System

Abstract

A system is provided.SOLUTION: The system includes an input means for inputting information of a trouble occurring daily by a user, a transmission means for transmitting the inputted information to a server, a generation means for analyzing the information received by the server and generating a fiction work based on a generation engine, a return means for returning the generated work to a terminal of the user, and a confirmation means for confirming the returned work by the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Bullying often begins as a small dispute that occurs daily among impressionable elementary and junior high school students. Traditional moral education lacks effective methods for dealing with these problems. Furthermore, in order to prevent and develop the ability to deal with bullying, self-awareness, emotional expression, empathy for others, and problem-solving skills are required. However, there is a lack of educational materials that allow students to learn these skills while experiencing them, which is an issue that needs to be addressed. [Means for solving the problem]

[0005] The present invention includes an input means for users (children or teachers) to input information about conflicts that occur on a daily basis. It also includes a transmission means for transmitting the input information to a server. The server then analyzes the received information and generates a fictional work using a generation engine (using natural language processing technology). It also includes a return means for returning the generated work to the user's terminal. It also includes a confirmation means for the user to confirm the returned work. By including a discussion means for using the generated work in class and holding discussions, children can concretely learn how to express emotions, empathize, and solve problems.

[0006] "Users" refer to children or teachers who use the system, inputting information about everyday disputes and reviewing the generated fictional works.

[0007] "Input means" refers to a method or device for a user to specifically input information about a dispute, including a dedicated application or web form.

[0008] The "transmission means" refers to a method or device for transmitting information input by a user to a server, and has the function of transmitting data via a communication network.

[0009] "Server" refers to a computer system that receives and analyzes information submitted by a user, generates a work of fiction based on a generation engine, and then returns the generated work to the user.

[0010] "Generation Engine" means software or algorithms located within the Server that use natural language processing techniques to generate works of fiction based on information received.

[0011] "Generation Means" refers to the set of processes or methods by which the server generates a work of fiction using the generation engine.

[0012] "Returning means" refers to a method or device for the server to transmit the generated fictional work to the user's terminal, and has the function of transmitting data via a communications network.

[0013] "Verification means" refers to a method or device for a user to verify a returned work of fiction, and has the ability to display or play it on a terminal.

[0014] "Discussion tools" refers to a set of processes and methods for using fictional works generated in class to encourage children to express their opinions about the feelings and actions of the characters and discuss empathy and problem-solving methods.

[0015] "Conflicts" refer to small disputes and conflicts that arise in children's daily lives, mainly caused by differences in emotions or behavior. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] This system allows users to input information about everyday disputes, and uses the information to generate fictional stories that can be used as teaching materials for moral education. This system allows children to concretely learn emotional expression, empathy, and problem-solving skills.

[0038] The system of the present invention is implemented by the following configuration and processing steps.

[0039] System Configuration

[0040] 1. User Device

[0041] As an input method, we provide a function that allows users to enter specific information about disputes on a daily basis. This is realized by a dedicated application or a web form.

[0042] As a transmission means, it has a function of transmitting the input information to the server.

[0043] 2. Server

[0044] As an analytical tool, it has the function of analyzing dispute information sent by users.

[0045] As a generation means, it has the function of generating fictional works using a generation engine based on the analyzed information.

[0046] As a return means, it has a function to send the generated fictional work to the user's terminal.

[0047] 3. Generation Engine

[0048] Software that uses natural language processing technology to generate fictional works based on detailed information about disputes.

[0049] 4. User Device

[0050] As a means of verification, it has the ability to display or play the returned fictional work.

[0051] As a means of discussion, we provide a function to use the generated fictional works in classes and hold discussions.

[0052] Specific examples of program processing

[0053] Enter and submit dispute information

[0054] Users enter details of the dispute through a dedicated application or a web form. For example, they enter information like, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[0055] The device converts the input information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[0056] Analyzing information and generating fiction

[0057] The server receives the JSON data sent from the device, analyzes the details of the dispute, and then passes the analyzed information to a generation engine (using natural language processing technology) to instruct it to generate a work of fiction.

[0058] An example of what might be generated is a short story like this:

[0059] "One day in the classroom, A-kun started to worry that B-kun hadn't returned the pencil he'd lent him. A-kun asked B-kun to return the pencil, but B-kun apologized, saying that he had been busy and had forgotten. A-kun and B-kun talked it over and decided that from now on they would keep their promises to each other."

[0060] Return and Review of Works of Fiction

[0061] The server formats the generated short story and returns it to the user's device in JSON format.

[0062] The terminal displays the short story received from the server and allows the user to review it, allowing the user to read the generated work of fiction.

[0063] Classroom use and discussion

[0064] The user (teacher) can use the displayed short story in class and read it aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems, thereby concretely learning the elements of the SEL program.

[0065] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills.

[0066] The processing flow will be explained below.

[0067] Step 1:

[0068] The user opens a dedicated application or web form. In the input field, they fill in the details of the dispute, for example, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[0069] Step 2:

[0070] The device converts the input information into JSON format and sends the converted data to the specified API endpoint (e.g., / generate_story).

[0071] Step 3:

[0072] The server receives the JSON data sent from the device, analyzes the received JSON data, extracts detailed information about the dispute, and executes an analysis method to analyze the extracted information.

[0073] Step 4:

[0074] The server passes the analyzed information to a generation engine, which uses natural language processing technology to generate a work of fiction based on the analyzed information.

[0075] Step 5:

[0076] The server formats the fictional work returned by the generation engine and returns the generated fictional work in JSON format to the user's device. The server constructs an appropriate API response to send back.

[0077] Step 6:

[0078] The device parses the JSON-formatted fictional work received from the server, converts it into a human-readable format, and displays the converted fictional work for the user to review.

[0079] Step 7:

[0080] The user (teacher) uses a fictional work in class. The user reads the displayed fictional work aloud to the entire class. After reading, the user starts a discussion with all the students, in which they share their opinions about the feelings and actions of the characters.

[0081] Example 1

[0082] 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."

[0083] In the traditional education system, it is difficult for children to concretely learn emotional expression, empathy, and problem-solving skills through everyday conflicts. As a result, the effectiveness of SEL (Social and Emotional Learning) programs is limited, and education based on real-life situations is not sufficiently provided.

[0084] 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.

[0085] In this invention, the server includes input means for a user to input information about conflicts that occur on a daily basis, transmission means for transmitting the input information to the server, generation means for the server to analyze the received information and generate a fictional work using natural language processing technology, return means for returning the generated work to the user's terminal, and confirmation means for the user to confirm the returned work. This enables children to learn emotional expression, empathy, and problem-solving skills through fictional works based on specific conflict scenarios.

[0086] "Input means" refers to the means by which users input specific information about disputes that arise on a daily basis, and includes dedicated applications and web forms.

[0087] The "transmission means" is a means for transmitting information input by the input means to a server, and includes a function for transmitting data using a communication protocol (e.g., HTTP).

[0088] "Generation means" means the means by which the server analyzes the information it receives and generates a work of fiction using natural language processing technology, including a generative AI model.

[0089] The "returning means" is a means for returning the fictional work generated by the generating means to the user's terminal, and includes a function for transmitting data using a communication protocol.

[0090] "Verification means" refers to a means by which the user can verify the returned fictional work, and includes a function for displaying it on the terminal.

[0091] "Discussion tools" are means for using the generated fictional works in class and for children to discuss the assignments, including educational frameworks and tools.

[0092] The "generation engine" is software that uses natural language processing technology to generate fictional works based on dispute information.

[0093] A "prompt" is a document that provides specific instructions to the generation engine and contains detailed information about the dispute.

[0094] MODE FOR CARRYING OUT THE INVENTION

[0095] This system allows users to input information about everyday disputes, and uses the information to generate fictional stories that can be used as teaching materials for moral education. This system allows children to concretely learn emotional expression, empathy, and problem-solving skills.

[0096] System Configuration

[0097] The system of the present invention has the following hardware and software configuration.

[0098] 1. User Device

[0099] An input means using a dedicated application or web form is provided, which allows users to input specific information about disputes on a daily basis.

[0100] As a transmission method, it has a function to send the input information to the server, using the HTTP protocol.

[0101] 2. Server

[0102] As an analytical tool, it has a function to analyze dispute information sent by users. This analysis is handled by software on the server, and parses data in JSON format.

[0103] As a generation means, it has the ability to generate fictional works using a generative AI model (e.g., GPT-3 (registered trademark)) based on the analyzed information.

[0104] As a means of returning the work, the system has the function of sending the generated fictional work to the user's device, and this also uses the HTTP protocol.

[0105] 3. Generation Engine

[0106] This software uses natural language processing technology to generate fictional works based on detailed information about disputes. The generative AI model used is specifically GPT-3.

[0107] 4. User Device

[0108] The returned fictional work is displayed as a means of verification, and it also has a playback function that allows users to use the fictional work in classes after verification.

[0109] The generated fictional works are used in classes as a means of discussion, and functions for holding discussions are provided, such as comment functions and video playback functions.

[0110] Specific examples of program processing

[0111] Enter and submit dispute information

[0112] The user enters information about the dispute through a dedicated application or a web form. For example, they might enter, "I lent my friend a pencil, but he didn't return it, and we got into an argument." Once they've finished entering information, they press the "Submit" button. The device converts the entered information into JSON format and sends it to the specified API endpoint.

[0113] Analyzing information and generating fiction

[0114] The server receives the JSON data sent from the device and analyzes the details of the dispute. It then uses the analyzed information to instruct the generation engine to generate a work of fiction using natural language processing technology. An example of the generated content could be a short story like this:

[0115] "You lent a friend a pencil and they didn't return it, and you got into an argument. Write a children's fiction story based on this argument."

[0116] Examples of generated short stories include:

[0117] "One day in the classroom, A-kun started to worry that B-kun hadn't returned the pencil he'd lent him. A-kun asked B-kun to return the pencil, but B-kun apologized, saying that he had been busy and had forgotten. A-kun and B-kun talked it over and decided that from now on they would keep their promises to each other."

[0118] Return and Review of Works of Fiction

[0119] The server formats the generated short story and returns it in JSON format to the user's device, which then displays the short story received from the server for the user to confirm.

[0120] Classroom use and discussion

[0121] Teachers can use the generated short stories in class and read them to all students. Students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems. This allows students to concretely learn the elements of SEL (social and emotional learning) programs.

[0122] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills.

[0123] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0124] Step 1:

[0125] Users open a dedicated application or web form and enter details of everyday disputes into text fields, such as "I lent my friend a pencil and he didn't return it, which led to an argument." After completing the input, users press a "Submit" button. This input data becomes the input for the next processing step.

[0126] Step 2:

[0127] The device converts the conflict information entered by the user into JSON format. For example, the input text is converted to {"conflict": "I lent my friend a pencil and he didn't return it, so we had an argument"}. The converted JSON data is sent as an HTTP POST request to the specified API endpoint (e.g., / generate_story). This becomes the input for the next processing step.

[0128] Step 3:

[0129] The server receives an HTTP request sent from a device. The received JSON data is passed to an internal process for parsing. For example, the data to be parsed is {"conflict": "I lent my friend a pencil, but he didn't return it, and we had an argument"}. The parsed data is passed to the generation engine for the next processing step.

[0130] Step 4:

[0131] The server uses the analyzed data to generate a prompt for a generative AI model (e.g., GPT-3). An example prompt might be, "I lent a pencil to a friend, but he didn't return it, and we got into an argument. Please write a fictional story for children based on this argument." This prompt is input into the generation engine, and the AI ​​model generates a work of fiction.

[0132] Step 5:

[0133] The generation engine (using natural language processing technology) receives the prompt and generates a work of fiction based on the details of the dispute. An example of a generated short story might be, "One day in the classroom, student A began to worry that student B had not returned the pencil he had lent to him. Student A asked student B, "Please return the pencil," but student B apologized, saying that he had been busy and had forgotten. Student A and student B talked it over and decided to keep their promise to each other in the future." This generated work is then passed to the next processing step.

[0134] Step 6:

[0135] The server formats the generated fiction and converts it back into JSON format, for example, {"story": "One day in the classroom, student A began to worry that student B had not returned the pencil he had lent him..."}. This JSON data is then sent back to the user's device.

[0136] Step 7:

[0137] The device receives the JSON data returned from the server and displays the fictional work on the application screen based on the received data, allowing the user to view the generated fictional work.

[0138] Step 8:

[0139] Teachers can use the generated fictional works in class and read them aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve problems. This allows students to learn emotional expression, empathy, and problem-solving skills through concrete scenarios.

[0140] Through this processing step, the system of the present invention can transform everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills.

[0141] (Application example 1)

[0142] 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."

[0143] Until now, there has been no system that generates fictional stories based on everyday conflicts and uses them in moral education. This has resulted in a lack of educational materials that allow children to specifically learn emotional expression, empathy, and problem-solving skills. Furthermore, there is no function to share the generated fictional stories with family and friends, or to hold quizzes or discussions based on the stories, preventing the full educational effect of this system.

[0144] 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.

[0145] In this invention, the server includes input means for a user to input information about disputes that arise on a daily basis, transmission means for transmitting the input information, generation means for analyzing the received information and generating a fictional work based on a generation engine, return means for returning the generated work to the user's terminal, confirmation means for confirming the returned work, learning means for providing educational quizzes and discussion functions for learning interpersonal problem solving and emotional empathy, and sharing means for sharing the generated work with family and friends. This allows children to concretely learn emotional expression, empathy, and problem-solving skills through fictional works, and to gain deeper understanding and learning by sharing them with family and friends.

[0146] "Input means" refers to a device or interface that allows a user to input information about disputes that arise on a daily basis.

[0147] The "transmission means" is a device or function for transmitting input information to a server.

[0148] An "analysis means" is a device or software module for analyzing information received by the server.

[0149] A "generator" is a device or software module that uses a generative engine to generate a work of fiction based on the analyzed information.

[0150] "Returning means" is a device or function for returning the generated work of fiction to the user's terminal.

[0151] "Verification means" is a device or function that allows a user to verify a returned work of fiction.

[0152] A "learning tool" is a device or software module that provides educational quizzes and discussion functions for learning interpersonal problem solving and emotional empathy.

[0153] A "sharing means" is a device or function for sharing the created fictional work with family and friends.

[0154] "Natural language processing technology" is a technology that enables computers to understand and generate human language.

[0155] The present invention is a system that allows users to input information about everyday disputes and use fictional works generated based on that information as teaching materials for moral education. This system is realized with the following hardware and software configuration.

[0156] System Configuration

[0157] 1. User Device

[0158] As an input method, we provide a function that allows users to enter specific information about disputes on a daily basis. This is realized by a dedicated application or a web form.

[0159] As a transmission means, it has a function of transmitting the input information to the server.

[0160] As a means of verification, it has the ability to display or play the returned fictional work.

[0161] As a learning tool, it provides functions for quizzes and discussions based on the fictional works that are generated, and also allows users to share their works with their families and friends.

[0162] 2. Server

[0163] As an analytical tool, it has the function of analyzing dispute information sent by users and converting it into an appropriate fictional work. Specifically, it generates a fictional work using a generation engine based on the analyzed information.

[0164] The generative method is to generate fictional works based on the analyzed information, using natural language processing techniques to generate stories based on the details of the dispute.

[0165] As a return means, it has a function to return the generated fictional work to the user's terminal.

[0166] Program processing explanation

[0167] The server uses cloud servers such as Alexa and Google® Cloud Platform (GCP). For natural language processing, OpenAI®'s GPT model is used. The program's processing begins with the user entering information about the dispute, which is then converted into JSON format and sent to the server. The server analyzes the received information and generates a work of fiction using a generation engine. The generated work of fiction is then sent back to the user's device, where the user can view it.

[0168] For example:

[0169] Entering information about a dispute: The user enters information such as "I lent my friend a pencil, but he never returned it, and we got into an argument."

[0170] Example prompt: "You lent a friend a pencil, but he didn't return it, and you got into an argument. Generate a fictional moral story based on this."

[0171] This system allows users to concretely learn emotional expression, empathy, and problem-solving skills through fictional works, and allows them to share the created works with family and friends.

[0172] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0173] Step 1:

[0174] The user enters the dispute information

[0175] Users can use a dedicated application or a web form to enter specific details about everyday disputes. For example, they can enter information like, "I lent my friend a pencil and he didn't return it, so we got into an argument." The input data is represented in JSON format. Based on the input, the system stores it in a database and prepares it for the next step.

[0176] Step 2:

[0177] Sending data from the device to the server

[0178] The user device converts the entered dispute information into JSON format and sends it to the specified API endpoint (e.g., / generate_story). This is done using an HTTP POST request, which sends the input data to the server. The server then validates the received data and checks for any problems before proceeding with analysis.

[0179] Step 3:

[0180] The server analyzes the information

[0181] The server receives the JSON data sent from the device. This analysis method analyzes the received data and understands the meaning of the input information. Specifically, it uses natural language processing technology to analyze the details of the dispute. Based on this analysis, it generates prompts to generate appropriate fiction works.

[0182] Step 4:

[0183] Generate a work of fiction

[0184] The server passes the parsed information to a generation engine, which generates a fictional work based on the prompt. This generation method uses natural language processing techniques such as OpenAI's GPT model. For example, if the prompt is "I lent my friend a pencil and he didn't return it, and we got into an argument. Please generate a fictional story with a moral based on this content.", the engine will generate a corresponding fictional work. The generated fictional work is saved in JSON format.

[0185] Step 5:

[0186] Send the generated work back to the user's device

[0187] The server formats the generated work of fiction and returns it to the user's device. This returns the generated JSON data as an HTTP response to the user's device. The user's device parses the received JSON data and displays or plays the work of fiction to the user.

[0188] Step 6:

[0189] Users can review their work and use the learning mode

[0190] The user reviews the returned fictional work. This reviewing means provides the user's device with the ability to display and play the work in text or audio. The user can also use the learning means to participate in quizzes and discussions based on the work. This allows the user to specifically learn skills such as empathy and problem-solving.

