system

Abstract

Provide a system. [Solution] A means for inputting text information, image information, or a presentation file to explain the business content; A means for analyzing input character information and extracting key points; A means for analyzing input image information and identifying a structure; A means for selecting optimal characters and scenarios based on the extracted and identified information and generating explanatory materials in comic form; A means for allowing a user to make corrections to the generated comic-style explanatory material; A system including:

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] Explaining business processes and procedures efficiently and clearly to people who are unfamiliar with the details of the work is a difficult challenge. In particular, when explanations are given using only text and diagrams, there can be inconsistencies in the level of understanding depending on the recipient. This makes it time-consuming and labor-intensive for employees and managers to effectively explain their work to others. Additionally, current methods require cumbersome preparation of presentation materials, and creating explanatory materials in a visually easy-to-understand format, such as a comic book, increases the amount of work required. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means. This system includes: a means for inputting text information, image information, or a presentation file to explain business operations; a means for analyzing the input text information and extracting key points; a means for analyzing the input image information and identifying a structure; a means for selecting optimal characters and scenarios based on the extracted and identified information and generating a comic-style explanatory material; and a means for allowing the user to make corrections to the generated comic-style explanatory material. The system also includes a means for automatically generating a comic layout based on the selected characters and scenario, and a means for outputting the generated comic-style explanatory material in PDF or image file format. This system allows complex business operations to be communicated visually in an easy-to-understand manner, simplifying the preparation of presentation materials.

[0006] "Textual information" refers to documents or text data related to business operations or processes, provided in electronic or physical form.

[0007] "Image information" refers to data including rough hand-drawn sketches, charts, illustrations, etc. that visually show the content of work.

[0008] A "presentation file" refers to a digital file created to explain information in the form of slides, typically created using presentation software.

[0009] "Analysis" refers to the process of using artificial intelligence and other technologies to interpret provided text and image information and identify important elements and structures.

[0010] "Key points" refer to particularly important steps or information elements in a business process.

[0011] "Characters" refers to personified people and character graphics used to convey information within manga.

[0012] "Scenario" refers to the storyline and dialogue used within the comic-style explanatory material.

[0013] "Comic-style explanatory materials" refer to explanatory materials written in a comic style to visually and intuitively convey business content and processes.

[0014] "Automatically generating" refers to using artificial intelligence or a computer program to automatically generate output based on the required information.

[0015] "Layout" refers to the arrangement and composition of each element of a manga (characters, background, text). [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0024] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] A specific embodiment for carrying out the present invention will be described in detail below. This system includes means for inputting text information, image information, and presentation files for explaining business content, and means for analyzing this information. Furthermore, means for selecting characters and scenarios based on the analysis results and generating comic-style explanatory materials is provided. The generated comic-style explanatory materials can be edited by the user and output in PDF or image file format.

[0038] System Overview

[0039] The system operates as a web application. Users upload data related to their work through a dedicated interface. The server receives the data and analyzes it using artificial intelligence (AI) and natural language processing (NLP) models. Based on the analysis results, a comic-style explanatory document is automatically generated. Users can preview the generated document and make any necessary corrections. The final comic-style explanatory document can be downloaded as a PDF or image file.

[0040] Program processing

[0041] The program processing of the system will be specifically explained below.

[0042] Data entry and analysis

[0043] 1. Data entry method

[0044] The terminal displays an interface for users to input their business details: they can upload text information, rough sketches, or presentation files.

[0045] 2. Data analysis methods

[0046] The server receives the uploaded data, analyzes the text information using an NLP model to extract key points, and uses image recognition technology to identify the structure of the image information.

[0047] Manga generation means

[0048] 1. Character and scenario selection method

[0049] The server selects the most suitable characters and scenarios based on the analysis results, using pre-trained manga templates.

[0050] 2. Manga generation means

[0051] The server automatically generates a manga based on the selected characters and scenario. The generated manga is temporarily saved and displayed as a preview on the user interface.

[0052] User customization

[0053] 1. Customization methods

[0054] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[0055] Final output and saving

[0056] 1. Output Method

[0057] After the revisions are complete, the server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[0058] 2. Preservation means

[0059] The server stores the generated comics and related data, allowing users to re-edit them later.

[0060] Specific examples

[0061] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes the rough sketch and identifies each step in the process. It then selects a product development scenario and appropriate characters, and automatically generates a comic-style explanatory document. The user can review the document and make adjustments, such as changing the line "prototype testing" to "quality testing." Finally, the document can be downloaded in PDF format and used for internal presentations.

[0062] As described above, the system of the present invention efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and provides a format that is easy for users to use.

[0063] The processing flow will be explained below.

[0064] Step 1:

[0065] The terminal displays an interface for the user to input business details, and the user can upload text information, rough sketches, or presentation files through this interface.

[0066] Step 2:

[0067] The server receives the uploaded data and temporarily stores it.

[0068] Step 3:

[0069] The server analyzes the received text using natural language processing (NLP) models to extract key points and important phrases, such as stages in a business process or important actions.

[0070] Step 4:

[0071] The server analyzes the received image information (rough sketch) using image recognition technology, identifies elements such as diagrams and characters, and determines their relationships.

[0072] Step 5:

[0073] The server selects the optimal characters and scenarios based on the results of NLP analysis and image recognition. This is done by referencing pre-trained manga templates. For example, a template related to a business flow is selected, and a scene in which a character performs a specific business action is created.

[0074] Step 6:

[0075] The server automatically generates a manga based on the selected characters and scenario. Each character performs appropriate actions and speaks lines in the designated stage. The background is also selected to match the scenario.

[0076] Step 7:

[0077] The server temporarily stores the generated comic and displays it as a preview on the user interface.

[0078] Step 8:

[0079] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[0080] Step 9:

[0081] The server updates the final comic book-style instruction material to reflect the modifications made by the user.

[0082] Step 10:

[0083] The server generates the updated and final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[0084] Step 11:

[0085] The server stores the generated comics and related data, allowing users to re-edit them later.

[0086] Example 1

[0087] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0088] Conventional systems for creating explanatory materials lack the means to visually and intuitively convey the content of work, and creating materials under specific conditions is often complex and time-consuming. There is a demand for systems that allow users to efficiently explain the content of work.

[0089] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0090] In this invention, the server includes means for inputting text information, image information, or a presentation file for explaining business content, means for analyzing the input text information and extracting key points, means for analyzing the input image information and identifying a structure, means for selecting optimal characters and scenarios based on the extracted and identified information and generating comic-style explanatory materials, means for allowing a user to make corrections to the generated comic-style explanatory materials, and means for saving the generated comic-style explanatory materials so that they can be re-edited later. This makes it possible to provide a system for efficiently generating comic-style explanatory materials for visually and intuitively conveying business content, and for allowing a user to easily modify and save them.

[0091] "Text information" is information expressed as sentences or text, and is a data format used to explain business content.

[0092] "Image information" is data provided as a visual representation, including photographs, illustrations, diagrams, and the like.

[0093] A "presentation file" is a slide-format file used to explain business operations, and is a document that includes images, text information, graphs, and the like.

[0094] An "input method" is the method or interface by which a user provides data to a system, typically a file upload function or an input form.

[0095] "Means for analysis" refers to the system functions for processing input data and extracting necessary information and patterns, and includes natural language processing and image recognition technology.

[0096] "Key points" are important elements or themes extracted from the analyzed textual and image information, and are central information for understanding and explaining the business content.

[0097] "Means for identifying structure" refers to techniques or methods for analyzing input image information and identifying components and relationships.

[0098] "Characters" are characters or characters that appear in comic-style explanatory materials, and are elements with specific roles and personalities.

[0099] A "scenario" is a plot or story that characters follow, a storyline that effectively communicates the contents of explanatory material.

[0100] "Means of generation" refers to the functions and processes for creating explanatory materials in comic format based on input data and analysis results.

[0101] "Means by which the user can make modifications" refers to an interface or tool that allows the user to make changes or adjustments to the generated comic-style explanatory material.

[0102] "Means for saving" refers to a system function that allows the generated comic-style explanatory materials and related data to be retained and made available for reuse and re-editing at a later date.

[0103] "Means for enabling re-editing" refers to a function or method for making previously generated or saved explanatory material editable again.

[0104] Specific embodiments for carrying out the invention will be described in detail below.

[0105] System Overview

[0106] The system operates as a web application. Users upload data related to their work through a dedicated interface. The server receives the data and analyzes it using artificial intelligence (AI) and natural language processing (NLP) models. Based on the analysis results, a comic-style explanatory document is automatically generated. Users can preview the generated document and make any necessary corrections. The final comic-style explanatory document can be downloaded as a PDF or image file.

[0107] Data entry and analysis

[0108] Users use their devices to upload text information, image information, or presentation files to explain their work. The devices provide an interface to the users and send the input data to the server. The server then analyzes the text information using an NLP model (e.g., GPT-4 (registered trademark) or BERT) to extract key points. For image information, the server uses image recognition technology (e.g., Tesseract or OpenCV) to identify its structure.

[0109] manga generation

[0110] The server selects the optimal characters and scenario based on the analysis results. It uses pre-trained manga templates and character libraries (e.g., DCGAN, StyleGAN). The server then creates an automatically generated manga based on the selected characters and scenario. This may involve using software such as Unity or Unreal Engine. The generated manga is temporarily saved and displayed as a preview in the user interface.

[0111] User customization

[0112] Users can preview the video on their devices and make any necessary edits. The interface supports editing dialogue, changing character expressions, adjusting backgrounds, etc. Users can make changes using text boxes and drop-down menus.

[0113] Final output and saving

[0114] After the user has completed the revisions, the server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link. The server also provides a means for storing the generated comic and related data so that the user can re-edit it later. This may involve the use of a database (e.g., MySQL (registered trademark), MongoDB).

[0115] Specific examples

[0116] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes the rough sketch and identifies each step in the process. It then selects a product development scenario and appropriate characters, and automatically generates a comic-style explanatory document. The user can review the document and make adjustments, such as changing the line "prototype testing" to "quality testing." Finally, the document can be downloaded in PDF format and used for internal presentations.

[0117] Prompt Sentence Examples

[0118] Business: New product development process

[0119] Rough sketch: Attachment 1.png

[0120] Analysis purpose: Generate explanatory materials in comic format

[0121] As described above, the system of the present invention efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and provides a format that users can easily modify and save.

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

[0123] Step 1:

[0124] The user uploads text information, image information, or a presentation file from the terminal to explain the details of the work.

[0125] Specific actions: A user uses the web application interface to enter text information into an input form and to select and upload the required files using the file upload button.

[0126] Input: Text, images, or presentation files entered by the user.

[0127] Output: Uploaded data is sent to the server.

[0128] Step 2:

[0129] The server receives the uploaded text information and analyzes it using a natural language processing (NLP) model.

[0130] Specific operation: The server tokenizes the text information and extracts key points using an NLP model (e.g., GPT-4 or BERT).

[0131] Input: Textual information received from the user.

[0132] Output: Analysis results with extracted key points, e.g., key phrases such as "project launch," "product design," and "market research."

[0133] Step 3:

[0134] The server receives the uploaded image information and analyzes it using image recognition technology.

[0135] What happens: The server reads the image and uses OCR technology (e.g., Tesseract or OpenCV) to extract text from the image and, if necessary, identify structures within the image.

[0136] Input: Image information received from the user.

[0137] Output: Extracted text and identified structural information from the image.

[0138] Step 4:

[0139] The server selects the optimal characters and scenarios based on the analysis results.

[0140] Specific operation: The server refers to pre-trained manga templates and character libraries (e.g., DCGAN, StyleGAN) and selects characters and scenarios appropriate for the task.

[0141] Input: Keypoints, structural information from images.

[0142] Output: Selected characters and scenarios.

[0143] Step 5:

[0144] The server automatically generates a manga based on the selected characters and scenario.

[0145] Specific operation: The server generates a scene by arranging the position, facial expression, and lines of each character based on the selected template. This process may use software such as Unity or Unreal Engine.

[0146] Input: Selected characters and scenario.

[0147] Output: Each page of the automatically generated comic.

[0148] Step 6:

[0149] The terminal provides the user with a preview of the generated comic.

[0150] Specific operation: The server temporarily saves the generated manga and displays it as a preview in the user interface.

[0151] Input: Each page of the automatically generated comic.

[0152] Output: Preview data to the user.

[0153] Step 7:

[0154] The user checks the preview and makes any necessary corrections.

[0155] Specific operations: The user can modify dialogue, change character expressions, adjust the background, etc. through the interface.

[0156] Input: Preview data.

[0157] Output: The final comic, as modified by the user.

[0158] Step 8:

[0159] The server saves the comic-style explanatory material after the user has completed the edits and outputs it in PDF or image file format.

[0160] What it does: The server saves the final manga, converts it to PDF or JPEG format, provides a download link to the user, and stores it in a database so that it can be re-edited later.

[0161] Input: The final comic, as revised by the user.

[0162] Output: Final manga in PDF or image file format, re-editable saved data.

[0163] (Application example 1)

[0164] 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."

[0165] Modern brick-and-mortar stores offer a wide variety of products and services, and it is important to effectively communicate their features and how to use them to customers. However, traditional methods, such as using text and diagrams, can be difficult to understand. Furthermore, the quality of explanations can vary depending on the store staff's explanation skills and time constraints. Therefore, a new method is needed that can quickly provide customers with visually easy-to-understand, consistent information.

[0166] 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.

[0167] In this invention, the server includes means for inputting text information, image information, or a presentation file to explain business operations, means for analyzing the input text information and extracting key points, means for analyzing the input image information and identifying the structure, means for inputting product information and service details for a physical store and displaying them in a comic format, and means for allowing the user to make corrections to the generated comic-format explanatory materials. This allows product explanations and service guides for physical stores to be provided in a visually easy-to-understand comic format, thereby enabling effective information transmission to customers.

[0168] "Business content" is information about the specific tasks and activities performed by a company or organization.

[0169] "Character information" is text data such as sentences and words.

[0170] "Image information" refers to visual data such as photographs and illustrations.

[0171] A "presentation file" is a document format that organizes and visually presents information in slide format.

[0172] "Input means" refers to devices or interfaces that input data such as text information, image information, and presentation files into the system.

[0173] "Means of analysis" refers to software or algorithms that break down and analyze input information to extract key points.

[0174] A "means for extracting key points" is a method or device for identifying the main information or content from input text information.

[0175] "Means for identifying structure" refers to technology or devices that recognize the elements and arrangement of input image information.

[0176] "Means for selecting optimal characters and scenarios" refers to techniques and methods for determining appropriate characters and story flow based on the analysis results.

[0177] "Means for generating explanatory materials in comic format" refers to technology or software that automatically generates the layout and content of a comic based on selected characters and a scenario.

[0178] "Means by which a user can make corrections to the generated comic-style explanatory material" refers to an interface or editing tool that allows a user to check the content of the generated comic and make any necessary changes.

[0179] A "brick and mortar store" is a store that has a physical location and where customers can visit in person to purchase goods or services.

[0180] "Product information" means data and descriptions about a product's characteristics, uses, benefits, etc.

[0181] "Service details" is information about the details of various services provided by the store and how to use them.

[0182] "Means for displaying in comic format" refers to technology or devices that display product information or service content in the form of comics that are visually easy to understand.

[0183] A specific embodiment of the present invention will be described in detail below. The present invention is a system for providing product explanations and service guides for brick-and-mortar stores in a visually easy-to-understand comic format.

[0184] System configuration

[0185] This system operates primarily using devices such as smartphones or tablets and a cloud server. Users install a dedicated application on their device and use it to input business details, product information, and service details. The input information is sent to the cloud server, where it is analyzed and processed to generate the manga.

[0186] Hardware and software used:

[0187] Hardware: Smartphone, tablet (iOS or ANDROID (registered trademark))

[0188] Software: Dedicated applications, cloud servers, artificial intelligence (AI) models, natural language processing (NLP) models

[0189] The program proceeds as follows:

[0190] 1. Data entry method:

[0191] Users start a dedicated application and input product information and service details. Input methods include text input, image upload, and presentation file upload.

