System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving a plurality of inputs; means for summarizing the plurality of inputs; means for converting the summarized contents into a designated format; and means for outputting the converted contents.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] Traditionally, story creation has mainly been the work of individual authors or scriptwriters, requiring a lot of time and effort. Furthermore, the involvement of multiple people makes it difficult to incorporate original ideas or unexpected developments. Furthermore, ideas cannot be submitted anonymously, which can sometimes inhibit free thinking. For this reason, there is a need for a method to efficiently construct a story while incorporating diverse perspectives. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including a means for accepting multiple inputs, a means for summarizing the multiple inputs, a means for converting the summarized content into a specified format, and a means for outputting the converted content. This system allows for the efficient collection and summarization of diverse ideas, and can also output the content in a specified format. Furthermore, by including a means for anonymously accepting ideas, it facilitates the elicitation of free imagination. This allows for the efficient creation of stories with novel and unexpected developments.

[0006] "Input means" refers to the means by which a user provides ideas and information to the system in a free format.

[0007] A "summarization means" is a means for extracting important parts from multiple inputs and summarizing them concisely.

[0008] "Format conversion means" means means for converting the summarized content into a specified format (e.g., text, video, or a combination thereof).

[0009] "Output means" refers to a means for displaying or providing the converted content in a form that can be viewed and used by the user.

[0010] The "anonymous input means" is a means by which users can anonymously provide their ideas to the system.

[0011] "System" refers to a complex device or collection of software that performs a series of processes that accept multiple inputs, summarize them, convert them into a specified form, and finally produce an output. [Brief explanation of the drawings]

[0012] [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

[0013] 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.

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

[0015] 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).

[0016] 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.

[0017] 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.

[0018] 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.

[0019] 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."

[0020] [First embodiment]

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

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0027] 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.

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

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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."

[0033] The present invention is a system that summarizes the ideas of multiple users, such as characters, plots, and developments, and outputs them in a specified format (text, video, a combined format, etc.) to create a single work.

[0034] Program Overview

[0035] 1. User Idea Input and Submission

[0036] Users use a dedicated input form or application to input their ideas into the device in any format (text, images, etc.). The ideas are then sent from the device to the server, which receives the ideas and stores them in a database.

[0037] 2. Collecting and Summarizing Ideas

[0038] The server collects all ideas from the database, and based on the collected ideas, the summarization program analyzes and summarizes the information, extracts the important parts, and generates a concise story.

[0039] 3. Convert to the specified format

[0040] The summarized story is then converted into a pre-specified format (text, video, or a combination) by a formatting output program on the server, which provides the story in a format that is easy for the user to read and understand.

[0041] 4. Narrative output and display

[0042] The converted story is finally sent to the device and displayed in a viewable format for the user, allowing the user to easily refer to and enjoy the generated story.

[0043] Specific examples

[0044] User input and submission

[0045] User 1: "He's a brave warrior and he's looking for a magic sword."

[0046] User 2: "She was a wise wizard who set out on a journey to help the warrior."

[0047] User 3: "They fight a giant dragon and save the village."

[0048] These ideas are sent from each user's terminal to the server.

[0049] Server processing and result output

[0050] The server collects these ideas and uses a summarization program to generate a condensed story like this:

[0051] "The story of a brave warrior and a wise wizard who embark on a journey to battle a giant dragon and save their village."

[0052] A formatted output program will convert this condensed story into text and display it on the terminal as follows:

[0053] Story Title: The Adventure of the Hero and the Wizard

[0054] He is a brave warrior searching for a magical sword, and she is a wise wizard who sets out on a journey to help him. Together they battle a giant dragon and save their village.

[0055] In this way, the system of the present invention can efficiently collect and summarize diverse ideas, output them in a specified format, and create a novel story, thereby realizing creative activities that go beyond the limitations of conventional individual work.

[0056] The processing flow will be explained below.

[0057] Step 1:

[0058] Users input their ideas using their own devices. Using a dedicated input form or application, users can input their ideas in any format, such as text or images.

[0059] Step 2:

[0060] The terminal sends the input idea to the server, along with the user's identification information (e.g., user ID) and idea format information.

[0061] Step 3:

[0062] The server receives the ideas sent from the device and stores them in a data store (database).

[0063] Step 4:

[0064] The server collects all ideas from the data store. In this step, all ideas submitted by multiple users are obtained.

[0065] Step 5:

[0066] The server's summarization program analyzes and summarizes the collected ideas, extracting the key points and summarizing them into a concise narrative.

[0067] Step 6:

[0068] The server passes the summarized story to a formatting program, which converts the summarized story into a specified format (e.g., text format, video format, etc.).

[0069] Step 7:

[0070] The server sends the formatted story to the device, which receives it and displays it in a format that the user can view.

[0071] Step 8:

[0072] The user can view the generated story through a terminal. The user can read the story or watch it as a video.

[0073] By using the above steps, the system of the present invention can efficiently collect and summarize ideas provided by multiple users and output them in a variety of formats.

[0074] Example 1

[0075] 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."

[0076] Conventional technologies have been unable to efficiently collect ideas entered by multiple users in different formats, summarize them, convert them into a specified format, and output them. Furthermore, there has been no system that can generate high-quality stories while protecting user privacy by accepting these ideas anonymously. Therefore, there is a need for a system that can accept ideas in various formats from users, summarize them, and output them in a specified format.

[0077] 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.

[0078] In this invention, the server includes means for accepting multiple inputs, means for storing the multiple inputs in a database, means for using a generative AI model to summarize the multiple inputs, means for converting the summarized content into a specified format, and means for outputting the converted content, thereby enabling efficient collection, analysis, and summary of various ideas from users, and outputting them in a specified format to provide an easy-to-read story.

[0079] "Multiple inputs" refers to ideas provided by multiple users in different formats (text, images, etc.).

[0080] "Database" refers to a digital information repository for storing and managing multiple inputs received.

[0081] A "summary" refers to information that extracts important content from multiple inputs and summarizes it concisely.

[0082] A "generative AI model" refers to an artificial intelligence algorithm that analyzes input data and performs summarization or transformation.

[0083] "Specified format" refers to the output format after conversion (e.g., text, video, or a combination thereof).

[0084] "Output" refers to the act of providing the user with the summary converted into a specified format.

[0085] The present invention is a system that summarizes the ideas of multiple users, such as characters, plots, and developments, and outputs them in a specified format (text, video, a combination of text, etc.) to create a single work. Specific embodiments of this system are described below.

[0086] User idea entry and submission

[0087] Users use a dedicated input form or application to input their ideas into the device in any format (text, images, etc.). The ideas are then sent from the device to the server, which receives the ideas and stores them in a database.

[0088] Idea collection and summarization

[0089] The server collects all ideas from the database. Based on the collected ideas, a summary program analyzes and summarizes the information using a generative AI model (e.g., GPT-4), extracts the important parts, and generates a concise story. An example of a specific prompt is "Generate a concise story based on the following user ideas:" followed by a list of the user's ideas.

[0090] for example,

[0091] "Generate a concise narrative based on the following user ideas:

[0092] 1. He is a brave warrior and is searching for a magic sword.

[0093] 2. She was a wise wizard who set out on a journey to help the warrior.

[0094] 3. The two fight a giant dragon and save the village.

[0095] Conversion to a specified format

[0096] The summarized story is then converted into a pre-specified format (text, video, or a combination) by a formatting output program on the server, which provides the story in a format that is easy for the user to read and understand.

[0097] Narrative output and display

[0098] The converted story is finally sent to the device and displayed in a viewable format for the user, allowing the user to easily refer to and enjoy the generated story.

[0099] Specific examples

[0100] User 1: "He's a brave warrior and he's looking for a magic sword."

[0101] User 2: "She was a wise wizard who set out on a journey to help the warrior."

[0102] User 3: "They fight a giant dragon and save the village."

[0103] These ideas are sent from the device to a server, which stores the data in a database. The server collects these ideas and uses a generative AI model to generate a summarized story, such as:

[0104] "The story of a brave warrior and a wise wizard who embark on a journey to battle a giant dragon and save their village."

[0105] A formatted output program converts this condensed story into text and displays it on the terminal:

[0106] Story Title: The Adventure of the Hero and the Wizard

[0107] He is a brave warrior searching for a magical sword, and she is a wise wizard who sets out on a journey to help him. Together they battle a giant dragon and save their village.

[0108] In this way, the system can efficiently collect, analyze, summarize, and output various ideas from users in a specified format, providing them with an easy-to-understand story, thereby enabling creative activities that go beyond the limitations of traditional individual work.

[0109] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0110] Step 1:

[0111] The user launches a dedicated input form or application. The user enters their idea in the input form in the form of text or images. When the user clicks the "Send" button, the device sends the information to the server. Specifically, User 1 enters "He is a brave warrior and is looking for a magic sword" and presses the send button.

[0112] Input: The idea the user entered into the form (e.g., "He is a brave warrior and is looking for a magic sword.")

[0113] Output: The input ideas are sent from the terminal to the server.

[0114] Step 2:

[0115] The server stores the received ideas in a database, which records and manages all ideas received from each user.

[0116] Input: User ideas sent from the device (e.g., "He is a brave warrior and is looking for a magic sword.")

[0117] Output: Ideas stored in a database.

[0118] Step 3:

[0119] The server collects all user ideas from the database and passes the collected ideas to the summarization program.

[0120] Input: All user ideas in the database

[0121] Output: A set of ideas that is passed to the summarization program.

[0122] Step 4:

[0123] The summarization program calls a generative AI model (e.g., GPT-4) to analyze and summarize the input idea. Specifically, the user's idea is input along with the prompt, "Generate a concise story based on the user's idea below:" The generative AI model extracts key elements and generates a concise story.

[0124] Input: The user's idea passed to the summary program along with the prompt.

[0125] Output: The summary produced by the generative AI model.

[0126] Step 5:

[0127] The server stores the generated summary in a database, which is used to convert the summary to the specified format in the next step.

[0128] Input: A summary generated by a generative AI model (e.g., "A story about a brave warrior and a wise wizard who embark on a journey to battle a giant dragon and save their village.")

[0129] Output: A summary stored in a database.

[0130] Step 6:

[0131] The server passes the summarized story to a formatting program, which converts it into a specified format (text, video, etc.), for example, converting the summarized story into text format.

[0132] Input: Abstracted stories in the database

[0133] Output: The story converted to the specified format.

[0134] Step 7:

[0135] The server sends the converted story to the terminal, which displays the received story to the user.

[0136] Input: A textual narrative generated by a formatted output program

[0137] Output: The story displayed on the user's terminal.

[0138] Through this series of processes, the diverse ideas of users are efficiently collected, analyzed, summarized, and output in the specified format to form a novel story. The user can easily browse and enjoy the final story that is displayed.

[0139] (Application example 1)

[0140] 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."

[0141] Conventional story generation systems have had difficulty automatically generating efficient and compelling content when integrating individual user ideas into a single work. Effectively summarizing ideas input by multiple users and outputting them in a specified format requires advanced natural language processing capabilities. Another challenge is accepting these ideas anonymously while integrating and outputting them as a compelling story.

[0142] 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.

[0143] In this invention, the server includes means for accepting multiple inputs, means for summarizing the multiple inputs, means for converting the summarized content into a specified format, means for outputting the converted content, means for analyzing the multiple inputs using a generative AI model to generate a story, and means for displaying the generated story in a format that can be viewed by the user. This makes it possible to effectively collect and summarize individual user ideas, automatically generate an attractive story, and output it in a specified format.

[0144] "Multiple inputs" refers to information in various formats, such as text and images, provided by multiple users.

[0145] A "summarizer" is a part of a system that has the ability to extract important content from multiple inputs and summarize it in a compact form.

[0146] "Specified Format" means a format specified by the User that represents the Generated Content in text, video, or a combination thereof.

[0147] "Transforming means" refers to the process or algorithm used to transform the summarized content into the specified format.

[0148] "Means for outputting" refers to an interface or device for displaying the converted content in a form that can be viewed by a user.

[0149] A "generative AI model" refers to an artificial intelligence model that has the ability to analyze information collected from users and generate stories in the form of text, video, etc.

[0150] "Means for analyzing and generating a narrative" refers to the process of automatically generating a narrative from multiple inputs using a generative AI model.

[0151] "Means for displaying in a viewable form" refers to the function of providing the generated story in a form that can be viewed by users through devices such as smartphones or computers.

[0152] To implement this invention, it is necessary to build a system that involves the following process between a server, a terminal, and a user. First, a user inputs their idea through a dedicated application. Ideas can be input in a variety of formats, including text and images, and are then sent to the server. The server receives the data using a web framework such as Flask and stores it in a database such as SQLite.

[0153] Next, the server collects the saved ideas and analyzes them using a generative AI model (e.g., OpenAI's GPT-3) to generate a summarized story. The prompt for the generative AI model consists of a combination of each of the user's ideas. For example, the prompt could be, "Generate a story based on the following idea: A brave warrior is searching for a magical sword. A wise wizard sets out on a journey to help the warrior. The two fight a giant dragon and save the village."

[0154] The generated story is converted into a specified format (e.g., text, video, or a combination of both). After conversion, the story is sent to the user's smartphone or computer and displayed in a viewable format. This allows the user to enjoy a story that integrates their own ideas.

[0155] Examples of prompts used are:

[0156] Generate a story based on the following ideas:

[0157] A brave warrior is searching for a magical sword.

[0158] A wise wizard set out to help the warrior.

[0159] The two fight a giant dragon and save the village.

[0160] By integrating these methods and processes, the server can effectively summarize the ideas of multiple users, automatically generate an engaging story, and output it in a specified format, allowing users to enjoy a new creative experience.

[0161] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0162] Step 1:

[0163] Users input their ideas through a dedicated application. Ideas can be entered in a variety of formats, including text and images, and are then sent to the server. The entered ideas are then properly formatted within the application and sent to the server via API. The input data includes the user's ID and the content of the idea.

[0164] Step 2:

[0165] The server receives the data using a web framework such as Flask and stores it in a database such as SQLite. The server records the received ideas in the database for later processing. The input is the user's idea data, and the output is the idea data stored in the database.

[0166] Step 3:

[0167] The server collects multiple saved ideas and analyzes them using a generative AI model (e.g., OpenAI's GPT-3). First, it retrieves all ideas from the database and formats them into a single prompt. The input is a set of ideas retrieved from the database, and the output is a prompt for the generative AI model.

[0168] Step 4:

[0169] A prompt is input into the generative AI model, which then generates a story. The AI ​​model analyzes the given prompt and generates a coherent story based on the context. The input is the prompt, and the output is the generated story.

[0170] Step 5:

[0171] Convert the generated story into a specified format (e.g., text, video, or a combination). For example, perform a formatting process to convert it into a text-based story, or use a video generation library (e.g., Stable Diffusion) if a video format is required. The input is the generated story, and the output is a story in the specified format.

[0172] Step 6:

[0173] The converted story is sent to the user's smartphone or computer and displayed in a viewable format. The story is sent to the user's device via an API and displayed within the application. The input is a story in the specified format, and the output is the story displayed on the user's device.

[0174] As an example of specific behavior, the prompt sentence to the generative AI model is as follows:

[0175] Generate a story based on the following ideas:

[0176] A brave warrior is searching for a magical sword.

[0177] A wise wizard set out to help the warrior.

[0178] The two fight a giant dragon and save the village.

[0179] Based on this prompt, the AI ​​model will generate a story, which will ultimately be presented to the user in a format that can be viewed.

[0180] 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.

[0181] This invention is a system that combines an emotion engine with ideas for characters, plots, developments, etc. that multiple users have each come up with, and adjusts the summarization and format conversion process to create a single work that reflects the emotional state of the users.

[0182] Program Overview

[0183] 1. User Idea Input and Submission

[0184] Users use a dedicated input form or application to input their ideas into the device in any format (text, images, etc.). The ideas are then sent from the device to the server, which receives the ideas and stores them in a database.

