and impressions. The input data is sent to the server.

[0397] Input: Book title, work content, impressions

[0398] Output: Book title, work content, and impressions data are sent to the server

[0399] Step 2:

[0400] Based on the book title received by the server, information on the relevant book is obtained from the book information database.

[0401] Input: Book title

[0402] Output: Basic information about the book (author, summary, main characters, etc.)

[0403] Step 3:

[0404] The server generates the first question based on the acquired book information or the initial work content.

[0405] Input: Basic information about the book, initial work

[0406] Output: Initial question (e.g., "Why did you choose this book?")

[0407] Step 4:

[0408] The terminal displays the generated question to the user and obtains the user's answer.

[0409] Input: First question

[0410] Output: User's answer (e.g., "Because I love magical worlds")

[0411] Step 5:

[0412] The server analyzes the user's response using a natural language processing engine (e.g., SpaCy) to analyze it grammatically and semantically, and then uses a sentiment analysis engine (e.g., IBM Watson Tone Analyzer) to recognize the emotional state.

[0413] Input: User's answer

[0414] Output: Analysis results after natural language processing, sentiment analysis results (e.g., "joy")

[0415] Step 6:

[0416] Based on the analysis results, the server generates the next question, which is determined taking into account the user's emotional state and the content of their answers.

[0417] Input: Natural language processing results, sentiment analysis results

[0418] Output: Next question (e.g., "What about Harry impressed you most?")

[0419] Step 7:

[0420] The terminal presents the next generated question to the user to obtain a more detailed answer.

[0421] Input: Next question

[0422] Output: User's detailed response (e.g., "I was impressed by his sense of adventure.")

[0423] Step 8:

[0424] The server generates a draft of a book report based on the user's responses. In a factory application, the collected feedback is used to generate a report on work improvement.

[0425] Input: A set of user answers

[0426] Output: Draft book review, work improvement report

[0427] Step 9:

[0428] The server sends the generated drafts and reports to the terminal and displays them to the user, who can then check them and make corrections or additions as necessary.

[0429] Input: Draft of book review, work improvement report

[0430] Output: Drafts and reports displayed to users, and corrections and additions made by users

[0431] The above are the processing steps of the system and their specific operations.

[0432] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0433] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0434] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0435] [Second embodiment]

[0436] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0437] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0438] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0439] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0440] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0441] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0442] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0443] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0444] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0445] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0446] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0447] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0448] ---

[0449] The present invention is a system that helps children write book reports efficiently and effectively. This system acquires information about the book that the user has read, presents questions in an interview format, and generates a draft of the book report based on the user's answers. A specific embodiment of this system is described below.

[0450] First, the user (child) accesses the system using a terminal. The terminal provides an interface for the user to input the title of the book they have finished reading. The book title entered by the user is sent to the server via the terminal.

[0451] The server searches for and retrieves information about the book from a book information database based on the received book title. This book information includes basic information such as the author, summary, and main characters. Next, the server generates initial interview questions based on the book's detailed information. For example, a question such as "Why did you choose this book?" is generated.

[0452] The generated question is sent to the terminal, which displays the question to the user. The user then inputs their thoughts and impressions about the question and submits their answer.

[0453] The device sends the user's answer to the server, which uses a natural language processing engine to analyze the answer and generate the next question based on its content. This process is repeated, digging deeper into the user's answer. For example, more specific questions are generated, such as, "Which part of Harry resonated with you most?"

[0454] Based on the collected responses, the server generates a draft of the book report, which organizes the user's responses into a coherent text. The draft is then sent to the terminal and displayed to the user.

[0455] The user can review the displayed draft and make corrections or additions as needed, and finally the device will give the user the option to save or print the completed book report.

[0456] For example, if a user reads "Harry Potter and the Philosopher's Stone," the first question presented to them is, "Why did you choose this book?" If the user answers, "Because I love the magical world," the next question presented is, "What did you think of Harry?" The user answers, "Harry is very brave, and I was impressed by his adventurous spirit," and then delves deeper with, "Which part of him do you most identify with?" This process elicits the user's thoughts, ultimately resulting in a completed review that reads, "The book I read was 'Harry Potter and the Philosopher's Stone.' I chose this book because I love the magical world. Harry is very brave, and I was impressed by his adventurous spirit. I especially empathized with how he faced challenges together with his friends. Reading this book made me want to have the courage to face challenges myself."

[0457] As described above, the present invention is a system for drawing out the user's thoughts one by one and creating a book review in a natural way. This reduces the burden of writing a book review and also contributes to training children's imagination and thinking skills.

[0458] ---

[0459] The processing flow will be explained below.

[0460] Step 1:

[0461] The terminal provides the user with an interface for inputting the book title.

[0462] Step 2:

[0463] The user inputs the title of the book they have finished reading into the terminal and transmits it.

[0464] Step 3:

[0465] The terminal transmits the entered book title to the server.

[0466] Step 4:

[0467] The server searches for and obtains detailed information about the book from the book information database based on the received book title.

[0468] Step 5:

[0469] The server generates initial interview questions for writing a book review based on the collected book information, such as "Please tell us why you chose this book."

[0470] Step 6:

[0471] The server sends the generated question to the terminal.

[0472] Step 7:

[0473] The terminal displays an initial question to the user.

[0474] Step 8:

[0475] The user answers the questions displayed on the terminal and sends them.

[0476] Step 9:

[0477] The terminal transmits the user's answer to the server.

[0478] Step 10:

[0479] The server analyzes the received user response using a natural language processing engine and considers and generates the next question based on the content.

[0480] Step 11:

[0481] The server sends the newly generated question to the terminal.

[0482] Step 12:

[0483] The terminal displays the new question to the user.

[0484] Step 13:

[0485] The user again answers the questions and transmits the answers via the terminal.

[0486] Step 14:

[0487] The terminal transmits the user's answer to the server.

[0488] Step 15:

[0489] The server repeats this process, accumulating multiple answers, and in the process, analyzes the user's answers sequentially and generates the next question appropriately.

[0490] Step 16:

[0491] The server generates a draft of the book report based on the collected series of user responses. The draft organizes the user responses and forms a coherent sentence.

[0492] Step 17:

[0493] The server transmits the generated draft to the terminal.

[0494] Step 18:

[0495] The terminal displays the generated draft of the book review to the user.

[0496] Step 19:

[0497] The user checks the displayed draft and makes corrections or additions as necessary.

[0498] Step 20:

[0499] The terminal sends any modifications or additions made by the user to the server (if necessary).

[0500] Step 21:

[0501] The server receives corrections and additions and prepares the final draft.

[0502] Step 22:

[0503] The server saves the final book report and exports it in the required format (e.g. PDF).

[0504] Step 23:

[0505] The device displays the completed book report to the user and offers the option to save or print it.

[0506] The above are the specific processing steps and operations of the system.

[0507] Example 1

[0508] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0509] Conventional book review writing support systems often rely solely on user input, requiring users to think up all the content from scratch. This makes it difficult for children, especially, to write book reviews effectively and efficiently. Furthermore, some systems are unable to adequately analyze user responses, resulting in inappropriate generation of the next question. As a result, the content of the book review can be shallow, preventing users from deepening their thoughts.

[0510] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0511] In this invention, the server includes means for providing an interface for users to access using multiple communication devices, means for searching and retrieving book titles obtained from the user via the communication devices from a database on the network, means for generating an initial question based on book information and presenting it to the user, means for obtaining the user's answers via the communication devices, means for analyzing the user's answers and generating a next question, means for presenting the next question to the user via the communication devices, means for generating a draft of a book review based on all of the user's answers, and means for displaying the generated draft to the user via the communication devices and providing an interface for corrections or additions. This enables the user to write a book review efficiently and effectively, and supports the process of deepening one's thinking.

[0512] A "communication device" is a device used by a user for access and has the ability to input and display data through an interface.

[0513] A "network" is a communication system that interconnects multiple information terminals and transmits and receives data.

[0514] A "database" is a system for organizing and storing specific information, and is designed with a structure that allows for efficient searching and retrieval of that information.

[0515] An "initial question" is a question that is first generated based on input from the user, and serves as a starting point for the system to elicit the user's thoughts.

[0516] "User answers" are the content entered by the user in response to the questions presented, and are important data for the system to generate the next question or draft of the feedback.

[0517] A "natural language processing engine" refers to software technology that analyzes text entered by a user and understands its meaning and intent.

[0518] A "draft" is an early version of the final document, before users can make any corrections or additions.

[0519] An "interface" refers to elements such as an operation screen and input form that enable interaction between a user and a system.

[0520] The present invention is a system for efficiently and effectively writing book reviews. The system allows a user to input the title of a book they have read, retrieves detailed information about the book based on the title, presents the user with a series of questions, and ultimately generates a draft of the book review.

[0521] First, a user accesses the system using a communication device. The communication device provides an interface for the user to input the title of the book they have just read. For example, the user inputs "Harry Potter and the Philosopher's Stone." This input title is sent to the server via the communication device.

[0522] The server searches for and retrieves information about the book from a database on the network based on the received book title. This database uses, for example, the Google Books API. This book information includes the author's name, summary, and main characters.

[0523] Next, the server generates initial interview questions based on the acquired book information. The initial questions are general, such as "Why did you choose this book?". A generative AI model is used to create prompt sentences and generate initial questions like these.

[0524] The generated question is presented to the user via a communication device. The user inputs their thoughts and impressions about the question and sends the answer to the server. For example, the user might answer, "Because I like the world of magic."

[0525] The server analyzes the user's answer using a natural language processing engine (e.g., GPT-3) and generates the next question based on the answer. For example, if the user's answer is "Because I like the magical world," the next question generated will be "What did you think of Harry?" By repeating this process, the server collects a series of answers from the user.

[0526] Based on the collected answers, the server generates a draft of the book report, which is structured as a coherent sentence, such as, "The book I read was 'Harry Potter and the Philosopher's Stone.' I chose this book because I love the magical world. Harry is very brave, and I was impressed by his sense of adventure..."

[0527] The generated draft is displayed to the user via the communication device, where the user can review the displayed draft and make corrections or additions as needed. Finally, the communication device provides the user with the option to save or print the completed book report.

[0528] For example, here's a prompt that might appear if the user reads "Harry Potter and the Philosopher's Stone":

[0529] Prompt statement:

[0530] "Suppose a user has read "Harry Potter and the Philosopher's Stone." Please generate the next question based on the user's answers to the following questions:

[0531] Question 1: Why did you choose this book?

[0532] User Answer: Because I love the magical world.

[0533] Generate the following question: What did you think of Harry?”

[0534] In this way, the present invention gradually elicits the user's thoughts and ultimately supports them in writing a natural book review. This process reduces the burden of writing a book review and also contributes to training the user's imagination and thinking skills.

[0535] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0536] Step 1:

[0537] A user accesses the system using a communication device. The communication device provides an interface for the user to input the title of the book they have finished reading. The user inputs the title of the book they have finished reading, and the communication device sends the title to the server. The input is the book title, and the output is the book title data sent to the server. For example, the title "Harry Potter and the Philosopher's Stone" is input.

[0538] Step 2:

[0539] Based on the received book title, the server searches for and retrieves information about the corresponding book from a database on the network. The database uses the Google Books API, etc. The input is the book title data, and the output is book information such as the author name, summary, and main characters. The server retrieves the author name and summary of "Harry Potter and the Philosopher's Stone."

[0540] Step 3:

[0541] The server generates initial interview questions based on the acquired book information. It uses a generative AI model to generate appropriate questions. The input is the book information, and the output is the initial question. Specifically, the server generates the question, "Please tell us why you chose this book."

[0542] Step 4:

[0543] The generated initial question is sent from the server to the communication device, which then presents the question to the user. The input is the initial question, and the output is the question displayed on the communication device. The communication device displays to the user, "Please tell us why you chose this book."

[0544] Step 5:

[0545] The user inputs their thoughts in response to the questions presented, and the communication device sends the answer to the server. The input is the user's answer, and the output is the answer data sent to the server. For example, the user might answer, "Because I like the world of magic."

[0546] Step 6:

[0547] The server uses a natural language processing engine to analyze the received user response and generate the next question based on the content. The input is the user response data and the output is the next question. The server analyzes a response such as "Because I love the magical world" and then generates the question "What did you think of Harry?"

[0548] Step 7:

[0549] The generated next question is sent from the server to the communication device, which again presents the question to the user. The input is the next question and the output is the next question displayed on the communication device. The communication device displays to the user, "What did you think of Harry?"

[0550] Step 8:

[0551] This process is repeated until all of the user's answers are collected. The answer to each question is sent to the server, which generates the next question, maintaining a sequential interview format. The input is all of the user's answers, and the output is the collected answer data.

[0552] Step 9:

[0553] The server generates a draft of the book report based on all the answers. A generative AI model is used to synthesize the series of answers into a coherent sentence. The input is all the answer data, and the output is a draft of the book report. The server generates a draft with content such as, "The book I read was 'Harry Potter and the Philosopher's Stone.' I chose this book because I love the magical world. Harry is very brave, and I was impressed by his sense of adventure..."

[0554] Step 10:

[0555] The generated draft is sent from the server to the communication device, and the communication device displays the draft to the user. The input is the generated draft, and the output is the draft displayed on the communication device. The user can check the displayed draft and make corrections or additions as necessary.

[0556] Step 11:

[0557] Finally, the communication device provides the option to save or print the completed book review. The input is a revised draft and the output is the final book review that is saved or printed. The user can save the completed book review.

[0558] (Application example 1)

[0559] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0560] The process of writing a book report is a difficult and time-consuming task for many children. Many children find it particularly difficult to organize and summarize their impressions and opinions. For this reason, there is a need for a method that allows them to write book reports efficiently and effectively. Furthermore, there is a need for a method that generates questions based on the content entered by the user and naturally draws out the user's thoughts and feelings. A system that can solve these problems is highly anticipated.

[0561] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0562] In this invention, the server includes means for acquiring book information, means for presenting questions to the user, means for acquiring the user's answers, means for analyzing the user's answers and generating the next question, means for generating a draft of the book report based on the user's answers, means for displaying the draft to the user for correction or addition, means for using a generative AI model to generate the next question based on the user's input, and means for creating a prompt sentence to present the generated question. This makes it possible to create a book report efficiently and naturally, making it easier for children to organize and express their thoughts.

[0563] "Means for obtaining book information" refers to a function that obtains information about books entered by users through a database or API.

[0564] "Means of presenting questions to the user" refers to a function that displays or presents questions on a screen or via voice for the user to answer.

[0565] The "means for acquiring the user's answer" refers to an interface or input device for recording the answer entered by the user and transmitting it to the server.

[0566] The "means for analyzing the user's answer and generating the next question" is a function that uses natural language processing technology to analyze the answer entered by the user and automatically generates the next appropriate question based on that.

[0567] "Means for generating a draft of a book review based on the user's answers" refers to a function that organizes and consolidates the answers provided by the user to create a consistent draft of a book review.

[0568] The "means for displaying the draft to the user and making corrections or additions" is a function that provides an interface for the user to check the generated draft and make any necessary corrections or additions.