[0191] Step 7:

[0192] Share your creations

[0193] Users can share the fictional works they create with their families and friends. This sharing method generates a link for sharing the work and provides the ability to share it with others via social networking sites, email, etc. The shared work can then be used by others to view and learn from.

[0194] 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.

[0195] This system allows users to input information about everyday disputes, and then generates fictional works based on that information, which can then be used as teaching materials for moral education. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the system aims to provide a more effective educational experience. This system allows children to concretely learn emotional expression, empathy, and problem-solving skills.

[0196] The system of the present invention is implemented by the following configuration and processing steps.

[0197] System Configuration

[0198] 1. User Device

[0199] As an input method, we provide a function that allows users to enter specific information about disputes on a daily basis. This is realized by a dedicated application or a web form.

[0200] As a transmission means, it has a function of transmitting the input information to the server.

[0201] 2. Server

[0202] As an analytical tool, it has the function of analyzing dispute information sent by users.

[0203] As a generation means, it has the function of generating fictional works using a generation engine based on the analyzed information.

[0204] As an emotion engine, it has the ability to recognize the user's emotions from the dispute information entered by the user.

[0205] As a return means, it has a function to send the generated fictional work to the user's terminal.

[0206] 3. Generation Engine

[0207] Software that uses natural language processing technology to generate fictional works based on detailed dispute information and perceived emotions.

[0208] 4. User Device

[0209] As a means of verification, it has the ability to display or play the returned fictional work.

[0210] As a means of discussion, we provide a function to use the generated fictional works in classes and hold discussions.

[0211] Specific examples of program processing

[0212] Enter and submit dispute information

[0213] Users enter details of the dispute through a dedicated application or a web form. For example, they enter information like, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[0214] The device converts the input information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[0215] Information analysis and emotion recognition

[0216] The server receives the JSON data sent from the device and analyzes the details of the dispute. It also uses an emotion engine to recognize the user's emotion from the entered details of the dispute. This emotion information is included in the analyzed data passed to the generation engine.

[0217] Generating a work of fiction

[0218] The server then passes the analyzed information and emotional information to a generation engine (using natural language processing technology) and instructs it to generate a fictional work. For example, if the user's emotion is "anger," a story will unfold that corresponds to that emotion.

[0219] An example of what might be generated is a short story like this:

[0220] "One day in the classroom, A-kun started to worry that B-kun hadn't returned the pencil he'd lent him. A-kun asked B-kun to return the pencil, but B-kun apologized, saying that he had been busy and had forgotten. A-kun and B-kun talked it over and decided that from now on they would keep their promises to each other."

[0221] Return and Review of Works of Fiction

[0222] The server formats the generated short story and returns it to the user's device in JSON format.

[0223] The terminal displays the short story received from the server and allows the user to review it, allowing the user to read the generated work of fiction.

[0224] Classroom use and discussion

[0225] The user (teacher) can use the displayed short story in class and read it aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems, thereby concretely learning the elements of the SEL program.

[0226] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills. Furthermore, by combining it with an emotion engine, it is possible to provide a more personalized educational experience.

[0227] The processing flow will be explained below.

[0228] Step 1:

[0229] The user opens a dedicated application or web form. In the input field, they fill in the details of the dispute, for example, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[0230] Step 2:

[0231] The device converts the input information into JSON format and sends the converted data to the specified API endpoint (e.g., / generate_story).

[0232] Step 3:

[0233] The server receives the JSON data sent from the device, analyzes it, and extracts detailed information about the dispute.

[0234] Step 4:

[0235] The server sends the analyzed information to the emotion engine, which recognizes the user's emotion based on the conflict.

[0236] Step 5:

[0237] The server receives the emotion information obtained from the emotion engine and sends it along with the analyzed information to the generation engine, which then generates a fictional work based on the input data and emotion information.

[0238] Step 6:

[0239] The server formats the fictional work returned by the generation engine and returns the generated fictional work in JSON format to the user's device.

[0240] Step 7:

[0241] The device parses the JSON-formatted fictional work received from the server, converts it into a human-readable format, and displays the converted fictional work for the user to review.

[0242] Step 8:

[0243] The user (teacher) uses the displayed fictional work in class. The user reads the short story to the entire class and discusses the conflict with all the students. Through the discussion, children can learn to express emotions, develop empathy, and problem-solving skills.

[0244] In this way, the use of the emotion engine enables a system that provides a more personalized educational experience.

[0245] Example 2

[0246] 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."

[0247] The current education system provides limited opportunities for children to specifically learn emotional expression, empathy, and problem-solving skills. It also lacks ways to effectively use everyday conflicts as educational resources. This calls for a new system to increase opportunities for social and emotional learning (SEL) and promote children's emotional growth.

[0248] 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.

[0249] In this invention, the server includes an emotion engine that analyzes input information and recognizes emotions, a means for generating a fictional work using a generation engine based on the results of the emotion engine, and a means for returning the generated work to the user's terminal. This allows a user to input information about everyday conflicts, recognize emotions based on that information, and generate and return an appropriate fictional work. This provides concrete social and emotional learning opportunities in educational settings and effectively fosters children's emotional expression, empathy, and problem-solving skills.

[0250] The "input means" is a part of the system that provides a function that allows users to input specific information about disputes on a daily basis.

[0251] The "transmission means" is a part of the system that has the function of transmitting input information to the server.

[0252] A "server" is a computing device that receives and analyzes information over a network and performs specific processing.

[0253] The "emotion engine" is software that recognizes emotions from dispute information entered by the user.

[0254] A "generation engine" is software that uses natural language processing technology to generate fictional works based on analyzed information.

[0255] A "generator" is a part of the system that has the function of generating a work of fiction based on the analyzed information.

[0256] The "returning means" is a part of the system that has the function of returning the fictional work generated by the server to the user's terminal.

[0257] A "verification means" is the part of the system that allows a user to verify a returned work of fiction.

[0258] The "discussion tool" is part of a system for using the generated fictional works in class and holding discussions.

[0259] "Natural language processing technology" is a computer science technology for understanding and generating human language.

[0260] This system allows users to input information about everyday disputes, and then generates fictional works based on that information, which can then be used as teaching materials for moral education. The system is particularly equipped with an emotion engine that recognizes the user's emotions, aiming to provide a more effective educational experience. This system allows children to specifically learn emotional expression, empathy, and problem-solving skills.

[0261] Hardware and software used

[0262] 1. User Device

[0263] It uses a computer, tablet, or smartphone, which can be operated via a dedicated application or a web browser.

[0264] 2. Server

[0265] The information is received, analyzed, fictionalized, and returned using servers of cloud service providers (e.g., Amazon Web Services, Microsoft® Azure®, Google Cloud Platform).

[0266] 3. Emotion Engine

[0267] Software that recognizes user emotions from input dispute information. Examples include Microsoft Azure's Cognitive Services and Google Cloud's Natural Language API.

[0268] 4. Generation Engine

[0269] Software that uses natural language processing technology to generate fictional works based on input information and recognized emotions. Specific examples include OpenAI's GPT-3 and GPT-4 (registered trademarks).

[0270] System operation example

[0271] Enter and submit dispute information

[0272] Users enter details of the dispute through a dedicated application or a web form. For example, they enter information like, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[0273] The device converts the input information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[0274] Information analysis and emotion recognition

[0275] The server receives the JSON data sent from the device and analyzes the details of the dispute. Using the emotion engine, it recognizes the user's emotion from the entered details of the dispute. This emotion information is included in the analyzed data passed to the generation engine.

[0276] Generating a work of fiction

[0277] The server then passes the analyzed information and emotion information to the generation engine, instructing it to generate a fictional work. For example, if the user's emotion is "anger," a story will unfold according to that emotion.

[0278] An example of what might be generated is a short story like this:

[0279] "One day in the classroom, A was worried because B hadn't returned the pencil he'd lent him. A asked B to return the pencil, but B apologized, saying that he had been busy and had forgotten. A and B talked it over and decided that from now on they would keep their promises to each other."

[0280] Return and Review of Works of Fiction

[0281] The server formats the generated short story and returns it to the user's device in JSON format.

[0282] The terminal displays the short story received from the server and allows the user to review it, allowing the user to read the generated work of fiction.

[0283] Classroom use and discussion

[0284] The user (teacher) can use the displayed short story in class and read it aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems, thereby concretely learning the elements of the SEL program.

[0285] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills. Furthermore, by combining it with an emotion engine, it is possible to provide a more personalized educational experience.

[0286] Examples of prompt statements

[0287] A possible prompt might be written as follows:

[0288] Dispute: I lent my friend a pencil and he never returned it, so we got into an argument.

[0289] Emotion: Anger

[0290] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0291] Step 1:

[0292] Users enter details of the dispute through a dedicated application or web form. For example, they might enter a specific situation, such as, "I lent my friend a pencil, but he never returned it, and we got into an argument." The entered data is sent directly to the device in JSON format.

[0293] Input: User-entered dispute information

[0294] Output: JSON formatted dispute information

[0295] What happens: A user opens an application or web form, enters details about the dispute, and presses the "Submit" button.

[0296] Step 2:

[0297] The device receives the dispute information entered by the user and converts it into JSON format, which is then sent to the server, for example, to the API endpoint ( / generate_story).

[0298] Input: User-entered dispute information

[0299] Output: JSON formatted dispute information sent to the server

[0300] Specific operation: The device formats the input information into the appropriate JSON format and sends it to the specified API endpoint.

[0301] Step 3:

[0302] The server receives the JSON data sent from the device, analyzes it, and extracts details of the dispute. It then uses an emotion engine to recognize the user's emotion from the input information. For example, based on the keyword "argument," it determines that the emotion is "anger."

[0303] Input: JSON formatted dispute information sent from the device

[0304] Output: Analyzed details and emotional information of the conflict

[0305] Specific operation: The server analyzes detailed information about the dispute and uses an emotion engine to recognize emotions.

[0306] Step 4:

[0307] The server passes the analyzed details of the dispute and the recognized emotion information to a generation engine, instructing it to generate a fictional work. For example, if the emotion is "anger," a story will unfold according to that emotion. The generation engine uses natural language processing technology to generate a fictional work.

[0308] Input: Analyzed details and emotional information about the conflict

[0309] Output: A generated work of fiction

[0310] What it does: Pass data to a generation engine and generate a work of fiction using natural language processing techniques.

[0311] Step 5:

[0312] The server formats the generated fictional work and returns it to the user's device in JSON format.

[0313] Input: A generated work of fiction

[0314] Output: JSON fiction data

[0315] Specific operation: The server formats the generated fictional work into fields and returns it to the terminal in JSON format.

[0316] Step 6:

[0317] The terminal displays the fictional work received from the server to the user, who can then view and read the work.

[0318] Input: JSON formatted fiction data

[0319] Output: A work of fiction displayed to the user

[0320] Specific behavior: The device properly formats and displays the received work of fiction for the user to review.

[0321] Step 7:

[0322] The user (teacher) uses the generated short story in class and reads it to all the students. The students comment on the feelings and actions of the characters and discuss how to solve the problems.

[0323] Input: A work of fiction displayed to the user

[0324] Output: Class discussion and learning outcomes

[0325] Specific operations: The user (teacher) reads a work of fiction to the students and engages in a discussion.

[0326] (Application example 2)

[0327] 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."

[0328] One issue facing brick-and-mortar stores is the lack of effective training methods for staff to resolve disputes that arise when dealing with customers. It's particularly difficult to accurately grasp customer emotions and learn how to respond appropriately. Current training methods are insufficient to teach specific skills that can be applied in real-world situations, resulting in lower customer satisfaction and increased customer trouble.

[0329] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion engine means for analyzing input information and recognizing emotions, generation engine means for generating a fictional work based on the analyzed information and emotion information, and return means for returning the generated work to the user's terminal. This allows users to generate fictional works corresponding to emotions based on information about disputes that arise in actual customer interactions and use them as training materials. Staff can learn specific response methods through the generated works and improve their customer interaction skills.

[0330] "Input means" refers to a device or interface that allows users to input specific information about disputes that arise on a daily basis.

[0331] "Transmission means" refers to a device or protocol that has the function of transmitting input information to a server.

[0332] "Generation means" means a system or software that has the function of analyzing the information received by the server and generating a work of fiction based on a generation engine.

[0333] An "emotion engine" is a technology or algorithm that analyzes the information received by the server and recognizes the user's emotions.

[0334] "Returning means" refers to a communication function for returning the created work to the user's terminal.

[0335] "Verification means" refers to a device or application that allows a user to view and verify the returned work.

[0336] "Discussion tool" refers to an interface or functionality for using the generated work to hold discussions in classes or training.

[0337] "Natural language processing technology" is a general term for technology that uses computers to analyze and understand human language.

[0338] This invention is a system that inputs information about customer troubles that staff members actually encounter in a brick-and-mortar store, and generates fictional works based on that information to be used as educational content. The system includes a user terminal, a server, a generation engine, and an emotion engine. Each component and processing step is described in detail below.

[0339] System Configuration

[0340] 1. User Device

[0341] The user terminal is a device such as a smartphone or tablet. This terminal provides an input means for staff to input and submit customer trouble information through a dedicated application or web form. It also has the function of displaying and checking the fictional work that is later generated.

[0342] 2. Server

[0343] The server has the following main functions:

[0344] Analysis of information: The server receives and analyzes the dispute information sent from the user terminal.

[0345] Emotion recognition: An emotion engine is used to recognize customer emotions from dispute information. Specific technologies used include IBM Watson® emotion analysis API.

[0346] Fiction generation: Using the analyzed information and sentiment information, fiction is generated through a generative engine (e.g., OpenAI's GPT-3), which uses natural language processing techniques.

[0347] Return: The generated fictional work is formatted and returned to the user's device.

[0348] 3. Generation Engine

[0349] The generation engine uses natural language processing techniques to generate fictional stories based on conflicts, specifically using AI models such as OpenAI's GPT-3. Example prompts include:

[0350] "A customer wants to return an item, but is having trouble because it violates the return policy. The customer is dissatisfied. Generate a story based on this."

[0351] Specific processing of the program

[0352] Enter and submit information

[0353] The user (staff member) enters details of the customer issue through a dedicated application or web form. For example, they might enter information such as, "The customer wants to return a product, but we are having trouble handling this because it violates our return policy." Once the information is complete, the user presses the "Submit" button. The terminal converts this information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[0354] Information analysis and emotion recognition

[0355] The server receives the JSON data sent from the device and analyzes the details of the dispute. At the same time, it uses an emotion engine to recognize the customer's emotions from the detailed dispute information entered. This emotion information is included in the analyzed data passed to the generation engine. The emotion engine uses IBM Watson's emotion analysis API.

[0356] Generating a work of fiction

[0357] The server passes the analyzed information and emotion information to a generation engine (such as OpenAI's GPT-3) and instructs it to generate a work of fiction. For example, if the customer's emotion is "dissatisfied," a story will unfold that corresponds to that emotion. An example of the generated content could be a short story like the one below:

[0358] "One day, clerk A received an item from customer B that he wanted to return, but it violated the return policy. B looked dissatisfied and said, 'This item is defective. Please do something about it.' A spoke to a manager and was able to alleviate B's frustration by offering a discount coupon for their next purchase instead of a return."

[0359] Return and Review of Works of Fiction

[0360] The server formats the generated fictional work and returns it in JSON format to the user's device. The user's device displays the fictional work received from the server and allows the user to confirm it, allowing the user to read the generated fictional work.

[0361] Classroom use and discussion

[0362] The user (e.g., a store staff member) can use the displayed short story in a training session and read it aloud to all staff members. The staff members can then comment on the feelings and actions of the characters and discuss how to solve the problems, thereby learning specific skills for dealing with customers.

[0363] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0364] Step 1: Enter and submit information

[0365] The user enters details of the customer issue through a dedicated application or web form. For example, they might enter information such as, "The customer wants to return a product, but we are having trouble doing so because it violates our return policy." The entered information is converted to JSON format within the application. The user then presses the "Submit" button, which sends the entered information to an API endpoint (e.g., / generate_story). Specifically, the form is submitted by touching the smartphone.

[0366] input:

[0367] Detailed information about customer trouble

[0368] output:

[0369] Information converted to JSON format

[0370] Step 2: Receiving and analyzing information

[0371] The server receives the JSON data sent from the device. The received data is passed to the analysis module, where detailed information about the dispute is extracted through text analysis. Based on this analysis data, the server calls an emotion engine (e.g., IBM Watson's emotion analysis API) to recognize the customer's emotions.

[0372] input:

[0373] JSON format customer trouble information

[0374] output:

[0375] Parsed text data

[0376] Customer sentiment information

[0377] Step 3: Recognize emotions

[0378] The server uses an emotion engine to analyze customer emotions. At this time, emotions such as "dissatisfaction" and "anger" are recognized from the text data. The analyzed emotion data is then passed to a generation engine. The server then integrates the text analysis results with the emotion information.

[0379] input:

[0380] Parsed text data

[0381] output:

[0382] Customer sentiment information

[0383] Step 4: Generate a work of fiction

[0384] Based on the analyzed information and emotion information, the server issues instructions to a generation engine (e.g., OpenAI's GPT-3) to generate a work of fiction. The generation engine generates a story based on a specified prompt. For example, it sends a prompt such as, "A customer wants to return a product, but a problem has arisen because it violates the return policy. The customer is dissatisfied. Please generate a story based on this."

[0385] input:

[0386] Integrated text and sentiment information

[0387] Prompt statement

[0388] output:

[0389] Generated works of fiction

[0390] Step 5: Return your work of fiction

[0391] The server then formats the generated fictional work into JSON format again and sends it back to the user's device, where it can be viewed.

[0392] input:

[0393] Generated works of fiction

[0394] output:

[0395] Works of fiction in JSON format

[0396] Step 6: Identifying works of fiction

[0397] The user terminal displays the fictional work received from the server and allows the user to review it. This allows store staff to read the generated fictional work. Specific operations include displaying the work on a smartphone or tablet screen.

[0398] input:

[0399] Works of fiction in JSON format

[0400] output:

[0401] The fictional work displayed

[0402] Step 7: Classroom Use and Discussion

[0403] Users (such as store staff) train based on the displayed fictional work. Specifically, the work is read aloud during the training session, and staff discuss the characters' actions and emotions. This allows them to learn skills that will be useful when dealing with real customers.