[0192] 2. Data analysis methods:

[0193] The cloud server receives the uploaded data and uses NLP models to analyze the text information and extract key points, while image recognition technology is used to identify the structure of the image information.

[0194] 3. Manga generation method:

[0195] The server selects the most suitable characters and scenario based on the analysis results and automatically generates explanatory materials in the form of a manga. The generated manga is temporarily saved and displayed as a preview on the user interface.

[0196] 4. Customization methods:

[0197] Users can use the interface to check the preview and make any necessary edits, such as modifying dialogue, changing character expressions, or adjusting the background.

[0198] 5. Output Method:

[0199] Finally, the revised comic-style explanatory material is generated as a PDF or image file, and a download link is provided to the user.

[0200] 6. Preservation means:

[0201] The cloud server stores the generated comics and related data, allowing users to re-edit them later.

[0202] Specific examples

[0203] For example, consider a scenario in which a user is explaining to a customer how to use a newly arrived electronic device. The user uploads a document containing the product's specifications and usage examples to the app. The app analyzes this using NLP and image recognition, selects characters and scenarios appropriate for each specification and usage example, and automatically generates a manga. The user then looks at the generated manga, fine-tunes the dialogue and facial expressions, and downloads the final version as a PDF to present to the customer. In this way, explanations can be provided in a visually easy-to-understand manner.

[0204] Example prompt sentence:

[0205] Documentation on how to use your new tablet:

[0206] 1. How to use the touch screen

[0207] 2. Installing and Using the App

[0208] 3. Internet connection settings

[0209] As described above, the system of the present invention provides product explanations and service guides in physical stores in a visually easy-to-understand comic format, thereby improving the quality of explanations given to customers.

[0210] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0211] Step 1:

[0212] Data entry method:

[0213] Users launch a dedicated application on their smartphone or tablet and enter product information and service details. Specifically, they can enter text, upload images, and upload presentation files. Input data includes product features, usage instructions, and benefits.

[0214] input:

[0215] Product information (text, images, presentation files)

[0216] output:

[0217] Data transfer to cloud server

[0218] Step 2:

[0219] Data analysis methods:

[0220] The cloud server analyzes the received data. First, it analyzes the text information using a natural language processing (NLP) model to extract key points. Next, it analyzes the image information using image recognition technology to identify its structure.

[0221] input:

[0222] Product information received in step 1

[0223] output:

[0224] Keypoint Extraction (Text)

[0225] Identifying image structures

[0226] Specific behavior:

[0227] It uses NLP models to analyze the content of the input text and extract key information.

[0228] Image recognition software is used to analyze the structure of uploaded images and identify key elements.

[0229] Step 3:

[0230] Manga generation means:

[0231] The server selects the optimal characters and scenario based on the analysis results obtained in step 2. Using an artificial intelligence (AI) model, it automatically selects the optimal layout from pre-trained manga templates and generates explanatory materials in manga format.

[0232] input:

[0233] Keypoint extraction results

[0234] Image structure analysis results

[0235] output:

[0236] Comic book format explanatory material (for preview)

[0237] Specific behavior:

[0238] Using an AI model, the optimal characters and scenarios are selected from the analysis results.

[0239] Automatically create a manga layout based on selected elements.

[0240] Step 4:

[0241] Customization methods:

[0242] The generated manga-style explanatory material is displayed as a preview in the user interface. The user can check this preview and make any necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[0243] input:

[0244] Comic book format explanatory material (for preview)

[0245] output:

[0246] Final version with user modifications

[0247] Specific behavior:

[0248] Through the user interface, the user edits each part of the manga (dialogue, characters, background, etc.).

[0249] Edits are reflected in the preview in real time.

[0250] Step 5:

[0251] Output Method:

[0252] After the edits are complete, the cloud server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[0253] input:

[0254] Final version with user modifications

[0255] output:

[0256] Final version in PDF or image file format

[0257] Specific behavior:

[0258] The server saves and converts the final manga format description material and generates a download link.

[0259] Step 6:

[0260] Storage method:

[0261] The cloud server stores the generated comics and related data, allowing users to re-edit them later.

[0262] input:

[0263] Final version in PDF or image file format

[0264] output:

[0265] Saved manga data and related information

[0266] Specific behavior:

[0267] The server stores the generated explanatory material and related data in a database.

[0268] Data is managed and provided in a format that allows for re-editing.

[0269] 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.

[0270] A specific embodiment for carrying out the present invention will be described in detail below. This system includes means for inputting text information, image information, and presentation files for explaining business content, and means for analyzing this information. Furthermore, means for selecting characters and scenarios based on the analysis results and generating comic-style explanatory materials is provided. The generated comic-style explanatory materials can be edited by the user and output in PDF or image file format.

[0271] The system of the present invention further incorporates an emotion engine that recognizes the user's emotions. Based on the user's emotions recognized by the emotion engine, the selection of characters and scenarios can be automatically adjusted. The dialogue and character expressions of the cartoon are also adjusted to reflect the user's emotional state.

[0272] System Overview

[0273] The system operates as a web application. Users upload data related to their work through a dedicated interface. The server receives this data and analyzes it using artificial intelligence (AI) and natural language processing (NLP) models. Based on the analysis results, explanatory materials in comic form are automatically generated. An emotion engine then analyzes the user's emotions and adjusts the content of the generated comic before displaying it. Users can preview the generated materials and make any necessary corrections. The final explanatory materials in comic form can be downloaded as a PDF or image file.

[0274] Program processing

[0275] The program processing of the system will be specifically explained below.

[0276] Data entry and analysis

[0277] 1. Data entry method

[0278] The terminal displays an interface for users to input their business details, such as text information, rough sketches, or presentation files, and upload them through this interface.

[0279] 2. Data analysis methods

[0280] The server receives the uploaded data and temporarily stores it.

[0281] The server analyzes the received text information using a natural language processing (NLP) model to extract key points and important phrases, such as stages such as "planning," "implementation," and "evaluation."

[0282] The server analyzes the received image information (rough sketch) using image recognition technology, identifies elements such as diagrams and characters, and determines their relationships.

[0283] Manga generation means

[0284] 1. Character and scenario selection method

[0285] The server then selects the most suitable characters and scenario based on the analysis results, referencing pre-trained manga templates. For example, a template explaining the progress of a project may be selected.

[0286] 2. Emotion Engine

[0287] The device analyzes the user's facial expressions and tone of voice to collect emotional data and send it to the server. The server then uses an emotion engine to analyze this data and determine the user's emotional state. For example, if the user is nervous, the server will set a relaxed expression and dialogue for the character accordingly.

[0288] 3. Manga generation means

[0289] The server automatically generates a cartoon based on the selected characters and scenario. The generated cartoon is adjusted based on the results of the emotion engine. For example, if the user has a happy expression, a smiling face is added to the character.

[0290] User customization

[0291] 1. Customization methods

[0292] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[0293] Final output and saving

[0294] 1. Output Method

[0295] After the revisions are complete, the server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[0296] 2. Preservation means

[0297] The server stores the generated comics and related data, allowing users to re-edit them later.

[0298] Specific examples

[0299] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes this rough sketch and identifies each step in the process. It then selects a product development scenario and an appropriate character, and automatically generates a comic-style explanatory document. The emotion engine analyzes the user's emotions and adds a character with a relaxed expression and encouraging words to a nervous user. The user can review this document and, if necessary, change "prototype testing" to "quality testing," and finally download it in PDF format for use in internal presentations.

[0300] As described above, the system of the present invention efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and by adjusting them according to the user's emotions, it provides a form of presentation that enhances its effectiveness.

[0301] The processing flow will be explained below.

[0302] Step 1:

[0303] The terminal displays an interface for the user to input business details, and the user can upload text information, rough sketches, or presentation files through this interface.

[0304] Step 2:

[0305] The server receives the uploaded data and temporarily stores it.

[0306] Step 3:

[0307] The server analyzes the received text using a natural language processing (NLP) model to extract key points and important phrases, such as major stages such as "new product planning" and "market research."

[0308] Step 4:

[0309] The server uses image recognition technology to analyze the received image information (rough sketches), identify elements such as diagrams and characters, and determine their relationships. For example, it recognizes each step in a flow diagram as a box or arrow.

[0310] Step 5:

[0311] The server selects the most suitable characters and scenarios based on the results of NLP analysis and image recognition. This is done by referencing pre-trained manga templates. For example, a scenario in which the "development team leader" "presents a product idea" may be selected.

[0312] Step 6:

[0313] The device analyzes the user's facial expressions and tone of voice in real time to collect emotional data, which is then sent to a server.

[0314] Step 7:

[0315] The server uses an emotion engine to analyze the user's emotion data and identify the emotion the user is currently feeling. For example, if the user is nervous, the server analyzes the emotion data.

[0316] Step 8:

[0317] The server then adjusts the character's facial expression and dialogue based on the recognized emotion data. For example, if the user is nervous, a character with a relaxed expression and encouraging dialogue will be placed.

[0318] Step 9:

[0319] The server automatically generates a manga based on the selected characters and the adjusted scenario. The generated manga is temporarily saved and displayed as a preview on the user interface.

[0320] Step 10:

[0321] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[0322] Step 11:

[0323] The server updates the final comic book-style instruction material to reflect the modifications made by the user.

[0324] Step 12:

[0325] The server generates the updated and final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[0326] Step 13:

[0327] The server stores the generated comics and related data, allowing users to re-edit them later.

[0328] Example 2

[0329] 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."

[0330] When explaining business operations, it is important to convey information visually, but conventional methods require time and effort. It is also difficult to create materials that take the user's emotions into account, limiting the effectiveness of communication. Another issue is the difficulty of re-editing or customizing materials once they have been created.

[0331] 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 a means for inputting data for explaining business operations, a means for temporarily saving the input data, a means for analyzing text information and extracting key points, a means for analyzing image information and identifying a structure, a means for selecting optimal characters and scenarios based on the extracted and identified information and generating a comic-style explanatory material, a means for analyzing a user's emotions regarding the generated comic-style explanatory material and adjusting the content, a means for allowing a user to make corrections to the generated comic-style explanatory material, and a means for saving the generated comic-style explanatory material and enabling re-editing. This allows for efficient creation of materials for explaining business operations visually and intuitively and allows adjustments based on the user's emotions. Furthermore, re-editing and customization can be easily performed, thereby enhancing the effectiveness of communication.

[0332] "Means for inputting data" refers to an interface that allows a user to provide text information, image information, or a presentation file to explain the content of a business to the system.

[0333] "Means for temporarily storing input data" refers to a storage or memory area for temporarily storing user-provided data before analysis or processing.

[0334] "Means for analyzing textual information and extracting key points" refers to a program that uses natural language processing technology to analyze textual information and identify important phrases and keywords.

[0335] "Means for analyzing image information and identifying its structure" refers to a program that uses computer vision technology to analyze image information and identify the elements of diagrams and characters and their relationships.

[0336] "Means for selecting optimal characters and scenarios" refers to an algorithm for selecting optimal characters and scenarios from pre-trained templates and databases based on the analyzed information.

[0337] "Means for generating explanatory materials in comic format" refers to programs and tools for automatically creating materials in comic format based on selected characters and scenarios.

[0338] "Means for analyzing user emotions and adjusting content" refers to an algorithm that analyzes the user's facial expressions and tone of voice to determine the user's emotions and adjust the manga characters and scenario accordingly.

[0339] "Means for making edits to the generated comic-style explanatory materials" refers to an interface that allows users to edit and adjust the content of the generated comic (such as lines, character expressions, backgrounds, etc.).

[0340] "Means for saving the generated comic-format explanatory materials and enabling them to be re-edited" refers to a system that allows comic-format materials to be saved in cloud storage or a database once they have been generated, allowing them to be re-edited or updated later.

[0341] "Means to enable output in PDF or image file format" refers to the function for outputting the final comic-format explanatory materials as a PDF file or image file (JPEG, PNG, etc.).

[0342] The system for implementing this invention operates as a web application. This system is composed of a user, a terminal, and a server. The specific operation of each element will be described in detail below.

[0343] System Overview

[0344] Users upload data related to their work through a dedicated interface, typically using a form or file upload function displayed on a web page. The server receives this data and temporarily stores it in cloud storage.

[0345] Data entry and analysis

[0346] Data Entry Method

[0347] The terminal displays an interface for users to input their business details, using which they can upload text information, rough sketches, or presentation files.

[0348] Data Analysis Methods

[0349] The server receives the uploaded data and temporarily stores it. This is done using cloud storage. The server then uses an NLP (natural language processing) model to analyze the text information. This model uses a Python NLP library (such as spacy or nltk). Through the analysis, key points and important phrases are extracted. For example, stages such as "planning," "implementation," and "evaluation" are identified.

[0350] The server analyzes the received image information (rough sketches) using image recognition technology. Specifically, it uses computer vision libraries (such as OpenCV or TENSORFLOW®) to identify elements such as diagrams and characters and determine their relationships.

[0351] Manga generation means

[0352] Character and scenario selection method

[0353] The server selects the most suitable characters and scenarios based on the analysis results. This selection is made by referring to pre-trained manga templates. These templates are trained by a generative AI model (e.g., GPT-4). For example, a template describing the progress of a project is selected.

[0354] Emotion Engine

[0355] The device uses a camera and microphone to collect data to analyze the user's facial expressions and tone of voice. The collected data is sent to a server. The server then analyzes the collected data using an emotion engine. For example, it uses a machine learning model (SVM or neural network) to classify the user's emotions. If the user is nervous, the character's facial expression and lines are set accordingly.

[0356] Manga generation means

[0357] The server automatically generates a comic based on the selected characters and scenario. This uses a generative AI model (such as DALL-E or MidJourney). The generated comic is adjusted based on the results of the emotion engine. For example, if the user has a happy expression, a smiling face is added to the character.

[0358] User customization

[0359] The device provides an interface for users to preview the generated manga and make any necessary edits. Specifically, it has drag-and-drop and text editing functions. Users can edit dialogue, change character expressions, adjust backgrounds, and more.

[0360] Final output and saving

[0361] Output Method

[0362] After the revisions are complete, the server generates the final comic-style explanatory material in PDF or image file format using a library (such as ReportLab or Pillow) and provides the user with a download link for the generated file.

[0363] Preservation means

[0364] The server saves the generated comics and related data. The data is stored in a database (e.g., PostgreSQL or MongoDB). This allows users to re-edit the data later and allows history management.

[0365] Specific examples

[0366] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes the rough sketch and identifies each step in the process. It then selects a product development scenario and an appropriate character, automatically generating a comic-style explanatory document. The emotion engine analyzes the user's emotions and adds a character with a relaxed expression and encouraging words to a nervous user. The user can review the document and, if necessary, change "prototype testing" to "quality testing," and finally download it as a PDF for use in internal presentations.

[0367] Examples of prompt statements

[0368] - "Please upload a rough sketch to create a comic-style document that explains the new product development process. Which stage is the most important in terms of trends?"

[0369] - "Enable the emotion engine and adjust the character's facial expressions. Tell us their current emotional state."

[0370] In this way, this system efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and by adjusting them according to the user's emotions, it enhances the effectiveness of presentations.

[0371] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0372] Step 1: Enter your data

[0373] The terminal displays an interface for the user to input data related to the business content. This interface includes a text input field, a rough sketch upload function, and a presentation file upload function. The input data can be text information, a rough sketch, or a presentation file. The input data can be provided by the user by direct input or file upload.

[0374] Step 2: Save your data

[0375] The terminal sends the data entered by the user to the server, which then temporarily stores the received data in cloud storage. For example, text information, image information (rough sketches), and presentation files are temporarily stored in the cloud storage.

[0376] Step 3: Analyzing the text

[0377] The server analyzes the temporarily stored text information using an NLP (natural language processing) model. In this process, Python NLP libraries (e.g., spacy, nltk) are used to extract key points and important phrases from the text information. As a result, important phrases such as "planning," "implementation," and "evaluation" are output.