[0569] "Means for using a generative AI model to generate the next question based on user input" refers to a function that uses a generative AI model to automatically generate the next question based on the user's input.

[0570] The "means for creating a prompt sentence to present the generated question" is a function for creating an appropriate prompt sentence to display to the user the question generated by the generative AI model.

[0571] This invention is a system for efficiently and effectively creating book reviews. This system acquires information about a book that a user has read, presents questions in an interview format, and generates a draft of the review based on the user's answers. A specific embodiment of this system is described below.

[0572] The overall system configuration mainly includes the following hardware and software:

[0573] User device (smartphone or tablet)

[0574] server

[0575] Book information database (e.g. Google Books API)

[0576] Natural language processing engine (e.g. OpenAI GPT-3)

[0577] First, users access the system using a terminal, which provides an interface for inputting the title of the book they have finished reading, and also provides a function for scanning ISBN codes, which can automatically obtain book information.

[0578] The book title entered by the user is sent to the server via the terminal. The server searches and retrieves the corresponding book information from the book information database based on the received book title. This book information includes basic information such as the author, summary, and main characters.

[0579] The server then uses the book details to generate initial interview questions, using a generative AI model to present the questions that best fit the user's input, such as a specific question like, "Why did you choose this book?"

[0580] The generated question is sent to the terminal, which displays it to the user. The user answers the question by inputting their thoughts and impressions. Answers can be entered either by voice or text.

[0581] The device sends the user's answer to the server, which uses a natural language processing engine to analyze the answer and generate the next question based on its content. This process is repeated, digging deeper into the user's answer. For example, if the user answers, "Because I like magical worlds," the next question generated might be more specific, such as, "Which part of this book impressed you the most?"

[0582] Based on the collected responses, the server generates a draft of the book report, which organizes the user's responses into a coherent text. The draft is then sent to the terminal and displayed to the user.

[0583] The user can review the displayed draft and make corrections or additions as needed, and finally the device will give the user the option to save or print the completed book report.

[0584] For example, if a user answers "Because I like the world of magic," the next question generated based on that answer is "Which part of this book impressed you the most?" Through this process, the user's thoughts are drawn out one after another, and ultimately the review is completed efficiently and naturally.

[0585] An example of a prompt sentence would be, "Generate the next question based on the user's answer: 'Because I like magical worlds.' Next question:" and would be input to the generative AI model.

[0586] As described above, this system reduces the burden of writing a book review and provides a concrete means for users to easily express themselves.

[0587] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0588] Step 1:

[0589] A user uses a terminal to input the book title or ISBN code, and the terminal receives this input and sends a request to a book information database to obtain detailed information about the book (author, synopsis, main characters, etc.).

[0590] Step 2:

[0591] The device sends the acquired book information to the server, which uses a generative AI model to generate initial interview questions to present to the user based on this book information. For example, a question like, "Please tell us why you chose this book."

[0592] Step 3:

[0593] The generated question is sent to the device and displayed to the user, who then uses voice or text input to enter an answer to the question, which the device then captures and sends to the server.

[0594] Step 4:

[0595] The server receives the user's answer and analyzes it using a natural language processing engine. Based on this analysis, the generative AI model generates the next question. For example, if the user's answer is "Because I like magical worlds," the next question generated would be "Which part of this book impressed you the most?"

[0596] Step 5:

[0597] The next question generated by the server is sent to the device and displayed to the user. The user answers the question again, and the device sends the answer to the server. This process is repeated, digging deeper into the user's answers.

[0598] Step 6:

[0599] The server generates a draft of the book report based on the collected responses from the user. The generated draft logically organizes the user's responses and forms a coherent sentence.

[0600] Step 7:

[0601] The generated draft is sent to the terminal and displayed to the user. The user checks the draft and makes corrections or additions as necessary. The terminal then sends the user's corrections to the server.

[0602] Step 8:

[0603] Finally, the user has the option to save or print the completed book report. The device also provides the ability to save the completed book report in PDF format or send it via email.

[0604] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0605] ---

[0606] This invention is a system that helps children write book reports efficiently and effectively. This system acquires information about the book the user has read, presents questions in an interview format, and generates a draft of the book report based on the user's answers. In addition, by combining it with an emotion engine that analyzes the user's emotions, the system generates questions and writes the book report while taking the user's emotions into consideration.

[0607] First, the user (child) accesses the system using a terminal. The terminal provides an interface for the user to input the title of the book they have finished reading. The book title entered by the user is sent to the server via the terminal.

[0608] The server searches for and retrieves information about the book from a book information database based on the received book title. This book information includes basic information such as the author, summary, and main characters. Next, the server generates initial interview questions based on the book's detailed information. For example, a question such as "Why did you choose this book?" is generated.

[0609] The generated question is sent to the terminal, which displays the question to the user. The user then inputs their thoughts and impressions about the question and submits their answer.

[0610] The device sends the user's answer to the server, which then analyzes the received answer using a natural language processing engine and an emotion engine. The natural language processing engine analyzes the user's text grammatically and semantically, and the emotion engine recognizes the emotional state (e.g., joy, sadness, surprise, etc.) contained in the user's answer.

[0611] Based on the results of this analysis, the server generates the next question. At this time, the analysis results of the emotion engine are also taken into consideration, and a question is presented that corresponds to the user's emotions. For example, if the user answers that they were moved, a question is generated that draws out the details of that emotion. For example, a question such as "Which part of Harry most moved you?" may be generated.

[0612] This process is repeated, digging deeper into the user's answers and taking into account their emotional state. Based on the collected responses, the server generates a draft of the book review. This draft organizes the user's answers and reflects the emotional nuances analyzed by the emotion engine.

[0613] The generated draft is sent to the device and displayed to the user, who can review the displayed draft and make corrections or additions as needed. Finally, the device provides the option to save or print the completed book report.

[0614] For example, if a user reads "Harry Potter and the Philosopher's Stone," the first question presented to them is, "Why did you choose this book?" If the user answers, "Because I love the magical world," the next question generated is, "What did you think of Harry?" If the user answers, "Harry is very brave, and I was moved by his adventurous spirit," the emotion engine recognizes the emotional state of "moved," and generates the next question, "What about him moved you the most?" This completes a detailed review that reflects the user's emotional state.

[0615] As described above, the present invention is a system for drawing out the user's thoughts and feelings in a natural way and writing a book review. This reduces the burden of writing a book review and also contributes to training children's imagination, thinking skills, and emotional expression.

[0616] ---

[0617] The processing flow will be explained below.

[0618] Step 1:

[0619] The terminal provides the user with an interface for inputting the book title.

[0620] Step 2:

[0621] The user inputs the title of the book they have finished reading into the terminal and transmits it.

[0622] Step 3:

[0623] The terminal transmits the entered book title to the server.

[0624] Step 4:

[0625] The server searches for and obtains detailed information about the book from the book information database based on the received book title.

[0626] Step 5:

[0627] The server generates initial interview questions for writing a book review based on the collected book information, such as "Please tell us why you chose this book."

[0628] Step 6:

[0629] The server sends the generated question to the terminal.

[0630] Step 7:

[0631] The terminal displays an initial question to the user.

[0632] Step 8:

[0633] The user answers the questions displayed on the terminal and sends them.

[0634] Step 9:

[0635] The terminal transmits the user's answer to the server.

[0636] Step 10:

[0637] The server analyzes the received user response using a natural language processing engine.

[0638] Step 11:

[0639] The server also uses an emotion engine to recognize the emotional state contained in the user's response.

[0640] Step 12:

[0641] The server generates the next question based on the analysis results of the natural language processing engine and the recognition results of the emotion engine. For example, if the user answers "I was moved," it generates a question according to the emotion, such as "Which scene moved you the most?"

[0642] Step 13:

[0643] The server sends the newly generated question to the terminal.

[0644] Step 14:

[0645] The terminal displays the new question to the user.

[0646] Step 15:

[0647] The user again answers the questions and transmits the answers via the terminal.

[0648] Step 16:

[0649] The terminal transmits the user's answer to the server.

[0650] Step 17:

[0651] The server repeats this process, analyzing each user's answers and generating multiple questions, each of which is analyzed and refined using natural language processing and an emotion engine.

[0652] Step 18:

[0653] The server generates a draft of the book report based on the collected series of user responses. The draft organizes the user responses and reflects the emotional nuances based on the analysis results of the emotion engine.

[0654] Step 19:

[0655] The server transmits the generated draft to the terminal.

[0656] Step 20:

[0657] The terminal displays the generated draft of the book review to the user.

[0658] Step 21:

[0659] The user checks the displayed draft and makes corrections or additions as necessary.

[0660] Step 22:

[0661] The terminal sends any modifications or additions made by the user to the server (if necessary).

[0662] Step 23:

[0663] The server receives corrections and additions and prepares the final draft.

[0664] Step 24:

[0665] The server saves the final book report and exports it in the required format (e.g. PDF).

[0666] Step 25:

[0667] The device displays the completed book report to the user and offers the option to save or print it.

[0668] The above are the specific processing steps and operations of the system that combines the emotion engine.

[0669] Example 2

[0670] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0671] Conventional book review writing support systems are unable to take the user's emotions into account when writing a book review, making it difficult for the user to write a book review that reflects their true feelings. Furthermore, because the questions are uniform, it is not possible to elicit individual impressions from each user, resulting in variations in the quality of the book reviews. This makes writing a book review a heavy burden, especially for users who require advanced support, such as children.

[0672] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0673] In this invention, the server includes means for acquiring book information, means for presenting questions to the user, means for acquiring the user's answers, means for analyzing the user's answers and generating the next question, means for analyzing the user's emotions, means for generating a draft of a book review based on the user's answers, and means for displaying the draft to the user and allowing the user to make corrections or additions. This makes it possible to generate questions and draft reviews that reflect the user's emotions, and to efficiently create interesting reviews that are suitable for each user.

[0674] The "means for obtaining book information" is a function for searching and obtaining information on the corresponding book from the book information database based on the book title entered by the user.

[0675] The "means for presenting questions to the user" is a function for displaying to the user questions generated based on the book information and the user's answers.

[0676] The "means for acquiring the user's answer" is a function that receives the answer entered by the user to the question and sends it to the server.

[0677] The "means for analyzing the user's response and generating the next question" is a function that analyzes the user's response using a natural language processing engine and generates the next question based on the results.

[0678] The "emotion analysis means for analyzing the user's emotions" is a function for recognizing and analyzing the emotional state (for example, joy, sadness, surprise, etc.) contained in the user's response.

[0679] The "means for generating a draft of a book review based on the user's answers" is a function for generating a draft of a book review based on the analyzed answers and emotional state of the user.

[0680] "Means for displaying the draft to the user and making corrections or additions" is a function that displays the generated draft of the book review to the user and provides an interface for the user to make corrections or additions.

[0681] A "book information database" refers to a database that stores basic information about a book, such as its author, summary, and main characters.

[0682] A "natural language processing engine" is an engine (software component) for grammatically and semantically analyzing a user's response.

[0683] This invention is a system for making the creation of book reviews more efficient. This system acquires information about the book the user has read, presents questions in an interview format, and generates a draft of the review based on the user's answers. In addition, by combining it with an emotion analysis engine that analyzes the user's emotions, the system generates questions and creates a review that takes the user's emotions into consideration.

[0684] System configuration

[0685] The main components of the system include the following hardware and software:

[0686] Terminal (user side): A device used by the user to input and confirm data. This terminal can be a PC, tablet, smartphone, etc.

[0687] Server: A central processing unit that manages the processing of the entire system. The server integrates the book information database, natural language processing engine, and sentiment analysis engine, and processes various data according to user input.

[0688] Book information database: Contains basic information such as the book title, author, summary, and main characters.

[0689] Natural language processing engine: An engine for analyzing user responses grammatically and semantically. This engine can use technologies such as GPT-3.

[0690] Sentiment analysis engine: An engine for analyzing the emotional state contained in the user's answers.

[0691] System Operation

[0692] The user (child) uses a terminal to access the system, which incorporates a sentiment analysis engine. The terminal provides an interface for the user to input the title of the book they have finished reading. The book title entered by the user is sent to the server via the terminal.

[0693] Get book information

[0694] The server searches for and retrieves information about the book from the book information database based on the received book title, including basic information such as the author, summary, and main characters.

[0695] Question Generation

[0696] The server generates initial interview questions based on the book information, such as "Please tell us why you chose this book." The generated questions are sent to the terminal and displayed to the user.

[0697] User responses and their analysis

[0698] Users input their thoughts and feelings in response to the displayed questions and send their answers from their devices to the server. The server then analyzes the received answers using a natural language processing engine and a sentiment analysis engine. The natural language processing engine analyzes the user's text grammatically and semantically, and the sentiment analysis engine recognizes the emotional state contained in the user's answer.

[0699] Question generation and emotion consideration

[0700] Based on the analysis results, the server generates the next question. At this time, the results of the emotion analysis are also taken into consideration, and a question is presented that corresponds to the user's emotions. For example, if the user answers "I was moved," the next question generated would be "Which part of Harry impressed you the most?"

[0701] Generate a draft of your review

[0702] The server then digs deeper into the user's answers, collecting them in a way that takes into account their emotional state, and generates a draft of the book review. This draft organizes the user's answers and reflects the emotional nuances resulting from the emotion analysis.

[0703] Review and revise the draft

[0704] The generated draft is sent to the device and displayed to the user, who can review the displayed draft and make corrections or additions as needed. Finally, the device provides the option to save or print the completed book report.

[0705] Specific examples

[0706] When a user reads a "fantasy novel," the first question presented to them is, "Why did you choose this book?" If the user answers, "Because I like adventure," the next question generated is, "What did you think of the main character?" If the user answers, "I was moved by his bravery," the sentiment analysis engine recognizes the emotional state of "moved" and generates the next question, "What was it about his bravery that particularly impressed you?" This results in a detailed book review that reflects the user's emotional state.

[0707] Prompt Sentence Examples

[0708] User Answer: "Because I love adventure."

[0709] Generated question: Based on the answer "Because I love adventure" to the question "Why did you choose this book?", generate the following question taking into account the analysis results of the sentiment analysis engine.

[0710] User Answer: "I was impressed by his bravery."

[0711] Generated question: Based on the answer "I was moved by his bravery" to the question "What did you think of the main character?", generate the following question taking into account the analysis results of the sentiment analysis engine.

[0712] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0713] Step 1:

[0714] A user accesses the system and enters the title of a book.

[0715] Input: Title of the book the user has read

[0716] Specific actions: A user uses a device to access a web page or app on the system. The device interface displays a text box for entering the book title. The user enters the book title and presses the submit button.

[0717] Output: The book title is sent to the server.

[0718] Step 2:

[0719] The server retrieves information from the book information database.

[0720] Input: The book title entered by the user

[0721] Specific operation: The server searches the book information database based on the received book title, issues an SQL query to retrieve the corresponding book information, including the author name, summary, and main characters.

[0722] Output: Book information is retrieved and stored on the server.