[0185] 2. Sentiment analysis using an emotion engine

[0186] The server is equipped with an emotion engine that performs emotion analysis on received ideas. The emotion engine uses natural language processing technology to determine the emotion (e.g., joy, sadness, surprise, anger, etc.) contained in each idea.

[0187] 3. Collecting and Summarizing Ideas

[0188] The server collects all ideas from the database and retrieves the sentiment analysis results. Then, based on the collected ideas and their sentiment data, the summarization program extracts the key parts and generates a concise story that reflects the sentiment.

[0189] 4. Conversion to the specified format

[0190] The summarized story is converted into a pre-specified format (e.g., text format, video format, etc.) by a format output program on the server. At this time, the emotional information determined by the emotion engine is also taken into consideration, and the expression of the story is adjusted.

[0191] 5. Narrative output and display

[0192] The converted story is finally sent to the device and displayed in a viewable format for the user, allowing the user to easily refer to and enjoy the generated story, as well as to enjoy stories that reflect the emotional state of other users.

[0193] Specific examples

[0194] User input and submission

[0195] User 1 (Sentiment Analysis: Joy): "He is a brave warrior and is looking for a magic sword."

[0196] User 2 (Sentiment Analysis: Surprise): "She was a wise wizard who set out on a journey to help the warrior."

[0197] User 3 (Sentiment Analysis: Sadness): "They fight a giant dragon and save the village."

[0198] These ideas are sent from each user's terminal to the server.

[0199] Server processing and result output

[0200] The server collects these ideas and performs a sentiment analysis on each idea using a sentiment engine. It then uses a summarization program to generate a summarized story, taking into account the sentiment information, like this:

[0201] "A tale of a brave warrior and a wise wizard who battle a mighty dragon with astonishment and embark on a heartbreaking journey to save their village."

[0202] A formatted output program will convert this condensed story into text and display it on the terminal as follows:

[0203] Story Title: The Adventure of the Hero and the Wizard

[0204] He is a brave warrior searching for a magic sword (Joy), she is a wise wizard who sets out on a journey to help him (Surprise), and together they fight a giant dragon and save their village (Sadness).

[0205] In this way, the system of the present invention can efficiently collect ideas provided by multiple users, summarize them emotionally, and convert them into a format that reflects their emotions, thereby creating a richer, more emotionally appealing story.

[0206] The processing flow will be explained below.

[0207] Step 1:

[0208] Users input their ideas using their own devices. Using a dedicated input form or application, users can input their ideas in any format, such as text or images.

[0209] Step 2:

[0210] The terminal sends the input idea to the server, along with the user's identification information (e.g., user ID) and idea format information.

[0211] Step 3:

[0212] The server receives the ideas sent from the device and stores them in a data store (database).

[0213] Step 4:

[0214] The emotion engine built into the server performs emotion analysis of the received ideas. The emotion engine uses natural language processing technology to determine the emotion (joy, sadness, surprise, anger, etc.) contained in each idea.

[0215] Step 5:

[0216] The server collects all ideas and their sentiment analysis results from the data store. In this step, all ideas and sentiment data provided by multiple users are obtained.

[0217] Step 6:

[0218] A summarization program on the server analyzes and summarizes the collected ideas and emotion data, extracting key points and generating a concise narrative that reflects emotion.

[0219] Step 7:

[0220] The server passes the summarized story to the format output program, which converts the summarized story into a specified format (e.g., text format, video format, etc.). At this time, the emotional information determined by the emotion engine is also taken into account, and the presentation of the story is adjusted.

[0221] Step 8:

[0222] The server sends the formatted story to the device, which receives it and displays it in a format that the user can view.

[0223] Step 9:

[0224] The user can view the generated story through a terminal. The user can read the story or watch it as a video.

[0225] Example 2

[0226] 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."

[0227] Conventional story generation systems have difficulty processing inputs from multiple users simultaneously and reflecting their content in an emotionally rich way. Furthermore, summarizing and formatting the inputs must be done manually, which is inefficient. This has led to the problem that the stories created by users tend to be emotionally flat and lack appeal.

[0228] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting multiple inputs, means for saving the multiple inputs, means for analyzing the saved inputs to determine emotions, means for summarizing the analyzed inputs, means for converting the summarized content into a specified format, and means for outputting the converted content and emotional information in consideration. This makes it possible to efficiently collect multiple ideas provided by a user and automatically summarize and convert the format to reflect emotions, thereby generating rich, emotionally appealing stories.

[0229] "Means for accepting multiple inputs" refers to an interface or system for receiving multiple user-provided ideas or data as inputs.

[0230] The "means for saving the plurality of inputs" refers to a function or process for temporarily or permanently storing the plurality of input data received in storage.

[0231] "Means for analyzing the stored input to determine emotions" refers to an algorithm or engine for analyzing the stored input data and identifying the emotional information contained therein (e.g., joy, sadness, surprise, etc.).

[0232] The "means for summarizing the analyzed input" refers to a program or software for extracting important parts from the analyzed input data and summarizing them concisely.

[0233] The "means for converting the summarized content into a specified format" refers to a process for converting the summarized content into a specified format, such as text format or video format.

[0234] "Means for outputting in consideration of the converted content and emotional information" refers to a function for generating a final output based on the converted content and its emotional information and providing it to the user.

[0235] This system combines an emotion engine with ideas from multiple users, such as characters, plots, and developments, to coordinate the summarization and format conversion process and create a work that reflects the emotional state of the users. This system is implemented primarily using the following hardware and software:

[0236] Hardware and Software

[0237] User device: The device through which the user inputs ideas (e.g., smartphone, PC).

[0238] Server: A central processing unit that receives, stores, analyzes, summarizes, transforms, and outputs data sent by users.

[0239] Database: A persistent storage system for input data and analysis results (e.g., MySQL, MongoDB).

[0240] Emotion engine: Software that uses natural language processing technology to analyze the emotions contained in input data (e.g., Google Cloud Natural Language API, IBM Watson).

[0241] Summarizer: A generative AI model (e.g., BERT model, GPT model) for summarizing input data.

[0242] Formatting output program: Software (e.g., Python script, template engine) to convert the summarized content into a specified format.

[0243] System operation procedures

[0244] 1. User Idea Input and Submission

[0245] Users use a dedicated input form or application to input their ideas into their device in any format (text, images, etc.), and then send them from the device to the server. For example, a user opens an app on their smartphone and inputs, "He is a brave warrior and is looking for a magic sword." Then, they tap the send button to send the idea to the server.

[0246] 2. Receiving and storing ideas by the server

[0247] The server receives the submitted ideas and stores them in a database, where each received idea is recorded with a unique ID and a timestamp.

[0248] 3. Sentiment analysis using an emotion engine

[0249] The server retrieves the stored ideas and performs sentiment analysis using an emotion engine. For example, it uses the Google Cloud Natural Language API to detect the emotion "joy" from the idea "He is a brave warrior and is looking for a magic sword." The analysis results are stored in a database.

[0250] 4. Collecting and Summarizing Ideas

[0251] The server collects all ideas and their sentiment analysis results from the database, and uses a summarization program (e.g., BERT model, GPT model) to extract key parts from these ideas and generate a concise narrative that reflects sentiment.

[0252] 5. Conversion to the specified format

[0253] The generated summary story is converted into a specified format (text, video, etc.) using a format output program. The story presentation is optimized, taking into account the results of sentiment analysis. For example, it may be formatted as follows:

[0254] Story Title: The Adventure of the Hero and the Wizard

[0255] He is a brave warrior searching for a magic sword (Joy), she is a wise wizard who sets out on a journey to help him (Surprise), and together they fight a giant dragon and save their village (Sadness).

[0256] 6. Story output and display on the terminal

[0257] The converted story is sent from the server to each user's device and displayed in a viewable format. Users can check and enjoy the generated story on their own devices.

[0258] Specific examples

[0259] Specific prompts for users to submit their ideas include:

[0260] User 1 (Sentiment Analysis: Joy): "He is a brave warrior and is looking for a magic sword."

[0261] User 2 (Sentiment Analysis: Surprise): "She was a wise wizard who set out on a journey to help the warrior."

[0262] User 3 (Sentiment Analysis: Sadness): "They fight a giant dragon and save the village."

[0263] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0264] Step 1:

[0265] User idea entry and submission

[0266] A user inputs his / her idea into the device using a dedicated input form or application. For example, the user inputs "He is a brave warrior and is looking for a magic sword" in text format. Then, the user taps the send button to send the idea from the device to the server. The input data is the idea in text format, and the output is the raw idea data received by the server.

[0267] Step 2:

[0268] Server receives and stores ideas

[0269] The server receives idea data sent by users. The received data is assigned a unique ID and a timestamp and stored in a database. The input is the text idea sent by the user, and the output is structured data stored in the database.

[0270] Step 3:

[0271] Emotion analysis by the server's emotion engine

[0272] The server retrieves the saved idea data and performs sentiment analysis using an emotion engine. For example, the emotion engine uses the Google Cloud Natural Language API to determine the emotion of "joy" from the text "He is a brave warrior and is looking for a magic sword." This emotion data is then saved back to the database. The input is the saved idea data, and the output is data containing the sentiment analysis results.

[0273] Step 4:

[0274] Server idea collection and summary

[0275] The server collects all ideas and their sentiment analysis data from the database. Then, it uses a summarization program to extract the important parts and generate a concise story. For example, it uses the BERT model as a summarization program to summarize a story based on sentences like "He is a brave warrior who is searching for a magic sword" and "She is a wise wizard who sets out on a journey to help the warrior." The input is idea data including sentiment analysis results, and the output is a summarized story.

[0276] Step 5:

[0277] Conversion to specified format by server

[0278] The generated summary story is converted into a specified format (e.g., text format) using a format output program. The results of sentiment analysis are also taken into consideration during this process. For example, the converted story might look like this: "A brave warrior and a wise wizard fight a giant dragon with great surprise, and save the village in grief." The input is the summarized story data, and the output is the story converted into the specified format.

[0279] Step 6:

[0280] Story output and display on terminal

[0281] The final output story is sent from the server to the user's device. The device receives it and displays it in a viewable format for the user. For example, the story may be displayed on a smartphone screen. The user can read and enjoy it. The input is the story data sent from the server, and the output is the story displayed on the device.

[0282] (Application example 2)

[0283] 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."

[0284] Conventional story generation systems were unable to analyze emotions from user-input ideas and generate summaries that reflected those emotions. Furthermore, they lacked the ability to convert and output summaries generated based on the analyzed emotions into various formats, limiting the quality of the stories provided to users. This prevented users from enjoying stories with emotional depth, limiting their entertainment experience.

[0285] 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 means for accepting multiple inputs, means for analyzing emotions based on the multiple inputs, means for generating a summary including the analyzed emotions, means for converting the summarized content into a specified format, and means for outputting the converted content. This makes it possible to emotionally analyze ideas input by a user and automatically generate and output stories in various formats that reflect the emotions.

[0286] "Multiple inputs" refers to multiple ideas or pieces of information provided by a user, including various forms such as text, audio, and images.

[0287] "Sentiment analysis methods" refers to natural language processing techniques and algorithms used to identify and classify the emotions contained in input ideas and information.

[0288] "Means for generating summaries" refers to algorithms that take into account the analyzed sentiment, extract key parts, and automatically generate concise stories or content.

[0289] The "means for converting into a specified format" refers to a format conversion technology for converting the generated summary content into a pre-specified format (for example, text, audio, video, etc.).

[0290] "Means for outputting" refers to the system or protocol for transmitting the content in the final converted format to a user terminal so that it can be displayed or played back.

[0291] "Server" refers to a central processing unit for receiving input from users, performing sentiment analysis, summary generation and format conversion, and outputting the final content.

[0292] In this invention, a server executes a series of processes: collecting user ideas, analyzing their emotions, summarizing them, converting them into a specified format, and finally outputting them. Specifically, users input their ideas using a smartphone or head-mounted display (HMD) and send them to the server. The server analyzes the received ideas, generates a story based on the emotional data, converts them into various formats such as text, audio, and video, and outputs them to the user's device. The hardware and software used and their roles are explained below.

[0293] Hardware

[0294] Smartphone: A device that allows users to input ideas, allowing voice and text input, and communicating with a server via the Internet.

[0295] Head-mounted display (HMD): A device for visually experiencing a story in virtual reality (VR). It has the function of displaying ideas entered by the user in a VR space.

[0296] Server: As a central processing unit, it receives input from users and performs sentiment analysis, summary generation, format conversion, and final output.

[0297] software

[0298] Azure Text Analytics API: An API that provides natural language processing technology for sentiment analysis, extracting sentiment data based on user ideas.

[0299] Python script: A program to collect ideas and generate summaries based on sentiment analysis, leveraging NLP techniques to extract key points and create a concise narrative.

[0300] FFmpeg library: A library for converting the generated summaries into video format, with the ability to embed text information into video frames.

[0301] Unity Engine: A 3D engine for displaying stories in virtual reality (VR) spaces, providing a visually and audio-rich experience.

[0302] A natural language description of the process

[0303] 1. User input and submission:

[0304] Users use their smartphones or HMDs to input their ideas by voice or text. For example, a user might input the idea "A brave warrior is searching for a magic sword" into their smartphone, which is then immediately sent to the server.

[0305] 2. Emotion analysis:

[0306] The server uses the Azure Text Analytics API to perform sentiment analysis on the received ideas, and the sentiment data (happiness, surprise, sadness, etc.) is stored in a database along with the analysis results using a Python script.

[0307] 3. Summary generation:

[0308] Based on multiple ideas and their sentiment data stored on the server, the Python script uses NLP techniques to extract key parts and create a sentiment-based summary, such as "A brave warrior is searching for a magic sword (joy)."

[0309] 4. Format conversion:

[0310] The resulting summary is then converted to the specified format using the FFmpeg library. In the video format example, the text information is embedded into the video frames for visual display.

[0311] 5. Final output:

[0312] The stories in the specified format are displayed on an HMD using the Unity engine or made viewable on a smartphone app, allowing users to experience the generated stories in real time.

[0313] Specific examples

[0314] User A inputs "A brave warrior searches for a magic sword" into their smartphone, while User B inputs "A wise wizard goes on an adventure." These ideas are sent to the server, which performs sentiment analysis and generates a story: "A brave warrior searches for a magic sword and fights a giant dragon alongside the wise wizard." This story is displayed as video or text on the HMD or smartphone, depending on the presentation format.

[0315] Example prompt sentence:

[0316] "A brave warrior seeks a magic sword"

[0317] "A clever wizard goes on an adventure"

[0318] "A giant dragon attacks the village"

[0319] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0320] Step 1:

[0321] Users use a smartphone or head-mounted display (HMD) to input their ideas using text or voice. For example, they input a specific idea such as "A brave warrior is searching for a magic sword." The input idea is instantly sent to the server via the Internet. Input = user's idea (text or voice), output = idea data sent to the server.

[0322] Step 2:

[0323] The server stores the received ideas in a database. At this time, the attribute information of the idea (user ID, input format, etc.) is also recorded. Input = submitted idea data and its attribute information, Output = idea stored in the database.

[0324] Step 3:

[0325] The server uses the Azure Text Analytics API to perform sentiment analysis on the stored ideas. This process uses natural language processing technology to identify the emotions (happiness, sadness, surprise, etc.) contained in each idea and output them as emotional data. Input = ideas stored in the database, output = analyzed emotional data.

[0326] Step 4:

[0327] The server uses a Python script to generate a summary of the idea based on the results of the sentiment analysis. It uses NLP (Natural Language Processing) technology to extract key parts and automatically generate a concise story that reflects the sentiment. Input: analyzed sentiment data and original idea. Output: summarized story.

[0328] Step 5:

[0329] The server uses the FFmpeg library to convert the summarized story into the specified format (text, audio, video, etc.). For example, in video format, the summarized text is embedded into the video frames. Input = summarized story, output = content in the specified format (e.g. video file).