[0404] input:

[0405] The fictional work displayed

[0406] output:

[0407] Training discussion materials

[0408] The above processing steps realize a system for effectively providing customer service training for brick-and-mortar stores.

[0409] 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.

[0410] 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.

[0411] 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.

[0412] [Second embodiment]

[0413] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0414] 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.

[0415] 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).

[0416] 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.

[0417] 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.

[0418] 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).

[0419] 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. 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.

[0420] 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.

[0421] 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.

[0422] 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.

[0423] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0424] 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."

[0425] This system allows users to input information about everyday disputes, and uses the information to generate fictional stories that can be used as teaching materials for moral education. This system allows children to concretely learn emotional expression, empathy, and problem-solving skills.

[0426] The system of the present invention is implemented by the following configuration and processing steps.

[0427] System Configuration

[0428] 1. User Device

[0429] As an input method, we provide a function that allows users to enter specific information about disputes on a daily basis. This is realized by a dedicated application or a web form.

[0430] As a transmission means, it has a function of transmitting the input information to the server.

[0431] 2. Server

[0432] As an analytical tool, it has the function of analyzing dispute information sent by users.

[0433] As a generation means, it has the function of generating fictional works using a generation engine based on the analyzed information.

[0434] As a return means, it has a function to send the generated fictional work to the user's terminal.

[0435] 3. Generation Engine

[0436] Software that uses natural language processing technology to generate fictional works based on detailed information about disputes.

[0437] 4. User Device

[0438] As a means of verification, it has the ability to display or play the returned fictional work.

[0439] As a means of discussion, we provide a function to use the generated fictional works in classes and hold discussions.

[0440] Specific examples of program processing

[0441] Enter and submit dispute information

[0442] Users enter details of the dispute through a dedicated application or a web form. For example, they enter information like, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[0443] The device converts the input information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[0444] Analyzing information and generating fiction

[0445] The server receives the JSON data sent from the device, analyzes the details of the dispute, and then passes the analyzed information to a generation engine (using natural language processing technology) to instruct it to generate a work of fiction.

[0446] An example of what might be generated is a short story like this:

[0447] "One day in the classroom, A-kun started to worry that B-kun hadn't returned the pencil he'd lent him. A-kun asked B-kun to return the pencil, but B-kun apologized, saying that he had been busy and had forgotten. A-kun and B-kun talked it over and decided that from now on they would keep their promises to each other."

[0448] Return and Review of Works of Fiction

[0449] The server formats the generated short story and returns it to the user's device in JSON format.

[0450] The terminal displays the short story received from the server and allows the user to review it, allowing the user to read the generated work of fiction.

[0451] Classroom use and discussion

[0452] The user (teacher) can use the displayed short story in class and read it aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems, thereby concretely learning the elements of the SEL program.

[0453] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills.

[0454] The processing flow will be explained below.

[0455] Step 1:

[0456] The user opens a dedicated application or web form. In the input field, they fill in the details of the dispute, for example, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[0457] Step 2:

[0458] The device converts the input information into JSON format and sends the converted data to the specified API endpoint (e.g., / generate_story).

[0459] Step 3:

[0460] The server receives the JSON data sent from the device, analyzes the received JSON data, extracts detailed information about the dispute, and executes an analysis method to analyze the extracted information.

[0461] Step 4:

[0462] The server passes the analyzed information to a generation engine, which uses natural language processing technology to generate a work of fiction based on the analyzed information.

[0463] Step 5:

[0464] The server formats the fictional work returned by the generation engine and returns the generated fictional work in JSON format to the user's device. The server constructs an appropriate API response to send back.

[0465] Step 6:

[0466] The device parses the JSON-formatted fictional work received from the server, converts it into a human-readable format, and displays the converted fictional work for the user to review.

[0467] Step 7:

[0468] The user (teacher) uses a fictional work in class. The user reads the displayed fictional work aloud to the entire class. After reading, the user starts a discussion with all the students, in which they share their opinions about the feelings and actions of the characters.

[0469] Example 1

[0470] 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."

[0471] In the traditional education system, it is difficult for children to concretely learn emotional expression, empathy, and problem-solving skills through everyday conflicts. As a result, the effectiveness of SEL (Social and Emotional Learning) programs is limited, and education based on real-life situations is not sufficiently provided.

[0472] 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.

[0473] In this invention, the server includes input means for a user to input information about conflicts that occur on a daily basis, transmission means for transmitting the input information to the server, generation means for the server to analyze the received information and generate a fictional work using natural language processing technology, return means for returning the generated work to the user's terminal, and confirmation means for the user to confirm the returned work. This enables children to learn emotional expression, empathy, and problem-solving skills through fictional works based on specific conflict scenarios.

[0474] "Input means" refers to the means by which users input specific information about disputes that arise on a daily basis, and includes dedicated applications and web forms.

[0475] The "transmission means" is a means for transmitting information input by the input means to a server, and includes a function for transmitting data using a communication protocol (e.g., HTTP).

[0476] "Generation means" means the means by which the server analyzes the information it receives and generates a work of fiction using natural language processing technology, including a generative AI model.

[0477] The "returning means" is a means for returning the fictional work generated by the generating means to the user's terminal, and includes a function for transmitting data using a communication protocol.

[0478] "Verification means" refers to a means by which the user can verify the returned fictional work, and includes a function for displaying it on the terminal.

[0479] "Discussion tools" are means for using the generated fictional works in class and for children to discuss the assignments, including educational frameworks and tools.

[0480] The "generation engine" is software that uses natural language processing technology to generate fictional works based on dispute information.

[0481] A "prompt" is a document that provides specific instructions to the generation engine and contains detailed information about the dispute.

[0482] MODE FOR CARRYING OUT THE INVENTION

[0483] This system allows users to input information about everyday disputes, and uses the information to generate fictional stories that can be used as teaching materials for moral education. This system allows children to concretely learn emotional expression, empathy, and problem-solving skills.

[0484] System Configuration

[0485] The system of the present invention has the following hardware and software configuration.

[0486] 1. User Device

[0487] An input means using a dedicated application or web form is provided, which allows users to input specific information about disputes on a daily basis.

[0488] As a transmission method, it has a function to send the input information to the server, using the HTTP protocol.

[0489] 2. Server

[0490] As an analytical tool, it has a function to analyze dispute information sent by users. This analysis is handled by software on the server, and parses data in JSON format.

[0491] As a means of generation, it has the ability to generate fictional works using generative AI models (e.g., GPT-3) based on the analyzed information.

[0492] As a means of returning the work, the system has the function of sending the generated fictional work to the user's device, and this also uses the HTTP protocol.

[0493] 3. Generation Engine

[0494] This software uses natural language processing technology to generate fictional works based on detailed information about disputes. The generative AI model used is specifically GPT-3.

[0495] 4. User Device

[0496] The returned fictional work is displayed as a means of verification, and it also has a playback function that allows users to use the fictional work in classes after verification.

[0497] The generated fictional works are used in classes as a means of discussion, and functions for holding discussions are provided, such as comment functions and video playback functions.

[0498] Specific examples of program processing

[0499] Enter and submit dispute information

[0500] The user enters information about the dispute through a dedicated application or a web form. For example, they might enter, "I lent my friend a pencil, but he didn't return it, and we got into an argument." Once they've finished entering information, they press the "Submit" button. The device converts the entered information into JSON format and sends it to the specified API endpoint.

[0501] Analyzing information and generating fiction

[0502] The server receives the JSON data sent from the device and analyzes the details of the dispute. It then uses the analyzed information to instruct the generation engine to generate a work of fiction using natural language processing technology. An example of the generated content could be a short story like this:

[0503] "You lent a friend a pencil and they didn't return it, and you got into an argument. Write a children's fiction story based on this argument."

[0504] Examples of generated short stories include:

[0505] "One day in the classroom, A-kun started to worry that B-kun hadn't returned the pencil he'd lent him. A-kun asked B-kun to return the pencil, but B-kun apologized, saying that he had been busy and had forgotten. A-kun and B-kun talked it over and decided that from now on they would keep their promises to each other."

[0506] Return and Review of Works of Fiction

[0507] The server formats the generated short story and returns it in JSON format to the user's device, which then displays the short story received from the server for the user to confirm.

[0508] Classroom use and discussion

[0509] Teachers can use the generated short stories in class and read them to all students. Students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems. This allows students to concretely learn the elements of SEL (social and emotional learning) programs.

[0510] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills.

[0511] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0512] Step 1:

[0513] Users open a dedicated application or web form and enter details of everyday disputes into text fields, such as "I lent my friend a pencil and he didn't return it, which led to an argument." After completing the input, users press a "Submit" button. This input data becomes the input for the next processing step.

[0514] Step 2:

[0515] The device converts the conflict information entered by the user into JSON format. For example, the input text is converted to {"conflict": "I lent my friend a pencil and he didn't return it, so we had an argument"}. The converted JSON data is sent as an HTTP POST request to the specified API endpoint (e.g., / generate_story). This becomes the input for the next processing step.

[0516] Step 3:

[0517] The server receives an HTTP request sent from a device. The received JSON data is passed to an internal process for parsing. For example, the data to be parsed is {"conflict": "I lent my friend a pencil, but he didn't return it, and we had an argument"}. The parsed data is passed to the generation engine for the next processing step.

[0518] Step 4:

[0519] The server uses the analyzed data to generate a prompt for a generative AI model (e.g., GPT-3). An example prompt might be, "I lent a pencil to a friend, but he didn't return it, and we got into an argument. Please write a fictional story for children based on this argument." This prompt is input into the generation engine, and the AI ​​model generates a work of fiction.

[0520] Step 5:

[0521] The generation engine (using natural language processing technology) receives the prompt and generates a work of fiction based on the details of the dispute. An example of a generated short story might be, "One day in the classroom, student A began to worry that student B had not returned the pencil he had lent to him. Student A asked student B, "Please return the pencil," but student B apologized, saying that he had been busy and had forgotten. Student A and student B talked it over and decided to keep their promise to each other in the future." This generated work is then passed to the next processing step.

[0522] Step 6:

[0523] The server formats the generated fiction and converts it back into JSON format, for example, {"story": "One day in the classroom, student A began to worry that student B had not returned the pencil he had lent him..."}. This JSON data is then sent back to the user's device.

[0524] Step 7:

[0525] The device receives the JSON data returned from the server and displays the fictional work on the application screen based on the received data, allowing the user to view the generated fictional work.

[0526] Step 8:

[0527] Teachers can use the generated fictional works in class and read them aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve problems. This allows students to learn emotional expression, empathy, and problem-solving skills through concrete scenarios.

[0528] Through this processing step, the system of the present invention can transform everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills.

[0529] (Application example 1)

[0530] 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."

[0531] Until now, there has been no system that generates fictional stories based on everyday conflicts and uses them in moral education. This has resulted in a lack of educational materials that allow children to specifically learn emotional expression, empathy, and problem-solving skills. Furthermore, there is no function to share the generated fictional stories with family and friends, or to hold quizzes or discussions based on the stories, preventing the full educational effect of this system.

[0532] 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.

[0533] In this invention, the server includes input means for a user to input information about disputes that arise on a daily basis, transmission means for transmitting the input information, generation means for analyzing the received information and generating a fictional work based on a generation engine, return means for returning the generated work to the user's terminal, confirmation means for confirming the returned work, learning means for providing educational quizzes and discussion functions for learning interpersonal problem solving and emotional empathy, and sharing means for sharing the generated work with family and friends. This allows children to concretely learn emotional expression, empathy, and problem-solving skills through fictional works, and to gain deeper understanding and learning by sharing them with family and friends.

[0534] "Input means" refers to a device or interface that allows a user to input information about disputes that arise on a daily basis.

[0535] The "transmission means" is a device or function for transmitting input information to a server.

[0536] An "analysis means" is a device or software module for analyzing information received by the server.

[0537] A "generator" is a device or software module that uses a generative engine to generate a work of fiction based on the analyzed information.

[0538] "Returning means" is a device or function for returning the generated work of fiction to the user's terminal.

[0539] "Verification means" is a device or function that allows a user to verify a returned work of fiction.

[0540] A "learning tool" is a device or software module that provides educational quizzes and discussion functions for learning interpersonal problem solving and emotional empathy.

[0541] A "sharing means" is a device or function for sharing the created fictional work with family and friends.

[0542] "Natural language processing technology" is a technology that enables computers to understand and generate human language.

[0543] The present invention is a system that allows users to input information about everyday disputes and use fictional works generated based on that information as teaching materials for moral education. This system is realized with the following hardware and software configuration.

[0544] System Configuration

[0545] 1. User Device

[0546] As an input method, we provide a function that allows users to enter specific information about disputes on a daily basis. This is realized by a dedicated application or a web form.

[0547] As a transmission means, it has a function of transmitting the input information to the server.

[0548] As a means of verification, it has the ability to display or play the returned fictional work.

[0549] As a learning tool, it provides functions for quizzes and discussions based on the fictional works that are generated, and also allows users to share their works with their families and friends.

[0550] 2. Server

[0551] As an analytical tool, it has the function of analyzing dispute information sent by users and converting it into an appropriate fictional work. Specifically, it generates a fictional work using a generation engine based on the analyzed information.

[0552] The generative method is to generate fictional works based on the analyzed information, using natural language processing techniques to generate stories based on the details of the dispute.

[0553] As a return means, it has a function to return the generated fictional work to the user's terminal.

[0554] Program processing explanation

[0555] The server uses cloud servers such as Alexa and Google Cloud Platform (GCP). For natural language processing, OpenAI's GPT model is used. The program's processing begins with the user entering information about the dispute, which is then converted into JSON format and sent to the server. The server analyzes the received information and generates a work of fiction using a generation engine. The generated work of fiction is then sent back to the user's device, where the user can view it.

[0556] For example:

[0557] Entering information about a dispute: The user enters information such as "I lent my friend a pencil, but he never returned it, and we got into an argument."

[0558] Example prompt: "You lent a friend a pencil, but he didn't return it, and you got into an argument. Generate a fictional moral story based on this."

[0559] This system allows users to concretely learn emotional expression, empathy, and problem-solving skills through fictional works, and allows them to share the created works with family and friends.

[0560] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0561] Step 1:

[0562] The user enters the dispute information

[0563] Users can use a dedicated application or a web form to enter specific details about everyday disputes. For example, they can enter information like, "I lent my friend a pencil and he didn't return it, so we got into an argument." The input data is represented in JSON format. Based on the input, the system stores it in a database and prepares it for the next step.

[0564] Step 2:

[0565] Sending data from the device to the server

[0566] The user device converts the entered dispute information into JSON format and sends it to the specified API endpoint (e.g., / generate_story). This is done using an HTTP POST request, which sends the input data to the server. The server then validates the received data and checks for any problems before proceeding with analysis.

[0567] Step 3:

[0568] The server analyzes the information

[0569] The server receives the JSON data sent from the device. This analysis method analyzes the received data and understands the meaning of the input information. Specifically, it uses natural language processing technology to analyze the details of the dispute. Based on this analysis, it generates prompts to generate appropriate fiction works.

[0570] Step 4:

[0571] Generate a work of fiction

[0572] The server passes the parsed information to a generation engine, which generates a fictional work based on the prompt. This generation method uses natural language processing techniques such as OpenAI's GPT model. For example, if the prompt is "I lent my friend a pencil and he didn't return it, and we got into an argument. Please generate a fictional story with a moral based on this content.", the engine will generate a corresponding fictional work. The generated fictional work is saved in JSON format.

[0573] Step 5:

[0574] Send the generated work back to the user's device

[0575] The server formats the generated work of fiction and returns it to the user's device. This returns the generated JSON data as an HTTP response to the user's device. The user's device parses the received JSON data and displays or plays the work of fiction to the user.

[0576] Step 6:

[0577] Users can review their work and use the learning mode

[0578] The user reviews the returned fictional work. This reviewing means provides the user's device with the ability to display and play the work in text or audio. The user can also use the learning means to participate in quizzes and discussions based on the work. This allows the user to specifically learn skills such as empathy and problem-solving.

[0579] Step 7:

[0580] Share your creations

[0581] Users can share the fictional works they create with their families and friends. This sharing method generates a link for sharing the work and provides the ability to share it with others via social networking sites, email, etc. The shared work can then be used by others to view and learn from.

[0582] 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.

[0583] This system allows users to input information about everyday disputes, and then generates fictional works based on that information, which can then be used as teaching materials for moral education. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the system aims to provide a more effective educational experience. This system allows children to concretely learn emotional expression, empathy, and problem-solving skills.

[0584] The system of the present invention is implemented by the following configuration and processing steps.

[0585] System Configuration

[0586] 1. User Device

[0587] As an input method, we provide a function that allows users to enter specific information about disputes on a daily basis. This is realized by a dedicated application or a web form.

[0588] As a transmission means, it has a function of transmitting the input information to the server.

[0589] 2. Server

[0590] As an analytical tool, it has the function of analyzing dispute information sent by users.

[0591] As a generation means, it has the function of generating fictional works using a generation engine based on the analyzed information.

[0592] As an emotion engine, it has the ability to recognize the user's emotions from the dispute information entered by the user.

[0593] As a return means, it has a function to send the generated fictional work to the user's terminal.

[0594] 3. Generation Engine

[0595] Software that uses natural language processing technology to generate fictional works based on detailed dispute information and perceived emotions.

[0596] 4. User Device

[0597] As a means of verification, it has the ability to display or play the returned fictional work.

[0598] As a means of discussion, we provide a function to use the generated fictional works in classes and hold discussions.

[0599] Specific examples of program processing

[0600] Enter and submit dispute information

[0601] Users enter details of the dispute through a dedicated application or a web form. For example, they enter information like, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[0602] The device converts the input information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[0603] Information analysis and emotion recognition

[0604] The server receives the JSON data sent from the device and analyzes the details of the dispute. It also uses an emotion engine to recognize the user's emotion from the entered details of the dispute. This emotion information is included in the analyzed data passed to the generation engine.