[0378] Step 4: Analyze image information

[0379] The server analyzes the temporarily stored image information (rough sketches) using computer vision technology. This analysis uses libraries such as OpenCV and TensorFlow. The server identifies elements such as diagrams and characters from the rough sketches and determines their relationships. For example, the server identifies diagrams showing each stage of a project and determines their interrelationships.

[0380] Step 5: Character and scenario selection

[0381] The server selects the most suitable characters and scenarios based on key points and elements extracted from text and image information. This selection is performed by referring to pre-trained manga templates. For example, a template explaining the progress of a project may be selected.

[0382] Step 6: Sentiment Analysis

[0383] The device uses a camera and microphone to analyze the user's facial expressions and voice, and the collected emotional data is sent to a server.

[0384] The server analyzes the collected data using an emotion engine, which determines what emotions the user is feeling. For example, it can determine if the user is nervous. The results of the emotion analysis are output and used to adjust the character's facial expressions and dialogue.

[0385] Step 7: Generate the comic

[0386] The server automatically generates a manga based on the selected characters and scenario. This generation uses generative AI models such as DALL-E and MidJourney. The character's facial expressions and lines are adjusted based on the results of the emotion analysis. The generated manga is output, reflecting the results of the emotion analysis.

[0387] Step 8: Providing customizations

[0388] The device provides an interface for users to preview and modify the generated manga. This interface includes drag-and-drop and text editing functions. Users can modify dialogue, change character expressions, adjust backgrounds, and more. The modified and adjusted manga is output based on the user's input.

[0389] Step 9: Final Output

[0390] The server generates the final, edited version of the comic-style explanatory material in PDF or image file format using libraries such as ReportLab or Pillow. A download link for the generated file is provided to the user. The final output PDF or image file is provided to the user.

[0391] Step 10: Save your data

[0392] The server stores the generated manga and related data in a database (e.g., PostgreSQL, MongoDB), allowing users to re-edit the data later. The saved data is output in a format that allows for re-editing and history management.

[0393] Through the above processing steps, the system can efficiently generate comic-style materials that allow users to visually and intuitively communicate their work content, and can adjust the content according to the user's emotions.

[0394] (Application example 2)

[0395] 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."

[0396] Conventional work explanation materials generally use text or simple illustrations, making it difficult to present information in a visually understandable format. Furthermore, there is no means of providing appropriate information based on employees' emotions, which reduces the effectiveness of training and reduces work efficiency. To address these issues, the present invention aims to provide a system that explains work content in comic form and automatically adjusts based on emotions.

[0397] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0398] In this invention, the server includes means for inputting text information, image information, or a presentation file for explaining the content of work, means for analyzing the input text information and extracting key points, means for analyzing the input image information and identifying a structure, means for selecting optimal characters and scenarios based on the extracted and identified information and generating explanatory materials in comic form, means for automatically adjusting the characters and scenarios using an emotion engine that recognizes the user's emotions, and means for the user to make corrections to the generated explanatory materials in comic form. This makes it possible to provide information in a visually easy-to-understand format and provide optimal information according to the emotions of employees.

[0399] "Job Description" refers to detailed information about a specified task or process.

[0400] "Textual information" refers to data provided in text format.

[0401] "Image information" means data provided in a visual format, such as a photograph, illustration, or diagram.

[0402] A "presentation file" is a digital document created to explain business content in slide format.

[0403] The "emotion engine" is a system that analyzes a user's facial expressions, tone of voice, etc. to identify emotions.

[0404] "Means for extracting key points" is a function for identifying and extracting important information and phrases from input text information.

[0405] The "means for identifying structure" is a function for analyzing input image information and identifying its contents and relationships.

[0406] The "means for selecting characters and scenarios" is a function for selecting the most suitable characters and scenarios based on the extracted and identified information.

[0407] "Means for generating explanatory materials in comic format" is a function for creating materials that visually explain business details in comic format based on selected characters and scenarios.

[0408] "Means for automatic adjustment" is a function that automatically changes the content of characters and scenarios based on the user's emotions identified by the emotion engine.

[0409] "Means by which users can make modifications" is a function that provides an interface that allows users to freely edit and modify the generated comic-style explanatory material.

[0410] MODE FOR CARRYING OUT THE INVENTION

[0411] The following describes in detail a specific embodiment of the present invention. This system generates job explanation materials in cartoon format and automatically adjusts the content using an emotion engine. The entire system is designed to enable effective employee training and job explanations in factories using smart glasses.

[0412] Hardware and Software Configuration

[0413] Hardware:

[0414] Smart glasses (e.g., Microsoft® HoloLens®)

[0415] Server (Cloud or On-Premise)

[0416] software:

[0417] Natural Language Processing (NLP) models (e.g., Google® BERT)

[0418] Image recognition technology (e.g., OpenCV)

[0419] Sentiment analysis engine (e.g., Microsoft Azure (registered trademark) Emotion API)

[0420] Processing flow

[0421] 1. Data Entry

[0422] The terminal (smart glasses) provides an interface for inputting text information and presentation files related to business content. Users use the smart glasses to scan or upload data related to business materials.

[0423] 2. Data Analysis

[0424] The server analyzes the input text information using an NLP model to extract key business points, and also analyzes image information using image recognition technology to identify structure and important elements.

[0425] 3. Manga generation

[0426] The server selects the most suitable characters and scenario based on the key points and the identified structure, and generates explanatory materials in comic form. At the same time, an emotion analysis engine analyzes the user's facial expressions and tone of voice to set appropriate character expressions and lines.

[0427] 4. User Modifications

[0428] The generated comic-style explanatory materials can be previewed on the smart glasses and edited as needed, such as changing dialogue, adjusting character expressions, and adding backgrounds.

[0429] 5. Final output

[0430] Once the edits are complete, the document is generated as a PDF or image file and saved on the server. The final product can then be downloaded by the user via a download link.

[0431] Specific examples

[0432] For example, consider a case where an employee learning how to set up a new production line uses smart glasses to scan their work, and AI analyzes the content to generate a comic-style document. If the emotion engine detects that the user is nervous, it adds a character with a relaxed expression and reassuring words. The user can then review and edit the document, and finally save it as a PDF to use as training material.

[0433] Prompt Sentence Examples

[0434] "Scan the job description and generate a cartoon-style document, with characters that have relaxed expressions to make it easier for employees to understand."

[0435] By combining the above elements, the present invention makes it possible to quickly generate visually easy-to-understand work explanation materials and provide appropriate information according to the emotions of employees.

[0436] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0437] Step 1: Data entry

[0438] The terminal (smart glasses) provides an interface for inputting text information and presentation files related to work content. Users use the smart glasses to scan or upload data related to work materials. The input data is text-based work instructions and image-based presentation files.

[0439] Step 2: Data analysis

[0440] The server receives the text information sent from the device and analyzes it using a natural language processing (NLP) model (e.g., Google BERT). During the analysis, important steps and key points of the business (e.g., "work preparation," "equipment setup," and "quality check") are extracted. At the same time, image information is analyzed using image recognition technology (e.g., OpenCV) to identify structure and important elements (e.g., diagrams, equipment layout). These analysis results are used in the next step.

[0441] Step 3: Character and scenario selection

[0442] The server automatically selects the most suitable characters and scenarios based on the keypoints extracted and the structure identified in step 2. This selection uses pre-trained manga templates. For example, a scenario and its characters that explain the setup procedure for a manufacturing line are selected.

[0443] Step 4: Sentiment Analysis

[0444] The device analyzes the user's facial expressions and tone of voice using an emotion analysis engine (e.g., Microsoft Azure Emotion API) and sends the user's emotional data to the server. The emotional data (e.g., "tense," "relaxed," "excited") is used to adjust the content of the comic in a later step.

[0445] Step 5: Manga Generation

[0446] The server generates explanatory materials in comic form based on the characters and scenario selected in step 3. Furthermore, the character's facial expressions and lines are automatically adjusted based on the results of the emotion analysis engine. For example, if the user is nervous, a character with a relaxed expression and encouraging lines will be set.

[0447] Step 6: User Modifications

[0448] The generated comic-style explanatory materials are previewed on the device. The user can use smart glasses to check the preview and make any necessary corrections (e.g., changing dialogue, adjusting character expressions, adding backgrounds). The corrected data is then saved on the server.

[0449] Step 7: Final output

[0450] Once the edits are complete, the document is generated as a PDF or image file on the server, and a download link is provided to the user. The final product is then saved in the cloud, allowing for future editing.

[0451] Each step of this system presents work details in a visually easy-to-understand format, enabling appropriate information to be provided based on the employee's emotions.

[0452] 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.

[0453] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0454] 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.

[0455] [Second embodiment]

[0456] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0457] 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.

[0458] 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).

[0459] 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.

[0460] 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.

[0461] 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).

[0462] 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.

[0463] 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.

[0464] 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.

[0465] 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.

[0466] 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.

[0467] 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."

[0468] A specific embodiment for carrying out the present invention will be described in detail below. This system includes means for inputting text information, image information, and presentation files for explaining business content, and means for analyzing this information. Furthermore, means for selecting characters and scenarios based on the analysis results and generating comic-style explanatory materials is provided. The generated comic-style explanatory materials can be edited by the user and output in PDF or image file format.

[0469] System Overview

[0470] The system operates as a web application. Users upload data related to their work through a dedicated interface. The server receives the data and analyzes it using artificial intelligence (AI) and natural language processing (NLP) models. Based on the analysis results, a comic-style explanatory document is automatically generated. Users can preview the generated document and make any necessary corrections. The final comic-style explanatory document can be downloaded as a PDF or image file.

[0471] Program processing

[0472] The program processing of the system will be specifically explained below.

[0473] Data entry and analysis

[0474] 1. Data entry method

[0475] The terminal displays an interface for users to input their business details: they can upload text information, rough sketches, or presentation files.

[0476] 2. Data analysis methods

[0477] The server receives the uploaded data, analyzes the text information using an NLP model to extract key points, and uses image recognition technology to identify the structure of the image information.

[0478] Manga generation means

[0479] 1. Character and scenario selection method

[0480] The server selects the most suitable characters and scenarios based on the analysis results, using pre-trained manga templates.

[0481] 2. Manga generation means

[0482] The server automatically generates a manga based on the selected characters and scenario. The generated manga is temporarily saved and displayed as a preview on the user interface.

[0483] User customization

[0484] 1. Customization methods

[0485] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[0486] Final output and saving

[0487] 1. Output Method

[0488] After the revisions are complete, the server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[0489] 2. Preservation means

[0490] The server stores the generated comics and related data, allowing users to re-edit them later.

[0491] Specific examples

[0492] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes the rough sketch and identifies each step in the process. It then selects a product development scenario and appropriate characters, and automatically generates a comic-style explanatory document. The user can review the document and make adjustments, such as changing the line "prototype testing" to "quality testing." Finally, the document can be downloaded in PDF format and used for internal presentations.

[0493] As described above, the system of the present invention efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and provides a format that is easy for users to use.

[0494] The processing flow will be explained below.

[0495] Step 1:

[0496] The terminal displays an interface for the user to input business details, and the user can upload text information, rough sketches, or presentation files through this interface.

[0497] Step 2:

[0498] The server receives the uploaded data and temporarily stores it.

[0499] Step 3:

[0500] The server analyzes the received text using natural language processing (NLP) models to extract key points and important phrases, such as stages in a business process or important actions.

[0501] Step 4:

[0502] The server analyzes the received image information (rough sketch) using image recognition technology, identifies elements such as diagrams and characters, and determines their relationships.

[0503] Step 5:

[0504] The server selects the optimal characters and scenarios based on the results of NLP analysis and image recognition. This is done by referencing pre-trained manga templates. For example, a template related to a business flow is selected, and a scene in which a character performs a specific business action is created.

[0505] Step 6:

[0506] The server automatically generates a manga based on the selected characters and scenario. Each character performs appropriate actions and speaks lines in the designated stage. The background is also selected to match the scenario.

[0507] Step 7:

[0508] The server temporarily stores the generated comic and displays it as a preview on the user interface.

[0509] Step 8:

[0510] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[0511] Step 9:

[0512] The server updates the final comic book-style instruction material to reflect the modifications made by the user.

[0513] Step 10:

[0514] The server generates the updated and final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[0515] Step 11:

[0516] The server stores the generated comics and related data, allowing users to re-edit them later.

[0517] Example 1

[0518] 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."

[0519] Conventional systems for creating explanatory materials lack the means to visually and intuitively convey the content of work, and creating materials under specific conditions is often complex and time-consuming. There is a demand for systems that allow users to efficiently explain the content of work.

[0520] 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.

[0521] In this invention, the server includes means for inputting text information, image information, or a presentation file for explaining business content, means for analyzing the input text information and extracting key points, means for analyzing the input image information and identifying a structure, means for selecting optimal characters and scenarios based on the extracted and identified information and generating comic-style explanatory materials, means for allowing a user to make corrections to the generated comic-style explanatory materials, and means for saving the generated comic-style explanatory materials so that they can be re-edited later. This makes it possible to provide a system for efficiently generating comic-style explanatory materials for visually and intuitively conveying business content, and for allowing a user to easily modify and save them.

[0522] "Text information" is information expressed as sentences or text, and is a data format used to explain business content.

[0523] "Image information" is data provided as a visual representation, including photographs, illustrations, diagrams, and the like.

[0524] A "presentation file" is a slide-format file used to explain business operations, and is a document that includes images, text information, graphs, and the like.

[0525] An "input method" is the method or interface by which a user provides data to a system, typically a file upload function or an input form.

[0526] "Means for analysis" refers to the system functions for processing input data and extracting necessary information and patterns, and includes natural language processing and image recognition technology.

[0527] "Key points" are important elements or themes extracted from the analyzed textual and image information, and are central information for understanding and explaining the business content.

[0528] "Means for identifying structure" refers to techniques or methods for analyzing input image information and identifying components and relationships.

[0529] "Characters" are characters or characters that appear in comic-style explanatory materials, and are elements with specific roles and personalities.

[0530] A "scenario" is a plot or story that characters follow, a storyline that effectively communicates the contents of explanatory material.

[0531] "Means of generation" refers to the functions and processes for creating explanatory materials in comic format based on input data and analysis results.

[0532] "Means by which the user can make modifications" refers to an interface or tool that allows the user to make changes or adjustments to the generated comic-style explanatory material.

[0533] "Means for saving" refers to a system function that allows the generated comic-style explanatory materials and related data to be retained and made available for reuse and re-editing at a later date.

[0534] "Means for enabling re-editing" refers to a function or method for making previously generated or saved explanatory material editable again.

[0535] Specific embodiments for carrying out the invention will be described in detail below.

[0536] System Overview

[0537] The system operates as a web application. Users upload data related to their work through a dedicated interface. The server receives the data and analyzes it using artificial intelligence (AI) and natural language processing (NLP) models. Based on the analysis results, a comic-style explanatory document is automatically generated. Users can preview the generated document and make any necessary corrections. The final comic-style explanatory document can be downloaded as a PDF or image file.

[0538] Data entry and analysis

[0539] Users use their devices to upload text, image, or presentation files to explain their work. The devices provide an interface to the users and send the input data to the server. The server then analyzes the text using an NLP model (e.g., GPT-4 or BERT) to extract key points. For image data, the server uses image recognition technology (e.g., Tesseract or OpenCV) to identify the structure.

[0540] manga generation

[0541] The server selects the optimal characters and scenario based on the analysis results. It uses pre-trained manga templates and character libraries (e.g., DCGAN, StyleGAN). The server then creates an automatically generated manga based on the selected characters and scenario. This may involve using software such as Unity or Unreal Engine. The generated manga is temporarily saved and displayed as a preview in the user interface.

[0542] User customization

[0543] Users can preview the video on their devices and make any necessary edits. The interface supports editing dialogue, changing character expressions, adjusting backgrounds, etc. Users can make changes using text boxes and drop-down menus.

[0544] Final output and saving

[0545] After the user has completed the revisions, the server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link. The server also provides a means for storing the generated comic and related data so that the user can re-edit it later. This may involve the use of a database (e.g., MySQL, MongoDB).