[0330] Step 6:

[0331] The server sends the content in the generated format to the user's device. The user can view and experience the generated story through their smartphone or HMD. Input = content in the specified format, Output = final content displayed on the user's device.

[0332] 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.

[0333] 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.

[0334] 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.

[0335] [Second embodiment]

[0336] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0337] 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.

[0338] 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).

[0339] 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.

[0340] 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.

[0341] 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).

[0342] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0343] 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.

[0344] 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.

[0345] 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.

[0346] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0347] 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."

[0348] The present invention is a system that summarizes the ideas of multiple users, such as characters, plots, and developments, and outputs them in a specified format (text, video, a combined format, etc.) to create a single work.

[0349] Program Overview

[0350] 1. User Idea Input and Submission

[0351] Users use a dedicated input form or application to input their ideas into the device in any format (text, images, etc.). The ideas are then sent from the device to the server, which receives the ideas and stores them in a database.

[0352] 2. Collecting and Summarizing Ideas

[0353] The server collects all ideas from the database, and based on the collected ideas, the summarization program analyzes and summarizes the information, extracts the important parts, and generates a concise story.

[0354] 3. Convert to the specified format

[0355] The summarized story is then converted into a pre-specified format (text, video, or a combination) by a formatting output program on the server, which provides the story in a format that is easy for the user to read and understand.

[0356] 4. Narrative output and display

[0357] The converted story is finally sent to the device and displayed in a viewable format for the user, allowing the user to easily refer to and enjoy the generated story.

[0358] Specific examples

[0359] User input and submission

[0360] User 1: "He's a brave warrior and he's looking for a magic sword."

[0361] User 2: "She was a wise wizard who set out on a journey to help the warrior."

[0362] User 3: "They fight a giant dragon and save the village."

[0363] These ideas are sent from each user's terminal to the server.

[0364] Server processing and result output

[0365] The server collects these ideas and uses a summarization program to generate a condensed story like this:

[0366] "The story of a brave warrior and a wise wizard who embark on a journey to battle a giant dragon and save their village."

[0367] A formatted output program will convert this condensed story into text and display it on the terminal as follows:

[0368] Story Title: The Adventure of the Hero and the Wizard

[0369] He is a brave warrior searching for a magical sword, and she is a wise wizard who sets out on a journey to help him. Together they battle a giant dragon and save their village.

[0370] In this way, the system of the present invention can efficiently collect and summarize diverse ideas, output them in a specified format, and create a novel story, thereby realizing creative activities that go beyond the limitations of conventional individual work.

[0371] The processing flow will be explained below.

[0372] Step 1:

[0373] Users input their ideas using their own devices. Using a dedicated input form or application, users can input their ideas in any format, such as text or images.

[0374] Step 2:

[0375] The terminal sends the input idea to the server, along with the user's identification information (e.g., user ID) and idea format information.

[0376] Step 3:

[0377] The server receives the ideas sent from the device and stores them in a data store (database).

[0378] Step 4:

[0379] The server collects all ideas from the data store. In this step, all ideas submitted by multiple users are obtained.

[0380] Step 5:

[0381] The server's summarization program analyzes and summarizes the collected ideas, extracting the key points and summarizing them into a concise narrative.

[0382] Step 6:

[0383] The server passes the summarized story to a formatting program, which converts the summarized story into a specified format (e.g., text format, video format, etc.).

[0384] Step 7:

[0385] The server sends the formatted story to the device, which receives it and displays it in a format that the user can view.

[0386] Step 8:

[0387] The user can view the generated story through a terminal. The user can read the story or watch it as a video.

[0388] By using the above steps, the system of the present invention can efficiently collect and summarize ideas provided by multiple users and output them in a variety of formats.

[0389] Example 1

[0390] 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."

[0391] Conventional technologies have been unable to efficiently collect ideas entered by multiple users in different formats, summarize them, convert them into a specified format, and output them. Furthermore, there has been no system that can generate high-quality stories while protecting user privacy by accepting these ideas anonymously. Therefore, there is a need for a system that can accept ideas in various formats from users, summarize them, and output them in a specified format.

[0392] 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.

[0393] In this invention, the server includes means for accepting multiple inputs, means for storing the multiple inputs in a database, means for using a generative AI model to summarize the multiple inputs, means for converting the summarized content into a specified format, and means for outputting the converted content, thereby enabling efficient collection, analysis, and summary of various ideas from users, and outputting them in a specified format to provide an easy-to-read story.

[0394] "Multiple inputs" refers to ideas provided by multiple users in different formats (text, images, etc.).

[0395] "Database" refers to a digital information repository for storing and managing multiple inputs received.

[0396] A "summary" refers to information that extracts important content from multiple inputs and summarizes it concisely.

[0397] A "generative AI model" refers to an artificial intelligence algorithm that analyzes input data and performs summarization or transformation.

[0398] "Specified format" refers to the output format after conversion (e.g., text, video, or a combination thereof).

[0399] "Output" refers to the act of providing the user with the summary converted into a specified format.

[0400] The present invention is a system that summarizes the ideas of multiple users, such as characters, plots, and developments, and outputs them in a specified format (text, video, a combination of text, etc.) to create a single work. Specific embodiments of this system are described below.

[0401] User idea entry and submission

[0402] Users use a dedicated input form or application to input their ideas into the device in any format (text, images, etc.). The ideas are then sent from the device to the server, which receives the ideas and stores them in a database.

[0403] Idea collection and summarization

[0404] The server collects all ideas from the database. Based on the collected ideas, a summary program analyzes and summarizes the information using a generative AI model (e.g., GPT-4), extracts the important parts, and generates a concise story. An example of a specific prompt is "Generate a concise story based on the following user ideas:" followed by a list of the user's ideas.

[0405] for example,

[0406] "Generate a concise narrative based on the following user ideas:

[0407] 1. He is a brave warrior and is searching for a magic sword.

[0408] 2. She was a wise wizard who set out on a journey to help the warrior.

[0409] 3. The two fight a giant dragon and save the village.

[0410] Conversion to a specified format

[0411] The summarized story is then converted into a pre-specified format (text, video, or a combination) by a formatting output program on the server, which provides the story in a format that is easy for the user to read and understand.

[0412] Narrative output and display

[0413] The converted story is finally sent to the device and displayed in a viewable format for the user, allowing the user to easily refer to and enjoy the generated story.

[0414] Specific examples

[0415] User 1: "He's a brave warrior and he's looking for a magic sword."

[0416] User 2: "She was a wise wizard who set out on a journey to help the warrior."

[0417] User 3: "They fight a giant dragon and save the village."

[0418] These ideas are sent from the device to a server, which stores the data in a database. The server collects these ideas and uses a generative AI model to generate a summarized story, such as:

[0419] "The story of a brave warrior and a wise wizard who embark on a journey to battle a giant dragon and save their village."

[0420] A formatted output program converts this condensed story into text and displays it on the terminal:

[0421] Story Title: The Adventure of the Hero and the Wizard

[0422] He is a brave warrior searching for a magical sword, and she is a wise wizard who sets out on a journey to help him. Together they battle a giant dragon and save their village.

[0423] In this way, the system can efficiently collect, analyze, summarize, and output various ideas from users in a specified format, providing them with an easy-to-understand story, thereby enabling creative activities that go beyond the limitations of traditional individual work.

[0424] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0425] Step 1:

[0426] The user launches a dedicated input form or application. The user enters their idea in the input form in the form of text or images. When the user clicks the "Send" button, the device sends the information to the server. Specifically, User 1 enters "He is a brave warrior and is looking for a magic sword" and presses the send button.

[0427] Input: The idea the user entered into the form (e.g., "He is a brave warrior and is looking for a magic sword.")

[0428] Output: The input ideas are sent from the terminal to the server.

[0429] Step 2:

[0430] The server stores the received ideas in a database, which records and manages all ideas received from each user.

[0431] Input: User ideas sent from the device (e.g., "He is a brave warrior and is looking for a magic sword.")

[0432] Output: Ideas stored in a database.

[0433] Step 3:

[0434] The server collects all user ideas from the database and passes the collected ideas to the summarization program.

[0435] Input: All user ideas in the database

[0436] Output: A set of ideas that is passed to the summarization program.

[0437] Step 4:

[0438] The summarization program calls a generative AI model (e.g., GPT-4) to analyze and summarize the input idea. Specifically, the user's idea is input along with the prompt, "Generate a concise story based on the user's idea below:" The generative AI model extracts key elements and generates a concise story.

[0439] Input: The user's idea passed to the summary program along with the prompt.

[0440] Output: The summary produced by the generative AI model.

[0441] Step 5:

[0442] The server stores the generated summary in a database, which is used to convert the summary to the specified format in the next step.

[0443] Input: A summary generated by a generative AI model (e.g., "A story about a brave warrior and a wise wizard who embark on a journey to battle a giant dragon and save their village.")

[0444] Output: A summary stored in a database.

[0445] Step 6:

[0446] The server passes the summarized story to a formatting program, which converts it into a specified format (text, video, etc.), for example, converting the summarized story into text format.

[0447] Input: Abstracted stories in the database

[0448] Output: The story converted to the specified format.

[0449] Step 7:

[0450] The server sends the converted story to the terminal, which displays the received story to the user.

[0451] Input: A textual narrative generated by a formatted output program

[0452] Output: The story displayed on the user's terminal.

[0453] Through this series of processes, the diverse ideas of users are efficiently collected, analyzed, summarized, and output in the specified format to form a novel story. The user can easily browse and enjoy the final story that is displayed.

[0454] (Application example 1)

[0455] 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."

[0456] Conventional story generation systems have had difficulty automatically generating efficient and compelling content when integrating individual user ideas into a single work. Effectively summarizing ideas input by multiple users and outputting them in a specified format requires advanced natural language processing capabilities. Another challenge is accepting these ideas anonymously while integrating and outputting them as a compelling story.

[0457] 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.

[0458] In this invention, the server includes means for accepting multiple inputs, means for summarizing the multiple inputs, means for converting the summarized content into a specified format, means for outputting the converted content, means for analyzing the multiple inputs using a generative AI model to generate a story, and means for displaying the generated story in a format that can be viewed by the user. This makes it possible to effectively collect and summarize individual user ideas, automatically generate an attractive story, and output it in a specified format.

[0459] "Multiple inputs" refers to information in various formats, such as text and images, provided by multiple users.

[0460] A "summarizer" is a part of a system that has the ability to extract important content from multiple inputs and summarize it in a compact form.

[0461] "Specified Format" means a format specified by the User that represents the Generated Content in text, video, or a combination thereof.

[0462] "Transforming means" refers to the process or algorithm used to transform the summarized content into the specified format.

[0463] "Means for outputting" refers to an interface or device for displaying the converted content in a form that can be viewed by a user.

[0464] A "generative AI model" refers to an artificial intelligence model that has the ability to analyze information collected from users and generate stories in the form of text, video, etc.

[0465] "Means for analyzing and generating a narrative" refers to the process of automatically generating a narrative from multiple inputs using a generative AI model.

[0466] "Means for displaying in a viewable form" refers to the function of providing the generated story in a form that can be viewed by users through devices such as smartphones or computers.

[0467] To implement this invention, it is necessary to build a system that involves the following process between a server, a terminal, and a user. First, a user inputs their idea through a dedicated application. Ideas can be input in a variety of formats, including text and images, and are then sent to the server. The server receives the data using a web framework such as Flask and stores it in a database such as SQLite.

[0468] Next, the server collects the saved ideas and analyzes them using a generative AI model (e.g., OpenAI's GPT-3) to generate a summarized story. The prompt for the generative AI model consists of a combination of each of the user's ideas. For example, the prompt could be, "Generate a story based on the following idea: A brave warrior is searching for a magical sword. A wise wizard sets out on a journey to help the warrior. The two fight a giant dragon and save the village."

[0469] The generated story is converted into a specified format (e.g., text, video, or a combination of both). After conversion, the story is sent to the user's smartphone or computer and displayed in a viewable format. This allows the user to enjoy a story that integrates their own ideas.

[0470] Examples of prompts used are:

[0471] Generate a story based on the following ideas:

[0472] A brave warrior is searching for a magical sword.

[0473] A wise wizard set out to help the warrior.

[0474] The two fight a giant dragon and save the village.

[0475] By integrating these methods and processes, the server can effectively summarize the ideas of multiple users, automatically generate an engaging story, and output it in a specified format, allowing users to enjoy a new creative experience.

[0476] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0477] Step 1:

[0478] Users input their ideas through a dedicated application. Ideas can be entered in a variety of formats, including text and images, and are then sent to the server. The entered ideas are then properly formatted within the application and sent to the server via API. The input data includes the user's ID and the content of the idea.

[0479] Step 2:

[0480] The server receives the data using a web framework such as Flask and stores it in a database such as SQLite. The server records the received ideas in the database for later processing. The input is the user's idea data, and the output is the idea data stored in the database.

[0481] Step 3:

[0482] The server collects multiple saved ideas and analyzes them using a generative AI model (e.g., OpenAI's GPT-3). First, it retrieves all ideas from the database and formats them into a single prompt. The input is a set of ideas retrieved from the database, and the output is a prompt for the generative AI model.

[0483] Step 4:

[0484] A prompt is input into the generative AI model, which then generates a story. The AI ​​model analyzes the given prompt and generates a coherent story based on the context. The input is the prompt, and the output is the generated story.

[0485] Step 5:

[0486] Convert the generated story into a specified format (e.g., text, video, or a combination). For example, perform a formatting process to convert it into a text-based story, or use a video generation library (e.g., Stable Diffusion) if a video format is required. The input is the generated story, and the output is a story in the specified format.

[0487] Step 6:

[0488] The converted story is sent to the user's smartphone or computer and displayed in a viewable format. The story is sent to the user's device via an API and displayed within the application. The input is a story in the specified format, and the output is the story displayed on the user's device.

[0489] As an example of specific behavior, the prompt sentence to the generative AI model is as follows:

[0490] Generate a story based on the following ideas:

[0491] A brave warrior is searching for a magical sword.

[0492] A wise wizard set out to help the warrior.

[0493] The two fight a giant dragon and save the village.

[0494] Based on this prompt, the AI ​​model will generate a story, which will ultimately be presented to the user in a format that can be viewed.

[0495] 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.

[0496] This invention is a system that combines an emotion engine with ideas for characters, plots, developments, etc. that multiple users have each come up with, and adjusts the summarization and format conversion process to create a single work that reflects the emotional state of the users.

[0497] Program Overview

[0498] 1. User Idea Input and Submission

[0499] Users use a dedicated input form or application to input their ideas into the device in any format (text, images, etc.). The ideas are then sent from the device to the server, which receives the ideas and stores them in a database.

[0500] 2. Sentiment analysis using an emotion engine

[0501] The server is equipped with an emotion engine that performs emotion analysis on received ideas. The emotion engine uses natural language processing technology to determine the emotion (e.g., joy, sadness, surprise, anger, etc.) contained in each idea.

[0502] 3. Collecting and Summarizing Ideas

[0503] The server collects all ideas from the database and retrieves the sentiment analysis results. Then, based on the collected ideas and their sentiment data, the summarization program extracts the key parts and generates a concise story that reflects the sentiment.

[0504] 4. Conversion to the specified format

[0505] The summarized story is converted into a pre-specified format (e.g., text format, video format, etc.) by a format output program on the server. At this time, the emotional information determined by the emotion engine is also taken into consideration, and the expression of the story is adjusted.

[0506] 5. Narrative output and display

[0507] The converted story is finally sent to the device and displayed in a viewable format for the user, allowing the user to easily refer to and enjoy the generated story, as well as to enjoy stories that reflect the emotional state of other users.

[0508] Specific examples

[0509] User input and submission

[0510] User 1 (Sentiment Analysis: Joy): "He is a brave warrior and is looking for a magic sword."

[0511] User 2 (Sentiment Analysis: Surprise): "She was a wise wizard who set out on a journey to help the warrior."

[0512] User 3 (Sentiment Analysis: Sadness): "They fight a giant dragon and save the village."