[0605] Generating a work of fiction

[0606] The server then passes the analyzed information and emotional information to a generation engine (using natural language processing technology) and instructs it to generate a fictional work. For example, if the user's emotion is "anger," a story will unfold that corresponds to that emotion.

[0607] An example of what might be generated is a short story like this:

[0608] "One day in the classroom, A-kun started to worry that B-kun hadn't returned the pencil he'd lent him. A-kun asked B-kun to return the pencil, but B-kun apologized, saying that he had been busy and had forgotten. A-kun and B-kun talked it over and decided that from now on they would keep their promises to each other."

[0609] Return and Review of Works of Fiction

[0610] The server formats the generated short story and returns it to the user's device in JSON format.

[0611] The terminal displays the short story received from the server and allows the user to review it, allowing the user to read the generated work of fiction.

[0612] Classroom use and discussion

[0613] The user (teacher) can use the displayed short story in class and read it aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems, thereby concretely learning the elements of the SEL program.

[0614] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills. Furthermore, by combining it with an emotion engine, it is possible to provide a more personalized educational experience.

[0615] The processing flow will be explained below.

[0616] Step 1:

[0617] The user opens a dedicated application or web form. In the input field, they fill in the details of the dispute, for example, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[0618] Step 2:

[0619] The device converts the input information into JSON format and sends the converted data to the specified API endpoint (e.g., / generate_story).

[0620] Step 3:

[0621] The server receives the JSON data sent from the device, analyzes it, and extracts detailed information about the dispute.

[0622] Step 4:

[0623] The server sends the analyzed information to the emotion engine, which recognizes the user's emotion based on the conflict.

[0624] Step 5:

[0625] The server receives the emotion information obtained from the emotion engine and sends it along with the analyzed information to the generation engine, which then generates a fictional work based on the input data and emotion information.

[0626] Step 6:

[0627] The server formats the fictional work returned by the generation engine and returns the generated fictional work in JSON format to the user's device.

[0628] Step 7:

[0629] The device parses the JSON-formatted fictional work received from the server, converts it into a human-readable format, and displays the converted fictional work for the user to review.

[0630] Step 8:

[0631] The user (teacher) uses the displayed fictional work in class. The user reads the short story to the entire class and discusses the conflict with all the students. Through the discussion, children can learn to express emotions, develop empathy, and problem-solving skills.

[0632] In this way, the use of the emotion engine enables a system that provides a more personalized educational experience.

[0633] Example 2

[0634] 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."

[0635] The current education system provides limited opportunities for children to specifically learn emotional expression, empathy, and problem-solving skills. It also lacks ways to effectively use everyday conflicts as educational resources. This calls for a new system to increase opportunities for social and emotional learning (SEL) and promote children's emotional growth.

[0636] 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.

[0637] In this invention, the server includes an emotion engine that analyzes input information and recognizes emotions, a means for generating a fictional work using a generation engine based on the results of the emotion engine, and a means for returning the generated work to the user's terminal. This allows a user to input information about everyday conflicts, recognize emotions based on that information, and generate and return an appropriate fictional work. This provides concrete social and emotional learning opportunities in educational settings and effectively fosters children's emotional expression, empathy, and problem-solving skills.

[0638] The "input means" is a part of the system that provides a function that allows users to input specific information about disputes on a daily basis.

[0639] The "transmission means" is a part of the system that has the function of transmitting input information to the server.

[0640] A "server" is a computing device that receives and analyzes information over a network and performs specific processing.

[0641] The "emotion engine" is software that recognizes emotions from dispute information entered by the user.

[0642] A "generation engine" is software that uses natural language processing technology to generate fictional works based on analyzed information.

[0643] A "generator" is a part of the system that has the function of generating a work of fiction based on the analyzed information.

[0644] The "returning means" is a part of the system that has the function of returning the fictional work generated by the server to the user's terminal.

[0645] A "verification means" is the part of the system that allows a user to verify a returned work of fiction.

[0646] The "discussion tool" is part of a system for using the generated fictional works in class and holding discussions.

[0647] "Natural language processing technology" is a computer science technology for understanding and generating human language.

[0648] This system allows users to input information about everyday disputes, and then generates fictional works based on that information, which can then be used as teaching materials for moral education. The system is particularly equipped with an emotion engine that recognizes the user's emotions, aiming to provide a more effective educational experience. This system allows children to specifically learn emotional expression, empathy, and problem-solving skills.

[0649] Hardware and software used

[0650] 1. User Device

[0651] It uses a computer, tablet, or smartphone, which can be operated via a dedicated application or a web browser.

[0652] 2. Server

[0653] The information is received, analyzed, the fiction is generated, and then returned to us using the servers of cloud service providers (e.g., Amazon Web Services, Microsoft Azure, Google Cloud Platform).

[0654] 3. Emotion Engine

[0655] Software that recognizes user emotions from input dispute information. Examples include Microsoft Azure's Cognitive Services and Google Cloud's Natural Language API.

[0656] 4. Generation Engine

[0657] Software that uses natural language processing technology to generate fictional works based on input information and recognized emotions. Specific examples include OpenAI's GPT-3 and GPT-4.

[0658] System operation example

[0659] Enter and submit dispute information

[0660] Users enter details of the dispute through a dedicated application or a web form. For example, they enter information like, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[0661] The device converts the input information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[0662] Information analysis and emotion recognition

[0663] The server receives the JSON data sent from the device and analyzes the details of the dispute. Using the emotion engine, it recognizes the user's emotion from the entered details of the dispute. This emotion information is included in the analyzed data passed to the generation engine.

[0664] Generating a work of fiction

[0665] The server then passes the analyzed information and emotion information to the generation engine, instructing it to generate a fictional work. For example, if the user's emotion is "anger," a story will unfold according to that emotion.

[0666] An example of what might be generated is a short story like this:

[0667] "One day in the classroom, A was worried because B hadn't returned the pencil he'd lent him. A asked B to return the pencil, but B apologized, saying that he had been busy and had forgotten. A and B talked it over and decided that from now on they would keep their promises to each other."

[0668] Return and Review of Works of Fiction

[0669] The server formats the generated short story and returns it to the user's device in JSON format.

[0670] The terminal displays the short story received from the server and allows the user to review it, allowing the user to read the generated work of fiction.

[0671] Classroom use and discussion

[0672] The user (teacher) can use the displayed short story in class and read it aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems, thereby concretely learning the elements of the SEL program.

[0673] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills. Furthermore, by combining it with an emotion engine, it is possible to provide a more personalized educational experience.

[0674] Examples of prompt statements

[0675] A possible prompt might be written as follows:

[0676] Dispute: I lent my friend a pencil and he never returned it, so we got into an argument.

[0677] Emotion: Anger

[0678] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0679] Step 1:

[0680] Users enter details of the dispute through a dedicated application or web form. For example, they might enter a specific situation, such as, "I lent my friend a pencil, but he never returned it, and we got into an argument." The entered data is sent directly to the device in JSON format.

[0681] Input: User-entered dispute information

[0682] Output: JSON formatted dispute information

[0683] What happens: A user opens an application or web form, enters details about the dispute, and presses the "Submit" button.

[0684] Step 2:

[0685] The device receives the dispute information entered by the user and converts it into JSON format, which is then sent to the server, for example, to the API endpoint ( / generate_story).

[0686] Input: User-entered dispute information

[0687] Output: JSON formatted dispute information sent to the server

[0688] Specific operation: The device formats the input information into the appropriate JSON format and sends it to the specified API endpoint.

[0689] Step 3:

[0690] The server receives the JSON data sent from the device, analyzes it, and extracts details of the dispute. It then uses an emotion engine to recognize the user's emotion from the input information. For example, based on the keyword "argument," it determines that the emotion is "anger."

[0691] Input: JSON formatted dispute information sent from the device

[0692] Output: Analyzed details and emotional information of the conflict

[0693] Specific operation: The server analyzes detailed information about the dispute and uses an emotion engine to recognize emotions.

[0694] Step 4:

[0695] The server passes the analyzed details of the dispute and the recognized emotion information to a generation engine, instructing it to generate a fictional work. For example, if the emotion is "anger," a story will unfold according to that emotion. The generation engine uses natural language processing technology to generate a fictional work.

[0696] Input: Analyzed details and emotional information about the conflict

[0697] Output: A generated work of fiction

[0698] What it does: Pass data to a generation engine and generate a work of fiction using natural language processing techniques.

[0699] Step 5:

[0700] The server formats the generated fictional work and returns it to the user's device in JSON format.

[0701] Input: A generated work of fiction

[0702] Output: JSON fiction data

[0703] Specific operation: The server formats the generated fictional work into fields and returns it to the terminal in JSON format.

[0704] Step 6:

[0705] The terminal displays the fictional work received from the server to the user, who can then view and read the work.

[0706] Input: JSON formatted fiction data

[0707] Output: A work of fiction displayed to the user

[0708] Specific behavior: The device properly formats and displays the received work of fiction for the user to review.

[0709] Step 7:

[0710] The user (teacher) uses the generated short story in class and reads it to all the students. The students comment on the feelings and actions of the characters and discuss how to solve the problems.

[0711] Input: A work of fiction displayed to the user

[0712] Output: Class discussion and learning outcomes

[0713] Specific operations: The user (teacher) reads a work of fiction to the students and engages in a discussion.

[0714] (Application example 2)

[0715] 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."

[0716] One issue facing brick-and-mortar stores is the lack of effective training methods for staff to resolve disputes that arise when dealing with customers. It's particularly difficult to accurately grasp customer emotions and learn how to respond appropriately. Current training methods are insufficient to teach specific skills that can be applied in real-world situations, resulting in lower customer satisfaction and increased customer trouble.

[0717] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion engine means for analyzing input information and recognizing emotions, generation engine means for generating a fictional work based on the analyzed information and emotion information, and return means for returning the generated work to the user's terminal. This allows users to generate fictional works corresponding to emotions based on information about disputes that arise in actual customer interactions and use them as training materials. Staff can learn specific response methods through the generated works and improve their customer interaction skills.

[0718] "Input means" refers to a device or interface that allows users to input specific information about disputes that arise on a daily basis.

[0719] "Transmission means" refers to a device or protocol that has the function of transmitting input information to a server.

[0720] "Generation means" means a system or software that has the function of analyzing the information received by the server and generating a work of fiction based on a generation engine.

[0721] An "emotion engine" is a technology or algorithm that analyzes the information received by the server and recognizes the user's emotions.

[0722] "Returning means" refers to a communication function for returning the created work to the user's terminal.

[0723] "Verification means" refers to a device or application that allows a user to view and verify the returned work.

[0724] "Discussion tool" refers to an interface or functionality for using the generated work to hold discussions in classes or training.

[0725] "Natural language processing technology" is a general term for technology that uses computers to analyze and understand human language.

[0726] This invention is a system that inputs information about customer troubles that staff members actually encounter in a brick-and-mortar store, and generates fictional works based on that information to be used as educational content. The system includes a user terminal, a server, a generation engine, and an emotion engine. Each component and processing step is described in detail below.

[0727] System Configuration

[0728] 1. User Device

[0729] The user terminal is a device such as a smartphone or tablet. This terminal provides an input means for staff to input and submit customer trouble information through a dedicated application or web form. It also has the function of displaying and checking the fictional work that is later generated.

[0730] 2. Server

[0731] The server has the following main functions:

[0732] Analysis of information: The server receives and analyzes the dispute information sent from the user terminal.

[0733] Emotion recognition: An emotion engine is used to recognize customer emotions from dispute information. Specific technologies used include IBM Watson's emotion analysis API.

[0734] Fiction generation: Using the analyzed information and sentiment information, fiction is generated through a generative engine (e.g., OpenAI's GPT-3), which uses natural language processing techniques.

[0735] Return: The generated fictional work is formatted and returned to the user's device.

[0736] 3. Generation Engine

[0737] The generation engine uses natural language processing techniques to generate fictional stories based on conflicts, specifically using AI models such as OpenAI's GPT-3. Example prompts include:

[0738] "A customer wants to return an item, but is having trouble because it violates the return policy. The customer is dissatisfied. Generate a story based on this."

[0739] Specific processing of the program

[0740] Enter and submit information

[0741] The user (staff member) enters details of the customer issue through a dedicated application or web form. For example, they might enter information such as, "The customer wants to return a product, but we are having trouble handling this because it violates our return policy." Once the information is complete, the user presses the "Submit" button. The terminal converts this information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[0742] Information analysis and emotion recognition

[0743] The server receives the JSON data sent from the device and analyzes the details of the dispute. At the same time, it uses an emotion engine to recognize the customer's emotions from the detailed dispute information entered. This emotion information is included in the analyzed data passed to the generation engine. The emotion engine uses IBM Watson's emotion analysis API.

[0744] Generating a work of fiction

[0745] The server passes the analyzed information and emotion information to a generation engine (such as OpenAI's GPT-3) and instructs it to generate a work of fiction. For example, if the customer's emotion is "dissatisfied," a story will unfold that corresponds to that emotion. An example of the generated content could be a short story like the one below:

[0746] "One day, clerk A received an item from customer B that he wanted to return, but it violated the return policy. B looked dissatisfied and said, 'This item is defective. Please do something about it.' A spoke to a manager and was able to alleviate B's frustration by offering a discount coupon for their next purchase instead of a return."

[0747] Return and Review of Works of Fiction

[0748] The server formats the generated fictional work and returns it in JSON format to the user's device. The user's device displays the fictional work received from the server and allows the user to confirm it, allowing the user to read the generated fictional work.

[0749] Classroom use and discussion

[0750] The user (e.g., a store staff member) can use the displayed short story in a training session and read it aloud to all staff members. The staff members can then comment on the feelings and actions of the characters and discuss how to solve the problems, thereby learning specific skills for dealing with customers.

[0751] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0752] Step 1: Enter and submit information

[0753] The user enters details of the customer issue through a dedicated application or web form. For example, they might enter information such as, "The customer wants to return a product, but we are having trouble doing so because it violates our return policy." The entered information is converted to JSON format within the application. The user then presses the "Submit" button, which sends the entered information to an API endpoint (e.g., / generate_story). Specifically, the form is submitted by touching the smartphone.

[0754] input:

[0755] Detailed information about customer trouble

[0756] output:

[0757] Information converted to JSON format

[0758] Step 2: Receiving and analyzing information

[0759] The server receives the JSON data sent from the device. The received data is passed to the analysis module, where detailed information about the dispute is extracted through text analysis. Based on this analysis data, the server calls an emotion engine (e.g., IBM Watson's emotion analysis API) to recognize the customer's emotions.

[0760] input:

[0761] JSON format customer trouble information

[0762] output:

[0763] Parsed text data

[0764] Customer sentiment information

[0765] Step 3: Recognize emotions

[0766] The server uses an emotion engine to analyze customer emotions. At this time, emotions such as "dissatisfaction" and "anger" are recognized from the text data. The analyzed emotion data is then passed to a generation engine. The server then integrates the text analysis results with the emotion information.

[0767] input:

[0768] Parsed text data

[0769] output:

[0770] Customer sentiment information

[0771] Step 4: Generate a work of fiction

[0772] Based on the analyzed information and emotion information, the server issues instructions to a generation engine (e.g., OpenAI's GPT-3) to generate a work of fiction. The generation engine generates a story based on a specified prompt. For example, it sends a prompt such as, "A customer wants to return a product, but a problem has arisen because it violates the return policy. The customer is dissatisfied. Please generate a story based on this."

[0773] input:

[0774] Integrated text and sentiment information

[0775] Prompt statement

[0776] output:

[0777] Generated works of fiction

[0778] Step 5: Return your work of fiction

[0779] The server then formats the generated fictional work into JSON format again and sends it back to the user's device, where it can be viewed.

[0780] input:

[0781] Generated works of fiction

[0782] output:

[0783] Works of fiction in JSON format

[0784] Step 6: Identifying works of fiction

[0785] The user terminal displays the fictional work received from the server and allows the user to review it. This allows store staff to read the generated fictional work. Specific operations include displaying the work on a smartphone or tablet screen.

[0786] input:

[0787] Works of fiction in JSON format

[0788] output:

[0789] The fictional work displayed

[0790] Step 7: Classroom Use and Discussion

[0791] Users (such as store staff) train based on the displayed fictional work. Specifically, the work is read aloud during the training session, and staff discuss the characters' actions and emotions. This allows them to learn skills that will be useful when dealing with real customers.

[0792] input:

[0793] The fictional work displayed

[0794] output:

[0795] Training discussion materials

[0796] The above processing steps realize a system for effectively providing customer service training for brick-and-mortar stores.

[0797] 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.

[0798] 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.

[0799] 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.

[0800] [Third embodiment]

[0801] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0802] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0803] 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).

[0804] 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.

[0805] 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.

[0806] 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).

[0807] 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. 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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."

[0813] This system allows users to input information about everyday disputes, and uses the information to generate fictional stories that can be used as teaching materials for moral education. This system allows children to concretely learn emotional expression, empathy, and problem-solving skills.

[0814] The system of the present invention is implemented by the following configuration and processing steps.

[0815] System Configuration

[0816] 1. User Device

[0817] As an input method, we provide a function that allows users to enter specific information about disputes on a daily basis. This is realized by a dedicated application or a web form.

[0818] As a transmission means, it has a function of transmitting the input information to the server.

[0819] 2. Server

[0820] As an analytical tool, it has the function of analyzing dispute information sent by users.

[0821] As a generation means, it has the function of generating fictional works using a generation engine based on the analyzed information.

[0822] As a return means, it has a function to send the generated fictional work to the user's terminal.

[0823] 3. Generation Engine

[0824] Software that uses natural language processing technology to generate fictional works based on detailed information about disputes.

[0825] 4. User Device

[0826] As a means of verification, it has the ability to display or play the returned fictional work.

[0827] As a means of discussion, we provide a function to use the generated fictional works in classes and hold discussions.

[0828] Specific examples of program processing

[0829] Enter and submit dispute information

[0830] Users enter details of the dispute through a dedicated application or a web form. For example, they enter information like, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[0831] The device converts the input information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[0832] Analyzing information and generating fiction

[0833] The server receives the JSON data sent from the device, analyzes the details of the dispute, and then passes the analyzed information to a generation engine (using natural language processing technology) to instruct it to generate a work of fiction.