[0546] Specific examples

[0547] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes the rough sketch and identifies each step in the process. It then selects a product development scenario and appropriate characters, and automatically generates a comic-style explanatory document. The user can review the document and make adjustments, such as changing the line "prototype testing" to "quality testing." Finally, the document can be downloaded in PDF format and used for internal presentations.

[0548] Prompt Sentence Examples

[0549] Business: New product development process

[0550] Rough sketch: Attachment 1.png

[0551] Analysis purpose: Generate explanatory materials in comic format

[0552] As described above, the system of the present invention efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and provides a format that users can easily modify and save.

[0553] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0554] Step 1:

[0555] The user uploads text information, image information, or a presentation file from the terminal to explain the details of the work.

[0556] Specific actions: A user uses the web application interface to enter text information into an input form and to select and upload the required files using the file upload button.

[0557] Input: Text, images, or presentation files entered by the user.

[0558] Output: Uploaded data is sent to the server.

[0559] Step 2:

[0560] The server receives the uploaded text information and analyzes it using a natural language processing (NLP) model.

[0561] Specific operation: The server tokenizes the text information and extracts key points using an NLP model (e.g., GPT-4 or BERT).

[0562] Input: Textual information received from the user.

[0563] Output: Analysis results with extracted key points, e.g., key phrases such as "project launch," "product design," and "market research."

[0564] Step 3:

[0565] The server receives the uploaded image information and analyzes it using image recognition technology.

[0566] What happens: The server reads the image and uses OCR technology (e.g., Tesseract or OpenCV) to extract text from the image and, if necessary, identify structures within the image.

[0567] Input: Image information received from the user.

[0568] Output: Extracted text and identified structural information from the image.

[0569] Step 4:

[0570] The server selects the optimal characters and scenarios based on the analysis results.

[0571] Specific operation: The server refers to pre-trained manga templates and character libraries (e.g., DCGAN, StyleGAN) and selects characters and scenarios appropriate for the task.

[0572] Input: Keypoints, structural information from images.

[0573] Output: Selected characters and scenarios.

[0574] Step 5:

[0575] The server automatically generates a manga based on the selected characters and scenario.

[0576] Specific operation: The server generates a scene by arranging the position, facial expression, and lines of each character based on the selected template. This process may use software such as Unity or Unreal Engine.

[0577] Input: Selected characters and scenario.

[0578] Output: Each page of the automatically generated comic.

[0579] Step 6:

[0580] The terminal provides the user with a preview of the generated comic.

[0581] Specific operation: The server temporarily saves the generated manga and displays it as a preview in the user interface.

[0582] Input: Each page of the automatically generated comic.

[0583] Output: Preview data to the user.

[0584] Step 7:

[0585] The user checks the preview and makes any necessary corrections.

[0586] Specific operations: The user can modify dialogue, change character expressions, adjust the background, etc. through the interface.

[0587] Input: Preview data.

[0588] Output: The final comic, as modified by the user.

[0589] Step 8:

[0590] The server saves the comic-style explanatory material after the user has completed the edits and outputs it in PDF or image file format.

[0591] What it does: The server saves the final manga, converts it to PDF or JPEG format, provides a download link to the user, and stores it in a database so that it can be re-edited later.

[0592] Input: The final comic, as revised by the user.

[0593] Output: Final manga in PDF or image file format, re-editable saved data.

[0594] (Application example 1)

[0595] 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."

[0596] Modern brick-and-mortar stores offer a wide variety of products and services, and it is important to effectively communicate their features and how to use them to customers. However, traditional methods, such as using text and diagrams, can be difficult to understand. Furthermore, the quality of explanations can vary depending on the store staff's explanation skills and time constraints. Therefore, a new method is needed that can quickly provide customers with visually easy-to-understand, consistent information.

[0597] 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.

[0598] In this invention, the server includes means for inputting text information, image information, or a presentation file to explain business operations, means for analyzing the input text information and extracting key points, means for analyzing the input image information and identifying the structure, means for inputting product information and service details for a physical store and displaying them in a comic format, and means for allowing the user to make corrections to the generated comic-format explanatory materials. This allows product explanations and service guides for physical stores to be provided in a visually easy-to-understand comic format, thereby enabling effective information transmission to customers.

[0599] "Business content" is information about the specific tasks and activities performed by a company or organization.

[0600] "Character information" is text data such as sentences and words.

[0601] "Image information" refers to visual data such as photographs and illustrations.

[0602] A "presentation file" is a document format that organizes and visually presents information in slide format.

[0603] "Input means" refers to devices or interfaces that input data such as text information, image information, and presentation files into the system.

[0604] "Means of analysis" refers to software or algorithms that break down and analyze input information to extract key points.

[0605] A "means for extracting key points" is a method or device for identifying the main information or content from input text information.

[0606] "Means for identifying structure" refers to technology or devices that recognize the elements and arrangement of input image information.

[0607] "Means for selecting optimal characters and scenarios" refers to techniques and methods for determining appropriate characters and story flow based on the analysis results.

[0608] "Means for generating explanatory materials in comic format" refers to technology or software that automatically generates the layout and content of a comic based on selected characters and a scenario.

[0609] "Means by which a user can make corrections to the generated comic-style explanatory material" refers to an interface or editing tool that allows a user to check the content of the generated comic and make any necessary changes.

[0610] A "brick and mortar store" is a store that has a physical location and where customers can visit in person to purchase goods or services.

[0611] "Product information" means data and descriptions about a product's characteristics, uses, benefits, etc.

[0612] "Service details" is information about the details of various services provided by the store and how to use them.

[0613] "Means for displaying in comic format" refers to technology or devices that display product information or service content in the form of comics that are visually easy to understand.

[0614] A specific embodiment of the present invention will be described in detail below. The present invention is a system for providing product explanations and service guides for brick-and-mortar stores in a visually easy-to-understand comic format.

[0615] System configuration

[0616] This system operates primarily using devices such as smartphones or tablets and a cloud server. Users install a dedicated application on their device and use it to input business details, product information, and service details. The input information is sent to the cloud server, where it is analyzed and processed to generate the manga.

[0617] Hardware and software used:

[0618] Hardware: Smartphone, tablet (iOS or Android)

[0619] Software: Dedicated applications, cloud servers, artificial intelligence (AI) models, natural language processing (NLP) models

[0620] The program proceeds as follows:

[0621] 1. Data entry method:

[0622] Users start a dedicated application and input product information and service details. Input methods include text input, image upload, and presentation file upload.

[0623] 2. Data analysis methods:

[0624] The cloud server receives the uploaded data and uses NLP models to analyze the text information and extract key points, while image recognition technology is used to identify the structure of the image information.

[0625] 3. Manga generation method:

[0626] The server selects the most suitable characters and scenario based on the analysis results and automatically generates explanatory materials in the form of a manga. The generated manga is temporarily saved and displayed as a preview on the user interface.

[0627] 4. Customization methods:

[0628] Users can use the interface to check the preview and make any necessary edits, such as modifying dialogue, changing character expressions, or adjusting the background.

[0629] 5. Output Method:

[0630] Finally, the revised comic-style explanatory material is generated as a PDF or image file, and a download link is provided to the user.

[0631] 6. Preservation means:

[0632] The cloud server stores the generated comics and related data, allowing users to re-edit them later.

[0633] Specific examples

[0634] For example, consider a scenario in which a user is explaining to a customer how to use a newly arrived electronic device. The user uploads a document containing the product's specifications and usage examples to the app. The app analyzes this using NLP and image recognition, selects characters and scenarios appropriate for each specification and usage example, and automatically generates a manga. The user then looks at the generated manga, fine-tunes the dialogue and facial expressions, and downloads the final version as a PDF to present to the customer. In this way, explanations can be provided in a visually easy-to-understand manner.

[0635] Example prompt sentence:

[0636] Documentation on how to use your new tablet:

[0637] 1. How to use the touch screen

[0638] 2. Installing and Using the App

[0639] 3. Internet connection settings

[0640] As described above, the system of the present invention provides product explanations and service guides in physical stores in a visually easy-to-understand comic format, thereby improving the quality of explanations given to customers.

[0641] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0642] Step 1:

[0643] Data entry method:

[0644] Users launch a dedicated application on their smartphone or tablet and enter product information and service details. Specifically, they can enter text, upload images, and upload presentation files. Input data includes product features, usage instructions, and benefits.

[0645] input:

[0646] Product information (text, images, presentation files)

[0647] output:

[0648] Data transfer to cloud server

[0649] Step 2:

[0650] Data analysis methods:

[0651] The cloud server analyzes the received data. First, it analyzes the text information using a natural language processing (NLP) model to extract key points. Next, it analyzes the image information using image recognition technology to identify its structure.

[0652] input:

[0653] Product information received in step 1

[0654] output:

[0655] Keypoint Extraction (Text)

[0656] Identifying image structures

[0657] Specific behavior:

[0658] It uses NLP models to analyze the content of the input text and extract key information.

[0659] Image recognition software is used to analyze the structure of uploaded images and identify key elements.

[0660] Step 3:

[0661] Manga generation means:

[0662] The server selects the optimal characters and scenario based on the analysis results obtained in step 2. Using an artificial intelligence (AI) model, it automatically selects the optimal layout from pre-trained manga templates and generates explanatory materials in manga format.

[0663] input:

[0664] Keypoint extraction results

[0665] Image structure analysis results

[0666] output:

[0667] Comic book format explanatory material (for preview)

[0668] Specific behavior:

[0669] Using an AI model, the optimal characters and scenarios are selected from the analysis results.

[0670] Automatically create a manga layout based on selected elements.

[0671] Step 4:

[0672] Customization methods:

[0673] The generated manga-style explanatory material is displayed as a preview in the user interface. The user can check this preview and make any necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[0674] input:

[0675] Comic book format explanatory material (for preview)

[0676] output:

[0677] Final version with user modifications

[0678] Specific behavior:

[0679] Through the user interface, the user edits each part of the manga (dialogue, characters, background, etc.).

[0680] Edits are reflected in the preview in real time.

[0681] Step 5:

[0682] Output Method:

[0683] After the edits are complete, the cloud server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[0684] input:

[0685] Final version with user modifications

[0686] output:

[0687] Final version in PDF or image file format

[0688] Specific behavior:

[0689] The server saves and converts the final manga format description material and generates a download link.

[0690] Step 6:

[0691] Storage method:

[0692] The cloud server stores the generated comics and related data, allowing users to re-edit them later.

[0693] input:

[0694] Final version in PDF or image file format

[0695] output:

[0696] Saved manga data and related information

[0697] Specific behavior:

[0698] The server stores the generated explanatory material and related data in a database.

[0699] Data is managed and provided in a format that allows for re-editing.

[0700] 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.

[0701] A specific embodiment for carrying out the present invention will be described in detail below. This system includes means for inputting text information, image information, and presentation files for explaining business content, and means for analyzing this information. Furthermore, means for selecting characters and scenarios based on the analysis results and generating comic-style explanatory materials is provided. The generated comic-style explanatory materials can be edited by the user and output in PDF or image file format.

[0702] The system of the present invention further incorporates an emotion engine that recognizes the user's emotions. Based on the user's emotions recognized by the emotion engine, the selection of characters and scenarios can be automatically adjusted. The dialogue and character expressions of the cartoon are also adjusted to reflect the user's emotional state.

[0703] System Overview

[0704] The system operates as a web application. Users upload data related to their work through a dedicated interface. The server receives this data and analyzes it using artificial intelligence (AI) and natural language processing (NLP) models. Based on the analysis results, explanatory materials in comic form are automatically generated. An emotion engine then analyzes the user's emotions and adjusts the content of the generated comic before displaying it. Users can preview the generated materials and make any necessary corrections. The final explanatory materials in comic form can be downloaded as a PDF or image file.

[0705] Program processing

[0706] The program processing of the system will be specifically explained below.

[0707] Data entry and analysis

[0708] 1. Data entry method

[0709] The terminal displays an interface for users to input their business details, such as text information, rough sketches, or presentation files, and upload them through this interface.

[0710] 2. Data analysis methods

[0711] The server receives the uploaded data and temporarily stores it.

[0712] The server analyzes the received text information using a natural language processing (NLP) model to extract key points and important phrases, such as stages such as "planning," "implementation," and "evaluation."

[0713] The server analyzes the received image information (rough sketch) using image recognition technology, identifies elements such as diagrams and characters, and determines their relationships.

[0714] Manga generation means

[0715] 1. Character and scenario selection method

[0716] The server then selects the most suitable characters and scenario based on the analysis results, referencing pre-trained manga templates. For example, a template explaining the progress of a project may be selected.

[0717] 2. Emotion Engine

[0718] The device analyzes the user's facial expressions and tone of voice to collect emotional data and send it to the server. The server then uses an emotion engine to analyze this data and determine the user's emotional state. For example, if the user is nervous, the server will set a relaxed expression and dialogue for the character accordingly.

[0719] 3. Manga generation means

[0720] The server automatically generates a cartoon based on the selected characters and scenario. The generated cartoon is adjusted based on the results of the emotion engine. For example, if the user has a happy expression, a smiling face is added to the character.

[0721] User customization

[0722] 1. Customization methods

[0723] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[0724] Final output and saving

[0725] 1. Output Method

[0726] After the revisions are complete, the server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[0727] 2. Preservation means

[0728] The server stores the generated comics and related data, allowing users to re-edit them later.

[0729] Specific examples

[0730] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes this rough sketch and identifies each step in the process. It then selects a product development scenario and an appropriate character, and automatically generates a comic-style explanatory document. The emotion engine analyzes the user's emotions and adds a character with a relaxed expression and encouraging words to a nervous user. The user can review this document and, if necessary, change "prototype testing" to "quality testing," and finally download it in PDF format for use in internal presentations.

[0731] As described above, the system of the present invention efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and by adjusting them according to the user's emotions, it provides a form of presentation that enhances its effectiveness.

[0732] The processing flow will be explained below.

[0733] Step 1:

[0734] The terminal displays an interface for the user to input business details, and the user can upload text information, rough sketches, or presentation files through this interface.

[0735] Step 2:

[0736] The server receives the uploaded data and temporarily stores it.

[0737] Step 3:

[0738] The server analyzes the received text using a natural language processing (NLP) model to extract key points and important phrases, such as major stages such as "new product planning" and "market research."

[0739] Step 4:

[0740] The server uses image recognition technology to analyze the received image information (rough sketches), identify elements such as diagrams and characters, and determine their relationships. For example, it recognizes each step in a flow diagram as a box or arrow.

[0741] Step 5:

[0742] The server selects the most suitable characters and scenarios based on the results of NLP analysis and image recognition. This is done by referencing pre-trained manga templates. For example, a scenario in which the "development team leader" "presents a product idea" may be selected.

[0743] Step 6:

[0744] The device analyzes the user's facial expressions and tone of voice in real time to collect emotional data, which is then sent to a server.

[0745] Step 7:

[0746] The server uses an emotion engine to analyze the user's emotion data and identify the emotion the user is currently feeling. For example, if the user is nervous, the server analyzes the emotion data.

[0747] Step 8:

[0748] The server then adjusts the character's facial expression and dialogue based on the recognized emotion data. For example, if the user is nervous, a character with a relaxed expression and encouraging dialogue will be placed.

[0749] Step 9:

[0750] The server automatically generates a manga based on the selected characters and the adjusted scenario. The generated manga is temporarily saved and displayed as a preview on the user interface.

[0751] Step 10:

[0752] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[0753] Step 11:

[0754] The server updates the final comic book-style instruction material to reflect the modifications made by the user.

[0755] Step 12:

[0756] The server generates the updated and final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[0757] Step 13:

[0758] The server stores the generated comics and related data, allowing users to re-edit them later.

[0759] Example 2

[0760] 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."

[0761] When explaining business operations, it is important to convey information visually, but conventional methods require time and effort. It is also difficult to create materials that take the user's emotions into account, limiting the effectiveness of communication. Another issue is the difficulty of re-editing or customizing materials once they have been created.