[0513] These ideas are sent from each user's terminal to the server.

[0514] Server processing and result output

[0515] The server collects these ideas and performs a sentiment analysis on each idea using a sentiment engine. It then uses a summarization program to generate a summarized story, taking into account the sentiment information, like this:

[0516] "A tale of a brave warrior and a wise wizard who battle a mighty dragon with astonishment and embark on a heartbreaking journey to save their village."

[0517] A formatted output program will convert this condensed story into text and display it on the terminal as follows:

[0518] Story Title: The Adventure of the Hero and the Wizard

[0519] He is a brave warrior searching for a magic sword (Joy), she is a wise wizard who sets out on a journey to help him (Surprise), and together they fight a giant dragon and save their village (Sadness).

[0520] In this way, the system of the present invention can efficiently collect ideas provided by multiple users, summarize them emotionally, and convert them into a format that reflects their emotions, thereby creating a richer, more emotionally appealing story.

[0521] The processing flow will be explained below.

[0522] Step 1:

[0523] Users input their ideas using their own devices. Using a dedicated input form or application, users can input their ideas in any format, such as text or images.

[0524] Step 2:

[0525] The terminal sends the input idea to the server, along with the user's identification information (e.g., user ID) and idea format information.

[0526] Step 3:

[0527] The server receives the ideas sent from the device and stores them in a data store (database).

[0528] Step 4:

[0529] The emotion engine built into the server performs emotion analysis of the received ideas. The emotion engine uses natural language processing technology to determine the emotion (joy, sadness, surprise, anger, etc.) contained in each idea.

[0530] Step 5:

[0531] The server collects all ideas and their sentiment analysis results from the data store. In this step, all ideas and sentiment data provided by multiple users are obtained.

[0532] Step 6:

[0533] A summarization program on the server analyzes and summarizes the collected ideas and emotion data, extracting key points and generating a concise narrative that reflects emotion.

[0534] Step 7:

[0535] The server passes the summarized story to the format output program, which converts the summarized story into a specified format (e.g., text format, video format, etc.). At this time, the emotional information determined by the emotion engine is also taken into account, and the presentation of the story is adjusted.

[0536] Step 8:

[0537] The server sends the formatted story to the device, which receives it and displays it in a format that the user can view.

[0538] Step 9:

[0539] The user can view the generated story through a terminal. The user can read the story or watch it as a video.

[0540] Example 2

[0541] 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."

[0542] Conventional story generation systems have difficulty processing inputs from multiple users simultaneously and reflecting their content in an emotionally rich way. Furthermore, summarizing and formatting the inputs must be done manually, which is inefficient. This has led to the problem that the stories created by users tend to be emotionally flat and lack appeal.

[0543] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting multiple inputs, means for saving the multiple inputs, means for analyzing the saved inputs to determine emotions, means for summarizing the analyzed inputs, means for converting the summarized content into a specified format, and means for outputting the converted content and emotional information in consideration. This makes it possible to efficiently collect multiple ideas provided by a user and automatically summarize and convert the format to reflect emotions, thereby generating rich, emotionally appealing stories.

[0544] "Means for accepting multiple inputs" refers to an interface or system for receiving multiple user-provided ideas or data as inputs.

[0545] The "means for saving the plurality of inputs" refers to a function or process for temporarily or permanently storing the plurality of input data received in storage.

[0546] "Means for analyzing the stored input to determine emotions" refers to an algorithm or engine for analyzing the stored input data and identifying the emotional information contained therein (e.g., joy, sadness, surprise, etc.).

[0547] The "means for summarizing the analyzed input" refers to a program or software for extracting important parts from the analyzed input data and summarizing them concisely.

[0548] The "means for converting the summarized content into a specified format" refers to a process for converting the summarized content into a specified format, such as text format or video format.

[0549] "Means for outputting in consideration of the converted content and emotional information" refers to a function for generating a final output based on the converted content and its emotional information and providing it to the user.

[0550] This system combines an emotion engine with ideas from multiple users, such as characters, plots, and developments, to coordinate the summarization and format conversion process and create a work that reflects the emotional state of the users. This system is implemented primarily using the following hardware and software:

[0551] Hardware and Software

[0552] User device: The device through which the user inputs ideas (e.g., smartphone, PC).

[0553] Server: A central processing unit that receives, stores, analyzes, summarizes, transforms, and outputs data sent by users.

[0554] Database: A persistent storage system for input data and analysis results (e.g., MySQL, MongoDB).

[0555] Emotion engine: Software that uses natural language processing technology to analyze the emotions contained in input data (e.g., Google Cloud Natural Language API, IBM Watson).

[0556] Summarizer: A generative AI model (e.g., BERT model, GPT model) for summarizing input data.

[0557] Formatting output program: Software (e.g., Python script, template engine) to convert the summarized content into a specified format.

[0558] System operation procedures

[0559] 1. User Idea Input and Submission

[0560] Users use a dedicated input form or application to input their ideas into their device in any format (text, images, etc.), and then send them from the device to the server. For example, a user opens an app on their smartphone and inputs, "He is a brave warrior and is looking for a magic sword." Then, they tap the send button to send the idea to the server.

[0561] 2. Receiving and storing ideas by the server

[0562] The server receives the submitted ideas and stores them in a database, where each received idea is recorded with a unique ID and a timestamp.

[0563] 3. Sentiment analysis using an emotion engine

[0564] The server retrieves the stored ideas and performs sentiment analysis using an emotion engine. For example, it uses the Google Cloud Natural Language API to detect the emotion "joy" from the idea "He is a brave warrior and is looking for a magic sword." The analysis results are stored in a database.

[0565] 4. Collecting and Summarizing Ideas

[0566] The server collects all ideas and their sentiment analysis results from the database, and uses a summarization program (e.g., BERT model, GPT model) to extract key parts from these ideas and generate a concise narrative that reflects sentiment.

[0567] 5. Conversion to the specified format

[0568] The generated summary story is converted into a specified format (text, video, etc.) using a format output program. The story presentation is optimized, taking into account the results of sentiment analysis. For example, it may be formatted as follows:

[0569] Story Title: The Adventure of the Hero and the Wizard

[0570] He is a brave warrior searching for a magic sword (Joy), she is a wise wizard who sets out on a journey to help him (Surprise), and together they fight a giant dragon and save their village (Sadness).

[0571] 6. Story output and display on the terminal

[0572] The converted story is sent from the server to each user's device and displayed in a viewable format. Users can check and enjoy the generated story on their own devices.

[0573] Specific examples

[0574] Specific prompts for users to submit their ideas include:

[0575] User 1 (Sentiment Analysis: Joy): "He is a brave warrior and is looking for a magic sword."

[0576] User 2 (Sentiment Analysis: Surprise): "She was a wise wizard who set out on a journey to help the warrior."

[0577] User 3 (Sentiment Analysis: Sadness): "They fight a giant dragon and save the village."

[0578] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0579] Step 1:

[0580] User idea entry and submission

[0581] A user inputs his / her idea into the device using a dedicated input form or application. For example, the user inputs "He is a brave warrior and is looking for a magic sword" in text format. Then, the user taps the send button to send the idea from the device to the server. The input data is the idea in text format, and the output is the raw idea data received by the server.

[0582] Step 2:

[0583] Server receives and stores ideas

[0584] The server receives idea data sent by users. The received data is assigned a unique ID and a timestamp and stored in a database. The input is the text idea sent by the user, and the output is structured data stored in the database.

[0585] Step 3:

[0586] Emotion analysis by the server's emotion engine

[0587] The server retrieves the saved idea data and performs sentiment analysis using an emotion engine. For example, the emotion engine uses the Google Cloud Natural Language API to determine the emotion of "joy" from the text "He is a brave warrior and is looking for a magic sword." This emotion data is then saved back to the database. The input is the saved idea data, and the output is data containing the sentiment analysis results.

[0588] Step 4:

[0589] Server idea collection and summary

[0590] The server collects all ideas and their sentiment analysis data from the database. Then, it uses a summarization program to extract the important parts and generate a concise story. For example, it uses the BERT model as a summarization program to summarize a story based on sentences like "He is a brave warrior who is searching for a magic sword" and "She is a wise wizard who sets out on a journey to help the warrior." The input is idea data including sentiment analysis results, and the output is a summarized story.

[0591] Step 5:

[0592] Conversion to specified format by server

[0593] The generated summary story is converted into a specified format (e.g., text format) using a format output program. The results of sentiment analysis are also taken into consideration during this process. For example, the converted story might look like this: "A brave warrior and a wise wizard fight a giant dragon with great surprise, and save the village in grief." The input is the summarized story data, and the output is the story converted into the specified format.

[0594] Step 6:

[0595] Story output and display on terminal

[0596] The final output story is sent from the server to the user's device. The device receives it and displays it in a viewable format for the user. For example, the story may be displayed on a smartphone screen. The user can read and enjoy it. The input is the story data sent from the server, and the output is the story displayed on the device.

[0597] (Application example 2)

[0598] 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."

[0599] Conventional story generation systems were unable to analyze emotions from user-input ideas and generate summaries that reflected those emotions. Furthermore, they lacked the ability to convert and output summaries generated based on the analyzed emotions into various formats, limiting the quality of the stories provided to users. This prevented users from enjoying stories with emotional depth, limiting their entertainment experience.

[0600] 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 means for accepting multiple inputs, means for analyzing emotions based on the multiple inputs, means for generating a summary including the analyzed emotions, means for converting the summarized content into a specified format, and means for outputting the converted content. This makes it possible to emotionally analyze ideas input by a user and automatically generate and output stories in various formats that reflect the emotions.

[0601] "Multiple inputs" refers to multiple ideas or pieces of information provided by a user, including various forms such as text, audio, and images.

[0602] "Sentiment analysis methods" refers to natural language processing techniques and algorithms used to identify and classify the emotions contained in input ideas and information.

[0603] "Means for generating summaries" refers to algorithms that take into account the analyzed sentiment, extract key parts, and automatically generate concise stories or content.

[0604] The "means for converting into a specified format" refers to a format conversion technology for converting the generated summary content into a pre-specified format (for example, text, audio, video, etc.).

[0605] "Means for outputting" refers to the system or protocol for transmitting the content in the final converted format to a user terminal so that it can be displayed or played back.

[0606] "Server" refers to a central processing unit for receiving input from users, performing sentiment analysis, summary generation and format conversion, and outputting the final content.

[0607] In this invention, a server executes a series of processes: collecting user ideas, analyzing their emotions, summarizing them, converting them into a specified format, and finally outputting them. Specifically, users input their ideas using a smartphone or head-mounted display (HMD) and send them to the server. The server analyzes the received ideas, generates a story based on the emotional data, converts them into various formats such as text, audio, and video, and outputs them to the user's device. The hardware and software used and their roles are explained below.

[0608] Hardware

[0609] Smartphone: A device that allows users to input ideas, allowing voice and text input, and communicating with a server via the Internet.

[0610] Head-mounted display (HMD): A device for visually experiencing a story in virtual reality (VR). It has the function of displaying ideas entered by the user in a VR space.

[0611] Server: As a central processing unit, it receives input from users and performs sentiment analysis, summary generation, format conversion, and final output.

[0612] software

[0613] Azure Text Analytics API: An API that provides natural language processing technology for sentiment analysis, extracting sentiment data based on user ideas.

[0614] Python script: A program to collect ideas and generate summaries based on sentiment analysis, leveraging NLP techniques to extract key points and create a concise narrative.

[0615] FFmpeg library: A library for converting the generated summaries into video format, with the ability to embed text information into video frames.

[0616] Unity Engine: A 3D engine for displaying stories in virtual reality (VR) spaces, providing a visually and audio-rich experience.

[0617] A natural language description of the process

[0618] 1. User input and submission:

[0619] Users use their smartphones or HMDs to input their ideas by voice or text. For example, a user might input the idea "A brave warrior is searching for a magic sword" into their smartphone, which is then immediately sent to the server.

[0620] 2. Emotion analysis:

[0621] The server uses the Azure Text Analytics API to perform sentiment analysis on the received ideas, and the sentiment data (happiness, surprise, sadness, etc.) is stored in a database along with the analysis results using a Python script.

[0622] 3. Summary generation:

[0623] Based on multiple ideas and their sentiment data stored on the server, the Python script uses NLP techniques to extract key parts and create a sentiment-based summary, such as "A brave warrior is searching for a magic sword (joy)."

[0624] 4. Format conversion:

[0625] The resulting summary is then converted to the specified format using the FFmpeg library. In the video format example, the text information is embedded into the video frames for visual display.

[0626] 5. Final output:

[0627] The stories in the specified format are displayed on an HMD using the Unity engine or made viewable on a smartphone app, allowing users to experience the generated stories in real time.

[0628] Specific examples

[0629] User A inputs "A brave warrior searches for a magic sword" into their smartphone, while User B inputs "A wise wizard goes on an adventure." These ideas are sent to the server, which performs sentiment analysis and generates a story: "A brave warrior searches for a magic sword and fights a giant dragon alongside the wise wizard." This story is displayed as video or text on the HMD or smartphone, depending on the presentation format.

[0630] Example prompt sentence:

[0631] "A brave warrior seeks a magic sword"

[0632] "A clever wizard goes on an adventure"

[0633] "A giant dragon attacks the village"

[0634] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0635] Step 1:

[0636] Users use a smartphone or head-mounted display (HMD) to input their ideas using text or voice. For example, they input a specific idea such as "A brave warrior is searching for a magic sword." The input idea is instantly sent to the server via the Internet. Input = user's idea (text or voice), output = idea data sent to the server.

[0637] Step 2:

[0638] The server stores the received ideas in a database. At this time, the attribute information of the idea (user ID, input format, etc.) is also recorded. Input = submitted idea data and its attribute information, Output = idea stored in the database.

[0639] Step 3:

[0640] The server uses the Azure Text Analytics API to perform sentiment analysis on the stored ideas. This process uses natural language processing technology to identify the emotions (happiness, sadness, surprise, etc.) contained in each idea and output them as emotional data. Input = ideas stored in the database, output = analyzed emotional data.

[0641] Step 4:

[0642] The server uses a Python script to generate a summary of the idea based on the results of the sentiment analysis. It uses NLP (Natural Language Processing) technology to extract key parts and automatically generate a concise story that reflects the sentiment. Input: analyzed sentiment data and original idea. Output: summarized story.

[0643] Step 5:

[0644] The server uses the FFmpeg library to convert the summarized story into the specified format (text, audio, video, etc.). For example, in video format, the summarized text is embedded into the video frames. Input = summarized story, output = content in the specified format (e.g. video file).

[0645] Step 6:

[0646] The server sends the content in the generated format to the user's device. The user can view and experience the generated story through their smartphone or HMD. Input = content in the specified format, Output = final content displayed on the user's device.

[0647] 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.

[0648] 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.

[0649] 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.

[0650] [Third embodiment]

[0651] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0652] 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.

[0653] 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).

[0654] 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.

[0655] 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.

[0656] 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).

[0657] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0658] 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.

[0659] 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.

[0660] 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.

[0661] 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.

[0662] 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."

[0663] The present invention is a system that summarizes the ideas of multiple users, such as characters, plots, and developments, and outputs them in a specified format (text, video, a combined format, etc.) to create a single work.

[0664] Program Overview

[0665] 1. User Idea Input and Submission

[0666] Users use a dedicated input form or application to input their ideas into the device in any format (text, images, etc.). The ideas are then sent from the device to the server, which receives the ideas and stores them in a database.

[0667] 2. Collecting and Summarizing Ideas

[0668] The server collects all ideas from the database, and based on the collected ideas, the summarization program analyzes and summarizes the information, extracts the important parts, and generates a concise story.

[0669] 3. Convert to the specified format

[0670] The summarized story is then converted into a pre-specified format (text, video, or a combination) by a formatting output program on the server, which provides the story in a format that is easy for the user to read and understand.