[0834] An example of what might be generated is a short story like this:

[0835] "One day in the classroom, A-kun started to worry that B-kun hadn't returned the pencil he'd lent him. A-kun asked B-kun to return the pencil, but B-kun apologized, saying that he had been busy and had forgotten. A-kun and B-kun talked it over and decided that from now on they would keep their promises to each other."

[0836] Return and Review of Works of Fiction

[0837] The server formats the generated short story and returns it to the user's device in JSON format.

[0838] The terminal displays the short story received from the server and allows the user to review it, allowing the user to read the generated work of fiction.

[0839] Classroom use and discussion

[0840] The user (teacher) can use the displayed short story in class and read it aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems, thereby concretely learning the elements of the SEL program.

[0841] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills.

[0842] The processing flow will be explained below.

[0843] Step 1:

[0844] The user opens a dedicated application or web form. In the input field, they fill in the details of the dispute, for example, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[0845] Step 2:

[0846] The device converts the input information into JSON format and sends the converted data to the specified API endpoint (e.g., / generate_story).

[0847] Step 3:

[0848] The server receives the JSON data sent from the device, analyzes the received JSON data, extracts detailed information about the dispute, and executes an analysis method to analyze the extracted information.

[0849] Step 4:

[0850] The server passes the analyzed information to a generation engine, which uses natural language processing technology to generate a work of fiction based on the analyzed information.

[0851] Step 5:

[0852] The server formats the fictional work returned by the generation engine and returns the generated fictional work in JSON format to the user's device. The server constructs an appropriate API response to send back.

[0853] Step 6:

[0854] The device parses the JSON-formatted fictional work received from the server, converts it into a human-readable format, and displays the converted fictional work for the user to review.

[0855] Step 7:

[0856] The user (teacher) uses a fictional work in class. The user reads the displayed fictional work aloud to the entire class. After reading, the user starts a discussion with all the students, in which they share their opinions about the feelings and actions of the characters.

[0857] Example 1

[0858] 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."

[0859] In the traditional education system, it is difficult for children to concretely learn emotional expression, empathy, and problem-solving skills through everyday conflicts. As a result, the effectiveness of SEL (Social and Emotional Learning) programs is limited, and education based on real-life situations is not sufficiently provided.

[0860] 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.

[0861] In this invention, the server includes input means for a user to input information about conflicts that occur on a daily basis, transmission means for transmitting the input information to the server, generation means for the server to analyze the received information and generate a fictional work using natural language processing technology, return means for returning the generated work to the user's terminal, and confirmation means for the user to confirm the returned work. This enables children to learn emotional expression, empathy, and problem-solving skills through fictional works based on specific conflict scenarios.

[0862] "Input means" refers to the means by which users input specific information about disputes that arise on a daily basis, and includes dedicated applications and web forms.

[0863] The "transmission means" is a means for transmitting information input by the input means to a server, and includes a function for transmitting data using a communication protocol (e.g., HTTP).

[0864] "Generation means" means the means by which the server analyzes the information it receives and generates a work of fiction using natural language processing technology, including a generative AI model.

[0865] The "returning means" is a means for returning the fictional work generated by the generating means to the user's terminal, and includes a function for transmitting data using a communication protocol.

[0866] "Verification means" refers to a means by which the user can verify the returned fictional work, and includes a function for displaying it on the terminal.

[0867] "Discussion tools" are means for using the generated fictional works in class and for children to discuss the assignments, including educational frameworks and tools.

[0868] The "generation engine" is software that uses natural language processing technology to generate fictional works based on dispute information.

[0869] A "prompt" is a document that provides specific instructions to the generation engine and contains detailed information about the dispute.

[0870] MODE FOR CARRYING OUT THE INVENTION

[0871] This system allows users to input information about everyday disputes, and uses the information to generate fictional stories that can be used as teaching materials for moral education. This system allows children to concretely learn emotional expression, empathy, and problem-solving skills.

[0872] System Configuration

[0873] The system of the present invention has the following hardware and software configuration.

[0874] 1. User Device

[0875] An input means using a dedicated application or web form is provided, which allows users to input specific information about disputes on a daily basis.

[0876] As a transmission method, it has a function to send the input information to the server, using the HTTP protocol.

[0877] 2. Server

[0878] As an analytical tool, it has a function to analyze dispute information sent by users. This analysis is handled by software on the server, and parses data in JSON format.

[0879] As a means of generation, it has the ability to generate fictional works using generative AI models (e.g., GPT-3) based on the analyzed information.

[0880] As a means of returning the work, the system has the function of sending the generated fictional work to the user's device, and this also uses the HTTP protocol.

[0881] 3. Generation Engine

[0882] This software uses natural language processing technology to generate fictional works based on detailed information about disputes. The generative AI model used is specifically GPT-3.

[0883] 4. User Device

[0884] The returned fictional work is displayed as a means of verification, and it also has a playback function that allows users to use the fictional work in classes after verification.

[0885] The generated fictional works are used in classes as a means of discussion, and functions for holding discussions are provided, such as comment functions and video playback functions.

[0886] Specific examples of program processing

[0887] Enter and submit dispute information

[0888] The user enters information about the dispute through a dedicated application or a web form. For example, they might enter, "I lent my friend a pencil, but he didn't return it, and we got into an argument." Once they've finished entering information, they press the "Submit" button. The device converts the entered information into JSON format and sends it to the specified API endpoint.

[0889] Analyzing information and generating fiction

[0890] The server receives the JSON data sent from the device and analyzes the details of the dispute. It then uses the analyzed information to instruct the generation engine to generate a work of fiction using natural language processing technology. An example of the generated content could be a short story like this:

[0891] "You lent a friend a pencil and they didn't return it, and you got into an argument. Write a children's fiction story based on this argument."

[0892] Examples of generated short stories include:

[0893] "One day in the classroom, A-kun started to worry that B-kun hadn't returned the pencil he'd lent him. A-kun asked B-kun to return the pencil, but B-kun apologized, saying that he had been busy and had forgotten. A-kun and B-kun talked it over and decided that from now on they would keep their promises to each other."

[0894] Return and Review of Works of Fiction

[0895] The server formats the generated short story and returns it in JSON format to the user's device, which then displays the short story received from the server for the user to confirm.

[0896] Classroom use and discussion

[0897] Teachers can use the generated short stories in class and read them to all students. Students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems. This allows students to concretely learn the elements of SEL (social and emotional learning) programs.

[0898] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills.

[0899] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0900] Step 1:

[0901] Users open a dedicated application or web form and enter details of everyday disputes into text fields, such as "I lent my friend a pencil and he didn't return it, which led to an argument." After completing the input, users press a "Submit" button. This input data becomes the input for the next processing step.

[0902] Step 2:

[0903] The device converts the conflict information entered by the user into JSON format. For example, the input text is converted to {"conflict": "I lent my friend a pencil and he didn't return it, so we had an argument"}. The converted JSON data is sent as an HTTP POST request to the specified API endpoint (e.g., / generate_story). This becomes the input for the next processing step.

[0904] Step 3:

[0905] The server receives an HTTP request sent from a device. The received JSON data is passed to an internal process for parsing. For example, the data to be parsed is {"conflict": "I lent my friend a pencil, but he didn't return it, and we had an argument"}. The parsed data is passed to the generation engine for the next processing step.

[0906] Step 4:

[0907] The server uses the analyzed data to generate a prompt for a generative AI model (e.g., GPT-3). An example prompt might be, "I lent a pencil to a friend, but he didn't return it, and we got into an argument. Please write a fictional story for children based on this argument." This prompt is input into the generation engine, and the AI ​​model generates a work of fiction.

[0908] Step 5:

[0909] The generation engine (using natural language processing technology) receives the prompt and generates a work of fiction based on the details of the dispute. An example of a generated short story might be, "One day in the classroom, student A began to worry that student B had not returned the pencil he had lent to him. Student A asked student B, "Please return the pencil," but student B apologized, saying that he had been busy and had forgotten. Student A and student B talked it over and decided to keep their promise to each other in the future." This generated work is then passed to the next processing step.

[0910] Step 6:

[0911] The server formats the generated fiction and converts it back into JSON format, for example, {"story": "One day in the classroom, student A began to worry that student B had not returned the pencil he had lent him..."}. This JSON data is then sent back to the user's device.

[0912] Step 7:

[0913] The device receives the JSON data returned from the server and displays the fictional work on the application screen based on the received data, allowing the user to view the generated fictional work.

[0914] Step 8:

[0915] Teachers can use the generated fictional works in class and read them aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve problems. This allows students to learn emotional expression, empathy, and problem-solving skills through concrete scenarios.

[0916] Through this processing step, the system of the present invention can transform everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills.

[0917] (Application example 1)

[0918] 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."

[0919] Until now, there has been no system that generates fictional stories based on everyday conflicts and uses them in moral education. This has resulted in a lack of educational materials that allow children to specifically learn emotional expression, empathy, and problem-solving skills. Furthermore, there is no function to share the generated fictional stories with family and friends, or to hold quizzes or discussions based on the stories, preventing the full educational effect of this system.

[0920] 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.

[0921] In this invention, the server includes input means for a user to input information about disputes that arise on a daily basis, transmission means for transmitting the input information, generation means for analyzing the received information and generating a fictional work based on a generation engine, return means for returning the generated work to the user's terminal, confirmation means for confirming the returned work, learning means for providing educational quizzes and discussion functions for learning interpersonal problem solving and emotional empathy, and sharing means for sharing the generated work with family and friends. This allows children to concretely learn emotional expression, empathy, and problem-solving skills through fictional works, and to gain deeper understanding and learning by sharing them with family and friends.

[0922] "Input means" refers to a device or interface that allows a user to input information about disputes that arise on a daily basis.

[0923] The "transmission means" is a device or function for transmitting input information to a server.

[0924] An "analysis means" is a device or software module for analyzing information received by the server.

[0925] A "generator" is a device or software module that uses a generative engine to generate a work of fiction based on the analyzed information.

[0926] "Returning means" is a device or function for returning the generated work of fiction to the user's terminal.

[0927] "Verification means" is a device or function that allows a user to verify a returned work of fiction.

[0928] A "learning tool" is a device or software module that provides educational quizzes and discussion functions for learning interpersonal problem solving and emotional empathy.

[0929] A "sharing means" is a device or function for sharing the created fictional work with family and friends.

[0930] "Natural language processing technology" is a technology that enables computers to understand and generate human language.

[0931] The present invention is a system that allows users to input information about everyday disputes and use fictional works generated based on that information as teaching materials for moral education. This system is realized with the following hardware and software configuration.

[0932] System Configuration

[0933] 1. User Device

[0934] As an input method, we provide a function that allows users to enter specific information about disputes on a daily basis. This is realized by a dedicated application or a web form.

[0935] As a transmission means, it has a function of transmitting the input information to the server.

[0936] As a means of verification, it has the ability to display or play the returned fictional work.

[0937] As a learning tool, it provides functions for quizzes and discussions based on the fictional works that are generated, and also allows users to share their works with their families and friends.

[0938] 2. Server

[0939] As an analytical tool, it has the function of analyzing dispute information sent by users and converting it into an appropriate fictional work. Specifically, it generates a fictional work using a generation engine based on the analyzed information.

[0940] The generative method is to generate fictional works based on the analyzed information, using natural language processing techniques to generate stories based on the details of the dispute.

[0941] As a return means, it has a function to return the generated fictional work to the user's terminal.

[0942] Program processing explanation

[0943] The server uses cloud servers such as Alexa and Google Cloud Platform (GCP). For natural language processing, OpenAI's GPT model is used. The program's processing begins with the user entering information about the dispute, which is then converted into JSON format and sent to the server. The server analyzes the received information and generates a work of fiction using a generation engine. The generated work of fiction is then sent back to the user's device, where the user can view it.

[0944] For example:

[0945] Entering information about a dispute: The user enters information such as "I lent my friend a pencil, but he never returned it, and we got into an argument."

[0946] Example prompt: "You lent a friend a pencil, but he didn't return it, and you got into an argument. Generate a fictional moral story based on this."

[0947] This system allows users to concretely learn emotional expression, empathy, and problem-solving skills through fictional works, and allows them to share the created works with family and friends.

[0948] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0949] Step 1:

[0950] The user enters the dispute information

[0951] Users can use a dedicated application or a web form to enter specific details about everyday disputes. For example, they can enter information like, "I lent my friend a pencil and he didn't return it, so we got into an argument." The input data is represented in JSON format. Based on the input, the system stores it in a database and prepares it for the next step.

[0952] Step 2:

[0953] Sending data from the device to the server

[0954] The user device converts the entered dispute information into JSON format and sends it to the specified API endpoint (e.g., / generate_story). This is done using an HTTP POST request, which sends the input data to the server. The server then validates the received data and checks for any problems before proceeding with analysis.

[0955] Step 3:

[0956] The server analyzes the information

[0957] The server receives the JSON data sent from the device. This analysis method analyzes the received data and understands the meaning of the input information. Specifically, it uses natural language processing technology to analyze the details of the dispute. Based on this analysis, it generates prompts to generate appropriate fiction works.

[0958] Step 4:

[0959] Generate a work of fiction

[0960] The server passes the parsed information to a generation engine, which generates a fictional work based on the prompt. This generation method uses natural language processing techniques such as OpenAI's GPT model. For example, if the prompt is "I lent my friend a pencil and he didn't return it, and we got into an argument. Please generate a fictional story with a moral based on this content.", the engine will generate a corresponding fictional work. The generated fictional work is saved in JSON format.

[0961] Step 5:

[0962] Send the generated work back to the user's device

[0963] The server formats the generated work of fiction and returns it to the user's device. This returns the generated JSON data as an HTTP response to the user's device. The user's device parses the received JSON data and displays or plays the work of fiction to the user.

[0964] Step 6:

[0965] Users can review their work and use the learning mode

[0966] The user reviews the returned fictional work. This reviewing means provides the user's device with the ability to display and play the work in text or audio. The user can also use the learning means to participate in quizzes and discussions based on the work. This allows the user to specifically learn skills such as empathy and problem-solving.

[0967] Step 7:

[0968] Share your creations

[0969] Users can share the fictional works they create with their families and friends. This sharing method generates a link for sharing the work and provides the ability to share it with others via social networking sites, email, etc. The shared work can then be used by others to view and learn from.

[0970] 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.

[0971] This system allows users to input information about everyday disputes, and then generates fictional works based on that information, which can then be used as teaching materials for moral education. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the system aims to provide a more effective educational experience. This system allows children to concretely learn emotional expression, empathy, and problem-solving skills.

[0972] The system of the present invention is implemented by the following configuration and processing steps.

[0973] System Configuration

[0974] 1. User Device

[0975] As an input method, we provide a function that allows users to enter specific information about disputes on a daily basis. This is realized by a dedicated application or a web form.

[0976] As a transmission means, it has a function of transmitting the input information to the server.

[0977] 2. Server

[0978] As an analytical tool, it has the function of analyzing dispute information sent by users.

[0979] As a generation means, it has the function of generating fictional works using a generation engine based on the analyzed information.

[0980] As an emotion engine, it has the ability to recognize the user's emotions from the dispute information entered by the user.

[0981] As a return means, it has a function to send the generated fictional work to the user's terminal.

[0982] 3. Generation Engine

[0983] Software that uses natural language processing technology to generate fictional works based on detailed dispute information and perceived emotions.

[0984] 4. User Device

[0985] As a means of verification, it has the ability to display or play the returned fictional work.

[0986] As a means of discussion, we provide a function to use the generated fictional works in classes and hold discussions.

[0987] Specific examples of program processing

[0988] Enter and submit dispute information

[0989] Users enter details of the dispute through a dedicated application or a web form. For example, they enter information like, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[0990] The device converts the input information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[0991] Information analysis and emotion recognition

[0992] The server receives the JSON data sent from the device and analyzes the details of the dispute. It also uses an emotion engine to recognize the user's emotion from the entered details of the dispute. This emotion information is included in the analyzed data passed to the generation engine.

[0993] Generating a work of fiction

[0994] The server then passes the analyzed information and emotional information to a generation engine (using natural language processing technology) and instructs it to generate a fictional work. For example, if the user's emotion is "anger," a story will unfold that corresponds to that emotion.

[0995] An example of what might be generated is a short story like this:

[0996] "One day in the classroom, A-kun started to worry that B-kun hadn't returned the pencil he'd lent him. A-kun asked B-kun to return the pencil, but B-kun apologized, saying that he had been busy and had forgotten. A-kun and B-kun talked it over and decided that from now on they would keep their promises to each other."

[0997] Return and Review of Works of Fiction

[0998] The server formats the generated short story and returns it to the user's device in JSON format.

[0999] The terminal displays the short story received from the server and allows the user to review it, allowing the user to read the generated work of fiction.

[1000] Classroom use and discussion

[1001] The user (teacher) can use the displayed short story in class and read it aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems, thereby concretely learning the elements of the SEL program.

[1002] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills. Furthermore, by combining it with an emotion engine, it is possible to provide a more personalized educational experience.

[1003] The processing flow will be explained below.

[1004] Step 1:

[1005] The user opens a dedicated application or web form. In the input field, they fill in the details of the dispute, for example, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[1006] Step 2:

[1007] The device converts the input information into JSON format and sends the converted data to the specified API endpoint (e.g., / generate_story).

[1008] Step 3:

[1009] The server receives the JSON data sent from the device, analyzes it, and extracts detailed information about the dispute.

[1010] Step 4:

[1011] The server sends the analyzed information to the emotion engine, which recognizes the user's emotion based on the conflict.

[1012] Step 5:

[1013] The server receives the emotion information obtained from the emotion engine and sends it along with the analyzed information to the generation engine, which then generates a fictional work based on the input data and emotion information.

[1014] Step 6:

[1015] The server formats the fictional work returned by the generation engine and returns the generated fictional work in JSON format to the user's device.