[0723] Step 3:

[0724] The server generates the initial question

[0725] Input: Retrieved book information

[0726] Specific operation: The server generates the first interview questions based on the book information. For example, a question such as "Please tell us why you chose this book" is generated. The generated questions are sent to the terminal and displayed to the user.

[0727] Output: The initial question is sent to the terminal and displayed to the user.

[0728] Step 4:

[0729] The user answers the question

[0730] Input: Question sent by the server

[0731] Specific operation: The user inputs their thoughts and impressions in response to the questions displayed on the terminal. Once input is complete, they press the send button.

[0732] Output: The user's answer is sent from the device to the server.

[0733] Step 5:

[0734] The server analyzes the user's answers

[0735] Input: User's answer

[0736] Specific operation: The server passes the received user response to a natural language processing engine for grammatical and semantic analysis, and a sentiment analysis engine recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.) from the response.

[0737] Output: Analysis results (grammatical and semantic analysis results and emotional state) are obtained.

[0738] Step 6:

[0739] The server generates the next question

[0740] Input: Analysis results

[0741] Specific operation: The server generates the next question based on the analysis results. At this time, the results of the sentiment analysis are also taken into consideration. For example, if the user answers "I was moved," a question is generated to elicit more details about that emotion. For example, "Which part of him moved you the most?" The generated question is sent to the terminal and displayed to the user.

[0742] Output: The following question is sent to the terminal and displayed to the user.

[0743] Step 7:

[0744] Repeat steps 4-6

[0745] Input: The user's new answer

[0746] What happens: The user answers a new question, the server analyzes the answer, generates the next question, and the process repeats.

[0747] Output: Answers from multiple users are collected on the server.

[0748] Step 8:

[0749] The server generates a draft of the book report.

[0750] Input: Multiple user responses and sentiment analysis results

[0751] Specific operation: The server integrates all collected user responses and the results of sentiment analysis, and generates a draft book report using natural language processing. This draft organizes the user responses and reflects the emotional nuances.

[0752] Output: The generated draft of the book report is sent to the device.

[0753] Step 9:

[0754] User reviews and modifies draft

[0755] Input: A generated draft of the book report

[0756] Specific operation: The terminal displays the generated draft to the user. The user checks the draft and makes corrections or additions as necessary. After entering the corrections, the user presses the save button to confirm.

[0757] Output: The revised or finalized book report is finally saved.

[0758] Step 10:

[0759] Save and print your book report

[0760] Input: Revised or confirmed book report

[0761] Specific operation: The terminal finally provides the user with the option to save or print the completed review. The user saves or prints the review according to the selection.

[0762] Output: The user receives a saved file or a printed book report.

[0763] (Application example 2)

[0764] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0765] Conventional book review writing systems struggled to generate questions that took the user's emotional state into account, making it impossible to elicit effective feedback or detailed reviews. Furthermore, in factory work environments, it was difficult to efficiently collect and analyze feedback from workers and suggest areas for improvement in the next step. For these reasons, a system that could contribute to improving work efficiency and quality was needed.

[0766] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0767] In this invention, the server includes means for acquiring book information, means for presenting questions to the user, means for acquiring the user's answers, means for analyzing the user's answers and generating the next question, means for generating a draft of a book review based on the user's answers, means for displaying the draft to the user and for corrections or additions, means for collecting work content and impressions input by workers, means for analyzing the input work content and impressions with a natural language processing engine and recognizing the emotional state using an emotion analysis engine, means for generating questions to draw out improvements for the next work based on the work content and emotions, and means for organizing the collected feedback data and creating a report containing the improvements. This makes it possible to collect detailed feedback and present impressions and improvements while taking into consideration the emotional states of the user and workers.

[0768] The "means for acquiring book information" is a means for searching and acquiring information on the corresponding book from a book information database based on the title of the book entered by the user.

[0769] The "means for presenting questions to the user" is an interface that displays questions to assist the user in writing a book review based on the acquired book information.

[0770] The "means for acquiring user answers" refers to a means for collecting and saving answers entered by users in response to questions presented to them.

[0771] The "means for analyzing the user's answers and generating the next question" is a means for analyzing the collected answers using a natural language processing and sentiment analysis engine, and generating the next question based on the analysis results.

[0772] The "means for generating a draft of a book review based on the user's responses" is a means for automatically generating an initial draft of a book review based on the analyzed user's response data.

[0773] The "means for displaying the draft to the user and for making corrections or additions" is an interface for displaying the generated draft of the book review to the user and for the user to make corrections or additions.

[0774] The "means for collecting work details and feedback entered by workers" is an interface for collecting work details and feedback from workers in the factory.

[0775] "Means for analyzing input work details and impressions using a natural language processing engine and recognizing emotional states using an emotion analysis engine" refers to means for analyzing work details and impressions collected from workers using a natural language processing engine and further recognizing their emotional states using an emotion analysis engine.

[0776] The "means for generating questions to draw out improvements to the next task based on the task content and emotions" refers to a means for creating questions to draw out improvements to the next task based on the analyzed data and presenting them to the worker.

[0777] "Means for organizing collected feedback data and creating a report listing areas for improvement" refers to means for systematically organizing collected feedback data and automatically generating a report listing areas for improvement.

[0778] This invention provides a system that allows users to write book reports efficiently and effectively. This system can also collect feedback from factory workers and use it to improve future operations. The system consists of the following main components:

[0779] System Configuration

[0780] 1. Hardware Configuration

[0781] Terminal: A device on which a user writes a book report or writes about their work. The terminal in question can be a tablet or a PC.

[0782] Server: A computer with a database and analytical capabilities that runs a natural language processing engine and a sentiment analysis engine.

[0783] 2. Software Configuration

[0784] Natural language processing engines (e.g. SpaCy)

[0785] Sentiment analysis engine (e.g. IBM Watson Tone Analyzer)

[0786] Feedback management interface (frontend: React, backend: Node.js)

[0787] Data processing and calculation flow

[0788] 1. Data Acquisition

[0789] The user inputs the book title, work content, and impressions through the terminal and sends them to the server.

[0790] The server receives the data entered by the user and retrieves information about the book from a book information database based on the book title.

[0791] 2. Question generation

[0792] Based on the book information and the initial task, the server generates the initial interview questions. For example, for a book, the server generates an initial question such as "Why did you choose this book?". For the task, the server generates an initial question such as "What were the particular difficulties you had while working?".

[0793] 3. Analysis of user responses

[0794] The terminal presents the generated question to the user and transmits the user's answer to the server.

[0795] The server analyzes the received user responses using a natural language processing engine and a sentiment analysis engine.

[0796] 4. Generate the next question

[0797] Based on the analysis results, the server generates the next question according to the user's emotions and the content of the task. For example, if the user answers "I was moved," it generates a follow-up question such as "Which part moved you?"

[0798] 5. Draft and Report Generation

[0799] The server collects all questions and answers and generates a feedback report for drafting impressions and improving work.

[0800] The generated drafts and reports are sent to the terminal, where the user can make final confirmations and make corrections or additions.

[0801] Examples of concrete examples and prompts

[0802] For example, if a user answers, "I chose this book because I love the magical world," the server uses a natural language processing engine to analyze the text and a sentiment analysis engine to recognize the emotion of "joy."Then, the server generates the next question, "Which of Harry's adventures did you like best?"

[0803] Prompt sentence format example

[0804] "Which part of the task did you find difficult?"

[0805] “What support did you feel you needed to overcome that challenge?”

[0806] In this way, it is possible to collect detailed feedback and provide written impressions and suggestions for work improvement, while taking into consideration the emotional state of the user or worker.

[0807] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0808] Step 1:

[0809] Users access the system through their terminals and input the book title, work content, and impressions. The input data is sent to the server.

[0810] Input: Book title, work content, impressions

[0811] Output: Book title, work content, and impressions data are sent to the server

[0812] Step 2:

[0813] Based on the book title received by the server, information on the relevant book is obtained from the book information database.

[0814] Input: Book title

[0815] Output: Basic information about the book (author, summary, main characters, etc.)

[0816] Step 3:

[0817] The server generates the first question based on the acquired book information or the initial work content.

[0818] Input: Basic information about the book, initial work

[0819] Output: Initial question (e.g., "Why did you choose this book?")

[0820] Step 4:

[0821] The terminal displays the generated question to the user and obtains the user's answer.

[0822] Input: First question

[0823] Output: User's answer (e.g., "Because I love magical worlds")

[0824] Step 5:

[0825] The server analyzes the user's response using a natural language processing engine (e.g., SpaCy) to analyze it grammatically and semantically, and then uses a sentiment analysis engine (e.g., IBM Watson Tone Analyzer) to recognize the emotional state.

[0826] Input: User's answer

[0827] Output: Analysis results after natural language processing, sentiment analysis results (e.g., "joy")

[0828] Step 6:

[0829] Based on the analysis results, the server generates the next question, which is determined taking into account the user's emotional state and the content of their answers.

[0830] Input: Natural language processing results, sentiment analysis results

[0831] Output: Next question (e.g., "What about Harry impressed you most?")

[0832] Step 7:

[0833] The terminal presents the next generated question to the user to obtain a more detailed answer.

[0834] Input: Next question

[0835] Output: User's detailed response (e.g., "I was impressed by his sense of adventure.")

[0836] Step 8:

[0837] The server generates a draft of a book report based on the user's responses. In a factory application, the collected feedback is used to generate a report on work improvement.

[0838] Input: A set of user answers

[0839] Output: Draft book review, work improvement report

[0840] Step 9:

[0841] The server sends the generated drafts and reports to the terminal and displays them to the user, who can then check them and make corrections or additions as necessary.

[0842] Input: Draft of book review, work improvement report

[0843] Output: Drafts and reports displayed to users, and corrections and additions made by users

[0844] The above are the processing steps of the system and their specific operations.

[0845] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0846] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0847] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0848] [Third embodiment]

[0849] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0850] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0851] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0852] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0853] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0854] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0855] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0856] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0857] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0858] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0859] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0860] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0861] ---

[0862] The present invention is a system that helps children write book reports efficiently and effectively. This system acquires information about the book that the user has read, presents questions in an interview format, and generates a draft of the book report based on the user's answers. A specific embodiment of this system is described below.

[0863] First, the user (child) accesses the system using a terminal. The terminal provides an interface for the user to input the title of the book they have finished reading. The book title entered by the user is sent to the server via the terminal.

[0864] The server searches for and retrieves information about the book from a book information database based on the received book title. This book information includes basic information such as the author, summary, and main characters. Next, the server generates initial interview questions based on the book's detailed information. For example, a question such as "Why did you choose this book?" is generated.

[0865] The generated question is sent to the terminal, which displays the question to the user. The user then inputs their thoughts and impressions about the question and submits their answer.

[0866] The device sends the user's answer to the server, which uses a natural language processing engine to analyze the answer and generate the next question based on its content. This process is repeated, digging deeper into the user's answer. For example, more specific questions are generated, such as, "Which part of Harry resonated with you most?"

[0867] Based on the collected responses, the server generates a draft of the book report, which organizes the user's responses into a coherent text. The draft is then sent to the terminal and displayed to the user.

[0868] The user can review the displayed draft and make corrections or additions as needed, and finally the device will give the user the option to save or print the completed book report.

[0869] For example, if a user reads "Harry Potter and the Philosopher's Stone," the first question presented to them is, "Why did you choose this book?" If the user answers, "Because I love the magical world," the next question presented is, "What did you think of Harry?" The user answers, "Harry is very brave, and I was impressed by his adventurous spirit," and then delves deeper with, "Which part of him do you most identify with?" This process elicits the user's thoughts, ultimately resulting in a completed review that reads, "The book I read was 'Harry Potter and the Philosopher's Stone.' I chose this book because I love the magical world. Harry is very brave, and I was impressed by his adventurous spirit. I especially empathized with how he faced challenges together with his friends. Reading this book made me want to have the courage to face challenges myself."

[0870] As described above, the present invention is a system for drawing out the user's thoughts one by one and creating a book review in a natural way. This reduces the burden of writing a book review and also contributes to training children's imagination and thinking skills.

[0871] ---

[0872] The processing flow will be explained below.

[0873] Step 1:

[0874] The terminal provides the user with an interface for inputting the book title.

[0875] Step 2:

[0876] The user inputs the title of the book they have finished reading into the terminal and transmits it.

[0877] Step 3:

[0878] The terminal transmits the entered book title to the server.

[0879] Step 4:

[0880] The server searches for and obtains detailed information about the book from the book information database based on the received book title.

[0881] Step 5:

[0882] The server generates initial interview questions for writing a book review based on the collected book information, such as "Please tell us why you chose this book."

[0883] Step 6:

[0884] The server sends the generated question to the terminal.

[0885] Step 7:

[0886] The terminal displays an initial question to the user.

[0887] Step 8:

[0888] The user answers the questions displayed on the terminal and sends them.

[0889] Step 9:

[0890] The terminal transmits the user's answer to the server.

[0891] Step 10:

[0892] The server analyzes the received user response using a natural language processing engine and considers and generates the next question based on the content.

[0893] Step 11:

[0894] The server sends the newly generated question to the terminal.

[0895] Step 12:

[0896] The terminal displays the new question to the user.

[0897] Step 13:

[0898] The user again answers the questions and transmits the answers via the terminal.

[0899] Step 14:

[0900] The terminal transmits the user's answer to the server.

[0901] Step 15:

[0902] The server repeats this process, accumulating multiple answers, and in the process, analyzes the user's answers sequentially and generates the next question appropriately.

[0903] Step 16:

[0904] The server generates a draft of the book report based on the collected series of user responses. The draft organizes the user responses and forms a coherent sentence.

[0905] Step 17:

[0906] The server transmits the generated draft to the terminal.

[0907] Step 18:

[0908] The terminal displays the generated draft of the book review to the user.

[0909] Step 19:

[0910] The user checks the displayed draft and makes corrections or additions as necessary.

[0911] Step 20:

[0912] The terminal sends any modifications or additions made by the user to the server (if necessary).

[0913] Step 21:

[0914] The server receives corrections and additions and prepares the final draft.

[0915] Step 22:

[0916] The server saves the final book report and exports it in the required format (e.g. PDF).

[0917] Step 23:

[0918] The device displays the completed book report to the user and offers the option to save or print it.

[0919] The above are the specific processing steps and operations of the system.

[0920] Example 1

[0921] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0922] Conventional book review writing support systems often rely solely on user input, requiring users to think up all the content from scratch. This makes it difficult for children, especially, to write book reviews effectively and efficiently. Furthermore, some systems are unable to adequately analyze user responses, resulting in inappropriate generation of the next question. As a result, the content of the book review can be shallow, preventing users from deepening their thoughts.

[0923] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0924] In this invention, the server includes means for providing an interface for users to access using multiple communication devices, means for searching and retrieving book titles obtained from the user via the communication devices from a database on the network, means for generating an initial question based on book information and presenting it to the user, means for obtaining the user's answers via the communication devices, means for analyzing the user's answers and generating a next question, means for presenting the next question to the user via the communication devices, means for generating a draft of a book review based on all of the user's answers, and means for displaying the generated draft to the user via the communication devices and providing an interface for corrections or additions. This enables the user to write a book review efficiently and effectively, and supports the process of deepening one's thinking.