[0762] 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 a means for inputting data for explaining business operations, a means for temporarily saving the input data, a means for analyzing text information and extracting key points, a means for analyzing image information and identifying a structure, a means for selecting optimal characters and scenarios based on the extracted and identified information and generating a comic-style explanatory material, a means for analyzing a user's emotions regarding the generated comic-style explanatory material and adjusting the content, a means for allowing a user to make corrections to the generated comic-style explanatory material, and a means for saving the generated comic-style explanatory material and enabling re-editing. This allows for efficient creation of materials for explaining business operations visually and intuitively and allows adjustments based on the user's emotions. Furthermore, re-editing and customization can be easily performed, thereby enhancing the effectiveness of communication.

[0763] "Means for inputting data" refers to an interface that allows a user to provide text information, image information, or a presentation file to explain the content of a business to the system.

[0764] "Means for temporarily storing input data" refers to a storage or memory area for temporarily storing user-provided data before analysis or processing.

[0765] "Means for analyzing textual information and extracting key points" refers to a program that uses natural language processing technology to analyze textual information and identify important phrases and keywords.

[0766] "Means for analyzing image information and identifying its structure" refers to a program that uses computer vision technology to analyze image information and identify the elements of diagrams and characters and their relationships.

[0767] "Means for selecting optimal characters and scenarios" refers to an algorithm for selecting optimal characters and scenarios from pre-trained templates and databases based on the analyzed information.

[0768] "Means for generating explanatory materials in comic format" refers to programs and tools for automatically creating materials in comic format based on selected characters and scenarios.

[0769] "Means for analyzing user emotions and adjusting content" refers to an algorithm that analyzes the user's facial expressions and tone of voice to determine the user's emotions and adjust the manga characters and scenario accordingly.

[0770] "Means for making edits to the generated comic-style explanatory materials" refers to an interface that allows users to edit and adjust the content of the generated comic (such as lines, character expressions, backgrounds, etc.).

[0771] "Means for saving the generated comic-format explanatory materials and enabling them to be re-edited" refers to a system that allows comic-format materials to be saved in cloud storage or a database once they have been generated, allowing them to be re-edited or updated later.

[0772] "Means to enable output in PDF or image file format" refers to the function for outputting the final comic-format explanatory materials as a PDF file or image file (JPEG, PNG, etc.).

[0773] The system for implementing this invention operates as a web application. This system is composed of a user, a terminal, and a server. The specific operation of each element will be described in detail below.

[0774] System Overview

[0775] Users upload data related to their work through a dedicated interface, typically using a form or file upload function displayed on a web page. The server receives this data and temporarily stores it in cloud storage.

[0776] Data entry and analysis

[0777] Data Entry Method

[0778] The terminal displays an interface for users to input their business details, using which they can upload text information, rough sketches, or presentation files.

[0779] Data Analysis Methods

[0780] The server receives the uploaded data and temporarily stores it. This is done using cloud storage. The server then uses an NLP (natural language processing) model to analyze the text information. This model uses a Python NLP library (such as spacy or nltk). Through the analysis, key points and important phrases are extracted. For example, stages such as "planning," "implementation," and "evaluation" are identified.

[0781] The server analyzes the received image information (rough sketches) using image recognition technology. Specifically, it uses computer vision libraries (such as OpenCV and TensorFlow) to identify elements such as diagrams and characters and determine their relationships.

[0782] Manga generation means

[0783] Character and scenario selection method

[0784] The server selects the most suitable characters and scenarios based on the analysis results. This selection is made by referring to pre-trained manga templates. These templates are trained by a generative AI model (e.g., GPT-4). For example, a template describing the progress of a project is selected.

[0785] Emotion Engine

[0786] The device uses a camera and microphone to collect data to analyze the user's facial expressions and tone of voice. The collected data is sent to a server. The server then analyzes the collected data using an emotion engine. For example, it uses a machine learning model (SVM or neural network) to classify the user's emotions. If the user is nervous, the character's facial expression and lines are set accordingly.

[0787] Manga generation means

[0788] The server automatically generates a comic based on the selected characters and scenario. This uses a generative AI model (such as DALL-E or MidJourney). The generated comic is adjusted based on the results of the emotion engine. For example, if the user has a happy expression, a smiling face is added to the character.

[0789] User customization

[0790] The device provides an interface for users to preview the generated manga and make any necessary edits. Specifically, it has drag-and-drop and text editing functions. Users can edit dialogue, change character expressions, adjust backgrounds, and more.

[0791] Final output and saving

[0792] Output Method

[0793] After the revisions are complete, the server generates the final comic-style explanatory material in PDF or image file format using a library (such as ReportLab or Pillow) and provides the user with a download link for the generated file.

[0794] Preservation means

[0795] The server saves the generated comics and related data. The data is stored in a database (e.g., PostgreSQL or MongoDB). This allows users to re-edit the data later and allows history management.

[0796] Specific examples

[0797] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes the rough sketch and identifies each step in the process. It then selects a product development scenario and an appropriate character, automatically generating a comic-style explanatory document. The emotion engine analyzes the user's emotions and adds a character with a relaxed expression and encouraging words to a nervous user. The user can review the document and, if necessary, change "prototype testing" to "quality testing," and finally download it as a PDF for use in internal presentations.

[0798] Examples of prompt statements

[0799] - "Please upload a rough sketch to create a comic-style document that explains the new product development process. Which stage is the most important in terms of trends?"

[0800] - "Enable the emotion engine and adjust the character's facial expressions. Tell us their current emotional state."

[0801] In this way, this system efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and by adjusting them according to the user's emotions, it enhances the effectiveness of presentations.

[0802] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0803] Step 1: Enter your data

[0804] The terminal displays an interface for the user to input data related to the business content. This interface includes a text input field, a rough sketch upload function, and a presentation file upload function. The input data can be text information, a rough sketch, or a presentation file. The input data can be provided by the user by direct input or file upload.

[0805] Step 2: Save your data

[0806] The terminal sends the data entered by the user to the server, which then temporarily stores the received data in cloud storage. For example, text information, image information (rough sketches), and presentation files are temporarily stored in the cloud storage.

[0807] Step 3: Analyzing the text

[0808] The server analyzes the temporarily stored text information using an NLP (natural language processing) model. In this process, Python NLP libraries (e.g., spacy, nltk) are used to extract key points and important phrases from the text information. As a result, important phrases such as "planning," "implementation," and "evaluation" are output.

[0809] Step 4: Analyze image information

[0810] The server analyzes the temporarily stored image information (rough sketches) using computer vision technology. This analysis uses libraries such as OpenCV and TensorFlow. The server identifies elements such as diagrams and characters from the rough sketches and determines their relationships. For example, the server identifies diagrams showing each stage of a project and determines their interrelationships.

[0811] Step 5: Character and scenario selection

[0812] The server selects the most suitable characters and scenarios based on key points and elements extracted from text and image information. This selection is performed by referring to pre-trained manga templates. For example, a template explaining the progress of a project may be selected.

[0813] Step 6: Sentiment Analysis

[0814] The device uses a camera and microphone to analyze the user's facial expressions and voice, and the collected emotional data is sent to a server.

[0815] The server analyzes the collected data using an emotion engine, which determines what emotions the user is feeling. For example, it can determine if the user is nervous. The results of the emotion analysis are output and used to adjust the character's facial expressions and dialogue.

[0816] Step 7: Generate the comic

[0817] The server automatically generates a manga based on the selected characters and scenario. This generation uses generative AI models such as DALL-E and MidJourney. The character's facial expressions and lines are adjusted based on the results of the emotion analysis. The generated manga is output, reflecting the results of the emotion analysis.

[0818] Step 8: Providing customizations

[0819] The device provides an interface for users to preview and modify the generated manga. This interface includes drag-and-drop and text editing functions. Users can modify dialogue, change character expressions, adjust backgrounds, and more. The modified and adjusted manga is output based on the user's input.

[0820] Step 9: Final Output

[0821] The server generates the final, edited version of the comic-style explanatory material in PDF or image file format using libraries such as ReportLab or Pillow. A download link for the generated file is provided to the user. The final output PDF or image file is provided to the user.

[0822] Step 10: Save your data

[0823] The server stores the generated manga and related data in a database (e.g., PostgreSQL, MongoDB), allowing users to re-edit the data later. The saved data is output in a format that allows for re-editing and history management.

[0824] Through the above processing steps, the system can efficiently generate comic-style materials that allow users to visually and intuitively communicate their work content, and can adjust the content according to the user's emotions.

[0825] (Application example 2)

[0826] 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."

[0827] Conventional work explanation materials generally use text or simple illustrations, making it difficult to present information in a visually understandable format. Furthermore, there is no means of providing appropriate information based on employees' emotions, which reduces the effectiveness of training and reduces work efficiency. To address these issues, the present invention aims to provide a system that explains work content in comic form and automatically adjusts based on emotions.

[0828] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0829] In this invention, the server includes means for inputting text information, image information, or a presentation file for explaining the content of work, means for analyzing the input text information and extracting key points, means for analyzing the input image information and identifying a structure, means for selecting optimal characters and scenarios based on the extracted and identified information and generating explanatory materials in comic form, means for automatically adjusting the characters and scenarios using an emotion engine that recognizes the user's emotions, and means for the user to make corrections to the generated explanatory materials in comic form. This makes it possible to provide information in a visually easy-to-understand format and provide optimal information according to the emotions of employees.

[0830] "Job Description" refers to detailed information about a specified task or process.

[0831] "Textual information" refers to data provided in text format.

[0832] "Image information" means data provided in a visual format, such as a photograph, illustration, or diagram.

[0833] A "presentation file" is a digital document created to explain business content in slide format.

[0834] The "emotion engine" is a system that analyzes a user's facial expressions, tone of voice, etc. to identify emotions.

[0835] "Means for extracting key points" is a function for identifying and extracting important information and phrases from input text information.

[0836] The "means for identifying structure" is a function for analyzing input image information and identifying its contents and relationships.

[0837] The "means for selecting characters and scenarios" is a function for selecting the most suitable characters and scenarios based on the extracted and identified information.

[0838] "Means for generating explanatory materials in comic format" is a function for creating materials that visually explain business details in comic format based on selected characters and scenarios.

[0839] "Means for automatic adjustment" is a function that automatically changes the content of characters and scenarios based on the user's emotions identified by the emotion engine.

[0840] "Means by which users can make modifications" is a function that provides an interface that allows users to freely edit and modify the generated comic-style explanatory material.

[0841] MODE FOR CARRYING OUT THE INVENTION

[0842] The following describes in detail a specific embodiment of the present invention. This system generates job explanation materials in cartoon format and automatically adjusts the content using an emotion engine. The entire system is designed to enable effective employee training and job explanations in factories using smart glasses.

[0843] Hardware and Software Configuration

[0844] Hardware:

[0845] Smart glasses (e.g. Microsoft HoloLens)

[0846] Server (Cloud or On-Premise)

[0847] software:

[0848] Natural Language Processing (NLP) models (e.g., Google BERT)

[0849] Image recognition technology (e.g., OpenCV)

[0850] Sentiment analysis engine (e.g. Microsoft Azure Emotion API)

[0851] Processing flow

[0852] 1. Data Entry

[0853] The terminal (smart glasses) provides an interface for inputting text information and presentation files related to business content. Users use the smart glasses to scan or upload data related to business materials.

[0854] 2. Data Analysis

[0855] The server analyzes the input text information using an NLP model to extract key business points, and also analyzes image information using image recognition technology to identify structure and important elements.

[0856] 3. Manga generation

[0857] The server selects the most suitable characters and scenario based on the key points and the identified structure, and generates explanatory materials in comic form. At the same time, an emotion analysis engine analyzes the user's facial expressions and tone of voice to set appropriate character expressions and lines.

[0858] 4. User Modifications

[0859] The generated comic-style explanatory materials can be previewed on the smart glasses and edited as needed, such as changing dialogue, adjusting character expressions, and adding backgrounds.

[0860] 5. Final output

[0861] Once the edits are complete, the document is generated as a PDF or image file and saved on the server. The final product can then be downloaded by the user via a download link.

[0862] Specific examples

[0863] For example, consider a case where an employee learning how to set up a new production line uses smart glasses to scan their work, and AI analyzes the content to generate a comic-style document. If the emotion engine detects that the user is nervous, it adds a character with a relaxed expression and reassuring words. The user can then review and edit the document, and finally save it as a PDF to use as training material.

[0864] Prompt Sentence Examples

[0865] "Scan the job description and generate a cartoon-style document, with characters that have relaxed expressions to make it easier for employees to understand."

[0866] By combining the above elements, the present invention makes it possible to quickly generate visually easy-to-understand work explanation materials and provide appropriate information according to the emotions of employees.

[0867] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0868] Step 1: Data entry

[0869] The terminal (smart glasses) provides an interface for inputting text information and presentation files related to work content. Users use the smart glasses to scan or upload data related to work materials. The input data is text-based work instructions and image-based presentation files.

[0870] Step 2: Data analysis

[0871] The server receives the text information sent from the device and analyzes it using a natural language processing (NLP) model (e.g., Google BERT). During the analysis, important steps and key points of the business (e.g., "work preparation," "equipment setup," and "quality check") are extracted. At the same time, image information is analyzed using image recognition technology (e.g., OpenCV) to identify structure and important elements (e.g., diagrams, equipment layout). These analysis results are used in the next step.

[0872] Step 3: Character and scenario selection

[0873] The server automatically selects the most suitable characters and scenarios based on the keypoints extracted and the structure identified in step 2. This selection uses pre-trained manga templates. For example, a scenario and its characters that explain the setup procedure for a manufacturing line are selected.

[0874] Step 4: Sentiment Analysis

[0875] The device analyzes the user's facial expressions and tone of voice using an emotion analysis engine (e.g., Microsoft Azure Emotion API) and sends the user's emotional data to the server. The emotional data (e.g., "tense," "relaxed," "excited") is used to adjust the content of the comic in a later step.

[0876] Step 5: Manga Generation

[0877] The server generates explanatory materials in comic form based on the characters and scenario selected in step 3. Furthermore, the character's facial expressions and lines are automatically adjusted based on the results of the emotion analysis engine. For example, if the user is nervous, a character with a relaxed expression and encouraging lines will be set.

[0878] Step 6: User Modifications

[0879] The generated comic-style explanatory materials are previewed on the device. The user can use smart glasses to check the preview and make any necessary corrections (e.g., changing dialogue, adjusting character expressions, adding backgrounds). The corrected data is then saved on the server.

[0880] Step 7: Final output

[0881] Once the edits are complete, the document is generated as a PDF or image file on the server, and a download link is provided to the user. The final product is then saved in the cloud, allowing for future editing.

[0882] Each step of this system presents work details in a visually easy-to-understand format, enabling appropriate information to be provided based on the employee's emotions.

[0883] 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.

[0884] 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.

[0885] 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.

[0886] [Third embodiment]

[0887] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0888] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0889] 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).

[0890] 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.

[0891] 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.

[0892] 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).

[0893] 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.

[0894] 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.

[0895] 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.

[0896] 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.

[0897] 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.

[0898] 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."

[0899] A specific embodiment for carrying out the present invention will be described in detail below. This system includes means for inputting text information, image information, and presentation files for explaining business content, and means for analyzing this information. Furthermore, means for selecting characters and scenarios based on the analysis results and generating comic-style explanatory materials is provided. The generated comic-style explanatory materials can be edited by the user and output in PDF or image file format.

[0900] System Overview

[0901] The system operates as a web application. Users upload data related to their work through a dedicated interface. The server receives the data and analyzes it using artificial intelligence (AI) and natural language processing (NLP) models. Based on the analysis results, a comic-style explanatory document is automatically generated. Users can preview the generated document and make any necessary corrections. The final comic-style explanatory document can be downloaded as a PDF or image file.

[0902] Program processing

[0903] The program processing of the system will be specifically explained below.

[0904] Data entry and analysis

[0905] 1. Data entry method

[0906] The terminal displays an interface for users to input their business details: they can upload text information, rough sketches, or presentation files.

[0907] 2. Data analysis methods

[0908] The server receives the uploaded data, analyzes the text information using an NLP model to extract key points, and uses image recognition technology to identify the structure of the image information.

[0909] Manga generation means

[0910] 1. Character and scenario selection method

[0911] The server selects the most suitable characters and scenarios based on the analysis results, using pre-trained manga templates.