[1016] Step 7:

[1017] The device parses the JSON-formatted fictional work received from the server, converts it into a human-readable format, and displays the converted fictional work for the user to review.

[1018] Step 8:

[1019] The user (teacher) uses the displayed fictional work in class. The user reads the short story to the entire class and discusses the conflict with all the students. Through the discussion, children can learn to express emotions, develop empathy, and problem-solving skills.

[1020] In this way, the use of the emotion engine enables a system that provides a more personalized educational experience.

[1021] Example 2

[1022] 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."

[1023] The current education system provides limited opportunities for children to specifically learn emotional expression, empathy, and problem-solving skills. It also lacks ways to effectively use everyday conflicts as educational resources. This calls for a new system to increase opportunities for social and emotional learning (SEL) and promote children's emotional growth.

[1024] 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.

[1025] In this invention, the server includes an emotion engine that analyzes input information and recognizes emotions, a means for generating a fictional work using a generation engine based on the results of the emotion engine, and a means for returning the generated work to the user's terminal. This allows a user to input information about everyday conflicts, recognize emotions based on that information, and generate and return an appropriate fictional work. This provides concrete social and emotional learning opportunities in educational settings and effectively fosters children's emotional expression, empathy, and problem-solving skills.

[1026] The "input means" is a part of the system that provides a function that allows users to input specific information about disputes on a daily basis.

[1027] The "transmission means" is a part of the system that has the function of transmitting input information to the server.

[1028] A "server" is a computing device that receives and analyzes information over a network and performs specific processing.

[1029] The "emotion engine" is software that recognizes emotions from dispute information entered by the user.

[1030] A "generation engine" is software that uses natural language processing technology to generate fictional works based on analyzed information.

[1031] A "generator" is a part of the system that has the function of generating a work of fiction based on the analyzed information.

[1032] The "returning means" is a part of the system that has the function of returning the fictional work generated by the server to the user's terminal.

[1033] A "verification means" is the part of the system that allows a user to verify a returned work of fiction.

[1034] The "discussion tool" is part of a system for using the generated fictional works in class and holding discussions.

[1035] "Natural language processing technology" is a computer science technology for understanding and generating human language.

[1036] This system allows users to input information about everyday disputes, and then generates fictional works based on that information, which can then be used as teaching materials for moral education. The system is particularly equipped with an emotion engine that recognizes the user's emotions, aiming to provide a more effective educational experience. This system allows children to specifically learn emotional expression, empathy, and problem-solving skills.

[1037] Hardware and software used

[1038] 1. User Device

[1039] It uses a computer, tablet, or smartphone, which can be operated via a dedicated application or a web browser.

[1040] 2. Server

[1041] The information is received, analyzed, the fiction is generated, and then returned to us using the servers of cloud service providers (e.g., Amazon Web Services, Microsoft Azure, Google Cloud Platform).

[1042] 3. Emotion Engine

[1043] Software that recognizes user emotions from input dispute information. Examples include Microsoft Azure's Cognitive Services and Google Cloud's Natural Language API.

[1044] 4. Generation Engine

[1045] Software that uses natural language processing technology to generate fictional works based on input information and recognized emotions. Specific examples include OpenAI's GPT-3 and GPT-4.

[1046] System operation example

[1047] Enter and submit dispute information

[1048] Users enter details of the dispute through a dedicated application or a web form. For example, they enter information like, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[1049] The device converts the input information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[1050] Information analysis and emotion recognition

[1051] The server receives the JSON data sent from the device and analyzes the details of the dispute. Using the emotion engine, it recognizes the user's emotion from the entered details of the dispute. This emotion information is included in the analyzed data passed to the generation engine.

[1052] Generating a work of fiction

[1053] The server then passes the analyzed information and emotion information to the generation engine, instructing it to generate a fictional work. For example, if the user's emotion is "anger," a story will unfold according to that emotion.

[1054] An example of what might be generated is a short story like this:

[1055] "One day in the classroom, A was worried because B hadn't returned the pencil he'd lent him. A asked B to return the pencil, but B apologized, saying that he had been busy and had forgotten. A and B talked it over and decided that from now on they would keep their promises to each other."

[1056] Return and Review of Works of Fiction

[1057] The server formats the generated short story and returns it to the user's device in JSON format.

[1058] The terminal displays the short story received from the server and allows the user to review it, allowing the user to read the generated work of fiction.

[1059] Classroom use and discussion

[1060] The user (teacher) can use the displayed short story in class and read it aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems, thereby concretely learning the elements of the SEL program.

[1061] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills. Furthermore, by combining it with an emotion engine, it is possible to provide a more personalized educational experience.

[1062] Examples of prompt statements

[1063] A possible prompt might be written as follows:

[1064] Dispute: I lent my friend a pencil and he never returned it, so we got into an argument.

[1065] Emotion: Anger

[1066] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1067] Step 1:

[1068] Users enter details of the dispute through a dedicated application or web form. For example, they might enter a specific situation, such as, "I lent my friend a pencil, but he never returned it, and we got into an argument." The entered data is sent directly to the device in JSON format.

[1069] Input: User-entered dispute information

[1070] Output: JSON formatted dispute information

[1071] What happens: A user opens an application or web form, enters details about the dispute, and presses the "Submit" button.

[1072] Step 2:

[1073] The device receives the dispute information entered by the user and converts it into JSON format, which is then sent to the server, for example, to the API endpoint ( / generate_story).

[1074] Input: User-entered dispute information

[1075] Output: JSON formatted dispute information sent to the server

[1076] Specific operation: The device formats the input information into the appropriate JSON format and sends it to the specified API endpoint.

[1077] Step 3:

[1078] The server receives the JSON data sent from the device, analyzes it, and extracts details of the dispute. It then uses an emotion engine to recognize the user's emotion from the input information. For example, based on the keyword "argument," it determines that the emotion is "anger."

[1079] Input: JSON formatted dispute information sent from the device

[1080] Output: Analyzed details and emotional information of the conflict

[1081] Specific operation: The server analyzes detailed information about the dispute and uses an emotion engine to recognize emotions.

[1082] Step 4:

[1083] The server passes the analyzed details of the dispute and the recognized emotion information to a generation engine, instructing it to generate a fictional work. For example, if the emotion is "anger," a story will unfold according to that emotion. The generation engine uses natural language processing technology to generate a fictional work.

[1084] Input: Analyzed details and emotional information about the conflict

[1085] Output: A generated work of fiction

[1086] What it does: Pass data to a generation engine and generate a work of fiction using natural language processing techniques.

[1087] Step 5:

[1088] The server formats the generated fictional work and returns it to the user's device in JSON format.

[1089] Input: A generated work of fiction

[1090] Output: JSON fiction data

[1091] Specific operation: The server formats the generated fictional work into fields and returns it to the terminal in JSON format.

[1092] Step 6:

[1093] The terminal displays the fictional work received from the server to the user, who can then view and read the work.

[1094] Input: JSON formatted fiction data

[1095] Output: A work of fiction displayed to the user

[1096] Specific behavior: The device properly formats and displays the received work of fiction for the user to review.

[1097] Step 7:

[1098] The user (teacher) uses the generated short story in class and reads it to all the students. The students comment on the feelings and actions of the characters and discuss how to solve the problems.

[1099] Input: A work of fiction displayed to the user

[1100] Output: Class discussion and learning outcomes

[1101] Specific operations: The user (teacher) reads a work of fiction to the students and engages in a discussion.

[1102] (Application example 2)

[1103] 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."

[1104] One issue facing brick-and-mortar stores is the lack of effective training methods for staff to resolve disputes that arise when dealing with customers. It's particularly difficult to accurately grasp customer emotions and learn how to respond appropriately. Current training methods are insufficient to teach specific skills that can be applied in real-world situations, resulting in lower customer satisfaction and increased customer trouble.

[1105] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion engine means for analyzing input information and recognizing emotions, generation engine means for generating a fictional work based on the analyzed information and emotion information, and return means for returning the generated work to the user's terminal. This allows users to generate fictional works corresponding to emotions based on information about disputes that arise in actual customer interactions and use them as training materials. Staff can learn specific response methods through the generated works and improve their customer interaction skills.

[1106] "Input means" refers to a device or interface that allows users to input specific information about disputes that arise on a daily basis.

[1107] "Transmission means" refers to a device or protocol that has the function of transmitting input information to a server.

[1108] "Generation means" means a system or software that has the function of analyzing the information received by the server and generating a work of fiction based on a generation engine.

[1109] An "emotion engine" is a technology or algorithm that analyzes the information received by the server and recognizes the user's emotions.

[1110] "Returning means" refers to a communication function for returning the created work to the user's terminal.

[1111] "Verification means" refers to a device or application that allows a user to view and verify the returned work.

[1112] "Discussion tool" refers to an interface or functionality for using the generated work to hold discussions in classes or training.

[1113] "Natural language processing technology" is a general term for technology that uses computers to analyze and understand human language.

[1114] This invention is a system that inputs information about customer troubles that staff members actually encounter in a brick-and-mortar store, and generates fictional works based on that information to be used as educational content. The system includes a user terminal, a server, a generation engine, and an emotion engine. Each component and processing step is described in detail below.

[1115] System Configuration

[1116] 1. User Device

[1117] The user terminal is a device such as a smartphone or tablet. This terminal provides an input means for staff to input and submit customer trouble information through a dedicated application or web form. It also has the function of displaying and checking the fictional work that is later generated.

[1118] 2. Server

[1119] The server has the following main functions:

[1120] Analysis of information: The server receives and analyzes the dispute information sent from the user terminal.

[1121] Emotion recognition: An emotion engine is used to recognize customer emotions from dispute information. Specific technologies used include IBM Watson's emotion analysis API.

[1122] Fiction generation: Using the analyzed information and sentiment information, fiction is generated through a generative engine (e.g., OpenAI's GPT-3), which uses natural language processing techniques.

[1123] Return: The generated fictional work is formatted and returned to the user's device.

[1124] 3. Generation Engine

[1125] The generation engine uses natural language processing techniques to generate fictional stories based on conflicts, specifically using AI models such as OpenAI's GPT-3. Example prompts include:

[1126] "A customer wants to return an item, but is having trouble because it violates the return policy. The customer is dissatisfied. Generate a story based on this."

[1127] Specific processing of the program

[1128] Enter and submit information

[1129] The user (staff member) enters details of the customer issue through a dedicated application or web form. For example, they might enter information such as, "The customer wants to return a product, but we are having trouble handling this because it violates our return policy." Once the information is complete, the user presses the "Submit" button. The terminal converts this information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[1130] Information analysis and emotion recognition

[1131] The server receives the JSON data sent from the device and analyzes the details of the dispute. At the same time, it uses an emotion engine to recognize the customer's emotions from the detailed dispute information entered. This emotion information is included in the analyzed data passed to the generation engine. The emotion engine uses IBM Watson's emotion analysis API.

[1132] Generating a work of fiction

[1133] The server passes the analyzed information and emotion information to a generation engine (such as OpenAI's GPT-3) and instructs it to generate a work of fiction. For example, if the customer's emotion is "dissatisfied," a story will unfold that corresponds to that emotion. An example of the generated content could be a short story like the one below:

[1134] "One day, clerk A received an item from customer B that he wanted to return, but it violated the return policy. B looked dissatisfied and said, 'This item is defective. Please do something about it.' A spoke to a manager and was able to alleviate B's frustration by offering a discount coupon for their next purchase instead of a return."

[1135] Return and Review of Works of Fiction

[1136] The server formats the generated fictional work and returns it in JSON format to the user's device. The user's device displays the fictional work received from the server and allows the user to confirm it, allowing the user to read the generated fictional work.

[1137] Classroom use and discussion

[1138] The user (e.g., a store staff member) can use the displayed short story in a training session and read it aloud to all staff members. The staff members can then comment on the feelings and actions of the characters and discuss how to solve the problems, thereby learning specific skills for dealing with customers.

[1139] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1140] Step 1: Enter and submit information

[1141] The user enters details of the customer issue through a dedicated application or web form. For example, they might enter information such as, "The customer wants to return a product, but we are having trouble doing so because it violates our return policy." The entered information is converted to JSON format within the application. The user then presses the "Submit" button, which sends the entered information to an API endpoint (e.g., / generate_story). Specifically, the form is submitted by touching the smartphone.

[1142] input:

[1143] Detailed information about customer trouble

[1144] output:

[1145] Information converted to JSON format

[1146] Step 2: Receiving and analyzing information

[1147] The server receives the JSON data sent from the device. The received data is passed to the analysis module, where detailed information about the dispute is extracted through text analysis. Based on this analysis data, the server calls an emotion engine (e.g., IBM Watson's emotion analysis API) to recognize the customer's emotions.

[1148] input:

[1149] JSON format customer trouble information

[1150] output:

[1151] Parsed text data

[1152] Customer sentiment information

[1153] Step 3: Recognize emotions

[1154] The server uses an emotion engine to analyze customer emotions. At this time, emotions such as "dissatisfaction" and "anger" are recognized from the text data. The analyzed emotion data is then passed to a generation engine. The server then integrates the text analysis results with the emotion information.

[1155] input:

[1156] Parsed text data

[1157] output:

[1158] Customer sentiment information

[1159] Step 4: Generate a work of fiction

[1160] Based on the analyzed information and emotion information, the server issues instructions to a generation engine (e.g., OpenAI's GPT-3) to generate a work of fiction. The generation engine generates a story based on a specified prompt. For example, it sends a prompt such as, "A customer wants to return a product, but a problem has arisen because it violates the return policy. The customer is dissatisfied. Please generate a story based on this."

[1161] input:

[1162] Integrated text and sentiment information

[1163] Prompt statement

[1164] output:

[1165] Generated works of fiction

[1166] Step 5: Return your work of fiction

[1167] The server then formats the generated fictional work into JSON format again and sends it back to the user's device, where it can be viewed.

[1168] input:

[1169] Generated works of fiction

[1170] output:

[1171] Works of fiction in JSON format

[1172] Step 6: Identifying works of fiction

[1173] The user terminal displays the fictional work received from the server and allows the user to review it. This allows store staff to read the generated fictional work. Specific operations include displaying the work on a smartphone or tablet screen.

[1174] input:

[1175] Works of fiction in JSON format

[1176] output:

[1177] The fictional work displayed

[1178] Step 7: Classroom Use and Discussion

[1179] Users (such as store staff) train based on the displayed fictional work. Specifically, the work is read aloud during the training session, and staff discuss the characters' actions and emotions. This allows them to learn skills that will be useful when dealing with real customers.

[1180] input:

[1181] The fictional work displayed

[1182] output:

[1183] Training discussion materials

[1184] The above processing steps realize a system for effectively providing customer service training for brick-and-mortar stores.

[1185] 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.

[1186] 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.

[1187] 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.

[1188] [Fourth embodiment]

[1189] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1190] 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.

[1191] 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).

[1192] 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.

[1193] 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.

[1194] 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).

[1195] 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. 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.

[1196] 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.

[1197] 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.

[1198] 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.

[1199] 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.

[1200] 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.

[1201] 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."

[1202] This system allows users to input information about everyday disputes, and uses the information to generate fictional stories that can be used as teaching materials for moral education. This system allows children to concretely learn emotional expression, empathy, and problem-solving skills.

[1203] The system of the present invention is implemented by the following configuration and processing steps.

[1204] System Configuration

[1205] 1. User Device

[1206] As an input method, we provide a function that allows users to enter specific information about disputes on a daily basis. This is realized by a dedicated application or a web form.

[1207] As a transmission means, it has a function of transmitting the input information to the server.

[1208] 2. Server

[1209] As an analytical tool, it has the function of analyzing dispute information sent by users.

[1210] As a generation means, it has the function of generating fictional works using a generation engine based on the analyzed information.

[1211] As a return means, it has a function to send the generated fictional work to the user's terminal.

[1212] 3. Generation Engine

[1213] Software that uses natural language processing technology to generate fictional works based on detailed information about disputes.

[1214] 4. User Device

[1215] As a means of verification, it has the ability to display or play the returned fictional work.

[1216] As a means of discussion, we provide a function to use the generated fictional works in classes and hold discussions.

[1217] Specific examples of program processing

[1218] Enter and submit dispute information

[1219] Users enter details of the dispute through a dedicated application or a web form. For example, they enter information like, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[1220] The device converts the input information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[1221] Analyzing information and generating fiction

[1222] The server receives the JSON data sent from the device, analyzes the details of the dispute, and then passes the analyzed information to a generation engine (using natural language processing technology) to instruct it to generate a work of fiction.

[1223] An example of what might be generated is a short story like this:

[1224] "One day in the classroom, A-kun started to worry that B-kun hadn't returned the pencil he'd lent him. A-kun asked B-kun to return the pencil, but B-kun apologized, saying that he had been busy and had forgotten. A-kun and B-kun talked it over and decided that from now on they would keep their promises to each other."

[1225] Return and Review of Works of Fiction

[1226] The server formats the generated short story and returns it to the user's device in JSON format.

[1227] The terminal displays the short story received from the server and allows the user to review it, allowing the user to read the generated work of fiction.

[1228] Classroom use and discussion

[1229] The user (teacher) can use the displayed short story in class and read it aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems, thereby concretely learning the elements of the SEL program.

[1230] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills.

[1231] The processing flow will be explained below.

[1232] Step 1:

[1233] The user opens a dedicated application or web form. In the input field, they fill in the details of the dispute, for example, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[1234] Step 2:

[1235] The device converts the input information into JSON format and sends the converted data to the specified API endpoint (e.g., / generate_story).

[1236] Step 3:

[1237] The server receives the JSON data sent from the device, analyzes the received JSON data, extracts detailed information about the dispute, and executes an analysis method to analyze the extracted information.

[1238] Step 4:

[1239] The server passes the analyzed information to a generation engine, which uses natural language processing technology to generate a work of fiction based on the analyzed information.

[1240] Step 5:

[1241] The server formats the fictional work returned by the generation engine and returns the generated fictional work in JSON format to the user's device. The server constructs an appropriate API response to send back.

[1242] Step 6:

[1243] The device parses the JSON-formatted fictional work received from the server, converts it into a human-readable format, and displays the converted fictional work for the user to review.