[0925] A "communication device" is a device used by a user for access and has the ability to input and display data through an interface.

[0926] A "network" is a communication system that interconnects multiple information terminals and transmits and receives data.

[0927] A "database" is a system for organizing and storing specific information, and is designed with a structure that allows for efficient searching and retrieval of that information.

[0928] An "initial question" is a question that is first generated based on input from the user, and serves as a starting point for the system to elicit the user's thoughts.

[0929] "User answers" are the content entered by the user in response to the questions presented, and are important data for the system to generate the next question or draft of the feedback.

[0930] A "natural language processing engine" refers to software technology that analyzes text entered by a user and understands its meaning and intent.

[0931] A "draft" is an early version of the final document, before users can make any corrections or additions.

[0932] An "interface" refers to elements such as an operation screen and input form that enable interaction between a user and a system.

[0933] The present invention is a system for efficiently and effectively writing book reviews. The system allows a user to input the title of a book they have read, retrieves detailed information about the book based on the title, presents the user with a series of questions, and ultimately generates a draft of the book review.

[0934] First, a user accesses the system using a communication device. The communication device provides an interface for the user to input the title of the book they have just read. For example, the user inputs "Harry Potter and the Philosopher's Stone." This input title is sent to the server via the communication device.

[0935] The server searches for and retrieves information about the book from a database on the network based on the received book title. This database uses, for example, the Google Books API. This book information includes the author's name, summary, and main characters.

[0936] Next, the server generates initial interview questions based on the acquired book information. The initial questions are general, such as "Why did you choose this book?". A generative AI model is used to create prompt sentences and generate initial questions like these.

[0937] The generated question is presented to the user via a communication device. The user inputs their thoughts and impressions about the question and sends the answer to the server. For example, the user might answer, "Because I like the world of magic."

[0938] The server analyzes the user's answer using a natural language processing engine (e.g., GPT-3) and generates the next question based on the answer. For example, if the user's answer is "Because I like the magical world," the next question generated will be "What did you think of Harry?" By repeating this process, the server collects a series of answers from the user.

[0939] Based on the collected answers, the server generates a draft of the book report, which is structured as a coherent sentence, such as, "The book I read was 'Harry Potter and the Philosopher's Stone.' I chose this book because I love the magical world. Harry is very brave, and I was impressed by his sense of adventure..."

[0940] The generated draft is displayed to the user via the communication device, where the user can review the displayed draft and make corrections or additions as needed. Finally, the communication device provides the user with the option to save or print the completed book report.

[0941] For example, here's a prompt that might appear if the user reads "Harry Potter and the Philosopher's Stone":

[0942] Prompt statement:

[0943] "Suppose a user has read "Harry Potter and the Philosopher's Stone." Please generate the next question based on the user's answers to the following questions:

[0944] Question 1: Why did you choose this book?

[0945] User Answer: Because I love the magical world.

[0946] Generate the following question: What did you think of Harry?”

[0947] In this way, the present invention gradually elicits the user's thoughts and ultimately supports them in writing a natural book review. This process reduces the burden of writing a book review and also contributes to training the user's imagination and thinking skills.

[0948] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0949] Step 1:

[0950] A user accesses the system using a communication device. The communication device provides an interface for the user to input the title of the book they have finished reading. The user inputs the title of the book they have finished reading, and the communication device sends the title to the server. The input is the book title, and the output is the book title data sent to the server. For example, the title "Harry Potter and the Philosopher's Stone" is input.

[0951] Step 2:

[0952] Based on the received book title, the server searches for and retrieves information about the corresponding book from a database on the network. The database uses the Google Books API, etc. The input is the book title data, and the output is book information such as the author name, summary, and main characters. The server retrieves the author name and summary of "Harry Potter and the Philosopher's Stone."

[0953] Step 3:

[0954] The server generates initial interview questions based on the acquired book information. It uses a generative AI model to generate appropriate questions. The input is the book information, and the output is the initial question. Specifically, the server generates the question, "Please tell us why you chose this book."

[0955] Step 4:

[0956] The generated initial question is sent from the server to the communication device, which then presents the question to the user. The input is the initial question, and the output is the question displayed on the communication device. The communication device displays to the user, "Please tell us why you chose this book."

[0957] Step 5:

[0958] The user inputs their thoughts in response to the questions presented, and the communication device sends the answer to the server. The input is the user's answer, and the output is the answer data sent to the server. For example, the user might answer, "Because I like the world of magic."

[0959] Step 6:

[0960] The server uses a natural language processing engine to analyze the received user response and generate the next question based on the content. The input is the user response data and the output is the next question. The server analyzes a response such as "Because I love the magical world" and then generates the question "What did you think of Harry?"

[0961] Step 7:

[0962] The generated next question is sent from the server to the communication device, which again presents the question to the user. The input is the next question and the output is the next question displayed on the communication device. The communication device displays to the user, "What did you think of Harry?"

[0963] Step 8:

[0964] This process is repeated until all of the user's answers are collected. The answer to each question is sent to the server, which generates the next question, maintaining a sequential interview format. The input is all of the user's answers, and the output is the collected answer data.

[0965] Step 9:

[0966] The server generates a draft of the book report based on all the answers. A generative AI model is used to synthesize the series of answers into a coherent sentence. The input is all the answer data, and the output is a draft of the book report. The server generates a draft with content such as, "The book I read was 'Harry Potter and the Philosopher's Stone.' I chose this book because I love the magical world. Harry is very brave, and I was impressed by his sense of adventure..."

[0967] Step 10:

[0968] The generated draft is sent from the server to the communication device, and the communication device displays the draft to the user. The input is the generated draft, and the output is the draft displayed on the communication device. The user can check the displayed draft and make corrections or additions as necessary.

[0969] Step 11:

[0970] Finally, the communication device provides the option to save or print the completed book review. The input is a revised draft and the output is the final book review that is saved or printed. The user can save the completed book review.

[0971] (Application example 1)

[0972] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0973] The process of writing a book report is a difficult and time-consuming task for many children. Many children find it particularly difficult to organize and summarize their impressions and opinions. For this reason, there is a need for a method that allows them to write book reports efficiently and effectively. Furthermore, there is a need for a method that generates questions based on the content entered by the user and naturally draws out the user's thoughts and feelings. A system that can solve these problems is highly anticipated.

[0974] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0975] In this invention, the server includes means for acquiring book information, means for presenting questions to the user, means for acquiring the user's answers, means for analyzing the user's answers and generating the next question, means for generating a draft of the book report based on the user's answers, means for displaying the draft to the user for correction or addition, means for using a generative AI model to generate the next question based on the user's input, and means for creating a prompt sentence to present the generated question. This makes it possible to create a book report efficiently and naturally, making it easier for children to organize and express their thoughts.

[0976] "Means for obtaining book information" refers to a function that obtains information about books entered by users through a database or API.

[0977] "Means of presenting questions to the user" refers to a function that displays or presents questions on a screen or via voice for the user to answer.

[0978] The "means for acquiring the user's answer" refers to an interface or input device for recording the answer entered by the user and transmitting it to the server.

[0979] The "means for analyzing the user's answer and generating the next question" is a function that uses natural language processing technology to analyze the answer entered by the user and automatically generates the next appropriate question based on that.

[0980] "Means for generating a draft of a book review based on the user's answers" refers to a function that organizes and consolidates the answers provided by the user to create a consistent draft of a book review.

[0981] The "means for displaying the draft to the user and making corrections or additions" is a function that provides an interface for the user to check the generated draft and make any necessary corrections or additions.

[0982] "Means for using a generative AI model to generate the next question based on user input" refers to a function that uses a generative AI model to automatically generate the next question based on the user's input.

[0983] The "means for creating a prompt sentence to present the generated question" is a function for creating an appropriate prompt sentence to display to the user the question generated by the generative AI model.

[0984] This invention is a system for efficiently and effectively creating book reviews. This system acquires information about a book that a user has read, presents questions in an interview format, and generates a draft of the review based on the user's answers. A specific embodiment of this system is described below.

[0985] The overall system configuration mainly includes the following hardware and software:

[0986] User device (smartphone or tablet)

[0987] server

[0988] Book information database (e.g. Google Books API)

[0989] Natural language processing engine (e.g. OpenAI GPT-3)

[0990] First, users access the system using a terminal, which provides an interface for inputting the title of the book they have finished reading, and also provides a function for scanning ISBN codes, which can automatically obtain book information.

[0991] The book title entered by the user is sent to the server via the terminal. The server searches and retrieves the corresponding book information from the book information database based on the received book title. This book information includes basic information such as the author, summary, and main characters.

[0992] The server then uses the book details to generate initial interview questions, using a generative AI model to present the questions that best fit the user's input, such as a specific question like, "Why did you choose this book?"

[0993] The generated question is sent to the terminal, which displays it to the user. The user answers the question by inputting their thoughts and impressions. Answers can be entered either by voice or text.

[0994] The device sends the user's answer to the server, which uses a natural language processing engine to analyze the answer and generate the next question based on its content. This process is repeated, digging deeper into the user's answer. For example, if the user answers, "Because I like magical worlds," the next question generated might be more specific, such as, "Which part of this book impressed you the most?"

[0995] Based on the collected responses, the server generates a draft of the book report, which organizes the user's responses into a coherent text. The draft is then sent to the terminal and displayed to the user.

[0996] The user can review the displayed draft and make corrections or additions as needed, and finally the device will give the user the option to save or print the completed book report.

[0997] For example, if a user answers "Because I like the world of magic," the next question generated based on that answer is "Which part of this book impressed you the most?" Through this process, the user's thoughts are drawn out one after another, and ultimately the review is completed efficiently and naturally.

[0998] An example of a prompt sentence would be, "Generate the next question based on the user's answer: 'Because I like magical worlds.' Next question:" and would be input to the generative AI model.

[0999] As described above, this system reduces the burden of writing a book review and provides a concrete means for users to easily express themselves.

[1000] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1001] Step 1:

[1002] A user uses a terminal to input the book title or ISBN code, and the terminal receives this input and sends a request to a book information database to obtain detailed information about the book (author, synopsis, main characters, etc.).

[1003] Step 2:

[1004] The device sends the acquired book information to the server, which uses a generative AI model to generate initial interview questions to present to the user based on this book information. For example, a question like, "Please tell us why you chose this book."

[1005] Step 3:

[1006] The generated question is sent to the device and displayed to the user, who then uses voice or text input to enter an answer to the question, which the device then captures and sends to the server.

[1007] Step 4:

[1008] The server receives the user's answer and analyzes it using a natural language processing engine. Based on this analysis, the generative AI model generates the next question. For example, if the user's answer is "Because I like magical worlds," the next question generated would be "Which part of this book impressed you the most?"

[1009] Step 5:

[1010] The next question generated by the server is sent to the device and displayed to the user. The user answers the question again, and the device sends the answer to the server. This process is repeated, digging deeper into the user's answers.

[1011] Step 6:

[1012] The server generates a draft of the book report based on the collected responses from the user. The generated draft logically organizes the user's responses and forms a coherent sentence.

[1013] Step 7:

[1014] The generated draft is sent to the terminal and displayed to the user. The user checks the draft and makes corrections or additions as necessary. The terminal then sends the user's corrections to the server.

[1015] Step 8:

[1016] Finally, the user has the option to save or print the completed book report. The device also provides the ability to save the completed book report in PDF format or send it via email.

[1017] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1018] ---

[1019] This invention is a system that helps children write book reports efficiently and effectively. This system acquires information about the book the user has read, presents questions in an interview format, and generates a draft of the book report based on the user's answers. In addition, by combining it with an emotion engine that analyzes the user's emotions, the system generates questions and writes the book report while taking the user's emotions into consideration.

[1020] First, the user (child) accesses the system using a terminal. The terminal provides an interface for the user to input the title of the book they have finished reading. The book title entered by the user is sent to the server via the terminal.

[1021] The server searches for and retrieves information about the book from a book information database based on the received book title. This book information includes basic information such as the author, summary, and main characters. Next, the server generates initial interview questions based on the book's detailed information. For example, a question such as "Why did you choose this book?" is generated.

[1022] The generated question is sent to the terminal, which displays the question to the user. The user then inputs their thoughts and impressions about the question and submits their answer.

[1023] The device sends the user's answer to the server, which then analyzes the received answer using a natural language processing engine and an emotion engine. The natural language processing engine analyzes the user's text grammatically and semantically, and the emotion engine recognizes the emotional state (e.g., joy, sadness, surprise, etc.) contained in the user's answer.

[1024] Based on the results of this analysis, the server generates the next question. At this time, the analysis results of the emotion engine are also taken into consideration, and a question is presented that corresponds to the user's emotions. For example, if the user answers that they were moved, a question is generated that draws out the details of that emotion. For example, a question such as "Which part of Harry most moved you?" may be generated.

[1025] This process is repeated, digging deeper into the user's answers and taking into account their emotional state. Based on the collected responses, the server generates a draft of the book review. This draft organizes the user's answers and reflects the emotional nuances analyzed by the emotion engine.

[1026] The generated draft is sent to the device and displayed to the user, who can review the displayed draft and make corrections or additions as needed. Finally, the device provides the option to save or print the completed book report.

[1027] For example, if a user reads "Harry Potter and the Philosopher's Stone," the first question presented to them is, "Why did you choose this book?" If the user answers, "Because I love the magical world," the next question generated is, "What did you think of Harry?" If the user answers, "Harry is very brave, and I was moved by his adventurous spirit," the emotion engine recognizes the emotional state of "moved," and generates the next question, "What about him moved you the most?" This completes a detailed review that reflects the user's emotional state.

[1028] As described above, the present invention is a system for drawing out the user's thoughts and feelings in a natural way and writing a book review. This reduces the burden of writing a book review and also contributes to training children's imagination, thinking skills, and emotional expression.

[1029] ---

[1030] The processing flow will be explained below.

[1031] Step 1:

[1032] The terminal provides the user with an interface for inputting the book title.

[1033] Step 2:

[1034] The user inputs the title of the book they have finished reading into the terminal and transmits it.

[1035] Step 3:

[1036] The terminal transmits the entered book title to the server.

[1037] Step 4:

[1038] The server searches for and obtains detailed information about the book from the book information database based on the received book title.

[1039] Step 5:

[1040] The server generates initial interview questions for writing a book review based on the collected book information, such as "Please tell us why you chose this book."

[1041] Step 6:

[1042] The server sends the generated question to the terminal.

[1043] Step 7:

[1044] The terminal displays an initial question to the user.

[1045] Step 8:

[1046] The user answers the questions displayed on the terminal and sends them.

[1047] Step 9:

[1048] The terminal transmits the user's answer to the server.

[1049] Step 10:

[1050] The server analyzes the received user response using a natural language processing engine.

[1051] Step 11:

[1052] The server also uses an emotion engine to recognize the emotional state contained in the user's response.