[0912] 2. Manga generation means

[0913] The server automatically generates a manga based on the selected characters and scenario. The generated manga is temporarily saved and displayed as a preview on the user interface.

[0914] User customization

[0915] 1. Customization methods

[0916] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[0917] Final output and saving

[0918] 1. Output Method

[0919] After the revisions are complete, the server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[0920] 2. Preservation means

[0921] The server stores the generated comics and related data, allowing users to re-edit them later.

[0922] Specific examples

[0923] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes the rough sketch and identifies each step in the process. It then selects a product development scenario and appropriate characters, and automatically generates a comic-style explanatory document. The user can review the document and make adjustments, such as changing the line "prototype testing" to "quality testing." Finally, the document can be downloaded in PDF format and used for internal presentations.

[0924] As described above, the system of the present invention efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and provides a format that is easy for users to use.

[0925] The processing flow will be explained below.

[0926] Step 1:

[0927] The terminal displays an interface for the user to input business details, and the user can upload text information, rough sketches, or presentation files through this interface.

[0928] Step 2:

[0929] The server receives the uploaded data and temporarily stores it.

[0930] Step 3:

[0931] The server analyzes the received text using natural language processing (NLP) models to extract key points and important phrases, such as stages in a business process or important actions.

[0932] Step 4:

[0933] The server analyzes the received image information (rough sketch) using image recognition technology, identifies elements such as diagrams and characters, and determines their relationships.

[0934] Step 5:

[0935] The server selects the optimal characters and scenarios based on the results of NLP analysis and image recognition. This is done by referencing pre-trained manga templates. For example, a template related to a business flow is selected, and a scene in which a character performs a specific business action is created.

[0936] Step 6:

[0937] The server automatically generates a manga based on the selected characters and scenario. Each character performs appropriate actions and speaks lines in the designated stage. The background is also selected to match the scenario.

[0938] Step 7:

[0939] The server temporarily stores the generated comic and displays it as a preview on the user interface.

[0940] Step 8:

[0941] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[0942] Step 9:

[0943] The server updates the final comic book-style instruction material to reflect the modifications made by the user.

[0944] Step 10:

[0945] The server generates the updated and final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[0946] Step 11:

[0947] The server stores the generated comics and related data, allowing users to re-edit them later.

[0948] Example 1

[0949] 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."

[0950] Conventional systems for creating explanatory materials lack the means to visually and intuitively convey the content of work, and creating materials under specific conditions is often complex and time-consuming. There is a demand for systems that allow users to efficiently explain the content of work.

[0951] 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.

[0952] In this invention, the server includes means for inputting text information, image information, or a presentation file for explaining business content, means for analyzing the input text information and extracting key points, means for analyzing the input image information and identifying a structure, means for selecting optimal characters and scenarios based on the extracted and identified information and generating comic-style explanatory materials, means for allowing a user to make corrections to the generated comic-style explanatory materials, and means for saving the generated comic-style explanatory materials so that they can be re-edited later. This makes it possible to provide a system for efficiently generating comic-style explanatory materials for visually and intuitively conveying business content, and for allowing a user to easily modify and save them.

[0953] "Text information" is information expressed as sentences or text, and is a data format used to explain business content.

[0954] "Image information" is data provided as a visual representation, including photographs, illustrations, diagrams, and the like.

[0955] A "presentation file" is a slide-format file used to explain business operations, and is a document that includes images, text information, graphs, and the like.

[0956] An "input method" is the method or interface by which a user provides data to a system, typically a file upload function or an input form.

[0957] "Means for analysis" refers to the system functions for processing input data and extracting necessary information and patterns, and includes natural language processing and image recognition technology.

[0958] "Key points" are important elements or themes extracted from the analyzed textual and image information, and are central information for understanding and explaining the business content.

[0959] "Means for identifying structure" refers to techniques or methods for analyzing input image information and identifying components and relationships.

[0960] "Characters" are characters or characters that appear in comic-style explanatory materials, and are elements with specific roles and personalities.

[0961] A "scenario" is a plot or story that characters follow, a storyline that effectively communicates the contents of explanatory material.

[0962] "Means of generation" refers to the functions and processes for creating explanatory materials in comic format based on input data and analysis results.

[0963] "Means by which the user can make modifications" refers to an interface or tool that allows the user to make changes or adjustments to the generated comic-style explanatory material.

[0964] "Means for saving" refers to a system function that allows the generated comic-style explanatory materials and related data to be retained and made available for reuse and re-editing at a later date.

[0965] "Means for enabling re-editing" refers to a function or method for making previously generated or saved explanatory material editable again.

[0966] Specific embodiments for carrying out the invention will be described in detail below.

[0967] System Overview

[0968] The system operates as a web application. Users upload data related to their work through a dedicated interface. The server receives the data and analyzes it using artificial intelligence (AI) and natural language processing (NLP) models. Based on the analysis results, a comic-style explanatory document is automatically generated. Users can preview the generated document and make any necessary corrections. The final comic-style explanatory document can be downloaded as a PDF or image file.

[0969] Data entry and analysis

[0970] Users use their devices to upload text, image, or presentation files to explain their work. The devices provide an interface to the users and send the input data to the server. The server then analyzes the text using an NLP model (e.g., GPT-4 or BERT) to extract key points. For image data, the server uses image recognition technology (e.g., Tesseract or OpenCV) to identify the structure.

[0971] manga generation

[0972] The server selects the optimal characters and scenario based on the analysis results. It uses pre-trained manga templates and character libraries (e.g., DCGAN, StyleGAN). The server then creates an automatically generated manga based on the selected characters and scenario. This may involve using software such as Unity or Unreal Engine. The generated manga is temporarily saved and displayed as a preview in the user interface.

[0973] User customization

[0974] Users can preview the video on their devices and make any necessary edits. The interface supports editing dialogue, changing character expressions, adjusting backgrounds, etc. Users can make changes using text boxes and drop-down menus.

[0975] Final output and saving

[0976] After the user has completed the revisions, the server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link. The server also provides a means for storing the generated comic and related data so that the user can re-edit it later. This may involve the use of a database (e.g., MySQL, MongoDB).

[0977] Specific examples

[0978] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes the rough sketch and identifies each step in the process. It then selects a product development scenario and appropriate characters, and automatically generates a comic-style explanatory document. The user can review the document and make adjustments, such as changing the line "prototype testing" to "quality testing." Finally, the document can be downloaded in PDF format and used for internal presentations.

[0979] Prompt Sentence Examples

[0980] Business: New product development process

[0981] Rough sketch: Attachment 1.png

[0982] Analysis purpose: Generate explanatory materials in comic format

[0983] As described above, the system of the present invention efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and provides a format that users can easily modify and save.

[0984] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0985] Step 1:

[0986] The user uploads text information, image information, or a presentation file from the terminal to explain the details of the work.

[0987] Specific actions: A user uses the web application interface to enter text information into an input form and to select and upload the required files using the file upload button.

[0988] Input: Text, images, or presentation files entered by the user.

[0989] Output: Uploaded data is sent to the server.

[0990] Step 2:

[0991] The server receives the uploaded text information and analyzes it using a natural language processing (NLP) model.

[0992] Specific operation: The server tokenizes the text information and extracts key points using an NLP model (e.g., GPT-4 or BERT).

[0993] Input: Textual information received from the user.

[0994] Output: Analysis results with extracted key points, e.g., key phrases such as "project launch," "product design," and "market research."

[0995] Step 3:

[0996] The server receives the uploaded image information and analyzes it using image recognition technology.

[0997] What happens: The server reads the image and uses OCR technology (e.g., Tesseract or OpenCV) to extract text from the image and, if necessary, identify structures within the image.

[0998] Input: Image information received from the user.

[0999] Output: Extracted text and identified structural information from the image.

[1000] Step 4:

[1001] The server selects the optimal characters and scenarios based on the analysis results.

[1002] Specific operation: The server refers to pre-trained manga templates and character libraries (e.g., DCGAN, StyleGAN) and selects characters and scenarios appropriate for the task.

[1003] Input: Keypoints, structural information from images.

[1004] Output: Selected characters and scenarios.

[1005] Step 5:

[1006] The server automatically generates a manga based on the selected characters and scenario.

[1007] Specific operation: The server generates a scene by arranging the position, facial expression, and lines of each character based on the selected template. This process may use software such as Unity or Unreal Engine.

[1008] Input: Selected characters and scenario.

[1009] Output: Each page of the automatically generated comic.

[1010] Step 6:

[1011] The terminal provides the user with a preview of the generated comic.

[1012] Specific operation: The server temporarily saves the generated manga and displays it as a preview in the user interface.

[1013] Input: Each page of the automatically generated comic.

[1014] Output: Preview data to the user.

[1015] Step 7:

[1016] The user checks the preview and makes any necessary corrections.

[1017] Specific operations: The user can modify dialogue, change character expressions, adjust the background, etc. through the interface.

[1018] Input: Preview data.

[1019] Output: The final comic, as modified by the user.

[1020] Step 8:

[1021] The server saves the comic-style explanatory material after the user has completed the edits and outputs it in PDF or image file format.

[1022] What it does: The server saves the final manga, converts it to PDF or JPEG format, provides a download link to the user, and stores it in a database so that it can be re-edited later.

[1023] Input: The final comic, as revised by the user.

[1024] Output: Final manga in PDF or image file format, re-editable saved data.

[1025] (Application example 1)

[1026] 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."

[1027] Modern brick-and-mortar stores offer a wide variety of products and services, and it is important to effectively communicate their features and how to use them to customers. However, traditional methods, such as using text and diagrams, can be difficult to understand. Furthermore, the quality of explanations can vary depending on the store staff's explanation skills and time constraints. Therefore, a new method is needed that can quickly provide customers with visually easy-to-understand, consistent information.

[1028] 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.

[1029] In this invention, the server includes means for inputting text information, image information, or a presentation file to explain business operations, means for analyzing the input text information and extracting key points, means for analyzing the input image information and identifying the structure, means for inputting product information and service details for a physical store and displaying them in a comic format, and means for allowing the user to make corrections to the generated comic-format explanatory materials. This allows product explanations and service guides for physical stores to be provided in a visually easy-to-understand comic format, thereby enabling effective information transmission to customers.

[1030] "Business content" is information about the specific tasks and activities performed by a company or organization.

[1031] "Character information" is text data such as sentences and words.

[1032] "Image information" refers to visual data such as photographs and illustrations.

[1033] A "presentation file" is a document format that organizes and visually presents information in slide format.

[1034] "Input means" refers to devices or interfaces that input data such as text information, image information, and presentation files into the system.

[1035] "Means of analysis" refers to software or algorithms that break down and analyze input information to extract key points.

[1036] A "means for extracting key points" is a method or device for identifying the main information or content from input text information.

[1037] "Means for identifying structure" refers to technology or devices that recognize the elements and arrangement of input image information.

[1038] "Means for selecting optimal characters and scenarios" refers to techniques and methods for determining appropriate characters and story flow based on the analysis results.

[1039] "Means for generating explanatory materials in comic format" refers to technology or software that automatically generates the layout and content of a comic based on selected characters and a scenario.

[1040] "Means by which a user can make corrections to the generated comic-style explanatory material" refers to an interface or editing tool that allows a user to check the content of the generated comic and make any necessary changes.

[1041] A "brick and mortar store" is a store that has a physical location and where customers can visit in person to purchase goods or services.

[1042] "Product information" means data and descriptions about a product's characteristics, uses, benefits, etc.

[1043] "Service details" is information about the details of various services provided by the store and how to use them.

[1044] "Means for displaying in comic format" refers to technology or devices that display product information or service content in the form of comics that are visually easy to understand.

[1045] A specific embodiment of the present invention will be described in detail below. The present invention is a system for providing product explanations and service guides for brick-and-mortar stores in a visually easy-to-understand comic format.

[1046] System configuration

[1047] This system operates primarily using devices such as smartphones or tablets and a cloud server. Users install a dedicated application on their device and use it to input business details, product information, and service details. The input information is sent to the cloud server, where it is analyzed and processed to generate the manga.

[1048] Hardware and software used:

[1049] Hardware: Smartphone, tablet (iOS or Android)

[1050] Software: Dedicated applications, cloud servers, artificial intelligence (AI) models, natural language processing (NLP) models

[1051] The program proceeds as follows:

[1052] 1. Data entry method:

[1053] Users start a dedicated application and input product information and service details. Input methods include text input, image upload, and presentation file upload.

[1054] 2. Data analysis methods:

[1055] The cloud server receives the uploaded data and uses NLP models to analyze the text information and extract key points, while image recognition technology is used to identify the structure of the image information.

[1056] 3. Manga generation method:

[1057] The server selects the most suitable characters and scenario based on the analysis results and automatically generates explanatory materials in the form of a manga. The generated manga is temporarily saved and displayed as a preview on the user interface.

[1058] 4. Customization methods:

[1059] Users can use the interface to check the preview and make any necessary edits, such as modifying dialogue, changing character expressions, or adjusting the background.

[1060] 5. Output Method:

[1061] Finally, the revised comic-style explanatory material is generated as a PDF or image file, and a download link is provided to the user.

[1062] 6. Preservation means:

[1063] The cloud server stores the generated comics and related data, allowing users to re-edit them later.

[1064] Specific examples

[1065] For example, consider a scenario in which a user is explaining to a customer how to use a newly arrived electronic device. The user uploads a document containing the product's specifications and usage examples to the app. The app analyzes this using NLP and image recognition, selects characters and scenarios appropriate for each specification and usage example, and automatically generates a manga. The user then looks at the generated manga, fine-tunes the dialogue and facial expressions, and downloads the final version as a PDF to present to the customer. In this way, explanations can be provided in a visually easy-to-understand manner.

[1066] Example prompt sentence:

[1067] Documentation on how to use your new tablet:

[1068] 1. How to use the touch screen

[1069] 2. Installing and Using the App

[1070] 3. Internet connection settings

[1071] As described above, the system of the present invention provides product explanations and service guides in physical stores in a visually easy-to-understand comic format, thereby improving the quality of explanations given to customers.

[1072] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1073] Step 1:

[1074] Data entry method:

[1075] Users launch a dedicated application on their smartphone or tablet and enter product information and service details. Specifically, they can enter text, upload images, and upload presentation files. Input data includes product features, usage instructions, and benefits.

[1076] input:

[1077] Product information (text, images, presentation files)

[1078] output:

[1079] Data transfer to cloud server

[1080] Step 2:

[1081] Data analysis methods:

[1082] The cloud server analyzes the received data. First, it analyzes the text information using a natural language processing (NLP) model to extract key points. Next, it analyzes the image information using image recognition technology to identify its structure.

[1083] input:

[1084] Product information received in step 1

[1085] output:

[1086] Keypoint Extraction (Text)

[1087] Identifying image structures

[1088] Specific behavior:

[1089] It uses NLP models to analyze the content of the input text and extract key information.

[1090] Image recognition software is used to analyze the structure of uploaded images and identify key elements.

[1091] Step 3:

[1092] Manga generation means:

[1093] The server selects the optimal characters and scenario based on the analysis results obtained in step 2. Using an artificial intelligence (AI) model, it automatically selects the optimal layout from pre-trained manga templates and generates explanatory materials in manga format.

[1094] input:

[1095] Keypoint extraction results

[1096] Image structure analysis results

[1097] output:

[1098] Comic book format explanatory material (for preview)

[1099] Specific behavior:

[1100] Using an AI model, the optimal characters and scenarios are selected from the analysis results.

[1101] Automatically create a manga layout based on selected elements.

[1102] Step 4:

[1103] Customization methods:

[1104] The generated manga-style explanatory material is displayed as a preview in the user interface. The user can check this preview and make any necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[1105] input:

[1106] Comic book format explanatory material (for preview)

[1107] output:

[1108] Final version with user modifications

[1109] Specific behavior:

[1110] Through the user interface, the user edits each part of the manga (dialogue, characters, background, etc.).

[1111] Edits are reflected in the preview in real time.