[1244] Step 7:

[1245] The user (teacher) uses a fictional work in class. The user reads the displayed fictional work aloud to the entire class. After reading, the user starts a discussion with all the students, in which they share their opinions about the feelings and actions of the characters.

[1246] Example 1

[1247] 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."

[1248] In the traditional education system, it is difficult for children to concretely learn emotional expression, empathy, and problem-solving skills through everyday conflicts. As a result, the effectiveness of SEL (Social and Emotional Learning) programs is limited, and education based on real-life situations is not sufficiently provided.

[1249] 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.

[1250] In this invention, the server includes input means for a user to input information about conflicts that occur on a daily basis, transmission means for transmitting the input information to the server, generation means for the server to analyze the received information and generate a fictional work using natural language processing technology, return means for returning the generated work to the user's terminal, and confirmation means for the user to confirm the returned work. This enables children to learn emotional expression, empathy, and problem-solving skills through fictional works based on specific conflict scenarios.

[1251] "Input means" refers to the means by which users input specific information about disputes that arise on a daily basis, and includes dedicated applications and web forms.

[1252] The "transmission means" is a means for transmitting information input by the input means to a server, and includes a function for transmitting data using a communication protocol (e.g., HTTP).

[1253] "Generation means" means the means by which the server analyzes the information it receives and generates a work of fiction using natural language processing technology, including a generative AI model.

[1254] The "returning means" is a means for returning the fictional work generated by the generating means to the user's terminal, and includes a function for transmitting data using a communication protocol.

[1255] "Verification means" refers to a means by which the user can verify the returned fictional work, and includes a function for displaying it on the terminal.

[1256] "Discussion tools" are means for using the generated fictional works in class and for children to discuss the assignments, including educational frameworks and tools.

[1257] The "generation engine" is software that uses natural language processing technology to generate fictional works based on dispute information.

[1258] A "prompt" is a document that provides specific instructions to the generation engine and contains detailed information about the dispute.

[1259] MODE FOR CARRYING OUT THE INVENTION

[1260] This system allows users to input information about everyday disputes, and uses the information to generate fictional stories that can be used as teaching materials for moral education. This system allows children to concretely learn emotional expression, empathy, and problem-solving skills.

[1261] System Configuration

[1262] The system of the present invention has the following hardware and software configuration.

[1263] 1. User Device

[1264] An input means using a dedicated application or web form is provided, which allows users to input specific information about disputes on a daily basis.

[1265] As a transmission method, it has a function to send the input information to the server, using the HTTP protocol.

[1266] 2. Server

[1267] As an analytical tool, it has a function to analyze dispute information sent by users. This analysis is handled by software on the server, and parses data in JSON format.

[1268] As a means of generation, it has the ability to generate fictional works using generative AI models (e.g., GPT-3) based on the analyzed information.

[1269] As a means of returning the work, the system has the function of sending the generated fictional work to the user's device, and this also uses the HTTP protocol.

[1270] 3. Generation Engine

[1271] This software uses natural language processing technology to generate fictional works based on detailed information about disputes. The generative AI model used is specifically GPT-3.

[1272] 4. User Device

[1273] The returned fictional work is displayed as a means of verification, and it also has a playback function that allows users to use the fictional work in classes after verification.

[1274] The generated fictional works are used in classes as a means of discussion, and functions for holding discussions are provided, such as comment functions and video playback functions.

[1275] Specific examples of program processing

[1276] Enter and submit dispute information

[1277] The user enters information about the dispute through a dedicated application or a web form. For example, they might enter, "I lent my friend a pencil, but he didn't return it, and we got into an argument." Once they've finished entering information, they press the "Submit" button. The device converts the entered information into JSON format and sends it to the specified API endpoint.

[1278] Analyzing information and generating fiction

[1279] The server receives the JSON data sent from the device and analyzes the details of the dispute. It then uses the analyzed information to instruct the generation engine to generate a work of fiction using natural language processing technology. An example of the generated content could be a short story like this:

[1280] "You lent a friend a pencil and they didn't return it, and you got into an argument. Write a children's fiction story based on this argument."

[1281] Examples of generated short stories include:

[1282] "One day in the classroom, A-kun started to worry that B-kun hadn't returned the pencil he'd lent him. A-kun asked B-kun to return the pencil, but B-kun apologized, saying that he had been busy and had forgotten. A-kun and B-kun talked it over and decided that from now on they would keep their promises to each other."

[1283] Return and Review of Works of Fiction

[1284] The server formats the generated short story and returns it in JSON format to the user's device, which then displays the short story received from the server for the user to confirm.

[1285] Classroom use and discussion

[1286] Teachers can use the generated short stories in class and read them to all students. Students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems. This allows students to concretely learn the elements of SEL (social and emotional learning) programs.

[1287] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills.

[1288] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1289] Step 1:

[1290] Users open a dedicated application or web form and enter details of everyday disputes into text fields, such as "I lent my friend a pencil and he didn't return it, which led to an argument." After completing the input, users press a "Submit" button. This input data becomes the input for the next processing step.

[1291] Step 2:

[1292] The device converts the conflict information entered by the user into JSON format. For example, the input text is converted to {"conflict": "I lent my friend a pencil and he didn't return it, so we had an argument"}. The converted JSON data is sent as an HTTP POST request to the specified API endpoint (e.g., / generate_story). This becomes the input for the next processing step.

[1293] Step 3:

[1294] The server receives an HTTP request sent from a device. The received JSON data is passed to an internal process for parsing. For example, the data to be parsed is {"conflict": "I lent my friend a pencil, but he didn't return it, and we had an argument"}. The parsed data is passed to the generation engine for the next processing step.

[1295] Step 4:

[1296] The server uses the analyzed data to generate a prompt for a generative AI model (e.g., GPT-3). An example prompt might be, "I lent a pencil to a friend, but he didn't return it, and we got into an argument. Please write a fictional story for children based on this argument." This prompt is input into the generation engine, and the AI ​​model generates a work of fiction.

[1297] Step 5:

[1298] The generation engine (using natural language processing technology) receives the prompt and generates a work of fiction based on the details of the dispute. An example of a generated short story might be, "One day in the classroom, student A began to worry that student B had not returned the pencil he had lent to him. Student A asked student B, "Please return the pencil," but student B apologized, saying that he had been busy and had forgotten. Student A and student B talked it over and decided to keep their promise to each other in the future." This generated work is then passed to the next processing step.

[1299] Step 6:

[1300] The server formats the generated fiction and converts it back into JSON format, for example, {"story": "One day in the classroom, student A began to worry that student B had not returned the pencil he had lent him..."}. This JSON data is then sent back to the user's device.

[1301] Step 7:

[1302] The device receives the JSON data returned from the server and displays the fictional work on the application screen based on the received data, allowing the user to view the generated fictional work.

[1303] Step 8:

[1304] Teachers can use the generated fictional works in class and read them aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve problems. This allows students to learn emotional expression, empathy, and problem-solving skills through concrete scenarios.

[1305] Through this processing step, the system of the present invention can transform everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills.

[1306] (Application example 1)

[1307] 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."

[1308] Until now, there has been no system that generates fictional stories based on everyday conflicts and uses them in moral education. This has resulted in a lack of educational materials that allow children to specifically learn emotional expression, empathy, and problem-solving skills. Furthermore, there is no function to share the generated fictional stories with family and friends, or to hold quizzes or discussions based on the stories, preventing the full educational effect of this system.

[1309] 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.

[1310] In this invention, the server includes input means for a user to input information about disputes that arise on a daily basis, transmission means for transmitting the input information, generation means for analyzing the received information and generating a fictional work based on a generation engine, return means for returning the generated work to the user's terminal, confirmation means for confirming the returned work, learning means for providing educational quizzes and discussion functions for learning interpersonal problem solving and emotional empathy, and sharing means for sharing the generated work with family and friends. This allows children to concretely learn emotional expression, empathy, and problem-solving skills through fictional works, and to gain deeper understanding and learning by sharing them with family and friends.

[1311] "Input means" refers to a device or interface that allows a user to input information about disputes that arise on a daily basis.

[1312] The "transmission means" is a device or function for transmitting input information to a server.

[1313] An "analysis means" is a device or software module for analyzing information received by the server.

[1314] A "generator" is a device or software module that uses a generative engine to generate a work of fiction based on the analyzed information.

[1315] "Returning means" is a device or function for returning the generated work of fiction to the user's terminal.

[1316] "Verification means" is a device or function that allows a user to verify a returned work of fiction.

[1317] A "learning tool" is a device or software module that provides educational quizzes and discussion functions for learning interpersonal problem solving and emotional empathy.

[1318] A "sharing means" is a device or function for sharing the created fictional work with family and friends.

[1319] "Natural language processing technology" is a technology that enables computers to understand and generate human language.

[1320] The present invention is a system that allows users to input information about everyday disputes and use fictional works generated based on that information as teaching materials for moral education. This system is realized with the following hardware and software configuration.

[1321] System Configuration

[1322] 1. User Device

[1323] As an input method, we provide a function that allows users to enter specific information about disputes on a daily basis. This is realized by a dedicated application or a web form.

[1324] As a transmission means, it has a function of transmitting the input information to the server.

[1325] As a means of verification, it has the ability to display or play the returned fictional work.

[1326] As a learning tool, it provides functions for quizzes and discussions based on the fictional works that are generated, and also allows users to share their works with their families and friends.

[1327] 2. Server

[1328] As an analytical tool, it has the function of analyzing dispute information sent by users and converting it into an appropriate fictional work. Specifically, it generates a fictional work using a generation engine based on the analyzed information.

[1329] The generative method is to generate fictional works based on the analyzed information, using natural language processing techniques to generate stories based on the details of the dispute.

[1330] As a return means, it has a function to return the generated fictional work to the user's terminal.

[1331] Program processing explanation

[1332] The server uses cloud servers such as Alexa and Google Cloud Platform (GCP). For natural language processing, OpenAI's GPT model is used. The program's processing begins with the user entering information about the dispute, which is then converted into JSON format and sent to the server. The server analyzes the received information and generates a work of fiction using a generation engine. The generated work of fiction is then sent back to the user's device, where the user can view it.

[1333] For example:

[1334] Entering information about a dispute: The user enters information such as "I lent my friend a pencil, but he never returned it, and we got into an argument."

[1335] Example prompt: "You lent a friend a pencil, but he didn't return it, and you got into an argument. Generate a fictional moral story based on this."

[1336] This system allows users to concretely learn emotional expression, empathy, and problem-solving skills through fictional works, and allows them to share the created works with family and friends.

[1337] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1338] Step 1:

[1339] The user enters the dispute information

[1340] Users can use a dedicated application or a web form to enter specific details about everyday disputes. For example, they can enter information like, "I lent my friend a pencil and he didn't return it, so we got into an argument." The input data is represented in JSON format. Based on the input, the system stores it in a database and prepares it for the next step.

[1341] Step 2:

[1342] Sending data from the device to the server

[1343] The user device converts the entered dispute information into JSON format and sends it to the specified API endpoint (e.g., / generate_story). This is done using an HTTP POST request, which sends the input data to the server. The server then validates the received data and checks for any problems before proceeding with analysis.

[1344] Step 3:

[1345] The server analyzes the information

[1346] The server receives the JSON data sent from the device. This analysis method analyzes the received data and understands the meaning of the input information. Specifically, it uses natural language processing technology to analyze the details of the dispute. Based on this analysis, it generates prompts to generate appropriate fiction works.

[1347] Step 4:

[1348] Generate a work of fiction

[1349] The server passes the parsed information to a generation engine, which generates a fictional work based on the prompt. This generation method uses natural language processing techniques such as OpenAI's GPT model. For example, if the prompt is "I lent my friend a pencil and he didn't return it, and we got into an argument. Please generate a fictional story with a moral based on this content.", the engine will generate a corresponding fictional work. The generated fictional work is saved in JSON format.

[1350] Step 5:

[1351] Send the generated work back to the user's device

[1352] The server formats the generated work of fiction and returns it to the user's device. This returns the generated JSON data as an HTTP response to the user's device. The user's device parses the received JSON data and displays or plays the work of fiction to the user.

[1353] Step 6:

[1354] Users can review their work and use the learning mode

[1355] The user reviews the returned fictional work. This reviewing means provides the user's device with the ability to display and play the work in text or audio. The user can also use the learning means to participate in quizzes and discussions based on the work. This allows the user to specifically learn skills such as empathy and problem-solving.

[1356] Step 7:

[1357] Share your creations

[1358] Users can share the fictional works they create with their families and friends. This sharing method generates a link for sharing the work and provides the ability to share it with others via social networking sites, email, etc. The shared work can then be used by others to view and learn from.

[1359] 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.

[1360] This system allows users to input information about everyday disputes, and then generates fictional works based on that information, which can then be used as teaching materials for moral education. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the system aims to provide a more effective educational experience. This system allows children to concretely learn emotional expression, empathy, and problem-solving skills.

[1361] The system of the present invention is implemented by the following configuration and processing steps.

[1362] System Configuration

[1363] 1. User Device

[1364] As an input method, we provide a function that allows users to enter specific information about disputes on a daily basis. This is realized by a dedicated application or a web form.

[1365] As a transmission means, it has a function of transmitting the input information to the server.

[1366] 2. Server

[1367] As an analytical tool, it has the function of analyzing dispute information sent by users.

[1368] As a generation means, it has the function of generating fictional works using a generation engine based on the analyzed information.

[1369] As an emotion engine, it has the ability to recognize the user's emotions from the dispute information entered by the user.

[1370] As a return means, it has a function to send the generated fictional work to the user's terminal.

[1371] 3. Generation Engine

[1372] Software that uses natural language processing technology to generate fictional works based on detailed dispute information and perceived emotions.

[1373] 4. User Device

[1374] As a means of verification, it has the ability to display or play the returned fictional work.

[1375] As a means of discussion, we provide a function to use the generated fictional works in classes and hold discussions.

[1376] Specific examples of program processing

[1377] Enter and submit dispute information

[1378] Users enter details of the dispute through a dedicated application or a web form. For example, they enter information like, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[1379] The device converts the input information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[1380] Information analysis and emotion recognition

[1381] The server receives the JSON data sent from the device and analyzes the details of the dispute. It also uses an emotion engine to recognize the user's emotion from the entered details of the dispute. This emotion information is included in the analyzed data passed to the generation engine.

[1382] Generating a work of fiction

[1383] The server then passes the analyzed information and emotional information to a generation engine (using natural language processing technology) and instructs it to generate a fictional work. For example, if the user's emotion is "anger," a story will unfold that corresponds to that emotion.

[1384] An example of what might be generated is a short story like this:

[1385] "One day in the classroom, A-kun started to worry that B-kun hadn't returned the pencil he'd lent him. A-kun asked B-kun to return the pencil, but B-kun apologized, saying that he had been busy and had forgotten. A-kun and B-kun talked it over and decided that from now on they would keep their promises to each other."

[1386] Return and Review of Works of Fiction

[1387] The server formats the generated short story and returns it to the user's device in JSON format.

[1388] The terminal displays the short story received from the server and allows the user to review it, allowing the user to read the generated work of fiction.

[1389] Classroom use and discussion

[1390] The user (teacher) can use the displayed short story in class and read it aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems, thereby concretely learning the elements of the SEL program.

[1391] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills. Furthermore, by combining it with an emotion engine, it is possible to provide a more personalized educational experience.

[1392] The processing flow will be explained below.

[1393] Step 1:

[1394] The user opens a dedicated application or web form. In the input field, they fill in the details of the dispute, for example, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[1395] Step 2:

[1396] The device converts the input information into JSON format and sends the converted data to the specified API endpoint (e.g., / generate_story).

[1397] Step 3:

[1398] The server receives the JSON data sent from the device, analyzes it, and extracts detailed information about the dispute.

[1399] Step 4:

[1400] The server sends the analyzed information to the emotion engine, which recognizes the user's emotion based on the conflict.

[1401] Step 5:

[1402] The server receives the emotion information obtained from the emotion engine and sends it along with the analyzed information to the generation engine, which then generates a fictional work based on the input data and emotion information.

[1403] Step 6:

[1404] The server formats the fictional work returned by the generation engine and returns the generated fictional work in JSON format to the user's device.

[1405] Step 7:

[1406] The device parses the JSON-formatted fictional work received from the server, converts it into a human-readable format, and displays the converted fictional work for the user to review.

[1407] Step 8:

[1408] The user (teacher) uses the displayed fictional work in class. The user reads the short story to the entire class and discusses the conflict with all the students. Through the discussion, children can learn to express emotions, develop empathy, and problem-solving skills.

[1409] In this way, the use of the emotion engine enables a system that provides a more personalized educational experience.

[1410] Example 2

[1411] 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."

[1412] The current education system provides limited opportunities for children to specifically learn emotional expression, empathy, and problem-solving skills. It also lacks ways to effectively use everyday conflicts as educational resources. This calls for a new system to increase opportunities for social and emotional learning (SEL) and promote children's emotional growth.

[1413] 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.

[1414] In this invention, the server includes an emotion engine that analyzes input information and recognizes emotions, a means for generating a fictional work using a generation engine based on the results of the emotion engine, and a means for returning the generated work to the user's terminal. This allows a user to input information about everyday conflicts, recognize emotions based on that information, and generate and return an appropriate fictional work. This provides concrete social and emotional learning opportunities in educational settings and effectively fosters children's emotional expression, empathy, and problem-solving skills.

[1415] The "input means" is a part of the system that provides a function that allows users to input specific information about disputes on a daily basis.

[1416] The "transmission means" is a part of the system that has the function of transmitting input information to the server.

[1417] A "server" is a computing device that receives and analyzes information over a network and performs specific processing.

[1418] The "emotion engine" is software that recognizes emotions from dispute information entered by the user.

[1419] A "generation engine" is software that uses natural language processing technology to generate fictional works based on analyzed information.

[1420] A "generator" is a part of the system that has the function of generating a work of fiction based on the analyzed information.

[1421] The "returning means" is a part of the system that has the function of returning the fictional work generated by the server to the user's terminal.