[1053] Step 12:

[1054] The server generates the next question based on the analysis results of the natural language processing engine and the recognition results of the emotion engine. For example, if the user answers "I was moved," it generates a question according to the emotion, such as "Which scene moved you the most?"

[1055] Step 13:

[1056] The server sends the newly generated question to the terminal.

[1057] Step 14:

[1058] The terminal displays the new question to the user.

[1059] Step 15:

[1060] The user again answers the questions and transmits the answers via the terminal.

[1061] Step 16:

[1062] The terminal transmits the user's answer to the server.

[1063] Step 17:

[1064] The server repeats this process, analyzing each user's answers and generating multiple questions, each of which is analyzed and refined using natural language processing and an emotion engine.

[1065] Step 18:

[1066] The server generates a draft of the book report based on the collected series of user responses. The draft organizes the user responses and reflects the emotional nuances based on the analysis results of the emotion engine.

[1067] Step 19:

[1068] The server transmits the generated draft to the terminal.

[1069] Step 20:

[1070] The terminal displays the generated draft of the book review to the user.

[1071] Step 21:

[1072] The user checks the displayed draft and makes corrections or additions as necessary.

[1073] Step 22:

[1074] The terminal sends any modifications or additions made by the user to the server (if necessary).

[1075] Step 23:

[1076] The server receives corrections and additions and prepares the final draft.

[1077] Step 24:

[1078] The server saves the final book report and exports it in the required format (e.g. PDF).

[1079] Step 25:

[1080] The device displays the completed book report to the user and offers the option to save or print it.

[1081] The above are the specific processing steps and operations of the system that combines the emotion engine.

[1082] Example 2

[1083] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1084] Conventional book review writing support systems are unable to take the user's emotions into account when writing a book review, making it difficult for the user to write a book review that reflects their true feelings. Furthermore, because the questions are uniform, it is not possible to elicit individual impressions from each user, resulting in variations in the quality of the book reviews. This makes writing a book review a heavy burden, especially for users who require advanced support, such as children.

[1085] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1086] In this invention, the server includes means for acquiring book information, means for presenting questions to the user, means for acquiring the user's answers, means for analyzing the user's answers and generating the next question, means for analyzing the user's emotions, means for generating a draft of a book review based on the user's answers, and means for displaying the draft to the user and allowing the user to make corrections or additions. This makes it possible to generate questions and draft reviews that reflect the user's emotions, and to efficiently create interesting reviews that are suitable for each user.

[1087] The "means for obtaining book information" is a function for searching and obtaining information on the corresponding book from the book information database based on the book title entered by the user.

[1088] The "means for presenting questions to the user" is a function for displaying to the user questions generated based on the book information and the user's answers.

[1089] The "means for acquiring the user's answer" is a function that receives the answer entered by the user to the question and sends it to the server.

[1090] The "means for analyzing the user's response and generating the next question" is a function that analyzes the user's response using a natural language processing engine and generates the next question based on the results.

[1091] The "emotion analysis means for analyzing the user's emotions" is a function for recognizing and analyzing the emotional state (for example, joy, sadness, surprise, etc.) contained in the user's response.

[1092] The "means for generating a draft of a book review based on the user's answers" is a function for generating a draft of a book review based on the analyzed answers and emotional state of the user.

[1093] "Means for displaying the draft to the user and making corrections or additions" is a function that displays the generated draft of the book review to the user and provides an interface for the user to make corrections or additions.

[1094] A "book information database" refers to a database that stores basic information about a book, such as its author, summary, and main characters.

[1095] A "natural language processing engine" is an engine (software component) for grammatically and semantically analyzing a user's response.

[1096] This invention is a system for making the creation of book reviews more efficient. This system acquires information about the book the user has read, presents questions in an interview format, and generates a draft of the review based on the user's answers. In addition, by combining it with an emotion analysis engine that analyzes the user's emotions, the system generates questions and creates a review that takes the user's emotions into consideration.

[1097] System configuration

[1098] The main components of the system include the following hardware and software:

[1099] Terminal (user side): A device used by the user to input and confirm data. This terminal can be a PC, tablet, smartphone, etc.

[1100] Server: A central processing unit that manages the processing of the entire system. The server integrates the book information database, natural language processing engine, and sentiment analysis engine, and processes various data according to user input.

[1101] Book information database: Contains basic information such as the book title, author, summary, and main characters.

[1102] Natural language processing engine: An engine for analyzing user responses grammatically and semantically. This engine can use technologies such as GPT-3.

[1103] Sentiment analysis engine: An engine for analyzing the emotional state contained in the user's answers.

[1104] System Operation

[1105] The user (child) uses a terminal to access the system, which incorporates a sentiment analysis engine. The terminal provides an interface for the user to input the title of the book they have finished reading. The book title entered by the user is sent to the server via the terminal.

[1106] Get book information

[1107] The server searches for and retrieves information about the book from the book information database based on the received book title, including basic information such as the author, summary, and main characters.

[1108] Question Generation

[1109] The server generates initial interview questions based on the book information, such as "Please tell us why you chose this book." The generated questions are sent to the terminal and displayed to the user.

[1110] User responses and their analysis

[1111] Users input their thoughts and feelings in response to the displayed questions and send their answers from their devices to the server. The server then analyzes the received answers using a natural language processing engine and a sentiment analysis engine. The natural language processing engine analyzes the user's text grammatically and semantically, and the sentiment analysis engine recognizes the emotional state contained in the user's answer.

[1112] Question generation and emotion consideration

[1113] Based on the analysis results, the server generates the next question. At this time, the results of the emotion analysis are also taken into consideration, and a question is presented that corresponds to the user's emotions. For example, if the user answers "I was moved," the next question generated would be "Which part of Harry impressed you the most?"

[1114] Generate a draft of your review

[1115] The server then digs deeper into the user's answers, collecting them in a way that takes into account their emotional state, and generates a draft of the book review. This draft organizes the user's answers and reflects the emotional nuances resulting from the emotion analysis.

[1116] Review and revise the draft

[1117] The generated draft is sent to the device and displayed to the user, who can review the displayed draft and make corrections or additions as needed. Finally, the device provides the option to save or print the completed book report.

[1118] Specific examples

[1119] When a user reads a "fantasy novel," the first question presented to them is, "Why did you choose this book?" If the user answers, "Because I like adventure," the next question generated is, "What did you think of the main character?" If the user answers, "I was moved by his bravery," the sentiment analysis engine recognizes the emotional state of "moved" and generates the next question, "What was it about his bravery that particularly impressed you?" This results in a detailed book review that reflects the user's emotional state.

[1120] Prompt Sentence Examples

[1121] User Answer: "Because I love adventure."

[1122] Generated question: Based on the answer "Because I love adventure" to the question "Why did you choose this book?", generate the following question taking into account the analysis results of the sentiment analysis engine.

[1123] User Answer: "I was impressed by his bravery."

[1124] Generated question: Based on the answer "I was moved by his bravery" to the question "What did you think of the main character?", generate the following question taking into account the analysis results of the sentiment analysis engine.

[1125] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1126] Step 1:

[1127] A user accesses the system and enters the title of a book.

[1128] Input: Title of the book the user has read

[1129] Specific actions: A user uses a device to access a web page or app on the system. The device interface displays a text box for entering the book title. The user enters the book title and presses the submit button.

[1130] Output: The book title is sent to the server.

[1131] Step 2:

[1132] The server retrieves information from the book information database.

[1133] Input: The book title entered by the user

[1134] Specific operation: The server searches the book information database based on the received book title, issues an SQL query to retrieve the corresponding book information, including the author name, summary, and main characters.

[1135] Output: Book information is retrieved and stored on the server.

[1136] Step 3:

[1137] The server generates the initial question

[1138] Input: Retrieved book information

[1139] Specific operation: The server generates the first interview questions based on the book information. For example, a question such as "Please tell us why you chose this book" is generated. The generated questions are sent to the terminal and displayed to the user.

[1140] Output: The initial question is sent to the terminal and displayed to the user.

[1141] Step 4:

[1142] The user answers the question

[1143] Input: Question sent by the server

[1144] Specific operation: The user inputs their thoughts and impressions in response to the questions displayed on the terminal. Once input is complete, they press the send button.

[1145] Output: The user's answer is sent from the device to the server.

[1146] Step 5:

[1147] The server analyzes the user's answers

[1148] Input: User's answer

[1149] Specific operation: The server passes the received user response to a natural language processing engine for grammatical and semantic analysis, and a sentiment analysis engine recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.) from the response.

[1150] Output: Analysis results (grammatical and semantic analysis results and emotional state) are obtained.

[1151] Step 6:

[1152] The server generates the next question

[1153] Input: Analysis results

[1154] Specific operation: The server generates the next question based on the analysis results. At this time, the results of the sentiment analysis are also taken into consideration. For example, if the user answers "I was moved," a question is generated to elicit more details about that emotion. For example, "Which part of him moved you the most?" The generated question is sent to the terminal and displayed to the user.

[1155] Output: The following question is sent to the terminal and displayed to the user.

[1156] Step 7:

[1157] Repeat steps 4-6

[1158] Input: The user's new answer

[1159] What happens: The user answers a new question, the server analyzes the answer, generates the next question, and the process repeats.

[1160] Output: Answers from multiple users are collected on the server.

[1161] Step 8:

[1162] The server generates a draft of the book report.

[1163] Input: Multiple user responses and sentiment analysis results

[1164] Specific operation: The server integrates all collected user responses and the results of sentiment analysis, and generates a draft book report using natural language processing. This draft organizes the user responses and reflects the emotional nuances.

[1165] Output: The generated draft of the book report is sent to the device.

[1166] Step 9:

[1167] User reviews and modifies draft

[1168] Input: A generated draft of the book report

[1169] Specific operation: The terminal displays the generated draft to the user. The user checks the draft and makes corrections or additions as necessary. After entering the corrections, the user presses the save button to confirm.

[1170] Output: The revised or finalized book report is finally saved.

[1171] Step 10:

[1172] Save and print your book report

[1173] Input: Revised or confirmed book report

[1174] Specific operation: The terminal finally provides the user with the option to save or print the completed review. The user saves or prints the review according to the selection.

[1175] Output: The user receives a saved file or a printed book report.

[1176] (Application example 2)

[1177] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1178] Conventional book review writing systems struggled to generate questions that took the user's emotional state into account, making it impossible to elicit effective feedback or detailed reviews. Furthermore, in factory work environments, it was difficult to efficiently collect and analyze feedback from workers and suggest areas for improvement in the next step. For these reasons, a system that could contribute to improving work efficiency and quality was needed.

[1179] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1180] In this invention, the server includes means for acquiring book information, means for presenting questions to the user, means for acquiring the user's answers, means for analyzing the user's answers and generating the next question, means for generating a draft of a book review based on the user's answers, means for displaying the draft to the user and for corrections or additions, means for collecting work content and impressions input by workers, means for analyzing the input work content and impressions with a natural language processing engine and recognizing the emotional state using an emotion analysis engine, means for generating questions to draw out improvements for the next work based on the work content and emotions, and means for organizing the collected feedback data and creating a report containing the improvements. This makes it possible to collect detailed feedback and present impressions and improvements while taking into consideration the emotional states of the user and workers.

[1181] The "means for acquiring book information" is a means for searching and acquiring information on the corresponding book from a book information database based on the title of the book entered by the user.

[1182] The "means for presenting questions to the user" is an interface that displays questions to assist the user in writing a book review based on the acquired book information.

[1183] The "means for acquiring user answers" refers to a means for collecting and saving answers entered by users in response to questions presented to them.

[1184] The "means for analyzing the user's answers and generating the next question" is a means for analyzing the collected answers using a natural language processing and sentiment analysis engine, and generating the next question based on the analysis results.

[1185] The "means for generating a draft of a book review based on the user's responses" is a means for automatically generating an initial draft of a book review based on the analyzed user's response data.

[1186] The "means for displaying the draft to the user and for making corrections or additions" is an interface for displaying the generated draft of the book review to the user and for the user to make corrections or additions.

[1187] The "means for collecting work details and feedback entered by workers" is an interface for collecting work details and feedback from workers in the factory.

[1188] "Means for analyzing input work details and impressions using a natural language processing engine and recognizing emotional states using an emotion analysis engine" refers to means for analyzing work details and impressions collected from workers using a natural language processing engine and further recognizing their emotional states using an emotion analysis engine.

[1189] The "means for generating questions to draw out improvements to the next task based on the task content and emotions" refers to a means for creating questions to draw out improvements to the next task based on the analyzed data and presenting them to the worker.

[1190] "Means for organizing collected feedback data and creating a report listing areas for improvement" refers to means for systematically organizing collected feedback data and automatically generating a report listing areas for improvement.

[1191] This invention provides a system that allows users to write book reports efficiently and effectively. This system can also collect feedback from factory workers and use it to improve future operations. The system consists of the following main components:

[1192] System Configuration

[1193] 1. Hardware Configuration

[1194] Terminal: A device on which a user writes a book report or writes about their work. The terminal in question can be a tablet or a PC.

[1195] Server: A computer with a database and analytical capabilities that runs a natural language processing engine and a sentiment analysis engine.

[1196] 2. Software Configuration

[1197] Natural language processing engines (e.g. SpaCy)

[1198] Sentiment analysis engine (e.g. IBM Watson Tone Analyzer)

[1199] Feedback management interface (frontend: React, backend: Node.js)

[1200] Data processing and calculation flow

[1201] 1. Data Acquisition

[1202] The user inputs the book title, work content, and impressions through the terminal and sends them to the server.

[1203] The server receives the data entered by the user and retrieves information about the book from a book information database based on the book title.

[1204] 2. Question generation

[1205] Based on the book information and the initial task, the server generates the initial interview questions. For example, for a book, the server generates an initial question such as "Why did you choose this book?". For the task, the server generates an initial question such as "What were the particular difficulties you had while working?".

[1206] 3. Analysis of user responses

[1207] The terminal presents the generated question to the user and transmits the user's answer to the server.

[1208] The server analyzes the received user responses using a natural language processing engine and a sentiment analysis engine.

[1209] 4. Generate the next question

[1210] Based on the analysis results, the server generates the next question according to the user's emotions and the content of the task. For example, if the user answers "I was moved," it generates a follow-up question such as "Which part moved you?"

[1211] 5. Draft and Report Generation

[1212] The server collects all questions and answers and generates a feedback report for drafting impressions and improving work.

[1213] The generated drafts and reports are sent to the terminal, where the user can make final confirmations and make corrections or additions.

[1214] Examples of concrete examples and prompts

[1215] For example, if a user answers, "I chose this book because I love the magical world," the server uses a natural language processing engine to analyze the text and a sentiment analysis engine to recognize the emotion of "joy."Then, the server generates the next question, "Which of Harry's adventures did you like best?"

[1216] Prompt sentence format example

[1217] "Which part of the task did you find difficult?"

[1218] “What support did you feel you needed to overcome that challenge?”

[1219] In this way, it is possible to collect detailed feedback and provide written impressions and suggestions for work improvement, while taking into consideration the emotional state of the user or worker.