[1112] Step 5:

[1113] Output Method:

[1114] After the edits are complete, the cloud server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[1115] input:

[1116] Final version with user modifications

[1117] output:

[1118] Final version in PDF or image file format

[1119] Specific behavior:

[1120] The server saves and converts the final manga format description material and generates a download link.

[1121] Step 6:

[1122] Storage method:

[1123] The cloud server stores the generated comics and related data, allowing users to re-edit them later.

[1124] input:

[1125] Final version in PDF or image file format

[1126] output:

[1127] Saved manga data and related information

[1128] Specific behavior:

[1129] The server stores the generated explanatory material and related data in a database.

[1130] Data is managed and provided in a format that allows for re-editing.

[1131] 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.

[1132] A specific embodiment for carrying out the present invention will be described in detail below. This system includes means for inputting text information, image information, and presentation files for explaining business content, and means for analyzing this information. Furthermore, means for selecting characters and scenarios based on the analysis results and generating comic-style explanatory materials is provided. The generated comic-style explanatory materials can be edited by the user and output in PDF or image file format.

[1133] The system of the present invention further incorporates an emotion engine that recognizes the user's emotions. Based on the user's emotions recognized by the emotion engine, the selection of characters and scenarios can be automatically adjusted. The dialogue and character expressions of the cartoon are also adjusted to reflect the user's emotional state.

[1134] System Overview

[1135] The system operates as a web application. Users upload data related to their work through a dedicated interface. The server receives this data and analyzes it using artificial intelligence (AI) and natural language processing (NLP) models. Based on the analysis results, explanatory materials in comic form are automatically generated. An emotion engine then analyzes the user's emotions and adjusts the content of the generated comic before displaying it. Users can preview the generated materials and make any necessary corrections. The final explanatory materials in comic form can be downloaded as a PDF or image file.

[1136] Program processing

[1137] The program processing of the system will be specifically explained below.

[1138] Data entry and analysis

[1139] 1. Data entry method

[1140] The terminal displays an interface for users to input their business details, such as text information, rough sketches, or presentation files, and upload them through this interface.

[1141] 2. Data analysis methods

[1142] The server receives the uploaded data and temporarily stores it.

[1143] The server analyzes the received text information using a natural language processing (NLP) model to extract key points and important phrases, such as stages such as "planning," "implementation," and "evaluation."

[1144] The server analyzes the received image information (rough sketch) using image recognition technology, identifies elements such as diagrams and characters, and determines their relationships.

[1145] Manga generation means

[1146] 1. Character and scenario selection method

[1147] The server then selects the most suitable characters and scenario based on the analysis results, referencing pre-trained manga templates. For example, a template explaining the progress of a project may be selected.

[1148] 2. Emotion Engine

[1149] The device analyzes the user's facial expressions and tone of voice to collect emotional data and send it to the server. The server then uses an emotion engine to analyze this data and determine the user's emotional state. For example, if the user is nervous, the server will set a relaxed expression and dialogue for the character accordingly.

[1150] 3. Manga generation means

[1151] The server automatically generates a cartoon based on the selected characters and scenario. The generated cartoon is adjusted based on the results of the emotion engine. For example, if the user has a happy expression, a smiling face is added to the character.

[1152] User customization

[1153] 1. Customization methods

[1154] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[1155] Final output and saving

[1156] 1. Output Method

[1157] After the revisions are complete, the server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[1158] 2. Preservation means

[1159] The server stores the generated comics and related data, allowing users to re-edit them later.

[1160] Specific examples

[1161] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes this rough sketch and identifies each step in the process. It then selects a product development scenario and an appropriate character, and automatically generates a comic-style explanatory document. The emotion engine analyzes the user's emotions and adds a character with a relaxed expression and encouraging words to a nervous user. The user can review this document and, if necessary, change "prototype testing" to "quality testing," and finally download it in PDF format for use in internal presentations.

[1162] As described above, the system of the present invention efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and by adjusting them according to the user's emotions, it provides a form of presentation that enhances its effectiveness.

[1163] The processing flow will be explained below.

[1164] Step 1:

[1165] The terminal displays an interface for the user to input business details, and the user can upload text information, rough sketches, or presentation files through this interface.

[1166] Step 2:

[1167] The server receives the uploaded data and temporarily stores it.

[1168] Step 3:

[1169] The server analyzes the received text using a natural language processing (NLP) model to extract key points and important phrases, such as major stages such as "new product planning" and "market research."

[1170] Step 4:

[1171] The server uses image recognition technology to analyze the received image information (rough sketches), identify elements such as diagrams and characters, and determine their relationships. For example, it recognizes each step in a flow diagram as a box or arrow.

[1172] Step 5:

[1173] The server selects the most suitable characters and scenarios based on the results of NLP analysis and image recognition. This is done by referencing pre-trained manga templates. For example, a scenario in which the "development team leader" "presents a product idea" may be selected.

[1174] Step 6:

[1175] The device analyzes the user's facial expressions and tone of voice in real time to collect emotional data, which is then sent to a server.

[1176] Step 7:

[1177] The server uses an emotion engine to analyze the user's emotion data and identify the emotion the user is currently feeling. For example, if the user is nervous, the server analyzes the emotion data.

[1178] Step 8:

[1179] The server then adjusts the character's facial expression and dialogue based on the recognized emotion data. For example, if the user is nervous, a character with a relaxed expression and encouraging dialogue will be placed.

[1180] Step 9:

[1181] The server automatically generates a manga based on the selected characters and the adjusted scenario. The generated manga is temporarily saved and displayed as a preview on the user interface.

[1182] Step 10:

[1183] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[1184] Step 11:

[1185] The server updates the final comic book-style instruction material to reflect the modifications made by the user.

[1186] Step 12:

[1187] The server generates the updated and final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[1188] Step 13:

[1189] The server stores the generated comics and related data, allowing users to re-edit them later.

[1190] Example 2

[1191] 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."

[1192] When explaining business operations, it is important to convey information visually, but conventional methods require time and effort. It is also difficult to create materials that take the user's emotions into account, limiting the effectiveness of communication. Another issue is the difficulty of re-editing or customizing materials once they have been created.

[1193] 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 a means for inputting data for explaining business operations, a means for temporarily saving the input data, a means for analyzing text information and extracting key points, a means for analyzing image information and identifying a structure, a means for selecting optimal characters and scenarios based on the extracted and identified information and generating a comic-style explanatory material, a means for analyzing a user's emotions regarding the generated comic-style explanatory material and adjusting the content, a means for allowing a user to make corrections to the generated comic-style explanatory material, and a means for saving the generated comic-style explanatory material and enabling re-editing. This allows for efficient creation of materials for explaining business operations visually and intuitively and allows adjustments based on the user's emotions. Furthermore, re-editing and customization can be easily performed, thereby enhancing the effectiveness of communication.

[1194] "Means for inputting data" refers to an interface that allows a user to provide text information, image information, or a presentation file to explain the content of a business to the system.

[1195] "Means for temporarily storing input data" refers to a storage or memory area for temporarily storing user-provided data before analysis or processing.

[1196] "Means for analyzing textual information and extracting key points" refers to a program that uses natural language processing technology to analyze textual information and identify important phrases and keywords.

[1197] "Means for analyzing image information and identifying its structure" refers to a program that uses computer vision technology to analyze image information and identify the elements of diagrams and characters and their relationships.

[1198] "Means for selecting optimal characters and scenarios" refers to an algorithm for selecting optimal characters and scenarios from pre-trained templates and databases based on the analyzed information.

[1199] "Means for generating explanatory materials in comic format" refers to programs and tools for automatically creating materials in comic format based on selected characters and scenarios.

[1200] "Means for analyzing user emotions and adjusting content" refers to an algorithm that analyzes the user's facial expressions and tone of voice to determine the user's emotions and adjust the manga characters and scenario accordingly.

[1201] "Means for making edits to the generated comic-style explanatory materials" refers to an interface that allows users to edit and adjust the content of the generated comic (such as lines, character expressions, backgrounds, etc.).

[1202] "Means for saving the generated comic-format explanatory materials and enabling them to be re-edited" refers to a system that allows comic-format materials to be saved in cloud storage or a database once they have been generated, allowing them to be re-edited or updated later.

[1203] "Means to enable output in PDF or image file format" refers to the function for outputting the final comic-format explanatory materials as a PDF file or image file (JPEG, PNG, etc.).

[1204] The system for implementing this invention operates as a web application. This system is composed of a user, a terminal, and a server. The specific operation of each element will be described in detail below.

[1205] System Overview

[1206] Users upload data related to their work through a dedicated interface, typically using a form or file upload function displayed on a web page. The server receives this data and temporarily stores it in cloud storage.

[1207] Data entry and analysis

[1208] Data Entry Method

[1209] The terminal displays an interface for users to input their business details, using which they can upload text information, rough sketches, or presentation files.

[1210] Data Analysis Methods

[1211] The server receives the uploaded data and temporarily stores it. This is done using cloud storage. The server then uses an NLP (natural language processing) model to analyze the text information. This model uses a Python NLP library (such as spacy or nltk). Through the analysis, key points and important phrases are extracted. For example, stages such as "planning," "implementation," and "evaluation" are identified.

[1212] The server analyzes the received image information (rough sketches) using image recognition technology. Specifically, it uses computer vision libraries (such as OpenCV and TensorFlow) to identify elements such as diagrams and characters and determine their relationships.

[1213] Manga generation means

[1214] Character and scenario selection method

[1215] The server selects the most suitable characters and scenarios based on the analysis results. This selection is made by referring to pre-trained manga templates. These templates are trained by a generative AI model (e.g., GPT-4). For example, a template describing the progress of a project is selected.

[1216] Emotion Engine

[1217] The device uses a camera and microphone to collect data to analyze the user's facial expressions and tone of voice. The collected data is sent to a server. The server then analyzes the collected data using an emotion engine. For example, it uses a machine learning model (SVM or neural network) to classify the user's emotions. If the user is nervous, the character's facial expression and lines are set accordingly.

[1218] Manga generation means

[1219] The server automatically generates a comic based on the selected characters and scenario. This uses a generative AI model (such as DALL-E or MidJourney). The generated comic is adjusted based on the results of the emotion engine. For example, if the user has a happy expression, a smiling face is added to the character.

[1220] User customization

[1221] The device provides an interface for users to preview the generated manga and make any necessary edits. Specifically, it has drag-and-drop and text editing functions. Users can edit dialogue, change character expressions, adjust backgrounds, and more.

[1222] Final output and saving

[1223] Output Method

[1224] After the revisions are complete, the server generates the final comic-style explanatory material in PDF or image file format using a library (such as ReportLab or Pillow) and provides the user with a download link for the generated file.

[1225] Preservation means

[1226] The server saves the generated comics and related data. The data is stored in a database (e.g., PostgreSQL or MongoDB). This allows users to re-edit the data later and allows history management.

[1227] Specific examples

[1228] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes the rough sketch and identifies each step in the process. It then selects a product development scenario and an appropriate character, automatically generating a comic-style explanatory document. The emotion engine analyzes the user's emotions and adds a character with a relaxed expression and encouraging words to a nervous user. The user can review the document and, if necessary, change "prototype testing" to "quality testing," and finally download it as a PDF for use in internal presentations.

[1229] Examples of prompt statements

[1230] - "Please upload a rough sketch to create a comic-style document that explains the new product development process. Which stage is the most important in terms of trends?"

[1231] - "Enable the emotion engine and adjust the character's facial expressions. Tell us their current emotional state."

[1232] In this way, this system efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and by adjusting them according to the user's emotions, it enhances the effectiveness of presentations.

[1233] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1234] Step 1: Enter your data

[1235] The terminal displays an interface for the user to input data related to the business content. This interface includes a text input field, a rough sketch upload function, and a presentation file upload function. The input data can be text information, a rough sketch, or a presentation file. The input data can be provided by the user by direct input or file upload.

[1236] Step 2: Save your data

[1237] The terminal sends the data entered by the user to the server, which then temporarily stores the received data in cloud storage. For example, text information, image information (rough sketches), and presentation files are temporarily stored in the cloud storage.

[1238] Step 3: Analyzing the text

[1239] The server analyzes the temporarily stored text information using an NLP (natural language processing) model. In this process, Python NLP libraries (e.g., spacy, nltk) are used to extract key points and important phrases from the text information. As a result, important phrases such as "planning," "implementation," and "evaluation" are output.

[1240] Step 4: Analyze image information

[1241] The server analyzes the temporarily stored image information (rough sketches) using computer vision technology. This analysis uses libraries such as OpenCV and TensorFlow. The server identifies elements such as diagrams and characters from the rough sketches and determines their relationships. For example, the server identifies diagrams showing each stage of a project and determines their interrelationships.

[1242] Step 5: Character and scenario selection

[1243] The server selects the most suitable characters and scenarios based on key points and elements extracted from text and image information. This selection is performed by referring to pre-trained manga templates. For example, a template explaining the progress of a project may be selected.

[1244] Step 6: Sentiment Analysis

[1245] The device uses a camera and microphone to analyze the user's facial expressions and voice, and the collected emotional data is sent to a server.

[1246] The server analyzes the collected data using an emotion engine, which determines what emotions the user is feeling. For example, it can determine if the user is nervous. The results of the emotion analysis are output and used to adjust the character's facial expressions and dialogue.

[1247] Step 7: Generate the comic

[1248] The server automatically generates a manga based on the selected characters and scenario. This generation uses generative AI models such as DALL-E and MidJourney. The character's facial expressions and lines are adjusted based on the results of the emotion analysis. The generated manga is output, reflecting the results of the emotion analysis.

[1249] Step 8: Providing customizations

[1250] The device provides an interface for users to preview and modify the generated manga. This interface includes drag-and-drop and text editing functions. Users can modify dialogue, change character expressions, adjust backgrounds, and more. The modified and adjusted manga is output based on the user's input.

[1251] Step 9: Final Output

[1252] The server generates the final, edited version of the comic-style explanatory material in PDF or image file format using libraries such as ReportLab or Pillow. A download link for the generated file is provided to the user. The final output PDF or image file is provided to the user.

[1253] Step 10: Save your data

[1254] The server stores the generated manga and related data in a database (e.g., PostgreSQL, MongoDB), allowing users to re-edit the data later. The saved data is output in a format that allows for re-editing and history management.

[1255] Through the above processing steps, the system can efficiently generate comic-style materials that allow users to visually and intuitively communicate their work content, and can adjust the content according to the user's emotions.

[1256] (Application example 2)

[1257] 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."

[1258] Conventional work explanation materials generally use text or simple illustrations, making it difficult to present information in a visually understandable format. Furthermore, there is no means of providing appropriate information based on employees' emotions, which reduces the effectiveness of training and reduces work efficiency. To address these issues, the present invention aims to provide a system that explains work content in comic form and automatically adjusts based on emotions.

[1259] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1260] In this invention, the server includes means for inputting text information, image information, or a presentation file for explaining the content of work, means for analyzing the input text information and extracting key points, means for analyzing the input image information and identifying a structure, means for selecting optimal characters and scenarios based on the extracted and identified information and generating explanatory materials in comic form, means for automatically adjusting the characters and scenarios using an emotion engine that recognizes the user's emotions, and means for the user to make corrections to the generated explanatory materials in comic form. This makes it possible to provide information in a visually easy-to-understand format and provide optimal information according to the emotions of employees.

[1261] "Job Description" refers to detailed information about a specified task or process.

[1262] "Textual information" refers to data provided in text format.

[1263] "Image information" means data provided in a visual format, such as a photograph, illustration, or diagram.

[1264] A "presentation file" is a digital document created to explain business content in slide format.

[1265] The "emotion engine" is a system that analyzes a user's facial expressions, tone of voice, etc. to identify emotions.

[1266] "Means for extracting key points" is a function for identifying and extracting important information and phrases from input text information.

[1267] The "means for identifying structure" is a function for analyzing input image information and identifying its contents and relationships.

[1268] The "means for selecting characters and scenarios" is a function for selecting the most suitable characters and scenarios based on the extracted and identified information.

[1269] "Means for generating explanatory materials in comic format" is a function for creating materials that visually explain business details in comic format based on selected characters and scenarios.