[1422] A "verification means" is the part of the system that allows a user to verify a returned work of fiction.

[1423] The "discussion tool" is part of a system for using the generated fictional works in class and holding discussions.

[1424] "Natural language processing technology" is a computer science technology for understanding and generating human language.

[1425] This system allows users to input information about everyday disputes, and then generates fictional works based on that information, which can then be used as teaching materials for moral education. The system is particularly equipped with an emotion engine that recognizes the user's emotions, aiming to provide a more effective educational experience. This system allows children to specifically learn emotional expression, empathy, and problem-solving skills.

[1426] Hardware and software used

[1427] 1. User Device

[1428] It uses a computer, tablet, or smartphone, which can be operated via a dedicated application or a web browser.

[1429] 2. Server

[1430] The information is received, analyzed, the fiction is generated, and then returned to us using the servers of cloud service providers (e.g., Amazon Web Services, Microsoft Azure, Google Cloud Platform).

[1431] 3. Emotion Engine

[1432] Software that recognizes user emotions from input dispute information. Examples include Microsoft Azure's Cognitive Services and Google Cloud's Natural Language API.

[1433] 4. Generation Engine

[1434] Software that uses natural language processing technology to generate fictional works based on input information and recognized emotions. Specific examples include OpenAI's GPT-3 and GPT-4.

[1435] System operation example

[1436] Enter and submit dispute information

[1437] Users enter details of the dispute through a dedicated application or a web form. For example, they enter information like, "I lent my friend a pencil and he never returned it, which led to an argument." Once they're done, they press the "Submit" button.

[1438] The device converts the input information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[1439] Information analysis and emotion recognition

[1440] The server receives the JSON data sent from the device and analyzes the details of the dispute. Using the emotion engine, it recognizes the user's emotion from the entered details of the dispute. This emotion information is included in the analyzed data passed to the generation engine.

[1441] Generating a work of fiction

[1442] The server then passes the analyzed information and emotion information to the generation engine, instructing it to generate a fictional work. For example, if the user's emotion is "anger," a story will unfold according to that emotion.

[1443] An example of what might be generated is a short story like this:

[1444] "One day in the classroom, A was worried because B hadn't returned the pencil he'd lent him. A asked B to return the pencil, but B apologized, saying that he had been busy and had forgotten. A and B talked it over and decided that from now on they would keep their promises to each other."

[1445] Return and Review of Works of Fiction

[1446] The server formats the generated short story and returns it to the user's device in JSON format.

[1447] The terminal displays the short story received from the server and allows the user to review it, allowing the user to read the generated work of fiction.

[1448] Classroom use and discussion

[1449] The user (teacher) can use the displayed short story in class and read it aloud to all the students. The students can then express their opinions about the characters' feelings and actions and discuss how to solve the problems, thereby concretely learning the elements of the SEL program.

[1450] In this way, the system of the present invention transforms everyday conflicts into educational resources, helping children develop emotional expression, empathy, and problem-solving skills. Furthermore, by combining it with an emotion engine, it is possible to provide a more personalized educational experience.

[1451] Examples of prompt statements

[1452] A possible prompt might be written as follows:

[1453] Dispute: I lent my friend a pencil and he never returned it, so we got into an argument.

[1454] Emotion: Anger

[1455] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1456] Step 1:

[1457] Users enter details of the dispute through a dedicated application or web form. For example, they might enter a specific situation, such as, "I lent my friend a pencil, but he never returned it, and we got into an argument." The entered data is sent directly to the device in JSON format.

[1458] Input: User-entered dispute information

[1459] Output: JSON formatted dispute information

[1460] What happens: A user opens an application or web form, enters details about the dispute, and presses the "Submit" button.

[1461] Step 2:

[1462] The device receives the dispute information entered by the user and converts it into JSON format, which is then sent to the server, for example, to the API endpoint ( / generate_story).

[1463] Input: User-entered dispute information

[1464] Output: JSON formatted dispute information sent to the server

[1465] Specific operation: The device formats the input information into the appropriate JSON format and sends it to the specified API endpoint.

[1466] Step 3:

[1467] The server receives the JSON data sent from the device, analyzes it, and extracts details of the dispute. It then uses an emotion engine to recognize the user's emotion from the input information. For example, based on the keyword "argument," it determines that the emotion is "anger."

[1468] Input: JSON formatted dispute information sent from the device

[1469] Output: Analyzed details and emotional information of the conflict

[1470] Specific operation: The server analyzes detailed information about the dispute and uses an emotion engine to recognize emotions.

[1471] Step 4:

[1472] The server passes the analyzed details of the dispute and the recognized emotion information to a generation engine, instructing it to generate a fictional work. For example, if the emotion is "anger," a story will unfold according to that emotion. The generation engine uses natural language processing technology to generate a fictional work.

[1473] Input: Analyzed details and emotional information about the conflict

[1474] Output: A generated work of fiction

[1475] What it does: Pass data to a generation engine and generate a work of fiction using natural language processing techniques.

[1476] Step 5:

[1477] The server formats the generated fictional work and returns it to the user's device in JSON format.

[1478] Input: A generated work of fiction

[1479] Output: JSON fiction data

[1480] Specific operation: The server formats the generated fictional work into fields and returns it to the terminal in JSON format.

[1481] Step 6:

[1482] The terminal displays the fictional work received from the server to the user, who can then view and read the work.

[1483] Input: JSON formatted fiction data

[1484] Output: A work of fiction displayed to the user

[1485] Specific behavior: The device properly formats and displays the received work of fiction for the user to review.

[1486] Step 7:

[1487] The user (teacher) uses the generated short story in class and reads it to all the students. The students comment on the feelings and actions of the characters and discuss how to solve the problems.

[1488] Input: A work of fiction displayed to the user

[1489] Output: Class discussion and learning outcomes

[1490] Specific operations: The user (teacher) reads a work of fiction to the students and engages in a discussion.

[1491] (Application example 2)

[1492] 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."

[1493] One issue facing brick-and-mortar stores is the lack of effective training methods for staff to resolve disputes that arise when dealing with customers. It's particularly difficult to accurately grasp customer emotions and learn how to respond appropriately. Current training methods are insufficient to teach specific skills that can be applied in real-world situations, resulting in lower customer satisfaction and increased customer trouble.

[1494] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion engine means for analyzing input information and recognizing emotions, generation engine means for generating a fictional work based on the analyzed information and emotion information, and return means for returning the generated work to the user's terminal. This allows users to generate fictional works corresponding to emotions based on information about disputes that arise in actual customer interactions and use them as training materials. Staff can learn specific response methods through the generated works and improve their customer interaction skills.

[1495] "Input means" refers to a device or interface that allows users to input specific information about disputes that arise on a daily basis.

[1496] "Transmission means" refers to a device or protocol that has the function of transmitting input information to a server.

[1497] "Generation means" means a system or software that has the function of analyzing the information received by the server and generating a work of fiction based on a generation engine.

[1498] An "emotion engine" is a technology or algorithm that analyzes the information received by the server and recognizes the user's emotions.

[1499] "Returning means" refers to a communication function for returning the created work to the user's terminal.

[1500] "Verification means" refers to a device or application that allows a user to view and verify the returned work.

[1501] "Discussion tool" refers to an interface or functionality for using the generated work to hold discussions in classes or training.

[1502] "Natural language processing technology" is a general term for technology that uses computers to analyze and understand human language.

[1503] This invention is a system that inputs information about customer troubles that staff members actually encounter in a brick-and-mortar store, and generates fictional works based on that information to be used as educational content. The system includes a user terminal, a server, a generation engine, and an emotion engine. Each component and processing step is described in detail below.

[1504] System Configuration

[1505] 1. User Device

[1506] The user terminal is a device such as a smartphone or tablet. This terminal provides an input means for staff to input and submit customer trouble information through a dedicated application or web form. It also has the function of displaying and checking the fictional work that is later generated.

[1507] 2. Server

[1508] The server has the following main functions:

[1509] Analysis of information: The server receives and analyzes the dispute information sent from the user terminal.

[1510] Emotion recognition: An emotion engine is used to recognize customer emotions from dispute information. Specific technologies used include IBM Watson's emotion analysis API.

[1511] Fiction generation: Using the analyzed information and sentiment information, fiction is generated through a generative engine (e.g., OpenAI's GPT-3), which uses natural language processing techniques.

[1512] Return: The generated fictional work is formatted and returned to the user's device.

[1513] 3. Generation Engine

[1514] The generation engine uses natural language processing techniques to generate fictional stories based on conflicts, specifically using AI models such as OpenAI's GPT-3. Example prompts include:

[1515] "A customer wants to return an item, but is having trouble because it violates the return policy. The customer is dissatisfied. Generate a story based on this."

[1516] Specific processing of the program

[1517] Enter and submit information

[1518] The user (staff member) enters details of the customer issue through a dedicated application or web form. For example, they might enter information such as, "The customer wants to return a product, but we are having trouble handling this because it violates our return policy." Once the information is complete, the user presses the "Submit" button. The terminal converts this information into JSON format and sends it to the specified API endpoint (e.g., / generate_story).

[1519] Information analysis and emotion recognition

[1520] The server receives the JSON data sent from the device and analyzes the details of the dispute. At the same time, it uses an emotion engine to recognize the customer's emotions from the detailed dispute information entered. This emotion information is included in the analyzed data passed to the generation engine. The emotion engine uses IBM Watson's emotion analysis API.

[1521] Generating a work of fiction

[1522] The server passes the analyzed information and emotion information to a generation engine (such as OpenAI's GPT-3) and instructs it to generate a work of fiction. For example, if the customer's emotion is "dissatisfied," a story will unfold that corresponds to that emotion. An example of the generated content could be a short story like the one below:

[1523] "One day, clerk A received an item from customer B that he wanted to return, but it violated the return policy. B looked dissatisfied and said, 'This item is defective. Please do something about it.' A spoke to a manager and was able to alleviate B's frustration by offering a discount coupon for their next purchase instead of a return."

[1524] Return and Review of Works of Fiction

[1525] The server formats the generated fictional work and returns it in JSON format to the user's device. The user's device displays the fictional work received from the server and allows the user to confirm it, allowing the user to read the generated fictional work.

[1526] Classroom use and discussion

[1527] The user (e.g., a store staff member) can use the displayed short story in a training session and read it aloud to all staff members. The staff members can then comment on the feelings and actions of the characters and discuss how to solve the problems, thereby learning specific skills for dealing with customers.

[1528] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1529] Step 1: Enter and submit information

[1530] The user enters details of the customer issue through a dedicated application or web form. For example, they might enter information such as, "The customer wants to return a product, but we are having trouble doing so because it violates our return policy." The entered information is converted to JSON format within the application. The user then presses the "Submit" button, which sends the entered information to an API endpoint (e.g., / generate_story). Specifically, the form is submitted by touching the smartphone.

[1531] input:

[1532] Detailed information about customer trouble

[1533] output:

[1534] Information converted to JSON format

[1535] Step 2: Receiving and analyzing information

[1536] The server receives the JSON data sent from the device. The received data is passed to the analysis module, where detailed information about the dispute is extracted through text analysis. Based on this analysis data, the server calls an emotion engine (e.g., IBM Watson's emotion analysis API) to recognize the customer's emotions.

[1537] input:

[1538] JSON format customer trouble information

[1539] output:

[1540] Parsed text data

[1541] Customer sentiment information

[1542] Step 3: Recognize emotions

[1543] The server uses an emotion engine to analyze customer emotions. At this time, emotions such as "dissatisfaction" and "anger" are recognized from the text data. The analyzed emotion data is then passed to a generation engine. The server then integrates the text analysis results with the emotion information.

[1544] input:

[1545] Parsed text data

[1546] output:

[1547] Customer sentiment information

[1548] Step 4: Generate a work of fiction

[1549] Based on the analyzed information and emotion information, the server issues instructions to a generation engine (e.g., OpenAI's GPT-3) to generate a work of fiction. The generation engine generates a story based on a specified prompt. For example, it sends a prompt such as, "A customer wants to return a product, but a problem has arisen because it violates the return policy. The customer is dissatisfied. Please generate a story based on this."

[1550] input:

[1551] Integrated text and sentiment information

[1552] Prompt statement

[1553] output:

[1554] Generated works of fiction

[1555] Step 5: Return your work of fiction

[1556] The server then formats the generated fictional work into JSON format again and sends it back to the user's device, where it can be viewed.

[1557] input:

[1558] Generated works of fiction

[1559] output:

[1560] Works of fiction in JSON format

[1561] Step 6: Identifying works of fiction

[1562] The user terminal displays the fictional work received from the server and allows the user to review it. This allows store staff to read the generated fictional work. Specific operations include displaying the work on a smartphone or tablet screen.

[1563] input:

[1564] Works of fiction in JSON format

[1565] output:

[1566] The fictional work displayed

[1567] Step 7: Classroom Use and Discussion

[1568] Users (such as store staff) train based on the displayed fictional work. Specifically, the work is read aloud during the training session, and staff discuss the characters' actions and emotions. This allows them to learn skills that will be useful when dealing with real customers.

[1569] input:

[1570] The fictional work displayed

[1571] output:

[1572] Training discussion materials

[1573] The above processing steps realize a system for effectively providing customer service training for brick-and-mortar stores.

[1574] 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.

[1575] 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.

[1576] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1577] 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.

[1578] 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.

[1579] 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.

[1580] 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).

[1581] 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.

[1582] 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."

[1583] 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.

[1584] 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).

[1585] 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.

[1586] 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.

[1587] 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.

[1588] 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.

[1589] 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.

[1590] 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.

[1591] 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.

[1592] 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.

[1593] 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.

[1594] 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.

[1595] The following is further disclosed regarding the above embodiment.

[1596] (Claim 1)

[1597] an input means for a user to input information about disputes that occur on a daily basis;

[1598] a transmitting means for transmitting the input information to a server;

[1599] generation means for analyzing the information received by the server and generating a work of fiction based on the generation engine;

[1600] a return means for returning the generated work to the user's terminal;

[1601] a means for the user to review the returned work;

[1602] A system including:

[1603] (Claim 2)

[1604] 10. The system according to claim 1, further comprising a discussion means for using the generated work in a class and holding a discussion.

[1605] (Claim 3)

[1606] 10. The system of claim 1, wherein the generation engine includes means for generating works of fiction using natural language processing techniques.

[1607] "Example 1"

[1608] (Claim 1)

[1609] an input means for a user to input information about disputes that occur on a daily basis;

[1610] a transmitting means for transmitting the input information to a server;

[1611] a generating means for analyzing the information received by the server and generating a work of fiction using natural language processing technology;

[1612] a return means for returning the generated work to the user's terminal;

[1613] a means for the user to review the returned work;

[1614] A system including:

[1615] (Claim 2)

[1616] 10. The system according to claim 1, further comprising a discussion means for using the generated work in a class and holding a discussion.

[1617] (Claim 3)

[1618] 10. The system of claim 1, wherein the generation engine includes means for generating prompt sentences based on conflict information and using the prompt sentences to generate a work of fiction.

[1619] "Application Example 1"

[1620] (Claim 1)

[1621] an input means for a user to input information about disputes that occur on a daily basis;

[1622] a transmitting means for transmitting the input information to a server;

[1623] generation means for analyzing the information received by the server and generating a work of fiction based on the generation engine;

[1624] a return means for returning the generated work to the user's terminal;

[1625] a means for the user to review the returned work;

[1626] A learning tool that provides an educational mode including educational quizzes and discussion features for solving interpersonal problems and learning emotional empathy;

[1627] A system including:

[1628] (Claim 2)

[1629] 10. The system of claim 1, further comprising a sharing means for sharing the generated work with family and friends.

[1630] (Claim 3)

[1631] 10. The system of claim 1, wherein the generation engine includes means for generating works of fiction using natural language processing techniques.

[1632] "Example 2: Combining Emotion Engines"

[1633] (Claim 1)

[1634] an input means for a user to input information about disputes that occur on a daily basis;

[1635] a transmitting means for transmitting the input information to a server;

[1636] An emotion engine that analyzes the information received by the server and recognizes emotions;

[1637] generating means for generating a work of fiction using a generation engine based on the results of the emotion engine;

[1638] a return means for returning the generated work to the user's terminal;

[1639] a means for the user to review the returned work;

[1640] A system including:

[1641] (Claim 2)

[1642] 10. The system according to claim 1, further comprising a discussion means for using the generated work in a class and holding a discussion.

[1643] (Claim 3)

[1644] 10. The system of claim 1, wherein the generation engine includes means for generating works of fiction using natural language processing techniques.

[1645] "Application example 2 when combining emotion engines"

[1646] (Claim 1)

[1647] an input means for a user to input information about disputes that occur on a daily basis;

[1648] a transmitting means for transmitting the input information to a server;

[1649] generation means for analyzing the information received by the server and generating a work of fiction based on the generation engine;

[1650] An emotion engine that analyzes the information received by the server and recognizes emotions;

[1651] a return means for returning the generated work to the user's terminal;

[1652] a means for the user to review the returned work;

[1653] A system including:

[1654] (Claim 2)

[1655] 10. The system of claim 1, further comprising a discussion means for using the generated work in classes or training and for holding discussions.

[1656] (Claim 3)

[1657] 10. The system of claim 1, wherein the generation engine includes means for generating works of fiction using natural language processing techniques.

[1658] (Claim 4)

[1659] The system of claim 1, wherein the server instructs the generation engine based on the analyzed information and emotional information to generate a work of fiction.

[1660] (Claim 5)

[1661] 2. The system according to claim 1, wherein a user terminal inputs dispute information through a specific application. [Explanation of symbols]

[1662] 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. an input means for a user to input information about disputes that occur on a daily basis; a transmitting means for transmitting the input information to a server; generation means for analyzing the information received by the server and generating a work of fiction based on the generation engine; a return means for returning the generated work to the user's terminal; a means for the user to review the returned work; A system including:

2. The system according to claim 1, further comprising a discussion means for using the generated work in a class and holding a discussion.

3. 10. The system of claim 1, wherein the generation engine includes means for generating works of fiction using natural language processing techniques.

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