[1220] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1221] Step 1:

[1222] Users access the system through their terminals and input the book title, work content, and impressions. The input data is sent to the server.

[1223] Input: Book title, work content, impressions

[1224] Output: Book title, work content, and impressions data are sent to the server

[1225] Step 2:

[1226] Based on the book title received by the server, information on the relevant book is obtained from the book information database.

[1227] Input: Book title

[1228] Output: Basic information about the book (author, summary, main characters, etc.)

[1229] Step 3:

[1230] The server generates the first question based on the acquired book information or the initial work content.

[1231] Input: Basic information about the book, initial work

[1232] Output: Initial question (e.g., "Why did you choose this book?")

[1233] Step 4:

[1234] The terminal displays the generated question to the user and obtains the user's answer.

[1235] Input: First question

[1236] Output: User's answer (e.g., "Because I love magical worlds")

[1237] Step 5:

[1238] The server analyzes the user's response using a natural language processing engine (e.g., SpaCy) to analyze it grammatically and semantically, and then uses a sentiment analysis engine (e.g., IBM Watson Tone Analyzer) to recognize the emotional state.

[1239] Input: User's answer

[1240] Output: Analysis results after natural language processing, sentiment analysis results (e.g., "joy")

[1241] Step 6:

[1242] Based on the analysis results, the server generates the next question, which is determined taking into account the user's emotional state and the content of their answers.

[1243] Input: Natural language processing results, sentiment analysis results

[1244] Output: Next question (e.g., "What about Harry impressed you most?")

[1245] Step 7:

[1246] The terminal presents the next generated question to the user to obtain a more detailed answer.

[1247] Input: Next question

[1248] Output: User's detailed response (e.g., "I was impressed by his sense of adventure.")

[1249] Step 8:

[1250] The server generates a draft of a book report based on the user's responses. In a factory application, the collected feedback is used to generate a report on work improvement.

[1251] Input: A set of user answers

[1252] Output: Draft book review, work improvement report

[1253] Step 9:

[1254] The server sends the generated drafts and reports to the terminal and displays them to the user, who can then check them and make corrections or additions as necessary.

[1255] Input: Draft of book review, work improvement report

[1256] Output: Drafts and reports displayed to users, and corrections and additions made by users

[1257] The above are the processing steps of the system and their specific operations.

[1258] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1259] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1260] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1261] [Fourth embodiment]

[1262] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1263] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1264] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1265] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1266] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1267] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1268] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1269] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1270] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1271] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1272] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1273] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1274] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1275] ---

[1276] The present invention is a system that helps children write book reports efficiently and effectively. This system acquires information about the book that the user has read, presents questions in an interview format, and generates a draft of the book report based on the user's answers. A specific embodiment of this system is described below.

[1277] First, the user (child) accesses the system using a terminal. The terminal provides an interface for the user to input the title of the book they have finished reading. The book title entered by the user is sent to the server via the terminal.

[1278] The server searches for and retrieves information about the book from a book information database based on the received book title. This book information includes basic information such as the author, summary, and main characters. Next, the server generates initial interview questions based on the book's detailed information. For example, a question such as "Why did you choose this book?" is generated.

[1279] The generated question is sent to the terminal, which displays the question to the user. The user then inputs their thoughts and impressions about the question and submits their answer.

[1280] The device sends the user's answer to the server, which uses a natural language processing engine to analyze the answer and generate the next question based on its content. This process is repeated, digging deeper into the user's answer. For example, more specific questions are generated, such as, "Which part of Harry resonated with you most?"

[1281] Based on the collected responses, the server generates a draft of the book report, which organizes the user's responses into a coherent text. The draft is then sent to the terminal and displayed to the user.

[1282] The user can review the displayed draft and make corrections or additions as needed, and finally the device will give the user the option to save or print the completed book report.

[1283] For example, if a user reads "Harry Potter and the Philosopher's Stone," the first question presented to them is, "Why did you choose this book?" If the user answers, "Because I love the magical world," the next question presented is, "What did you think of Harry?" The user answers, "Harry is very brave, and I was impressed by his adventurous spirit," and then delves deeper with, "Which part of him do you most identify with?" This process elicits the user's thoughts, ultimately resulting in a completed review that reads, "The book I read was 'Harry Potter and the Philosopher's Stone.' I chose this book because I love the magical world. Harry is very brave, and I was impressed by his adventurous spirit. I especially empathized with how he faced challenges together with his friends. Reading this book made me want to have the courage to face challenges myself."

[1284] As described above, the present invention is a system for drawing out the user's thoughts one by one and creating a book review in a natural way. This reduces the burden of writing a book review and also contributes to training children's imagination and thinking skills.

[1285] ---

[1286] The processing flow will be explained below.

[1287] Step 1:

[1288] The terminal provides the user with an interface for inputting the book title.

[1289] Step 2:

[1290] The user inputs the title of the book they have finished reading into the terminal and transmits it.

[1291] Step 3:

[1292] The terminal transmits the entered book title to the server.

[1293] Step 4:

[1294] The server searches for and obtains detailed information about the book from the book information database based on the received book title.

[1295] Step 5:

[1296] The server generates initial interview questions for writing a book review based on the collected book information, such as "Please tell us why you chose this book."

[1297] Step 6:

[1298] The server sends the generated question to the terminal.

[1299] Step 7:

[1300] The terminal displays an initial question to the user.

[1301] Step 8:

[1302] The user answers the questions displayed on the terminal and sends them.

[1303] Step 9:

[1304] The terminal transmits the user's answer to the server.

[1305] Step 10:

[1306] The server analyzes the received user response using a natural language processing engine and considers and generates the next question based on the content.

[1307] Step 11:

[1308] The server sends the newly generated question to the terminal.

[1309] Step 12:

[1310] The terminal displays the new question to the user.

[1311] Step 13:

[1312] The user again answers the questions and transmits the answers via the terminal.

[1313] Step 14:

[1314] The terminal transmits the user's answer to the server.

[1315] Step 15:

[1316] The server repeats this process, accumulating multiple answers, and in the process, analyzes the user's answers sequentially and generates the next question appropriately.

[1317] Step 16:

[1318] The server generates a draft of the book report based on the collected series of user responses. The draft organizes the user responses and forms a coherent sentence.

[1319] Step 17:

[1320] The server transmits the generated draft to the terminal.

[1321] Step 18:

[1322] The terminal displays the generated draft of the book review to the user.

[1323] Step 19:

[1324] The user checks the displayed draft and makes corrections or additions as necessary.

[1325] Step 20:

[1326] The terminal sends any modifications or additions made by the user to the server (if necessary).

[1327] Step 21:

[1328] The server receives corrections and additions and prepares the final draft.

[1329] Step 22:

[1330] The server saves the final book report and exports it in the required format (e.g. PDF).

[1331] Step 23:

[1332] The device displays the completed book report to the user and offers the option to save or print it.

[1333] The above are the specific processing steps and operations of the system.

[1334] Example 1

[1335] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1336] Conventional book review writing support systems often rely solely on user input, requiring users to think up all the content from scratch. This makes it difficult for children, especially, to write book reviews effectively and efficiently. Furthermore, some systems are unable to adequately analyze user responses, resulting in inappropriate generation of the next question. As a result, the content of the book review can be shallow, preventing users from deepening their thoughts.

[1337] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1338] In this invention, the server includes means for providing an interface for users to access using multiple communication devices, means for searching and retrieving book titles obtained from the user via the communication devices from a database on the network, means for generating an initial question based on book information and presenting it to the user, means for obtaining the user's answers via the communication devices, means for analyzing the user's answers and generating a next question, means for presenting the next question to the user via the communication devices, means for generating a draft of a book review based on all of the user's answers, and means for displaying the generated draft to the user via the communication devices and providing an interface for corrections or additions. This enables the user to write a book review efficiently and effectively, and supports the process of deepening one's thinking.

[1339] A "communication device" is a device used by a user for access and has the ability to input and display data through an interface.

[1340] A "network" is a communication system that interconnects multiple information terminals and transmits and receives data.

[1341] A "database" is a system for organizing and storing specific information, and is designed with a structure that allows for efficient searching and retrieval of that information.

[1342] An "initial question" is a question that is first generated based on input from the user, and serves as a starting point for the system to elicit the user's thoughts.

[1343] "User answers" are the content entered by the user in response to the questions presented, and are important data for the system to generate the next question or draft of the feedback.

[1344] A "natural language processing engine" refers to software technology that analyzes text entered by a user and understands its meaning and intent.

[1345] A "draft" is an early version of the final document, before users can make any corrections or additions.

[1346] An "interface" refers to elements such as an operation screen and input form that enable interaction between a user and a system.

[1347] The present invention is a system for efficiently and effectively writing book reviews. The system allows a user to input the title of a book they have read, retrieves detailed information about the book based on the title, presents the user with a series of questions, and ultimately generates a draft of the book review.

[1348] First, a user accesses the system using a communication device. The communication device provides an interface for the user to input the title of the book they have just read. For example, the user inputs "Harry Potter and the Philosopher's Stone." This input title is sent to the server via the communication device.

[1349] The server searches for and retrieves information about the book from a database on the network based on the received book title. This database uses, for example, the Google Books API. This book information includes the author's name, summary, and main characters.

[1350] Next, the server generates initial interview questions based on the acquired book information. The initial questions are general, such as "Why did you choose this book?". A generative AI model is used to create prompt sentences and generate initial questions like these.

[1351] The generated question is presented to the user via a communication device. The user inputs their thoughts and impressions about the question and sends the answer to the server. For example, the user might answer, "Because I like the world of magic."

[1352] The server analyzes the user's answer using a natural language processing engine (e.g., GPT-3) and generates the next question based on the answer. For example, if the user's answer is "Because I like the magical world," the next question generated will be "What did you think of Harry?" By repeating this process, the server collects a series of answers from the user.

[1353] Based on the collected answers, the server generates a draft of the book report, which is structured as a coherent sentence, such as, "The book I read was 'Harry Potter and the Philosopher's Stone.' I chose this book because I love the magical world. Harry is very brave, and I was impressed by his sense of adventure..."

[1354] The generated draft is displayed to the user via the communication device, where the user can review the displayed draft and make corrections or additions as needed. Finally, the communication device provides the user with the option to save or print the completed book report.

[1355] For example, here's a prompt that might appear if the user reads "Harry Potter and the Philosopher's Stone":

[1356] Prompt statement:

[1357] "Suppose a user has read "Harry Potter and the Philosopher's Stone." Please generate the next question based on the user's answers to the following questions:

[1358] Question 1: Why did you choose this book?

[1359] User Answer: Because I love the magical world.

[1360] Generate the following question: What did you think of Harry?”

[1361] In this way, the present invention gradually elicits the user's thoughts and ultimately supports them in writing a natural book review. This process reduces the burden of writing a book review and also contributes to training the user's imagination and thinking skills.

[1362] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1363] Step 1:

[1364] A user accesses the system using a communication device. The communication device provides an interface for the user to input the title of the book they have finished reading. The user inputs the title of the book they have finished reading, and the communication device sends the title to the server. The input is the book title, and the output is the book title data sent to the server. For example, the title "Harry Potter and the Philosopher's Stone" is input.

[1365] Step 2:

[1366] Based on the received book title, the server searches for and retrieves information about the corresponding book from a database on the network. The database uses the Google Books API, etc. The input is the book title data, and the output is book information such as the author name, summary, and main characters. The server retrieves the author name and summary of "Harry Potter and the Philosopher's Stone."

[1367] Step 3:

[1368] The server generates initial interview questions based on the acquired book information. It uses a generative AI model to generate appropriate questions. The input is the book information, and the output is the initial question. Specifically, the server generates the question, "Please tell us why you chose this book."

[1369] Step 4:

[1370] The generated initial question is sent from the server to the communication device, which then presents the question to the user. The input is the initial question, and the output is the question displayed on the communication device. The communication device displays to the user, "Please tell us why you chose this book."

[1371] Step 5:

[1372] The user inputs their thoughts in response to the questions presented, and the communication device sends the answer to the server. The input is the user's answer, and the output is the answer data sent to the server. For example, the user might answer, "Because I like the world of magic."

[1373] Step 6:

[1374] The server uses a natural language processing engine to analyze the received user response and generate the next question based on the content. The input is the user response data and the output is the next question. The server analyzes a response such as "Because I love the magical world" and then generates the question "What did you think of Harry?"

[1375] Step 7:

[1376] The generated next question is sent from the server to the communication device, which again presents the question to the user. The input is the next question and the output is the next question displayed on the communication device. The communication device displays to the user, "What did you think of Harry?"

[1377] Step 8:

[1378] This process is repeated until all of the user's answers are collected. The answer to each question is sent to the server, which generates the next question, maintaining a sequential interview format. The input is all of the user's answers, and the output is the collected answer data.

[1379] Step 9:

[1380] The server generates a draft of the book report based on all the answers. A generative AI model is used to synthesize the series of answers into a coherent sentence. The input is all the answer data, and the output is a draft of the book report. The server generates a draft with content such as, "The book I read was 'Harry Potter and the Philosopher's Stone.' I chose this book because I love the magical world. Harry is very brave, and I was impressed by his sense of adventure..."

[1381] Step 10:

[1382] The generated draft is sent from the server to the communication device, and the communication device displays the draft to the user. The input is the generated draft, and the output is the draft displayed on the communication device. The user can check the displayed draft and make corrections or additions as necessary.

[1383] Step 11:

[1384] Finally, the communication device provides the option to save or print the completed book review. The input is a revised draft and the output is the final book review that is saved or printed. The user can save the completed book review.

[1385] (Application example 1)

[1386] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1387] The process of writing a book report is a difficult and time-consuming task for many children. Many children find it particularly difficult to organize and summarize their impressions and opinions. For this reason, there is a need for a method that allows them to write book reports efficiently and effectively. Furthermore, there is a need for a method that generates questions based on the content entered by the user and naturally draws out the user's thoughts and feelings. A system that can solve these problems is highly anticipated.

[1388] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1389] In this invention, the server includes means for acquiring book information, means for presenting questions to the user, means for acquiring the user's answers, means for analyzing the user's answers and generating the next question, means for generating a draft of the book report based on the user's answers, means for displaying the draft to the user for correction or addition, means for using a generative AI model to generate the next question based on the user's input, and means for creating a prompt sentence to present the generated question. This makes it possible to create a book report efficiently and naturally, making it easier for children to organize and express their thoughts.

[1390] "Means for obtaining book information" refers to a function that obtains information about books entered by users through a database or API.

[1391] "Means of presenting questions to the user" refers to a function that displays or presents questions on a screen or via voice for the user to answer.

[1392] The "means for acquiring the user's answer" refers to an interface or input device for recording the answer entered by the user and transmitting it to the server.

[1393] The "means for analyzing the user's answer and generating the next question" is a function that uses natural language processing technology to analyze the answer entered by the user and automatically generates the next appropriate question based on that.