[0671] 4. Narrative output and display

[0672] The converted story is finally sent to the device and displayed in a viewable format for the user, allowing the user to easily refer to and enjoy the generated story.

[0673] Specific examples

[0674] User input and submission

[0675] User 1: "He's a brave warrior and he's looking for a magic sword."

[0676] User 2: "She was a wise wizard who set out on a journey to help the warrior."

[0677] User 3: "They fight a giant dragon and save the village."

[0678] These ideas are sent from each user's terminal to the server.

[0679] Server processing and result output

[0680] The server collects these ideas and uses a summarization program to generate a condensed story like this:

[0681] "The story of a brave warrior and a wise wizard who embark on a journey to battle a giant dragon and save their village."

[0682] A formatted output program will convert this condensed story into text and display it on the terminal as follows:

[0683] Story Title: The Adventure of the Hero and the Wizard

[0684] He is a brave warrior searching for a magical sword, and she is a wise wizard who sets out on a journey to help him. Together they battle a giant dragon and save their village.

[0685] In this way, the system of the present invention can efficiently collect and summarize diverse ideas, output them in a specified format, and create a novel story, thereby realizing creative activities that go beyond the limitations of conventional individual work.

[0686] The processing flow will be explained below.

[0687] Step 1:

[0688] Users input their ideas using their own devices. Using a dedicated input form or application, users can input their ideas in any format, such as text or images.

[0689] Step 2:

[0690] The terminal sends the input idea to the server, along with the user's identification information (e.g., user ID) and idea format information.

[0691] Step 3:

[0692] The server receives the ideas sent from the device and stores them in a data store (database).

[0693] Step 4:

[0694] The server collects all ideas from the data store. In this step, all ideas submitted by multiple users are obtained.

[0695] Step 5:

[0696] The server's summarization program analyzes and summarizes the collected ideas, extracting the key points and summarizing them into a concise narrative.

[0697] Step 6:

[0698] The server passes the summarized story to a formatting program, which converts the summarized story into a specified format (e.g., text format, video format, etc.).

[0699] Step 7:

[0700] The server sends the formatted story to the device, which receives it and displays it in a format that the user can view.

[0701] Step 8:

[0702] The user can view the generated story through a terminal. The user can read the story or watch it as a video.

[0703] By using the above steps, the system of the present invention can efficiently collect and summarize ideas provided by multiple users and output them in a variety of formats.

[0704] Example 1

[0705] 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."

[0706] Conventional technologies have been unable to efficiently collect ideas entered by multiple users in different formats, summarize them, convert them into a specified format, and output them. Furthermore, there has been no system that can generate high-quality stories while protecting user privacy by accepting these ideas anonymously. Therefore, there is a need for a system that can accept ideas in various formats from users, summarize them, and output them in a specified format.

[0707] 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.

[0708] In this invention, the server includes means for accepting multiple inputs, means for storing the multiple inputs in a database, means for using a generative AI model to summarize the multiple inputs, means for converting the summarized content into a specified format, and means for outputting the converted content, thereby enabling efficient collection, analysis, and summary of various ideas from users, and outputting them in a specified format to provide an easy-to-read story.

[0709] "Multiple inputs" refers to ideas provided by multiple users in different formats (text, images, etc.).

[0710] "Database" refers to a digital information repository for storing and managing multiple inputs received.

[0711] A "summary" refers to information that extracts important content from multiple inputs and summarizes it concisely.

[0712] A "generative AI model" refers to an artificial intelligence algorithm that analyzes input data and performs summarization or transformation.

[0713] "Specified format" refers to the output format after conversion (e.g., text, video, or a combination thereof).

[0714] "Output" refers to the act of providing the user with the summary converted into a specified format.

[0715] The present invention is a system that summarizes the ideas of multiple users, such as characters, plots, and developments, and outputs them in a specified format (text, video, a combination of text, etc.) to create a single work. Specific embodiments of this system are described below.

[0716] User idea entry and submission

[0717] Users use a dedicated input form or application to input their ideas into the device in any format (text, images, etc.). The ideas are then sent from the device to the server, which receives the ideas and stores them in a database.

[0718] Idea collection and summarization

[0719] The server collects all ideas from the database. Based on the collected ideas, a summary program analyzes and summarizes the information using a generative AI model (e.g., GPT-4), extracts the important parts, and generates a concise story. An example of a specific prompt is "Generate a concise story based on the following user ideas:" followed by a list of the user's ideas.

[0720] for example,

[0721] "Generate a concise narrative based on the following user ideas:

[0722] 1. He is a brave warrior and is searching for a magic sword.

[0723] 2. She was a wise wizard who set out on a journey to help the warrior.

[0724] 3. The two fight a giant dragon and save the village.

[0725] Conversion to a specified format

[0726] The summarized story is then converted into a pre-specified format (text, video, or a combination) by a formatting output program on the server, which provides the story in a format that is easy for the user to read and understand.

[0727] Narrative output and display

[0728] The converted story is finally sent to the device and displayed in a viewable format for the user, allowing the user to easily refer to and enjoy the generated story.

[0729] Specific examples

[0730] User 1: "He's a brave warrior and he's looking for a magic sword."

[0731] User 2: "She was a wise wizard who set out on a journey to help the warrior."

[0732] User 3: "They fight a giant dragon and save the village."

[0733] These ideas are sent from the device to a server, which stores the data in a database. The server collects these ideas and uses a generative AI model to generate a summarized story, such as:

[0734] "The story of a brave warrior and a wise wizard who embark on a journey to battle a giant dragon and save their village."

[0735] A formatted output program converts this condensed story into text and displays it on the terminal:

[0736] Story Title: The Adventure of the Hero and the Wizard

[0737] He is a brave warrior searching for a magical sword, and she is a wise wizard who sets out on a journey to help him. Together they battle a giant dragon and save their village.

[0738] In this way, the system can efficiently collect, analyze, summarize, and output various ideas from users in a specified format, providing them with an easy-to-understand story, thereby enabling creative activities that go beyond the limitations of traditional individual work.

[0739] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0740] Step 1:

[0741] The user launches a dedicated input form or application. The user enters their idea in the input form in the form of text or images. When the user clicks the "Send" button, the device sends the information to the server. Specifically, User 1 enters "He is a brave warrior and is looking for a magic sword" and presses the send button.

[0742] Input: The idea the user entered into the form (e.g., "He is a brave warrior and is looking for a magic sword.")

[0743] Output: The input ideas are sent from the terminal to the server.

[0744] Step 2:

[0745] The server stores the received ideas in a database, which records and manages all ideas received from each user.

[0746] Input: User ideas sent from the device (e.g., "He is a brave warrior and is looking for a magic sword.")

[0747] Output: Ideas stored in a database.

[0748] Step 3:

[0749] The server collects all user ideas from the database and passes the collected ideas to the summarization program.

[0750] Input: All user ideas in the database

[0751] Output: A set of ideas that is passed to the summarization program.

[0752] Step 4:

[0753] The summarization program calls a generative AI model (e.g., GPT-4) to analyze and summarize the input idea. Specifically, the user's idea is input along with the prompt, "Generate a concise story based on the user's idea below:" The generative AI model extracts key elements and generates a concise story.

[0754] Input: The user's idea passed to the summary program along with the prompt.

[0755] Output: The summary produced by the generative AI model.

[0756] Step 5:

[0757] The server stores the generated summary in a database, which is used to convert the summary to the specified format in the next step.

[0758] Input: A summary generated by a generative AI model (e.g., "A story about a brave warrior and a wise wizard who embark on a journey to battle a giant dragon and save their village.")

[0759] Output: A summary stored in a database.

[0760] Step 6:

[0761] The server passes the summarized story to a formatting program, which converts it into a specified format (text, video, etc.), for example, converting the summarized story into text format.

[0762] Input: Abstracted stories in the database

[0763] Output: The story converted to the specified format.

[0764] Step 7:

[0765] The server sends the converted story to the terminal, which displays the received story to the user.

[0766] Input: A textual narrative generated by a formatted output program

[0767] Output: The story displayed on the user's terminal.

[0768] Through this series of processes, the diverse ideas of users are efficiently collected, analyzed, summarized, and output in the specified format to form a novel story. The user can easily browse and enjoy the final story that is displayed.

[0769] (Application example 1)

[0770] 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."

[0771] Conventional story generation systems have had difficulty automatically generating efficient and compelling content when integrating individual user ideas into a single work. Effectively summarizing ideas input by multiple users and outputting them in a specified format requires advanced natural language processing capabilities. Another challenge is accepting these ideas anonymously while integrating and outputting them as a compelling story.

[0772] 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.

[0773] In this invention, the server includes means for accepting multiple inputs, means for summarizing the multiple inputs, means for converting the summarized content into a specified format, means for outputting the converted content, means for analyzing the multiple inputs using a generative AI model to generate a story, and means for displaying the generated story in a format that can be viewed by the user. This makes it possible to effectively collect and summarize individual user ideas, automatically generate an attractive story, and output it in a specified format.

[0774] "Multiple inputs" refers to information in various formats, such as text and images, provided by multiple users.

[0775] A "summarizer" is a part of a system that has the ability to extract important content from multiple inputs and summarize it in a compact form.

[0776] "Specified Format" means a format specified by the User that represents the Generated Content in text, video, or a combination thereof.

[0777] "Transforming means" refers to the process or algorithm used to transform the summarized content into the specified format.

[0778] "Means for outputting" refers to an interface or device for displaying the converted content in a form that can be viewed by a user.

[0779] A "generative AI model" refers to an artificial intelligence model that has the ability to analyze information collected from users and generate stories in the form of text, video, etc.

[0780] "Means for analyzing and generating a narrative" refers to the process of automatically generating a narrative from multiple inputs using a generative AI model.

[0781] "Means for displaying in a viewable form" refers to the function of providing the generated story in a form that can be viewed by users through devices such as smartphones or computers.

[0782] To implement this invention, it is necessary to build a system that involves the following process between a server, a terminal, and a user. First, a user inputs their idea through a dedicated application. Ideas can be input in a variety of formats, including text and images, and are then sent to the server. The server receives the data using a web framework such as Flask and stores it in a database such as SQLite.

[0783] Next, the server collects the saved ideas and analyzes them using a generative AI model (e.g., OpenAI's GPT-3) to generate a summarized story. The prompt for the generative AI model consists of a combination of each of the user's ideas. For example, the prompt could be, "Generate a story based on the following idea: A brave warrior is searching for a magical sword. A wise wizard sets out on a journey to help the warrior. The two fight a giant dragon and save the village."

[0784] The generated story is converted into a specified format (e.g., text, video, or a combination of both). After conversion, the story is sent to the user's smartphone or computer and displayed in a viewable format. This allows the user to enjoy a story that integrates their own ideas.

[0785] Examples of prompts used are:

[0786] Generate a story based on the following ideas:

[0787] A brave warrior is searching for a magical sword.

[0788] A wise wizard set out to help the warrior.

[0789] The two fight a giant dragon and save the village.

[0790] By integrating these methods and processes, the server can effectively summarize the ideas of multiple users, automatically generate an engaging story, and output it in a specified format, allowing users to enjoy a new creative experience.

[0791] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0792] Step 1:

[0793] Users input their ideas through a dedicated application. Ideas can be entered in a variety of formats, including text and images, and are then sent to the server. The entered ideas are then properly formatted within the application and sent to the server via API. The input data includes the user's ID and the content of the idea.

[0794] Step 2:

[0795] The server receives the data using a web framework such as Flask and stores it in a database such as SQLite. The server records the received ideas in the database for later processing. The input is the user's idea data, and the output is the idea data stored in the database.

[0796] Step 3:

[0797] The server collects multiple saved ideas and analyzes them using a generative AI model (e.g., OpenAI's GPT-3). First, it retrieves all ideas from the database and formats them into a single prompt. The input is a set of ideas retrieved from the database, and the output is a prompt for the generative AI model.

[0798] Step 4:

[0799] A prompt is input into the generative AI model, which then generates a story. The AI ​​model analyzes the given prompt and generates a coherent story based on the context. The input is the prompt, and the output is the generated story.

[0800] Step 5:

[0801] Convert the generated story into a specified format (e.g., text, video, or a combination). For example, perform a formatting process to convert it into a text-based story, or use a video generation library (e.g., Stable Diffusion) if a video format is required. The input is the generated story, and the output is a story in the specified format.

[0802] Step 6:

[0803] The converted story is sent to the user's smartphone or computer and displayed in a viewable format. The story is sent to the user's device via an API and displayed within the application. The input is a story in the specified format, and the output is the story displayed on the user's device.

[0804] As an example of specific behavior, the prompt sentence to the generative AI model is as follows:

[0805] Generate a story based on the following ideas:

[0806] A brave warrior is searching for a magical sword.

[0807] A wise wizard set out to help the warrior.

[0808] The two fight a giant dragon and save the village.

[0809] Based on this prompt, the AI ​​model will generate a story, which will ultimately be presented to the user in a format that can be viewed.

[0810] 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.

[0811] This invention is a system that combines an emotion engine with ideas for characters, plots, developments, etc. that multiple users have each come up with, and adjusts the summarization and format conversion process to create a single work that reflects the emotional state of the users.

[0812] Program Overview

[0813] 1. User Idea Input and Submission

[0814] Users use a dedicated input form or application to input their ideas into the device in any format (text, images, etc.). The ideas are then sent from the device to the server, which receives the ideas and stores them in a database.

[0815] 2. Sentiment analysis using an emotion engine

[0816] The server is equipped with an emotion engine that performs emotion analysis on received ideas. The emotion engine uses natural language processing technology to determine the emotion (e.g., joy, sadness, surprise, anger, etc.) contained in each idea.

[0817] 3. Collecting and Summarizing Ideas

[0818] The server collects all ideas from the database and retrieves the sentiment analysis results. Then, based on the collected ideas and their sentiment data, the summarization program extracts the key parts and generates a concise story that reflects the sentiment.

[0819] 4. Conversion to the specified format

[0820] The summarized story is converted into a pre-specified format (e.g., text format, video format, etc.) by a format output program on the server. At this time, the emotional information determined by the emotion engine is also taken into consideration, and the expression of the story is adjusted.

[0821] 5. Narrative output and display

[0822] The converted story is finally sent to the device and displayed in a viewable format for the user, allowing the user to easily refer to and enjoy the generated story, as well as to enjoy stories that reflect the emotional state of other users.

[0823] Specific examples

[0824] User input and submission

[0825] User 1 (Sentiment Analysis: Joy): "He is a brave warrior and is looking for a magic sword."

[0826] User 2 (Sentiment Analysis: Surprise): "She was a wise wizard who set out on a journey to help the warrior."

[0827] User 3 (Sentiment Analysis: Sadness): "They fight a giant dragon and save the village."

[0828] These ideas are sent from each user's terminal to the server.

[0829] Server processing and result output

[0830] The server collects these ideas and performs a sentiment analysis on each idea using a sentiment engine. It then uses a summarization program to generate a summarized story, taking into account the sentiment information, like this:

[0831] "A tale of a brave warrior and a wise wizard who battle a mighty dragon with astonishment and embark on a heartbreaking journey to save their village."

[0832] A formatted output program will convert this condensed story into text and display it on the terminal as follows:

[0833] Story Title: The Adventure of the Hero and the Wizard

[0834] He is a brave warrior searching for a magic sword (Joy), she is a wise wizard who sets out on a journey to help him (Surprise), and together they fight a giant dragon and save their village (Sadness).

[0835] In this way, the system of the present invention can efficiently collect ideas provided by multiple users, summarize them emotionally, and convert them into a format that reflects their emotions, thereby creating a richer, more emotionally appealing story.

[0836] The processing flow will be explained below.

[0837] Step 1:

[0838] Users input their ideas using their own devices. Using a dedicated input form or application, users can input their ideas in any format, such as text or images.

[0839] Step 2:

[0840] The terminal sends the input idea to the server, along with the user's identification information (e.g., user ID) and idea format information.

[0841] Step 3:

[0842] The server receives the ideas sent from the device and stores them in a data store (database).