[1394] "Means for generating a draft of a book review based on the user's answers" refers to a function that organizes and consolidates the answers provided by the user to create a consistent draft of a book review.

[1395] The "means for displaying the draft to the user and making corrections or additions" is a function that provides an interface for the user to check the generated draft and make any necessary corrections or additions.

[1396] "Means for using a generative AI model to generate the next question based on user input" refers to a function that uses a generative AI model to automatically generate the next question based on the user's input.

[1397] The "means for creating a prompt sentence to present the generated question" is a function for creating an appropriate prompt sentence to display to the user the question generated by the generative AI model.

[1398] This invention is a system for efficiently and effectively creating book reviews. This system acquires information about a book that a user has read, presents questions in an interview format, and generates a draft of the review based on the user's answers. A specific embodiment of this system is described below.

[1399] The overall system configuration mainly includes the following hardware and software:

[1400] User device (smartphone or tablet)

[1401] server

[1402] Book information database (e.g. Google Books API)

[1403] Natural language processing engine (e.g. OpenAI GPT-3)

[1404] First, users access the system using a terminal, which provides an interface for inputting the title of the book they have finished reading, and also provides a function for scanning ISBN codes, which can automatically obtain book information.

[1405] The book title entered by the user is sent to the server via the terminal. The server searches and retrieves the corresponding book information from the book information database based on the received book title. This book information includes basic information such as the author, summary, and main characters.

[1406] The server then uses the book details to generate initial interview questions, using a generative AI model to present the questions that best fit the user's input, such as a specific question like, "Why did you choose this book?"

[1407] The generated question is sent to the terminal, which displays it to the user. The user answers the question by inputting their thoughts and impressions. Answers can be entered either by voice or text.

[1408] The device sends the user's answer to the server, which uses a natural language processing engine to analyze the answer and generate the next question based on its content. This process is repeated, digging deeper into the user's answer. For example, if the user answers, "Because I like magical worlds," the next question generated might be more specific, such as, "Which part of this book impressed you the most?"

[1409] Based on the collected responses, the server generates a draft of the book report, which organizes the user's responses into a coherent text. The draft is then sent to the terminal and displayed to the user.

[1410] The user can review the displayed draft and make corrections or additions as needed, and finally the device will give the user the option to save or print the completed book report.

[1411] For example, if a user answers "Because I like the world of magic," the next question generated based on that answer is "Which part of this book impressed you the most?" Through this process, the user's thoughts are drawn out one after another, and ultimately the review is completed efficiently and naturally.

[1412] An example of a prompt sentence would be, "Generate the next question based on the user's answer: 'Because I like magical worlds.' Next question:" and would be input to the generative AI model.

[1413] As described above, this system reduces the burden of writing a book review and provides a concrete means for users to easily express themselves.

[1414] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1415] Step 1:

[1416] A user uses a terminal to input the book title or ISBN code, and the terminal receives this input and sends a request to a book information database to obtain detailed information about the book (author, synopsis, main characters, etc.).

[1417] Step 2:

[1418] The device sends the acquired book information to the server, which uses a generative AI model to generate initial interview questions to present to the user based on this book information. For example, a question like, "Please tell us why you chose this book."

[1419] Step 3:

[1420] The generated question is sent to the device and displayed to the user, who then uses voice or text input to enter an answer to the question, which the device then captures and sends to the server.

[1421] Step 4:

[1422] The server receives the user's answer and analyzes it using a natural language processing engine. Based on this analysis, the generative AI model generates the next question. For example, if the user's answer is "Because I like magical worlds," the next question generated would be "Which part of this book impressed you the most?"

[1423] Step 5:

[1424] The next question generated by the server is sent to the device and displayed to the user. The user answers the question again, and the device sends the answer to the server. This process is repeated, digging deeper into the user's answers.

[1425] Step 6:

[1426] The server generates a draft of the book report based on the collected responses from the user. The generated draft logically organizes the user's responses and forms a coherent sentence.

[1427] Step 7:

[1428] The generated draft is sent to the terminal and displayed to the user. The user checks the draft and makes corrections or additions as necessary. The terminal then sends the user's corrections to the server.

[1429] Step 8:

[1430] Finally, the user has the option to save or print the completed book report. The device also provides the ability to save the completed book report in PDF format or send it via email.

[1431] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1432] ---

[1433] This invention is a system that helps children write book reports efficiently and effectively. This system acquires information about the book the user has read, presents questions in an interview format, and generates a draft of the book report based on the user's answers. In addition, by combining it with an emotion engine that analyzes the user's emotions, the system generates questions and writes the book report while taking the user's emotions into consideration.

[1434] First, the user (child) accesses the system using a terminal. The terminal provides an interface for the user to input the title of the book they have finished reading. The book title entered by the user is sent to the server via the terminal.

[1435] The server searches for and retrieves information about the book from a book information database based on the received book title. This book information includes basic information such as the author, summary, and main characters. Next, the server generates initial interview questions based on the book's detailed information. For example, a question such as "Why did you choose this book?" is generated.

[1436] The generated question is sent to the terminal, which displays the question to the user. The user then inputs their thoughts and impressions about the question and submits their answer.

[1437] The device sends the user's answer to the server, which then analyzes the received answer using a natural language processing engine and an emotion engine. The natural language processing engine analyzes the user's text grammatically and semantically, and the emotion engine recognizes the emotional state (e.g., joy, sadness, surprise, etc.) contained in the user's answer.

[1438] Based on the results of this analysis, the server generates the next question. At this time, the analysis results of the emotion engine are also taken into consideration, and a question is presented that corresponds to the user's emotions. For example, if the user answers that they were moved, a question is generated that draws out the details of that emotion. For example, a question such as "Which part of Harry most moved you?" may be generated.

[1439] This process is repeated, digging deeper into the user's answers and taking into account their emotional state. Based on the collected responses, the server generates a draft of the book review. This draft organizes the user's answers and reflects the emotional nuances analyzed by the emotion engine.

[1440] The generated draft is sent to the device and displayed to the user, who can review the displayed draft and make corrections or additions as needed. Finally, the device provides the option to save or print the completed book report.

[1441] For example, if a user reads "Harry Potter and the Philosopher's Stone," the first question presented to them is, "Why did you choose this book?" If the user answers, "Because I love the magical world," the next question generated is, "What did you think of Harry?" If the user answers, "Harry is very brave, and I was moved by his adventurous spirit," the emotion engine recognizes the emotional state of "moved," and generates the next question, "What about him moved you the most?" This completes a detailed review that reflects the user's emotional state.

[1442] As described above, the present invention is a system for drawing out the user's thoughts and feelings in a natural way and writing a book review. This reduces the burden of writing a book review and also contributes to training children's imagination, thinking skills, and emotional expression.

[1443] ---

[1444] The processing flow will be explained below.

[1445] Step 1:

[1446] The terminal provides the user with an interface for inputting the book title.

[1447] Step 2:

[1448] The user inputs the title of the book they have finished reading into the terminal and transmits it.

[1449] Step 3:

[1450] The terminal transmits the entered book title to the server.

[1451] Step 4:

[1452] The server searches for and obtains detailed information about the book from the book information database based on the received book title.

[1453] Step 5:

[1454] The server generates initial interview questions for writing a book review based on the collected book information, such as "Please tell us why you chose this book."

[1455] Step 6:

[1456] The server sends the generated question to the terminal.

[1457] Step 7:

[1458] The terminal displays an initial question to the user.

[1459] Step 8:

[1460] The user answers the questions displayed on the terminal and sends them.

[1461] Step 9:

[1462] The terminal transmits the user's answer to the server.

[1463] Step 10:

[1464] The server analyzes the received user response using a natural language processing engine.

[1465] Step 11:

[1466] The server also uses an emotion engine to recognize the emotional state contained in the user's response.

[1467] Step 12:

[1468] The server generates the next question based on the analysis results of the natural language processing engine and the recognition results of the emotion engine. For example, if the user answers "I was moved," it generates a question according to the emotion, such as "Which scene moved you the most?"

[1469] Step 13:

[1470] The server sends the newly generated question to the terminal.

[1471] Step 14:

[1472] The terminal displays the new question to the user.

[1473] Step 15:

[1474] The user again answers the questions and transmits the answers via the terminal.

[1475] Step 16:

[1476] The terminal transmits the user's answer to the server.

[1477] Step 17:

[1478] The server repeats this process, analyzing each user's answers and generating multiple questions, each of which is analyzed and refined using natural language processing and an emotion engine.

[1479] Step 18:

[1480] The server generates a draft of the book report based on the collected series of user responses. The draft organizes the user responses and reflects the emotional nuances based on the analysis results of the emotion engine.

[1481] Step 19:

[1482] The server transmits the generated draft to the terminal.

[1483] Step 20:

[1484] The terminal displays the generated draft of the book review to the user.

[1485] Step 21:

[1486] The user checks the displayed draft and makes corrections or additions as necessary.

[1487] Step 22:

[1488] The terminal sends any modifications or additions made by the user to the server (if necessary).

[1489] Step 23:

[1490] The server receives corrections and additions and prepares the final draft.

[1491] Step 24:

[1492] The server saves the final book report and exports it in the required format (e.g. PDF).

[1493] Step 25:

[1494] The device displays the completed book report to the user and offers the option to save or print it.

[1495] The above are the specific processing steps and operations of the system that combines the emotion engine.

[1496] Example 2

[1497] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1498] Conventional book review writing support systems are unable to take the user's emotions into account when writing a book review, making it difficult for the user to write a book review that reflects their true feelings. Furthermore, because the questions are uniform, it is not possible to elicit individual impressions from each user, resulting in variations in the quality of the book reviews. This makes writing a book review a heavy burden, especially for users who require advanced support, such as children.

[1499] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1500] In this invention, the server includes means for acquiring book information, means for presenting questions to the user, means for acquiring the user's answers, means for analyzing the user's answers and generating the next question, means for analyzing the user's emotions, means for generating a draft of a book review based on the user's answers, and means for displaying the draft to the user and allowing the user to make corrections or additions. This makes it possible to generate questions and draft reviews that reflect the user's emotions, and to efficiently create interesting reviews that are suitable for each user.

[1501] The "means for obtaining book information" is a function for searching and obtaining information on the corresponding book from the book information database based on the book title entered by the user.

[1502] The "means for presenting questions to the user" is a function for displaying to the user questions generated based on the book information and the user's answers.

[1503] The "means for acquiring the user's answer" is a function that receives the answer entered by the user to the question and sends it to the server.

[1504] The "means for analyzing the user's response and generating the next question" is a function that analyzes the user's response using a natural language processing engine and generates the next question based on the results.

[1505] The "emotion analysis means for analyzing the user's emotions" is a function for recognizing and analyzing the emotional state (for example, joy, sadness, surprise, etc.) contained in the user's response.

[1506] The "means for generating a draft of a book review based on the user's answers" is a function for generating a draft of a book review based on the analyzed answers and emotional state of the user.

[1507] "Means for displaying the draft to the user and making corrections or additions" is a function that displays the generated draft of the book review to the user and provides an interface for the user to make corrections or additions.

[1508] A "book information database" refers to a database that stores basic information about a book, such as its author, summary, and main characters.

[1509] A "natural language processing engine" is an engine (software component) for grammatically and semantically analyzing a user's response.

[1510] This invention is a system for making the creation of book reviews more efficient. This system acquires information about the book the user has read, presents questions in an interview format, and generates a draft of the review based on the user's answers. In addition, by combining it with an emotion analysis engine that analyzes the user's emotions, the system generates questions and creates a review that takes the user's emotions into consideration.

[1511] System configuration

[1512] The main components of the system include the following hardware and software:

[1513] Terminal (user side): A device used by the user to input and confirm data. This terminal can be a PC, tablet, smartphone, etc.

[1514] Server: A central processing unit that manages the processing of the entire system. The server integrates the book information database, natural language processing engine, and sentiment analysis engine, and processes various data according to user input.

[1515] Book information database: Contains basic information such as the book title, author, summary, and main characters.

[1516] Natural language processing engine: An engine for analyzing user responses grammatically and semantically. This engine can use technologies such as GPT-3.

[1517] Sentiment analysis engine: An engine for analyzing the emotional state contained in the user's answers.

[1518] System Operation

[1519] The user (child) uses a terminal to access the system, which incorporates a sentiment analysis engine. The terminal provides an interface for the user to input the title of the book they have finished reading. The book title entered by the user is sent to the server via the terminal.

[1520] Get book information

[1521] The server searches for and retrieves information about the book from the book information database based on the received book title, including basic information such as the author, summary, and main characters.

[1522] Question Generation

[1523] The server generates initial interview questions based on the book information, such as "Please tell us why you chose this book." The generated questions are sent to the terminal and displayed to the user.

[1524] User responses and their analysis

[1525] Users input their thoughts and feelings in response to the displayed questions and send their answers from their devices to the server. The server then analyzes the received answers using a natural language processing engine and a sentiment analysis engine. The natural language processing engine analyzes the user's text grammatically and semantically, and the sentiment analysis engine recognizes the emotional state contained in the user's answer.

[1526] Question generation and emotion consideration

[1527] Based on the analysis results, the server generates the next question. At this time, the results of the emotion analysis are also taken into consideration, and a question is presented that corresponds to the user's emotions. For example, if the user answers "I was moved," the next question generated would be "Which part of Harry impressed you the most?"

[1528] Generate a draft of your review

[1529] The server then digs deeper into the user's answers, collecting them in a way that takes into account their emotional state, and generates a draft of the book review. This draft organizes the user's answers and reflects the emotional nuances resulting from the emotion analysis.

[1530] Review and revise the draft

[1531] The generated draft is sent to the device and displayed to the user, who can review the displayed draft and make corrections or additions as needed. Finally, the device provides the option to save or print the completed book report.

[1532] Specific examples

[1533] When a user reads a "fantasy novel," the first question presented to them is, "Why did you choose this book?" If the user answers, "Because I like adventure," the next question generated is, "What did you think of the main character?" If the user answers, "I was moved by his bravery," the sentiment analysis engine recognizes the emotional state of "moved" and generates the next question, "What was it about his bravery that particularly impressed you?" This results in a detailed book review that reflects the user's emotional state.

[1534] Prompt Sentence Examples

[1535] User Answer: "Because I love adventure."

[1536] Generated question: Based on the answer "Because I love adventure" to the question "Why did you choose this book?", generate the following question taking into account the analysis results of the sentiment analysis engine.

[1537] User Answer: "I was impressed by his bravery."

[1538] Generated question: Based on the answer "I was moved by his bravery" to the question "What did you think of the main character?", generate the following question taking into account the analysis results of the sentiment analysis engine.

[1539] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1540] Step 1:

[1541] A user accesses the system and enters the title of a book.

[1542] Input: Title of the book the user has read

[1543] Specific actions: A user uses a device to access a web page or app on the system. The device interface displays a text box for entering the book title. The user enters the book title and presses the submit button.

[1544] Output: The book title is sent to the server.

[1545] Step 2:

[1546] The server retrieves information from the book information database.

[1547] Input: The book title entered by the user

[1548] Specific operation: The server searches the book information database based on the received book title, issues an SQL query to retrieve the corresponding book information, including the author name, summary, and main characters.

[1549] Output: Book information is retrieved and stored on the server.

[1550] Step 3:

[1551] The server generates the initial question

[1552] Input: Retrieved book information

[1553] Specific operation: The server generates the first interview questions based on the book information. For example, a question such as "Please tell us why you chose this book" is generated. The generated questions are sent to the terminal and displayed to the user.

[1554] Output: The initial question is sent to the terminal and displayed to the user.

[1555] Step 4:

[1556] The user answers the question

[1557] Input: Question sent by the server

[1558] Specific operation: The user inputs their thoughts and impressions in response to the questions displayed on the terminal. Once input is complete, they press the send button.

[1559] Output: The user's answer is sent from the device to the server.

[1560] Step 5:

[1561] The server analyzes the user's answers

[1562] Input: User's answer

[1563] Specific operation: The server passes the received user response to a natural language processing engine for grammatical and semantic analysis, and a sentiment analysis engine recognizes the user's emotional state (e.g., joy, sadness, surprise, etc.) from the response.

[1564] Output: Analysis results (grammatical and semantic analysis results and emotional state) are obtained.

[1565] Step 6:

[1566] The server generates the next question

[1567] Input: Analysis results

[1568] Specific operation: The server generates the next question based on the analysis results. At this time, the results of the sentiment analysis are also taken into consideration. For example, if the user answers "I was moved," a question is generated to elicit more details about that emotion. For example, "Which part of him moved you the most?" The generated question is sent to the terminal and displayed to the user.

[1569] Output: The following question is sent to the terminal and displayed to the user.

[1570] Step 7:

[1571] Repeat steps 4-6

[1572] Input: The user's new answer

[1573] What happens: The user answers a new question, the server analyzes the answer, generates the next question, and the process repeats.

[1574] Output: Answers from multiple users are collected on the server.

[1575] Step 8:

[1576] The server generates a draft of the book report.

[1577] Input: Multiple user responses and sentiment analysis results

[1578] Specific operation: The server integrates all collected user responses and the results of sentiment analysis, and generates a draft book report using natural language processing. This draft organizes the user responses and reflects the emotional nuances.

[1579] Output: The generated draft of the book report is sent to the device.

[1580] Step 9:

[1581] User reviews and modifies draft

[1582] Input: A generated draft of the book report

[1583] Specific operation: The terminal displays the generated draft to the user. The user checks the draft and makes corrections or additions as necessary. After entering the corrections, the user presses the save button to confirm.

[1584] Output: The revised or finalized book report is finally saved.

[1585] Step 10:

[1586] Save and print your book report

[1587] Input: Revised or confirmed book report

[1588] Specific operation: The terminal finally provides the user with the option to save or print the completed review. The user saves or prints the review according to the selection.

[1589] Output: The user receives a saved file or a printed book report.

[1590] (Application example 2)

[1591] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1592] Conventional book review writing systems struggled to generate questions that took the user's emotional state into account, making it impossible to elicit effective feedback or detailed reviews. Furthermore, in factory work environments, it was difficult to efficiently collect and analyze feedback from workers and suggest areas for improvement in the next step. For these reasons, a system that could contribute to improving work efficiency and quality was needed.

[1593] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1594] In this invention, the server includes means for acquiring book information, means for presenting questions to the user, means for acquiring the user's answers, means for analyzing the user's answers and generating the next question, means for generating a draft of a book review based on the user's answers, means for displaying the draft to the user and for corrections or additions, means for collecting work content and impressions input by workers, means for analyzing the input work content and impressions with a natural language processing engine and recognizing the emotional state using an emotion analysis engine, means for generating questions to draw out improvements for the next work based on the work content and emotions, and means for organizing the collected feedback data and creating a report containing the improvements. This makes it possible to collect detailed feedback and present impressions and improvements while taking into consideration the emotional states of the user and workers.

[1595] The "means for acquiring book information" is a means for searching and acquiring information on the corresponding book from a book information database based on the title of the book entered by the user.

[1596] The "means for presenting questions to the user" is an interface that displays questions to assist the user in writing a book review based on the acquired book information.

[1597] The "means for acquiring user answers" refers to a means for collecting and saving answers entered by users in response to questions presented to them.

[1598] The "means for analyzing the user's answers and generating the next question" is a means for analyzing the collected answers using a natural language processing and sentiment analysis engine, and generating the next question based on the analysis results.

[1599] The "means for generating a draft of a book review based on the user's responses" is a means for automatically generating an initial draft of a book review based on the analyzed user's response data.

[1600] The "means for displaying the draft to the user and for making corrections or additions" is an interface for displaying the generated draft of the book review to the user and for the user to make corrections or additions.

[1601] The "means for collecting work details and feedback entered by workers" is an interface for collecting work details and feedback from workers in the factory.

[1602] "Means for analyzing input work details and impressions using a natural language processing engine and recognizing emotional states using an emotion analysis engine" refers to means for analyzing work details and impressions collected from workers using a natural language processing engine and further recognizing their emotional states using an emotion analysis engine.

[1603] The "means for generating questions to draw out improvements to the next task based on the task content and emotions" refers to a means for creating questions to draw out improvements to the next task based on the analyzed data and presenting them to the worker.

[1604] "Means for organizing collected feedback data and creating a report listing areas for improvement" refers to means for systematically organizing collected feedback data and automatically generating a report listing areas for improvement.

[1605] This invention provides a system that allows users to write book reports efficiently and effectively. This system can also collect feedback from factory workers and use it to improve future operations. The system consists of the following main components:

[1606] System Configuration

[1607] 1. Hardware Configuration

[1608] Terminal: A device on which a user writes a book report or writes about their work. The terminal in question can be a tablet or a PC.

[1609] Server: A computer with a database and analytical capabilities that runs a natural language processing engine and a sentiment analysis engine.

[1610] 2. Software Configuration

[1611] Natural language processing engines (e.g. SpaCy)

[1612] Sentiment analysis engine (e.g. IBM Watson Tone Analyzer)

[1613] Feedback management interface (frontend: React, backend: Node.js)

[1614] Data processing and calculation flow

[1615] 1. Data Acquisition

[1616] The user inputs the book title, work content, and impressions through the terminal and sends them to the server.

[1617] The server receives the data entered by the user and retrieves information about the book from a book information database based on the book title.

[1618] 2. Question generation

[1619] Based on the book information and the initial task, the server generates the initial interview questions. For example, for a book, the server generates an initial question such as "Why did you choose this book?". For the task, the server generates an initial question such as "What were the particular difficulties you had while working?".

[1620] 3. Analysis of user responses

[1621] The terminal presents the generated question to the user and transmits the user's answer to the server.

[1622] The server analyzes the received user responses using a natural language processing engine and a sentiment analysis engine.

[1623] 4. Generate the next question

[1624] Based on the analysis results, the server generates the next question according to the user's emotions and the content of the task. For example, if the user answers "I was moved," it generates a follow-up question such as "Which part moved you?"

[1625] 5. Draft and Report Generation

[1626] The server collects all questions and answers and generates a feedback report for drafting impressions and improving work.

[1627] The generated drafts and reports are sent to the terminal, where the user can make final confirmations and make corrections or additions.

[1628] Examples of concrete examples and prompts

[1629] For example, if a user answers, "I chose this book because I love the magical world," the server uses a natural language processing engine to analyze the text and a sentiment analysis engine to recognize the emotion of "joy."Then, the server generates the next question, "Which of Harry's adventures did you like best?"

[1630] Prompt sentence format example

[1631] "Which part of the task did you find difficult?"

[1632] “What support did you feel you needed to overcome that challenge?”

[1633] In this way, it is possible to collect detailed feedback and provide written impressions and suggestions for work improvement, while taking into consideration the emotional state of the user or worker.

[1634] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1635] Step 1:

[1636] Users access the system through their terminals and input the book title, work content, and impressions. The input data is sent to the server.

[1637] Input: Book title, work content, impressions

[1638] Output: Book title, work content, and impressions data are sent to the server

[1639] Step 2:

[1640] Based on the book title received by the server, information on the relevant book is obtained from the book information database.

[1641] Input: Book title

[1642] Output: Basic information about the book (author, summary, main characters, etc.)

[1643] Step 3:

[1644] The server generates the first question based on the acquired book information or the initial work content.

[1645] Input: Basic information about the book, initial work

[1646] Output: Initial question (e.g., "Why did you choose this book?")

[1647] Step 4:

[1648] The terminal displays the generated question to the user and obtains the user's answer.

[1649] Input: First question

[1650] Output: User's answer (e.g., "Because I love magical worlds")

[1651] Step 5:

[1652] The server analyzes the user's response using a natural language processing engine (e.g., SpaCy) to analyze it grammatically and semantically, and then uses a sentiment analysis engine (e.g., IBM Watson Tone Analyzer) to recognize the emotional state.

[1653] Input: User's answer

[1654] Output: Analysis results after natural language processing, sentiment analysis results (e.g., "joy")

[1655] Step 6:

[1656] Based on the analysis results, the server generates the next question, which is determined taking into account the user's emotional state and the content of their answers.

[1657] Input: Natural language processing results, sentiment analysis results

[1658] Output: Next question (e.g., "What about Harry impressed you most?")

[1659] Step 7:

[1660] The terminal presents the next generated question to the user to obtain a more detailed answer.

[1661] Input: Next question

[1662] Output: User's detailed response (e.g., "I was impressed by his sense of adventure.")

[1663] Step 8:

[1664] The server generates a draft of a book report based on the user's responses. In a factory application, the collected feedback is used to generate a report on work improvement.

[1665] Input: A set of user answers

[1666] Output: Draft book review, work improvement report

[1667] Step 9:

[1668] The server sends the generated drafts and reports to the terminal and displays them to the user, who can then check them and make corrections or additions as necessary.

[1669] Input: Draft of book review, work improvement report

[1670] Output: Drafts and reports displayed to users, and corrections and additions made by users

[1671] The above are the processing steps of the system and their specific operations.

[1672] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1673] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1674] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1675] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1676] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1677] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1678] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1679] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1680] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1681] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1682] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1683] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1684] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1685] 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.

[1686] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1687] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1688] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1689] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1690] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1691] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1692] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1693] The following is further disclosed regarding the above embodiment.

[1694] (Claim 1)

[1695] A means of obtaining information about the book;

[1696] means for presenting a question to a user;

[1697] a means for obtaining a user's response;

[1698] a means for analyzing the user's answer and generating a next question;

[1699] means for generating a draft of the book report based on the user's responses;

[1700] A means for users to view the draft and make corrections or additions.

[1701] A system including:

[1702] (Claim 2)

[1703] 2. The system of claim 1, further comprising means for retrieving information from a book information database based on a book title entered by a user.

[1704] (Claim 3)

[1705] 10. The system of claim 1, further comprising means for analyzing the user's responses with a natural language processing engine.

[1706] "Example 1"

[1707] (Claim 1)

[1708] means for providing an interface for user access using multiple communication devices;

[1709] A means for searching and acquiring the title of a book acquired from a user via a communication device from a database on a network;

[1710] a means for generating an initial question based on book information and presenting the initial question to a user;

[1711] means for acquiring a user's response via a communication device;

[1712] means for analyzing the user's answer and generating the next question;

[1713] means for presenting a next question to a user through a communication device;

[1714] means for generating a draft of the book report based on all of the user's responses;

[1715] means for displaying the generated draft to a user via a communication device and providing an interface for making corrections or additions;

[1716] A system including:

[1717] (Claim 2)

[1718] 2. The system according to claim 1, further comprising means for retrieving information from a database on a network based on the title of a book input by a user.

[1719] (Claim 3)

[1720] 10. The system of claim 1, further comprising means for analyzing the user's responses using a natural language processing engine.

[1721] "Application Example 1"

[1722] (Claim 1)

[1723] A means of obtaining information about the book;

[1724] means for presenting a question to a user;

[1725] a means for obtaining a user's response;

[1726] a means for analyzing the user's answer and generating a next question;

[1727] means for generating a draft of the book report based on the user's responses;

[1728] means for displaying the draft to a user for corrections or additions;

[1729] a means for using a generative AI model to generate a next question based on user input;

[1730] A means of creating prompt sentences to present the generated questions;

[1731] A system including:

[1732] (Claim 2)

[1733] 2. The system of claim 1, further comprising means for retrieving information from a book information database based on a book title entered by a user.

[1734] (Claim 3)

[1735] 10. The system of claim 1, further comprising means for analyzing the user's responses with a natural language processing engine.

[1736] "Example 2: Combining Emotion Engines"

[1737] (Claim 1)

[1738] A means of obtaining information about the book;

[1739] means for presenting a question to a user;

[1740] a means for obtaining a user's response;

[1741] a means for analyzing the user's answer and generating a next question;

[1742] emotion analysis means for analyzing the emotions of a user;

[1743] means for generating a draft of the book report based on the user's responses;

[1744] A means for users to view the draft and make corrections or additions.

[1745] A system including:

[1746] (Claim 2)

[1747] 2. The system of claim 1, further comprising means for retrieving information from a book information database based on a book title entered by a user.

[1748] (Claim 3)

[1749] 10. The system of claim 1, further comprising means for analyzing the user's responses with a natural language processing engine.

[1750] (Claim 4)

[1751] 10. The system of claim 1, further comprising means for generating a next question based on the result of the user sentiment analysis.

[1752] (Claim 5)

[1753] 2. The system according to claim 1, further comprising means for generating a draft of a book review in consideration of the result of the user's sentiment analysis.

[1754] "Application example 2 when combining emotion engines"

[1755] (Claim 1)

[1756] A means of obtaining information about the book;

[1757] means for presenting a question to a user;

[1758] a means for obtaining a user's response;

[1759] a means for analyzing the user's answer and generating a next question;

[1760] means for generating a draft of the book report based on the user's responses;

[1761] means for displaying the draft to a user for corrections or additions;

[1762] A means for collecting work details and impressions input by workers;

[1763] A means for analyzing the input work content and impressions using a natural language processing engine and recognizing the emotional state using an emotion analysis engine;

[1764] A means for generating questions to draw out improvements for the next work based on the work content and emotions;

[1765] A method to organize the collected feedback data and create a report on areas for improvement.

[1766] A system including:

[1767] (Claim 2)

[1768] 2. The system of claim 1, further comprising means for retrieving information from a book information database based on a book title entered by a user.

[1769] (Claim 3)

[1770] 2. The system according to claim 1, further comprising means for analyzing the user's answers and the worker's feedback using a natural language processing engine. [Explanation of symbols]

[1771] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of obtaining information about the book; means for presenting a question to a user; a means for obtaining a user's response; a means for analyzing the user's answer and generating a next question; means for generating a draft of the book report based on the user's responses; A means for users to view the draft and make corrections or additions. A system including:

2. 2. The system of claim 1, further comprising means for retrieving information from a book information database based on a book title entered by a user.

3. 10. The system of claim 1, further comprising means for analyzing the user's responses with a natural language processing engine.

Images