[0843] Step 4:

[0844] The emotion engine built into the server performs emotion analysis of the received ideas. The emotion engine uses natural language processing technology to determine the emotion (joy, sadness, surprise, anger, etc.) contained in each idea.

[0845] Step 5:

[0846] The server collects all ideas and their sentiment analysis results from the data store. In this step, all ideas and sentiment data provided by multiple users are obtained.

[0847] Step 6:

[0848] A summarization program on the server analyzes and summarizes the collected ideas and emotion data, extracting key points and generating a concise narrative that reflects emotion.

[0849] Step 7:

[0850] The server passes the summarized story to the format output program, which converts the summarized story into a specified format (e.g., text format, video format, etc.). At this time, the emotional information determined by the emotion engine is also taken into account, and the presentation of the story is adjusted.

[0851] Step 8:

[0852] The server sends the formatted story to the device, which receives it and displays it in a format that the user can view.

[0853] Step 9:

[0854] The user can view the generated story through a terminal. The user can read the story or watch it as a video.

[0855] Example 2

[0856] 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."

[0857] Conventional story generation systems have difficulty processing inputs from multiple users simultaneously and reflecting their content in an emotionally rich way. Furthermore, summarizing and formatting the inputs must be done manually, which is inefficient. This has led to the problem that the stories created by users tend to be emotionally flat and lack appeal.

[0858] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting multiple inputs, means for saving the multiple inputs, means for analyzing the saved inputs to determine emotions, means for summarizing the analyzed inputs, means for converting the summarized content into a specified format, and means for outputting the converted content and emotional information in consideration. This makes it possible to efficiently collect multiple ideas provided by a user and automatically summarize and convert the format to reflect emotions, thereby generating rich, emotionally appealing stories.

[0859] "Means for accepting multiple inputs" refers to an interface or system for receiving multiple user-provided ideas or data as inputs.

[0860] The "means for saving the plurality of inputs" refers to a function or process for temporarily or permanently storing the plurality of input data received in storage.

[0861] "Means for analyzing the stored input to determine emotions" refers to an algorithm or engine for analyzing the stored input data and identifying the emotional information contained therein (e.g., joy, sadness, surprise, etc.).

[0862] The "means for summarizing the analyzed input" refers to a program or software for extracting important parts from the analyzed input data and summarizing them concisely.

[0863] The "means for converting the summarized content into a specified format" refers to a process for converting the summarized content into a specified format, such as text format or video format.

[0864] "Means for outputting in consideration of the converted content and emotional information" refers to a function for generating a final output based on the converted content and its emotional information and providing it to the user.

[0865] This system combines an emotion engine with ideas from multiple users, such as characters, plots, and developments, to coordinate the summarization and format conversion process and create a work that reflects the emotional state of the users. This system is implemented primarily using the following hardware and software:

[0866] Hardware and Software

[0867] User device: The device through which the user inputs ideas (e.g., smartphone, PC).

[0868] Server: A central processing unit that receives, stores, analyzes, summarizes, transforms, and outputs data sent by users.

[0869] Database: A persistent storage system for input data and analysis results (e.g., MySQL, MongoDB).

[0870] Emotion engine: Software that uses natural language processing technology to analyze the emotions contained in input data (e.g., Google Cloud Natural Language API, IBM Watson).

[0871] Summarizer: A generative AI model (e.g., BERT model, GPT model) for summarizing input data.

[0872] Formatting output program: Software (e.g., Python script, template engine) to convert the summarized content into a specified format.

[0873] System operation procedures

[0874] 1. User Idea Input and Submission

[0875] Users use a dedicated input form or application to input their ideas into their device in any format (text, images, etc.), and then send them from the device to the server. For example, a user opens an app on their smartphone and inputs, "He is a brave warrior and is looking for a magic sword." Then, they tap the send button to send the idea to the server.

[0876] 2. Receiving and storing ideas by the server

[0877] The server receives the submitted ideas and stores them in a database, where each received idea is recorded with a unique ID and a timestamp.

[0878] 3. Sentiment analysis using an emotion engine

[0879] The server retrieves the stored ideas and performs sentiment analysis using an emotion engine. For example, it uses the Google Cloud Natural Language API to detect the emotion "joy" from the idea "He is a brave warrior and is looking for a magic sword." The analysis results are stored in a database.

[0880] 4. Collecting and Summarizing Ideas

[0881] The server collects all ideas and their sentiment analysis results from the database, and uses a summarization program (e.g., BERT model, GPT model) to extract key parts from these ideas and generate a concise narrative that reflects sentiment.

[0882] 5. Conversion to the specified format

[0883] The generated summary story is converted into a specified format (text, video, etc.) using a format output program. The story presentation is optimized, taking into account the results of sentiment analysis. For example, it may be formatted as follows:

[0884] Story Title: The Adventure of the Hero and the Wizard

[0885] He is a brave warrior searching for a magic sword (Joy), she is a wise wizard who sets out on a journey to help him (Surprise), and together they fight a giant dragon and save their village (Sadness).

[0886] 6. Story output and display on the terminal

[0887] The converted story is sent from the server to each user's device and displayed in a viewable format. Users can check and enjoy the generated story on their own devices.

[0888] Specific examples

[0889] Specific prompts for users to submit their ideas include:

[0890] User 1 (Sentiment Analysis: Joy): "He is a brave warrior and is looking for a magic sword."

[0891] User 2 (Sentiment Analysis: Surprise): "She was a wise wizard who set out on a journey to help the warrior."

[0892] User 3 (Sentiment Analysis: Sadness): "They fight a giant dragon and save the village."

[0893] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0894] Step 1:

[0895] User idea entry and submission

[0896] A user inputs his / her idea into the device using a dedicated input form or application. For example, the user inputs "He is a brave warrior and is looking for a magic sword" in text format. Then, the user taps the send button to send the idea from the device to the server. The input data is the idea in text format, and the output is the raw idea data received by the server.

[0897] Step 2:

[0898] Server receives and stores ideas

[0899] The server receives idea data sent by users. The received data is assigned a unique ID and a timestamp and stored in a database. The input is the text idea sent by the user, and the output is structured data stored in the database.

[0900] Step 3:

[0901] Emotion analysis by the server's emotion engine

[0902] The server retrieves the saved idea data and performs sentiment analysis using an emotion engine. For example, the emotion engine uses the Google Cloud Natural Language API to determine the emotion of "joy" from the text "He is a brave warrior and is looking for a magic sword." This emotion data is then saved back to the database. The input is the saved idea data, and the output is data containing the sentiment analysis results.

[0903] Step 4:

[0904] Server idea collection and summary

[0905] The server collects all ideas and their sentiment analysis data from the database. Then, it uses a summarization program to extract the important parts and generate a concise story. For example, it uses the BERT model as a summarization program to summarize a story based on sentences like "He is a brave warrior who is searching for a magic sword" and "She is a wise wizard who sets out on a journey to help the warrior." The input is idea data including sentiment analysis results, and the output is a summarized story.

[0906] Step 5:

[0907] Conversion to specified format by server

[0908] The generated summary story is converted into a specified format (e.g., text format) using a format output program. The results of sentiment analysis are also taken into consideration during this process. For example, the converted story might look like this: "A brave warrior and a wise wizard fight a giant dragon with great surprise, and save the village in grief." The input is the summarized story data, and the output is the story converted into the specified format.

[0909] Step 6:

[0910] Story output and display on terminal

[0911] The final output story is sent from the server to the user's device. The device receives it and displays it in a viewable format for the user. For example, the story may be displayed on a smartphone screen. The user can read and enjoy it. The input is the story data sent from the server, and the output is the story displayed on the device.

[0912] (Application example 2)

[0913] 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."

[0914] Conventional story generation systems were unable to analyze emotions from user-input ideas and generate summaries that reflected those emotions. Furthermore, they lacked the ability to convert and output summaries generated based on the analyzed emotions into various formats, limiting the quality of the stories provided to users. This prevented users from enjoying stories with emotional depth, limiting their entertainment experience.

[0915] 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 means for accepting multiple inputs, means for analyzing emotions based on the multiple inputs, means for generating a summary including the analyzed emotions, means for converting the summarized content into a specified format, and means for outputting the converted content. This makes it possible to emotionally analyze ideas input by a user and automatically generate and output stories in various formats that reflect the emotions.

[0916] "Multiple inputs" refers to multiple ideas or pieces of information provided by a user, including various forms such as text, audio, and images.

[0917] "Sentiment analysis methods" refers to natural language processing techniques and algorithms used to identify and classify the emotions contained in input ideas and information.

[0918] "Means for generating summaries" refers to algorithms that take into account the analyzed sentiment, extract key parts, and automatically generate concise stories or content.

[0919] The "means for converting into a specified format" refers to a format conversion technology for converting the generated summary content into a pre-specified format (for example, text, audio, video, etc.).

[0920] "Means for outputting" refers to the system or protocol for transmitting the content in the final converted format to a user terminal so that it can be displayed or played back.

[0921] "Server" refers to a central processing unit for receiving input from users, performing sentiment analysis, summary generation and format conversion, and outputting the final content.

[0922] In this invention, a server executes a series of processes: collecting user ideas, analyzing their emotions, summarizing them, converting them into a specified format, and finally outputting them. Specifically, users input their ideas using a smartphone or head-mounted display (HMD) and send them to the server. The server analyzes the received ideas, generates a story based on the emotional data, converts them into various formats such as text, audio, and video, and outputs them to the user's device. The hardware and software used and their roles are explained below.

[0923] Hardware

[0924] Smartphone: A device that allows users to input ideas, allowing voice and text input, and communicating with a server via the Internet.

[0925] Head-mounted display (HMD): A device for visually experiencing a story in virtual reality (VR). It has the function of displaying ideas entered by the user in a VR space.

[0926] Server: As a central processing unit, it receives input from users and performs sentiment analysis, summary generation, format conversion, and final output.

[0927] software

[0928] Azure Text Analytics API: An API that provides natural language processing technology for sentiment analysis, extracting sentiment data based on user ideas.

[0929] Python script: A program to collect ideas and generate summaries based on sentiment analysis, leveraging NLP techniques to extract key points and create a concise narrative.

[0930] FFmpeg library: A library for converting the generated summaries into video format, with the ability to embed text information into video frames.

[0931] Unity Engine: A 3D engine for displaying stories in virtual reality (VR) spaces, providing a visually and audio-rich experience.

[0932] A natural language description of the process

[0933] 1. User input and submission:

[0934] Users use their smartphones or HMDs to input their ideas by voice or text. For example, a user might input the idea "A brave warrior is searching for a magic sword" into their smartphone, which is then immediately sent to the server.

[0935] 2. Emotion analysis:

[0936] The server uses the Azure Text Analytics API to perform sentiment analysis on the received ideas, and the sentiment data (happiness, surprise, sadness, etc.) is stored in a database along with the analysis results using a Python script.

[0937] 3. Summary generation:

[0938] Based on multiple ideas and their sentiment data stored on the server, the Python script uses NLP techniques to extract key parts and create a sentiment-based summary, such as "A brave warrior is searching for a magic sword (joy)."

[0939] 4. Format conversion:

[0940] The resulting summary is then converted to the specified format using the FFmpeg library. In the video format example, the text information is embedded into the video frames for visual display.

[0941] 5. Final output:

[0942] The stories in the specified format are displayed on an HMD using the Unity engine or made viewable on a smartphone app, allowing users to experience the generated stories in real time.

[0943] Specific examples

[0944] User A inputs "A brave warrior searches for a magic sword" into their smartphone, while User B inputs "A wise wizard goes on an adventure." These ideas are sent to the server, which performs sentiment analysis and generates a story: "A brave warrior searches for a magic sword and fights a giant dragon alongside the wise wizard." This story is displayed as video or text on the HMD or smartphone, depending on the presentation format.

[0945] Example prompt sentence:

[0946] "A brave warrior seeks a magic sword"

[0947] "A clever wizard goes on an adventure"

[0948] "A giant dragon attacks the village"

[0949] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0950] Step 1:

[0951] Users use a smartphone or head-mounted display (HMD) to input their ideas using text or voice. For example, they input a specific idea such as "A brave warrior is searching for a magic sword." The input idea is instantly sent to the server via the Internet. Input = user's idea (text or voice), output = idea data sent to the server.

[0952] Step 2:

[0953] The server stores the received ideas in a database. At this time, the attribute information of the idea (user ID, input format, etc.) is also recorded. Input = submitted idea data and its attribute information, Output = idea stored in the database.

[0954] Step 3:

[0955] The server uses the Azure Text Analytics API to perform sentiment analysis on the stored ideas. This process uses natural language processing technology to identify the emotions (happiness, sadness, surprise, etc.) contained in each idea and output them as emotional data. Input = ideas stored in the database, output = analyzed emotional data.

[0956] Step 4:

[0957] The server uses a Python script to generate a summary of the idea based on the results of the sentiment analysis. It uses NLP (Natural Language Processing) technology to extract key parts and automatically generate a concise story that reflects the sentiment. Input: analyzed sentiment data and original idea. Output: summarized story.

[0958] Step 5:

[0959] The server uses the FFmpeg library to convert the summarized story into the specified format (text, audio, video, etc.). For example, in video format, the summarized text is embedded into the video frames. Input = summarized story, output = content in the specified format (e.g. video file).

[0960] Step 6:

[0961] The server sends the content in the generated format to the user's device. The user can view and experience the generated story through their smartphone or HMD. Input = content in the specified format, Output = final content displayed on the user's device.

[0962] 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.

[0963] 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.

[0964] 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.

[0965] [Fourth embodiment]

[0966] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0967] 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.

[0968] 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).

[0969] 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.

[0970] 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.

[0971] 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).

[0972] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0973] 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.

[0974] 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.

[0975] 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.

[0976] 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.

[0977] 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.

[0978] 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."

[0979] The present invention is a system that summarizes the ideas of multiple users, such as characters, plots, and developments, and outputs them in a specified format (text, video, a combined format, etc.) to create a single work.

[0980] Program Overview

[0981] 1. User Idea Input and Submission

[0982] Users use a dedicated input form or application to input their ideas into the device in any format (text, images, etc.). The ideas are then sent from the device to the server, which receives the ideas and stores them in a database.

[0983] 2. Collecting and Summarizing Ideas

[0984] The server collects all ideas from the database, and based on the collected ideas, the summarization program analyzes and summarizes the information, extracts the important parts, and generates a concise story.

[0985] 3. Convert to the specified format

[0986] The summarized story is then converted into a pre-specified format (text, video, or a combination) by a formatting output program on the server, which provides the story in a format that is easy for the user to read and understand.

[0987] 4. Narrative output and display

[0988] The converted story is finally sent to the device and displayed in a viewable format for the user, allowing the user to easily refer to and enjoy the generated story.

[0989] Specific examples

[0990] User input and submission

[0991] User 1: "He's a brave warrior and he's looking for a magic sword."

[0992] User 2: "She was a wise wizard who set out on a journey to help the warrior."

[0993] User 3: "They fight a giant dragon and save the village."

[0994] These ideas are sent from each user's terminal to the server.

[0995] Server processing and result output

[0996] The server collects these ideas and uses a summarization program to generate a condensed story like this:

[0997] "The story of a brave warrior and a wise wizard who embark on a journey to battle a giant dragon and save their village."

[0998] A formatted output program will convert this condensed story into text and display it on the terminal as follows:

[0999] Story Title: The Adventure of the Hero and the Wizard

[1000] He is a brave warrior searching for a magical sword, and she is a wise wizard who sets out on a journey to help him. Together they battle a giant dragon and save their village.

[1001] In this way, the system of the present invention can efficiently collect and summarize diverse ideas, output them in a specified format, and create a novel story, thereby realizing creative activities that go beyond the limitations of conventional individual work.

[1002] The processing flow will be explained below.

[1003] Step 1:

[1004] Users input their ideas using their own devices. Using a dedicated input form or application, users can input their ideas in any format, such as text or images.

[1005] Step 2:

[1006] The terminal sends the input idea to the server, along with the user's identification information (e.g., user ID) and idea format information.

[1007] Step 3:

[1008] The server receives the ideas sent from the device and stores them in a data store (database).

[1009] Step 4:

[1010] The server collects all ideas from the data store. In this step, all ideas submitted by multiple users are obtained.

[1011] Step 5:

[1012] The server's summarization program analyzes and summarizes the collected ideas, extracting the key points and summarizing them into a concise narrative.

[1013] Step 6:

[1014] The server passes the summarized story to a formatting program, which converts the summarized story into a specified format (e.g., text format, video format, etc.).

[1015] Step 7:

[1016] The server sends the formatted story to the device, which receives it and displays it in a format that the user can view.

[1017] Step 8:

[1018] The user can view the generated story through a terminal. The user can read the story or watch it as a video.

[1019] By using the above steps, the system of the present invention can efficiently collect and summarize ideas provided by multiple users and output them in a variety of formats.

[1020] Example 1

[1021] 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."

[1022] Conventional technologies have been unable to efficiently collect ideas entered by multiple users in different formats, summarize them, convert them into a specified format, and output them. Furthermore, there has been no system that can generate high-quality stories while protecting user privacy by accepting these ideas anonymously. Therefore, there is a need for a system that can accept ideas in various formats from users, summarize them, and output them in a specified format.

[1023] 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.

[1024] In this invention, the server includes means for accepting multiple inputs, means for storing the multiple inputs in a database, means for using a generative AI model to summarize the multiple inputs, means for converting the summarized content into a specified format, and means for outputting the converted content, thereby enabling efficient collection, analysis, and summary of various ideas from users, and outputting them in a specified format to provide an easy-to-read story.

[1025] "Multiple inputs" refers to ideas provided by multiple users in different formats (text, images, etc.).

[1026] "Database" refers to a digital information repository for storing and managing multiple inputs received.

[1027] A "summary" refers to information that extracts important content from multiple inputs and summarizes it concisely.

[1028] A "generative AI model" refers to an artificial intelligence algorithm that analyzes input data and performs summarization or transformation.

[1029] "Specified format" refers to the output format after conversion (e.g., text, video, or a combination thereof).

[1030] "Output" refers to the act of providing the user with the summary converted into a specified format.

[1031] The present invention is a system that summarizes the ideas of multiple users, such as characters, plots, and developments, and outputs them in a specified format (text, video, a combination of text, etc.) to create a single work. Specific embodiments of this system are described below.

[1032] User idea entry and submission

[1033] Users use a dedicated input form or application to input their ideas into the device in any format (text, images, etc.). The ideas are then sent from the device to the server, which receives the ideas and stores them in a database.

[1034] Idea collection and summarization

[1035] The server collects all ideas from the database. Based on the collected ideas, a summary program analyzes and summarizes the information using a generative AI model (e.g., GPT-4), extracts the important parts, and generates a concise story. An example of a specific prompt is "Generate a concise story based on the following user ideas:" followed by a list of the user's ideas.

[1036] for example,

[1037] "Generate a concise narrative based on the following user ideas:

[1038] 1. He is a brave warrior and is searching for a magic sword.

[1039] 2. She was a wise wizard who set out on a journey to help the warrior.

[1040] 3. The two fight a giant dragon and save the village.

[1041] Conversion to a specified format

[1042] The summarized story is then converted into a pre-specified format (text, video, or a combination) by a formatting output program on the server, which provides the story in a format that is easy for the user to read and understand.

[1043] Narrative output and display

[1044] The converted story is finally sent to the device and displayed in a viewable format for the user, allowing the user to easily refer to and enjoy the generated story.

[1045] Specific examples

[1046] User 1: "He's a brave warrior and he's looking for a magic sword."

[1047] User 2: "She was a wise wizard who set out on a journey to help the warrior."

[1048] User 3: "They fight a giant dragon and save the village."

[1049] These ideas are sent from the device to a server, which stores the data in a database. The server collects these ideas and uses a generative AI model to generate a summarized story, such as:

[1050] "The story of a brave warrior and a wise wizard who embark on a journey to battle a giant dragon and save their village."

[1051] A formatted output program converts this condensed story into text and displays it on the terminal:

[1052] Story Title: The Adventure of the Hero and the Wizard

[1053] He is a brave warrior searching for a magical sword, and she is a wise wizard who sets out on a journey to help him. Together they battle a giant dragon and save their village.

[1054] In this way, the system can efficiently collect, analyze, summarize, and output various ideas from users in a specified format, providing them with an easy-to-understand story, thereby enabling creative activities that go beyond the limitations of traditional individual work.

[1055] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1056] Step 1:

[1057] The user launches a dedicated input form or application. The user enters their idea in the input form in the form of text or images. When the user clicks the "Send" button, the device sends the information to the server. Specifically, User 1 enters "He is a brave warrior and is looking for a magic sword" and presses the send button.

[1058] Input: The idea the user entered into the form (e.g., "He is a brave warrior and is looking for a magic sword.")

[1059] Output: The input ideas are sent from the terminal to the server.

[1060] Step 2:

[1061] The server stores the received ideas in a database, which records and manages all ideas received from each user.

[1062] Input: User ideas sent from the device (e.g., "He is a brave warrior and is looking for a magic sword.")

[1063] Output: Ideas stored in a database.

[1064] Step 3:

[1065] The server collects all user ideas from the database and passes the collected ideas to the summarization program.

[1066] Input: All user ideas in the database

[1067] Output: A set of ideas that is passed to the summarization program.

[1068] Step 4:

[1069] The summarization program calls a generative AI model (e.g., GPT-4) to analyze and summarize the input idea. Specifically, the user's idea is input along with the prompt, "Generate a concise story based on the user's idea below:" The generative AI model extracts key elements and generates a concise story.

[1070] Input: The user's idea passed to the summary program along with the prompt.

[1071] Output: The summary produced by the generative AI model.

[1072] Step 5:

[1073] The server stores the generated summary in a database, which is used to convert the summary to the specified format in the next step.

[1074] Input: A summary generated by a generative AI model (e.g., "A story about a brave warrior and a wise wizard who embark on a journey to battle a giant dragon and save their village.")

[1075] Output: A summary stored in a database.

[1076] Step 6:

[1077] The server passes the summarized story to a formatting program, which converts it into a specified format (text, video, etc.), for example, converting the summarized story into text format.

[1078] Input: Abstracted stories in the database

[1079] Output: The story converted to the specified format.

[1080] Step 7:

[1081] The server sends the converted story to the terminal, which displays the received story to the user.

[1082] Input: A textual narrative generated by a formatted output program

[1083] Output: The story displayed on the user's terminal.

[1084] Through this series of processes, the diverse ideas of users are efficiently collected, analyzed, summarized, and output in the specified format to form a novel story. The user can easily browse and enjoy the final story that is displayed.

[1085] (Application example 1)

[1086] 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."

[1087] Conventional story generation systems have had difficulty automatically generating efficient and compelling content when integrating individual user ideas into a single work. Effectively summarizing ideas input by multiple users and outputting them in a specified format requires advanced natural language processing capabilities. Another challenge is accepting these ideas anonymously while integrating and outputting them as a compelling story.

[1088] 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.

[1089] In this invention, the server includes means for accepting multiple inputs, means for summarizing the multiple inputs, means for converting the summarized content into a specified format, means for outputting the converted content, means for analyzing the multiple inputs using a generative AI model to generate a story, and means for displaying the generated story in a format that can be viewed by the user. This makes it possible to effectively collect and summarize individual user ideas, automatically generate an attractive story, and output it in a specified format.

[1090] "Multiple inputs" refers to information in various formats, such as text and images, provided by multiple users.

[1091] A "summarizer" is a part of a system that has the ability to extract important content from multiple inputs and summarize it in a compact form.

[1092] "Specified Format" means a format specified by the User that represents the Generated Content in text, video, or a combination thereof.

[1093] "Transforming means" refers to the process or algorithm used to transform the summarized content into the specified format.

[1094] "Means for outputting" refers to an interface or device for displaying the converted content in a form that can be viewed by a user.

[1095] A "generative AI model" refers to an artificial intelligence model that has the ability to analyze information collected from users and generate stories in the form of text, video, etc.

[1096] "Means for analyzing and generating a narrative" refers to the process of automatically generating a narrative from multiple inputs using a generative AI model.

[1097] "Means for displaying in a viewable form" refers to the function of providing the generated story in a form that can be viewed by users through devices such as smartphones or computers.

[1098] To implement this invention, it is necessary to build a system that involves the following process between a server, a terminal, and a user. First, a user inputs their idea through a dedicated application. Ideas can be input in a variety of formats, including text and images, and are then sent to the server. The server receives the data using a web framework such as Flask and stores it in a database such as SQLite.

[1099] Next, the server collects the saved ideas and analyzes them using a generative AI model (e.g., OpenAI's GPT-3) to generate a summarized story. The prompt for the generative AI model consists of a combination of each of the user's ideas. For example, the prompt could be, "Generate a story based on the following idea: A brave warrior is searching for a magical sword. A wise wizard sets out on a journey to help the warrior. The two fight a giant dragon and save the village."

[1100] The generated story is converted into a specified format (e.g., text, video, or a combination of both). After conversion, the story is sent to the user's smartphone or computer and displayed in a viewable format. This allows the user to enjoy a story that integrates their own ideas.

[1101] Examples of prompts used are:

[1102] Generate a story based on the following ideas:

[1103] A brave warrior is searching for a magical sword.

[1104] A wise wizard set out to help the warrior.

[1105] The two fight a giant dragon and save the village.

[1106] By integrating these methods and processes, the server can effectively summarize the ideas of multiple users, automatically generate an engaging story, and output it in a specified format, allowing users to enjoy a new creative experience.

[1107] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1108] Step 1:

[1109] Users input their ideas through a dedicated application. Ideas can be entered in a variety of formats, including text and images, and are then sent to the server. The entered ideas are then properly formatted within the application and sent to the server via API. The input data includes the user's ID and the content of the idea.

[1110] Step 2:

[1111] The server receives the data using a web framework such as Flask and stores it in a database such as SQLite. The server records the received ideas in the database for later processing. The input is the user's idea data, and the output is the idea data stored in the database.

[1112] Step 3:

[1113] The server collects multiple saved ideas and analyzes them using a generative AI model (e.g., OpenAI's GPT-3). First, it retrieves all ideas from the database and formats them into a single prompt. The input is a set of ideas retrieved from the database, and the output is a prompt for the generative AI model.

[1114] Step 4:

[1115] A prompt is input into the generative AI model, which then generates a story. The AI ​​model analyzes the given prompt and generates a coherent story based on the context. The input is the prompt, and the output is the generated story.

[1116] Step 5:

[1117] Convert the generated story into a specified format (e.g., text, video, or a combination). For example, perform a formatting process to convert it into a text-based story, or use a video generation library (e.g., Stable Diffusion) if a video format is required. The input is the generated story, and the output is a story in the specified format.

[1118] Step 6:

[1119] The converted story is sent to the user's smartphone or computer and displayed in a viewable format. The story is sent to the user's device via an API and displayed within the application. The input is a story in the specified format, and the output is the story displayed on the user's device.

[1120] As an example of specific behavior, the prompt sentence to the generative AI model is as follows:

[1121] Generate a story based on the following ideas:

[1122] A brave warrior is searching for a magical sword.

[1123] A wise wizard set out to help the warrior.

[1124] The two fight a giant dragon and save the village.

[1125] Based on this prompt, the AI ​​model will generate a story, which will ultimately be presented to the user in a format that can be viewed.

[1126] 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.

[1127] This invention is a system that combines an emotion engine with ideas for characters, plots, developments, etc. that multiple users have each come up with, and adjusts the summarization and format conversion process to create a single work that reflects the emotional state of the users.

[1128] Program Overview

[1129] 1. User Idea Input and Submission

[1130] Users use a dedicated input form or application to input their ideas into the device in any format (text, images, etc.). The ideas are then sent from the device to the server, which receives the ideas and stores them in a database.

[1131] 2. Sentiment analysis using an emotion engine

[1132] The server is equipped with an emotion engine that performs emotion analysis on received ideas. The emotion engine uses natural language processing technology to determine the emotion (e.g., joy, sadness, surprise, anger, etc.) contained in each idea.

[1133] 3. Collecting and Summarizing Ideas

[1134] The server collects all ideas from the database and retrieves the sentiment analysis results. Then, based on the collected ideas and their sentiment data, the summarization program extracts the key parts and generates a concise story that reflects the sentiment.

[1135] 4. Conversion to the specified format

[1136] The summarized story is converted into a pre-specified format (e.g., text format, video format, etc.) by a format output program on the server. At this time, the emotional information determined by the emotion engine is also taken into consideration, and the expression of the story is adjusted.

[1137] 5. Narrative output and display

[1138] The converted story is finally sent to the device and displayed in a viewable format for the user, allowing the user to easily refer to and enjoy the generated story, as well as to enjoy stories that reflect the emotional state of other users.

[1139] Specific examples

[1140] User input and submission

[1141] User 1 (Sentiment Analysis: Joy): "He is a brave warrior and is looking for a magic sword."

[1142] User 2 (Sentiment Analysis: Surprise): "She was a wise wizard who set out on a journey to help the warrior."

[1143] User 3 (Sentiment Analysis: Sadness): "They fight a giant dragon and save the village."

[1144] These ideas are sent from each user's terminal to the server.

[1145] Server processing and result output

[1146] The server collects these ideas and performs a sentiment analysis on each idea using a sentiment engine. It then uses a summarization program to generate a summarized story, taking into account the sentiment information, like this:

[1147] "A tale of a brave warrior and a wise wizard who battle a mighty dragon with astonishment and embark on a heartbreaking journey to save their village."

[1148] A formatted output program will convert this condensed story into text and display it on the terminal as follows:

[1149] Story Title: The Adventure of the Hero and the Wizard

[1150] He is a brave warrior searching for a magic sword (Joy), she is a wise wizard who sets out on a journey to help him (Surprise), and together they fight a giant dragon and save their village (Sadness).

[1151] In this way, the system of the present invention can efficiently collect ideas provided by multiple users, summarize them emotionally, and convert them into a format that reflects their emotions, thereby creating a richer, more emotionally appealing story.

[1152] The processing flow will be explained below.

[1153] Step 1:

[1154] Users input their ideas using their own devices. Using a dedicated input form or application, users can input their ideas in any format, such as text or images.

[1155] Step 2:

[1156] The terminal sends the input idea to the server, along with the user's identification information (e.g., user ID) and idea format information.

[1157] Step 3:

[1158] The server receives the ideas sent from the device and stores them in a data store (database).

[1159] Step 4:

[1160] The emotion engine built into the server performs emotion analysis of the received ideas. The emotion engine uses natural language processing technology to determine the emotion (joy, sadness, surprise, anger, etc.) contained in each idea.

[1161] Step 5:

[1162] The server collects all ideas and their sentiment analysis results from the data store. In this step, all ideas and sentiment data provided by multiple users are obtained.

[1163] Step 6:

[1164] A summarization program on the server analyzes and summarizes the collected ideas and emotion data, extracting key points and generating a concise narrative that reflects emotion.

[1165] Step 7:

[1166] The server passes the summarized story to the format output program, which converts the summarized story into a specified format (e.g., text format, video format, etc.). At this time, the emotional information determined by the emotion engine is also taken into account, and the presentation of the story is adjusted.

[1167] Step 8:

[1168] The server sends the formatted story to the device, which receives it and displays it in a format that the user can view.

[1169] Step 9:

[1170] The user can view the generated story through a terminal. The user can read the story or watch it as a video.

[1171] Example 2

[1172] 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."

[1173] Conventional story generation systems have difficulty processing inputs from multiple users simultaneously and reflecting their content in an emotionally rich way. Furthermore, summarizing and formatting the inputs must be done manually, which is inefficient. This has led to the problem that the stories created by users tend to be emotionally flat and lack appeal.

[1174] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting multiple inputs, means for saving the multiple inputs, means for analyzing the saved inputs to determine emotions, means for summarizing the analyzed inputs, means for converting the summarized content into a specified format, and means for outputting the converted content and emotional information in consideration. This makes it possible to efficiently collect multiple ideas provided by a user and automatically summarize and convert the format to reflect emotions, thereby generating rich, emotionally appealing stories.

[1175] "Means for accepting multiple inputs" refers to an interface or system for receiving multiple user-provided ideas or data as inputs.

[1176] The "means for saving the plurality of inputs" refers to a function or process for temporarily or permanently storing the plurality of input data received in storage.

[1177] "Means for analyzing the stored input to determine emotions" refers to an algorithm or engine for analyzing the stored input data and identifying the emotional information contained therein (e.g., joy, sadness, surprise, etc.).

[1178] The "means for summarizing the analyzed input" refers to a program or software for extracting important parts from the analyzed input data and summarizing them concisely.

[1179] The "means for converting the summarized content into a specified format" refers to a process for converting the summarized content into a specified format, such as text format or video format.

[1180] "Means for outputting in consideration of the converted content and emotional information" refers to a function for generating a final output based on the converted content and its emotional information and providing it to the user.

[1181] This system combines an emotion engine with ideas from multiple users, such as characters, plots, and developments, to coordinate the summarization and format conversion process and create a work that reflects the emotional state of the users. This system is implemented primarily using the following hardware and software:

[1182] Hardware and Software

[1183] User device: The device through which the user inputs ideas (e.g., smartphone, PC).

[1184] Server: A central processing unit that receives, stores, analyzes, summarizes, transforms, and outputs data sent by users.

[1185] Database: A persistent storage system for input data and analysis results (e.g., MySQL, MongoDB).

[1186] Emotion engine: Software that uses natural language processing technology to analyze the emotions contained in input data (e.g., Google Cloud Natural Language API, IBM Watson).

[1187] Summarizer: A generative AI model (e.g., BERT model, GPT model) for summarizing input data.

[1188] Formatting output program: Software (e.g., Python script, template engine) to convert the summarized content into a specified format.

[1189] System operation procedures

[1190] 1. User Idea Input and Submission

[1191] Users use a dedicated input form or application to input their ideas into their device in any format (text, images, etc.), and then send them from the device to the server. For example, a user opens an app on their smartphone and inputs, "He is a brave warrior and is looking for a magic sword." Then, they tap the send button to send the idea to the server.

[1192] 2. Receiving and storing ideas by the server

[1193] The server receives the submitted ideas and stores them in a database, where each received idea is recorded with a unique ID and a timestamp.

[1194] 3. Sentiment analysis using an emotion engine

[1195] The server retrieves the stored ideas and performs sentiment analysis using an emotion engine. For example, it uses the Google Cloud Natural Language API to detect the emotion "joy" from the idea "He is a brave warrior and is looking for a magic sword." The analysis results are stored in a database.

[1196] 4. Collecting and Summarizing Ideas

[1197] The server collects all ideas and their sentiment analysis results from the database, and uses a summarization program (e.g., BERT model, GPT model) to extract key parts from these ideas and generate a concise narrative that reflects sentiment.

[1198] 5. Conversion to the specified format

[1199] The generated summary story is converted into a specified format (text, video, etc.) using a format output program. The story presentation is optimized, taking into account the results of sentiment analysis. For example, it may be formatted as follows:

[1200] Story Title: The Adventure of the Hero and the Wizard

[1201] He is a brave warrior searching for a magic sword (Joy), she is a wise wizard who sets out on a journey to help him (Surprise), and together they fight a giant dragon and save their village (Sadness).

[1202] 6. Story output and display on the terminal

[1203] The converted story is sent from the server to each user's device and displayed in a viewable format. Users can check and enjoy the generated story on their own devices.

[1204] Specific examples

[1205] Specific prompts for users to submit their ideas include:

[1206] User 1 (Sentiment Analysis: Joy): "He is a brave warrior and is looking for a magic sword."

[1207] User 2 (Sentiment Analysis: Surprise): "She was a wise wizard who set out on a journey to help the warrior."

[1208] User 3 (Sentiment Analysis: Sadness): "They fight a giant dragon and save the village."

[1209] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1210] Step 1:

[1211] User idea entry and submission

[1212] A user inputs his / her idea into the device using a dedicated input form or application. For example, the user inputs "He is a brave warrior and is looking for a magic sword" in text format. Then, the user taps the send button to send the idea from the device to the server. The input data is the idea in text format, and the output is the raw idea data received by the server.

[1213] Step 2:

[1214] Server receives and stores ideas

[1215] The server receives idea data sent by users. The received data is assigned a unique ID and a timestamp and stored in a database. The input is the text idea sent by the user, and the output is structured data stored in the database.

[1216] Step 3:

[1217] Emotion analysis by the server's emotion engine

[1218] The server retrieves the saved idea data and performs sentiment analysis using an emotion engine. For example, the emotion engine uses the Google Cloud Natural Language API to determine the emotion of "joy" from the text "He is a brave warrior and is looking for a magic sword." This emotion data is then saved back to the database. The input is the saved idea data, and the output is data containing the sentiment analysis results.

[1219] Step 4:

[1220] Server idea collection and summary

[1221] The server collects all ideas and their sentiment analysis data from the database. Then, it uses a summarization program to extract the important parts and generate a concise story. For example, it uses the BERT model as a summarization program to summarize a story based on sentences like "He is a brave warrior who is searching for a magic sword" and "She is a wise wizard who sets out on a journey to help the warrior." The input is idea data including sentiment analysis results, and the output is a summarized story.

[1222] Step 5:

[1223] Conversion to specified format by server

[1224] The generated summary story is converted into a specified format (e.g., text format) using a format output program. The results of sentiment analysis are also taken into consideration during this process. For example, the converted story might look like this: "A brave warrior and a wise wizard fight a giant dragon with great surprise, and save the village in grief." The input is the summarized story data, and the output is the story converted into the specified format.

[1225] Step 6:

[1226] Story output and display on terminal

[1227] The final output story is sent from the server to the user's device. The device receives it and displays it in a viewable format for the user. For example, the story may be displayed on a smartphone screen. The user can read and enjoy it. The input is the story data sent from the server, and the output is the story displayed on the device.

[1228] (Application example 2)

[1229] 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."

[1230] Conventional story generation systems were unable to analyze emotions from user-input ideas and generate summaries that reflected those emotions. Furthermore, they lacked the ability to convert and output summaries generated based on the analyzed emotions into various formats, limiting the quality of the stories provided to users. This prevented users from enjoying stories with emotional depth, limiting their entertainment experience.

[1231] 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 means for accepting multiple inputs, means for analyzing emotions based on the multiple inputs, means for generating a summary including the analyzed emotions, means for converting the summarized content into a specified format, and means for outputting the converted content. This makes it possible to emotionally analyze ideas input by a user and automatically generate and output stories in various formats that reflect the emotions.

[1232] "Multiple inputs" refers to multiple ideas or pieces of information provided by a user, including various forms such as text, audio, and images.

[1233] "Sentiment analysis methods" refers to natural language processing techniques and algorithms used to identify and classify the emotions contained in input ideas and information.

[1234] "Means for generating summaries" refers to algorithms that take into account the analyzed sentiment, extract key parts, and automatically generate concise stories or content.

[1235] The "means for converting into a specified format" refers to a format conversion technology for converting the generated summary content into a pre-specified format (for example, text, audio, video, etc.).

[1236] "Means for outputting" refers to the system or protocol for transmitting the content in the final converted format to a user terminal so that it can be displayed or played back.

[1237] "Server" refers to a central processing unit for receiving input from users, performing sentiment analysis, summary generation and format conversion, and outputting the final content.

[1238] In this invention, a server executes a series of processes: collecting user ideas, analyzing their emotions, summarizing them, converting them into a specified format, and finally outputting them. Specifically, users input their ideas using a smartphone or head-mounted display (HMD) and send them to the server. The server analyzes the received ideas, generates a story based on the emotional data, converts them into various formats such as text, audio, and video, and outputs them to the user's device. The hardware and software used and their roles are explained below.

[1239] Hardware

[1240] Smartphone: A device that allows users to input ideas, allowing voice and text input, and communicating with a server via the Internet.

[1241] Head-mounted display (HMD): A device for visually experiencing a story in virtual reality (VR). It has the function of displaying ideas entered by the user in a VR space.

[1242] Server: As a central processing unit, it receives input from users and performs sentiment analysis, summary generation, format conversion, and final output.

[1243] software

[1244] Azure Text Analytics API: An API that provides natural language processing technology for sentiment analysis, extracting sentiment data based on user ideas.

[1245] Python script: A program to collect ideas and generate summaries based on sentiment analysis, leveraging NLP techniques to extract key points and create a concise narrative.

[1246] FFmpeg library: A library for converting the generated summaries into video format, with the ability to embed text information into video frames.

[1247] Unity Engine: A 3D engine for displaying stories in virtual reality (VR) spaces, providing a visually and audio-rich experience.

[1248] A natural language description of the process

[1249] 1. User input and submission:

[1250] Users use their smartphones or HMDs to input their ideas by voice or text. For example, a user might input the idea "A brave warrior is searching for a magic sword" into their smartphone, which is then immediately sent to the server.

[1251] 2. Emotion analysis:

[1252] The server uses the Azure Text Analytics API to perform sentiment analysis on the received ideas, and the sentiment data (happiness, surprise, sadness, etc.) is stored in a database along with the analysis results using a Python script.

[1253] 3. Summary generation:

[1254] Based on multiple ideas and their sentiment data stored on the server, the Python script uses NLP techniques to extract key parts and create a sentiment-based summary, such as "A brave warrior is searching for a magic sword (joy)."

[1255] 4. Format conversion:

[1256] The resulting summary is then converted to the specified format using the FFmpeg library. In the video format example, the text information is embedded into the video frames for visual display.

[1257] 5. Final output:

[1258] The stories in the specified format are displayed on an HMD using the Unity engine or made viewable on a smartphone app, allowing users to experience the generated stories in real time.

[1259] Specific examples

[1260] User A inputs "A brave warrior searches for a magic sword" into their smartphone, while User B inputs "A wise wizard goes on an adventure." These ideas are sent to the server, which performs sentiment analysis and generates a story: "A brave warrior searches for a magic sword and fights a giant dragon alongside the wise wizard." This story is displayed as video or text on the HMD or smartphone, depending on the presentation format.

[1261] Example prompt sentence:

[1262] "A brave warrior seeks a magic sword"

[1263] "A clever wizard goes on an adventure"

[1264] "A giant dragon attacks the village"

[1265] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1266] Step 1:

[1267] Users use a smartphone or head-mounted display (HMD) to input their ideas using text or voice. For example, they input a specific idea such as "A brave warrior is searching for a magic sword." The input idea is instantly sent to the server via the Internet. Input = user's idea (text or voice), output = idea data sent to the server.

[1268] Step 2:

[1269] The server stores the received ideas in a database. At this time, the attribute information of the idea (user ID, input format, etc.) is also recorded. Input = submitted idea data and its attribute information, Output = idea stored in the database.

[1270] Step 3:

[1271] The server uses the Azure Text Analytics API to perform sentiment analysis on the stored ideas. This process uses natural language processing technology to identify the emotions (happiness, sadness, surprise, etc.) contained in each idea and output them as emotional data. Input = ideas stored in the database, output = analyzed emotional data.

[1272] Step 4:

[1273] The server uses a Python script to generate a summary of the idea based on the results of the sentiment analysis. It uses NLP (Natural Language Processing) technology to extract key parts and automatically generate a concise story that reflects the sentiment. Input: analyzed sentiment data and original idea. Output: summarized story.

[1274] Step 5:

[1275] The server uses the FFmpeg library to convert the summarized story into the specified format (text, audio, video, etc.). For example, in video format, the summarized text is embedded into the video frames. Input = summarized story, output = content in the specified format (e.g. video file).

[1276] Step 6:

[1277] The server sends the content in the generated format to the user's device. The user can view and experience the generated story through their smartphone or HMD. Input = content in the specified format, Output = final content displayed on the user's device.

[1278] 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.

[1279] 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.

[1280] 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.

[1281] 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.

[1282] 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.

[1283] 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.

[1284] 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).

[1285] 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.

[1286] 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."

[1287] 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.

[1288] 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).

[1289] 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.

[1290] 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.

[1291] 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.

[1292] 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.

[1293] 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.

[1294] 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.

[1295] 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.

[1296] 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.

[1297] 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.

[1298] 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.

[1299] The following is further disclosed regarding the above embodiment.

[1300] (Claim 1)

[1301] a means for accepting a plurality of inputs;

[1302] means for summarizing the plurality of inputs;

[1303] means for converting the summarized content into a specified format;

[1304] means for outputting the converted content;

[1305] A system including:

[1306] (Claim 2)

[1307] The system of claim 1 , further comprising: means for accepting the plurality of inputs anonymously.

[1308] (Claim 3)

[1309] 10. The system of claim 1, wherein the specified format is text, video, or a combination thereof.

[1310] "Example 1"

[1311] (Claim 1)

[1312] a means for accepting a plurality of inputs;

[1313] means for storing said plurality of inputs in a database;

[1314] means for using a generative AI model to summarize the plurality of inputs;

[1315] means for converting the summarized content into a specified format;

[1316] means for outputting the converted content;

[1317] A system including:

[1318] (Claim 2)

[1319] 10. The system of claim 1, further comprising means for accepting the plurality of inputs anonymously.

[1320] (Claim 3)

[1321] 10. The system of claim 1, wherein the specified format is text, video, or a combination thereof.

[1322] "Application Example 1"

[1323] (Claim 1)

[1324] a means for accepting a plurality of inputs;

[1325] means for summarizing the plurality of inputs;

[1326] means for converting the summarized content into a specified format;

[1327] means for outputting the converted content;

[1328] means for analyzing the plurality of inputs using a generative AI model to generate a narrative;

[1329] means for displaying the generated story in a form that can be viewed by a user;

[1330] A system including:

[1331] (Claim 2)

[1332] The system of claim 1 , further comprising: means for accepting the plurality of inputs anonymously.

[1333] (Claim 3)

[1334] 10. The system of claim 1, wherein the specified format is text, video, or a combination thereof.

[1335] "Example 2: Combining Emotion Engines"

[1336] (Claim 1)

[1337] a means for accepting a plurality of inputs;

[1338] means for storing said plurality of inputs;

[1339] means for analyzing the stored input to determine emotion;

[1340] means for summarizing the parsed input;

[1341] means for converting the summarized content into a specified format;

[1342] means for outputting the converted content and emotion information in consideration of the converted content and emotion information;

[1343] A system including:

[1344] (Claim 2)

[1345] The system of claim 1 , further comprising: means for accepting the plurality of inputs anonymously.

[1346] (Claim 3)

[1347] 10. The system of claim 1, wherein the specified format is text, video, or a combination thereof.

[1348] "Application example 2 when combining emotion engines"

[1349] (Claim 1)

[1350] a means for accepting a plurality of inputs;

[1351] means for analyzing emotions based on the plurality of inputs;

[1352] means for generating a summary including the analyzed emotions;

[1353] means for converting the summarized content into a specified format;

[1354] means for outputting the converted content;

[1355] A system including:

[1356] (Claim 2)

[1357] The system of claim 1 , further comprising: means for accepting the plurality of inputs anonymously.

[1358] (Claim 3)

[1359] 10. The system of claim 1, wherein the specified format is text, audio, video, or a combination thereof. [Explanation of symbols]

[1360] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for accepting a plurality of inputs; means for summarizing the plurality of inputs; means for converting the summarized content into a specified format; means for outputting the converted content; A system including:

2. The system of claim 1 , further comprising: means for accepting the plurality of inputs anonymously.

3. The system of claim 1 , wherein the specified format is text, video, or a combination thereof.

Images