[1270] "Means for automatic adjustment" is a function that automatically changes the content of characters and scenarios based on the user's emotions identified by the emotion engine.

[1271] "Means by which users can make modifications" is a function that provides an interface that allows users to freely edit and modify the generated comic-style explanatory material.

[1272] MODE FOR CARRYING OUT THE INVENTION

[1273] The following describes in detail a specific embodiment of the present invention. This system generates job explanation materials in cartoon format and automatically adjusts the content using an emotion engine. The entire system is designed to enable effective employee training and job explanations in factories using smart glasses.

[1274] Hardware and Software Configuration

[1275] Hardware:

[1276] Smart glasses (e.g. Microsoft HoloLens)

[1277] Server (Cloud or On-Premise)

[1278] software:

[1279] Natural Language Processing (NLP) models (e.g., Google BERT)

[1280] Image recognition technology (e.g., OpenCV)

[1281] Sentiment analysis engine (e.g. Microsoft Azure Emotion API)

[1282] Processing flow

[1283] 1. Data Entry

[1284] The terminal (smart glasses) provides an interface for inputting text information and presentation files related to business content. Users use the smart glasses to scan or upload data related to business materials.

[1285] 2. Data Analysis

[1286] The server analyzes the input text information using an NLP model to extract key business points, and also analyzes image information using image recognition technology to identify structure and important elements.

[1287] 3. Manga generation

[1288] The server selects the most suitable characters and scenario based on the key points and the identified structure, and generates explanatory materials in comic form. At the same time, an emotion analysis engine analyzes the user's facial expressions and tone of voice to set appropriate character expressions and lines.

[1289] 4. User Modifications

[1290] The generated comic-style explanatory materials can be previewed on the smart glasses and edited as needed, such as changing dialogue, adjusting character expressions, and adding backgrounds.

[1291] 5. Final output

[1292] Once the edits are complete, the document is generated as a PDF or image file and saved on the server. The final product can then be downloaded by the user via a download link.

[1293] Specific examples

[1294] For example, consider a case where an employee learning how to set up a new production line uses smart glasses to scan their work, and AI analyzes the content to generate a comic-style document. If the emotion engine detects that the user is nervous, it adds a character with a relaxed expression and reassuring words. The user can then review and edit the document, and finally save it as a PDF to use as training material.

[1295] Prompt Sentence Examples

[1296] "Scan the job description and generate a cartoon-style document, with characters that have relaxed expressions to make it easier for employees to understand."

[1297] By combining the above elements, the present invention makes it possible to quickly generate visually easy-to-understand work explanation materials and provide appropriate information according to the emotions of employees.

[1298] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1299] Step 1: Data entry

[1300] The terminal (smart glasses) provides an interface for inputting text information and presentation files related to work content. Users use the smart glasses to scan or upload data related to work materials. The input data is text-based work instructions and image-based presentation files.

[1301] Step 2: Data analysis

[1302] The server receives the text information sent from the device and analyzes it using a natural language processing (NLP) model (e.g., Google BERT). During the analysis, important steps and key points of the business (e.g., "work preparation," "equipment setup," and "quality check") are extracted. At the same time, image information is analyzed using image recognition technology (e.g., OpenCV) to identify structure and important elements (e.g., diagrams, equipment layout). These analysis results are used in the next step.

[1303] Step 3: Character and scenario selection

[1304] The server automatically selects the most suitable characters and scenarios based on the keypoints extracted and the structure identified in step 2. This selection uses pre-trained manga templates. For example, a scenario and its characters that explain the setup procedure for a manufacturing line are selected.

[1305] Step 4: Sentiment Analysis

[1306] The device analyzes the user's facial expressions and tone of voice using an emotion analysis engine (e.g., Microsoft Azure Emotion API) and sends the user's emotional data to the server. The emotional data (e.g., "tense," "relaxed," "excited") is used to adjust the content of the comic in a later step.

[1307] Step 5: Manga Generation

[1308] The server generates explanatory materials in comic form based on the characters and scenario selected in step 3. Furthermore, the character's facial expressions and lines are automatically adjusted based on the results of the emotion analysis engine. For example, if the user is nervous, a character with a relaxed expression and encouraging lines will be set.

[1309] Step 6: User Modifications

[1310] The generated comic-style explanatory materials are previewed on the device. The user can use smart glasses to check the preview and make any necessary corrections (e.g., changing dialogue, adjusting character expressions, adding backgrounds). The corrected data is then saved on the server.

[1311] Step 7: Final output

[1312] Once the edits are complete, the document is generated as a PDF or image file on the server, and a download link is provided to the user. The final product is then saved in the cloud, allowing for future editing.

[1313] Each step of this system presents work details in a visually easy-to-understand format, enabling appropriate information to be provided based on the employee's emotions.

[1314] 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.

[1315] 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.

[1316] 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.

[1317] [Fourth embodiment]

[1318] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1319] 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.

[1320] 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).

[1321] 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.

[1322] 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.

[1323] 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).

[1324] 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.

[1325] 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.

[1326] 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.

[1327] 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.

[1328] 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.

[1329] 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.

[1330] 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."

[1331] A specific embodiment for carrying out the present invention will be described in detail below. This system includes means for inputting text information, image information, and presentation files for explaining business content, and means for analyzing this information. Furthermore, means for selecting characters and scenarios based on the analysis results and generating comic-style explanatory materials is provided. The generated comic-style explanatory materials can be edited by the user and output in PDF or image file format.

[1332] System Overview

[1333] The system operates as a web application. Users upload data related to their work through a dedicated interface. The server receives the data and analyzes it using artificial intelligence (AI) and natural language processing (NLP) models. Based on the analysis results, a comic-style explanatory document is automatically generated. Users can preview the generated document and make any necessary corrections. The final comic-style explanatory document can be downloaded as a PDF or image file.

[1334] Program processing

[1335] The program processing of the system will be specifically explained below.

[1336] Data entry and analysis

[1337] 1. Data entry method

[1338] The terminal displays an interface for users to input their business details: they can upload text information, rough sketches, or presentation files.

[1339] 2. Data analysis methods

[1340] The server receives the uploaded data, analyzes the text information using an NLP model to extract key points, and uses image recognition technology to identify the structure of the image information.

[1341] Manga generation means

[1342] 1. Character and scenario selection method

[1343] The server selects the most suitable characters and scenarios based on the analysis results, using pre-trained manga templates.

[1344] 2. Manga generation means

[1345] The server automatically generates a manga based on the selected characters and scenario. The generated manga is temporarily saved and displayed as a preview on the user interface.

[1346] User customization

[1347] 1. Customization methods

[1348] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[1349] Final output and saving

[1350] 1. Output Method

[1351] After the revisions are complete, the server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[1352] 2. Preservation means

[1353] The server stores the generated comics and related data, allowing users to re-edit them later.

[1354] Specific examples

[1355] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes the rough sketch and identifies each step in the process. It then selects a product development scenario and appropriate characters, and automatically generates a comic-style explanatory document. The user can review the document and make adjustments, such as changing the line "prototype testing" to "quality testing." Finally, the document can be downloaded in PDF format and used for internal presentations.

[1356] As described above, the system of the present invention efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and provides a format that is easy for users to use.

[1357] The processing flow will be explained below.

[1358] Step 1:

[1359] The terminal displays an interface for the user to input business details, and the user can upload text information, rough sketches, or presentation files through this interface.

[1360] Step 2:

[1361] The server receives the uploaded data and temporarily stores it.

[1362] Step 3:

[1363] The server analyzes the received text using natural language processing (NLP) models to extract key points and important phrases, such as stages in a business process or important actions.

[1364] Step 4:

[1365] The server analyzes the received image information (rough sketch) using image recognition technology, identifies elements such as diagrams and characters, and determines their relationships.

[1366] Step 5:

[1367] The server selects the optimal characters and scenarios based on the results of NLP analysis and image recognition. This is done by referencing pre-trained manga templates. For example, a template related to a business flow is selected, and a scene in which a character performs a specific business action is created.

[1368] Step 6:

[1369] The server automatically generates a manga based on the selected characters and scenario. Each character performs appropriate actions and speaks lines in the designated stage. The background is also selected to match the scenario.

[1370] Step 7:

[1371] The server temporarily stores the generated comic and displays it as a preview on the user interface.

[1372] Step 8:

[1373] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[1374] Step 9:

[1375] The server updates the final comic book-style instruction material to reflect the modifications made by the user.

[1376] Step 10:

[1377] The server generates the updated and final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[1378] Step 11:

[1379] The server stores the generated comics and related data, allowing users to re-edit them later.

[1380] Example 1

[1381] 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."

[1382] Conventional systems for creating explanatory materials lack the means to visually and intuitively convey the content of work, and creating materials under specific conditions is often complex and time-consuming. There is a demand for systems that allow users to efficiently explain the content of work.

[1383] 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.

[1384] In this invention, the server includes means for inputting text information, image information, or a presentation file for explaining business content, means for analyzing the input text information and extracting key points, means for analyzing the input image information and identifying a structure, means for selecting optimal characters and scenarios based on the extracted and identified information and generating comic-style explanatory materials, means for allowing a user to make corrections to the generated comic-style explanatory materials, and means for saving the generated comic-style explanatory materials so that they can be re-edited later. This makes it possible to provide a system for efficiently generating comic-style explanatory materials for visually and intuitively conveying business content, and for allowing a user to easily modify and save them.

[1385] "Text information" is information expressed as sentences or text, and is a data format used to explain business content.

[1386] "Image information" is data provided as a visual representation, including photographs, illustrations, diagrams, and the like.

[1387] A "presentation file" is a slide-format file used to explain business operations, and is a document that includes images, text information, graphs, and the like.

[1388] An "input method" is the method or interface by which a user provides data to a system, typically a file upload function or an input form.

[1389] "Means for analysis" refers to the system functions for processing input data and extracting necessary information and patterns, and includes natural language processing and image recognition technology.

[1390] "Key points" are important elements or themes extracted from the analyzed textual and image information, and are central information for understanding and explaining the business content.

[1391] "Means for identifying structure" refers to techniques or methods for analyzing input image information and identifying components and relationships.

[1392] "Characters" are characters or characters that appear in comic-style explanatory materials, and are elements with specific roles and personalities.

[1393] A "scenario" is a plot or story that characters follow, a storyline that effectively communicates the contents of explanatory material.

[1394] "Means of generation" refers to the functions and processes for creating explanatory materials in comic format based on input data and analysis results.

[1395] "Means by which the user can make modifications" refers to an interface or tool that allows the user to make changes or adjustments to the generated comic-style explanatory material.

[1396] "Means for saving" refers to a system function that allows the generated comic-style explanatory materials and related data to be retained and made available for reuse and re-editing at a later date.

[1397] "Means for enabling re-editing" refers to a function or method for making previously generated or saved explanatory material editable again.

[1398] Specific embodiments for carrying out the invention will be described in detail below.

[1399] System Overview

[1400] The system operates as a web application. Users upload data related to their work through a dedicated interface. The server receives the data and analyzes it using artificial intelligence (AI) and natural language processing (NLP) models. Based on the analysis results, a comic-style explanatory document is automatically generated. Users can preview the generated document and make any necessary corrections. The final comic-style explanatory document can be downloaded as a PDF or image file.

[1401] Data entry and analysis

[1402] Users use their devices to upload text, image, or presentation files to explain their work. The devices provide an interface to the users and send the input data to the server. The server then analyzes the text using an NLP model (e.g., GPT-4 or BERT) to extract key points. For image data, the server uses image recognition technology (e.g., Tesseract or OpenCV) to identify the structure.

[1403] manga generation

[1404] The server selects the optimal characters and scenario based on the analysis results. It uses pre-trained manga templates and character libraries (e.g., DCGAN, StyleGAN). The server then creates an automatically generated manga based on the selected characters and scenario. This may involve using software such as Unity or Unreal Engine. The generated manga is temporarily saved and displayed as a preview in the user interface.

[1405] User customization

[1406] Users can preview the video on their devices and make any necessary edits. The interface supports editing dialogue, changing character expressions, adjusting backgrounds, etc. Users can make changes using text boxes and drop-down menus.

[1407] Final output and saving

[1408] After the user has completed the revisions, the server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link. The server also provides a means for storing the generated comic and related data so that the user can re-edit it later. This may involve the use of a database (e.g., MySQL, MongoDB).

[1409] Specific examples

[1410] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes the rough sketch and identifies each step in the process. It then selects a product development scenario and appropriate characters, and automatically generates a comic-style explanatory document. The user can review the document and make adjustments, such as changing the line "prototype testing" to "quality testing." Finally, the document can be downloaded in PDF format and used for internal presentations.

[1411] Prompt Sentence Examples

[1412] Business: New product development process

[1413] Rough sketch: Attachment 1.png

[1414] Analysis purpose: Generate explanatory materials in comic format

[1415] As described above, the system of the present invention efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and provides a format that users can easily modify and save.

[1416] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1417] Step 1:

[1418] The user uploads text information, image information, or a presentation file from the terminal to explain the details of the work.

[1419] Specific actions: A user uses the web application interface to enter text information into an input form and to select and upload the required files using the file upload button.

[1420] Input: Text, images, or presentation files entered by the user.

[1421] Output: Uploaded data is sent to the server.

[1422] Step 2:

[1423] The server receives the uploaded text information and analyzes it using a natural language processing (NLP) model.

[1424] Specific operation: The server tokenizes the text information and extracts key points using an NLP model (e.g., GPT-4 or BERT).

[1425] Input: Textual information received from the user.

[1426] Output: Analysis results with extracted key points, e.g., key phrases such as "project launch," "product design," and "market research."

[1427] Step 3:

[1428] The server receives the uploaded image information and analyzes it using image recognition technology.

[1429] What happens: The server reads the image and uses OCR technology (e.g., Tesseract or OpenCV) to extract text from the image and, if necessary, identify structures within the image.

[1430] Input: Image information received from the user.

[1431] Output: Extracted text and identified structural information from the image.

[1432] Step 4:

[1433] The server selects the optimal characters and scenarios based on the analysis results.

[1434] Specific operation: The server refers to pre-trained manga templates and character libraries (e.g., DCGAN, StyleGAN) and selects characters and scenarios appropriate for the task.

[1435] Input: Keypoints, structural information from images.

[1436] Output: Selected characters and scenarios.

[1437] Step 5:

[1438] The server automatically generates a manga based on the selected characters and scenario.

[1439] Specific operation: The server generates a scene by arranging the position, facial expression, and lines of each character based on the selected template. This process may use software such as Unity or Unreal Engine.

[1440] Input: Selected characters and scenario.

[1441] Output: Each page of the automatically generated comic.

[1442] Step 6:

[1443] The terminal provides the user with a preview of the generated comic.

[1444] Specific operation: The server temporarily saves the generated manga and displays it as a preview in the user interface.

[1445] Input: Each page of the automatically generated comic.

[1446] Output: Preview data to the user.

[1447] Step 7:

[1448] The user checks the preview and makes any necessary corrections.

[1449] Specific operations: The user can modify dialogue, change character expressions, adjust the background, etc. through the interface.

[1450] Input: Preview data.

[1451] Output: The final comic, as modified by the user.

[1452] Step 8:

[1453] The server saves the comic-style explanatory material after the user has completed the edits and outputs it in PDF or image file format.

[1454] What it does: The server saves the final manga, converts it to PDF or JPEG format, provides a download link to the user, and stores it in a database so that it can be re-edited later.

[1455] Input: The final comic, as revised by the user.

[1456] Output: Final manga in PDF or image file format, re-editable saved data.

[1457] (Application example 1)

[1458] 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."

[1459] Modern brick-and-mortar stores offer a wide variety of products and services, and it is important to effectively communicate their features and how to use them to customers. However, traditional methods, such as using text and diagrams, can be difficult to understand. Furthermore, the quality of explanations can vary depending on the store staff's explanation skills and time constraints. Therefore, a new method is needed that can quickly provide customers with visually easy-to-understand, consistent information.

[1460] 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.

[1461] In this invention, the server includes means for inputting text information, image information, or a presentation file to explain business operations, means for analyzing the input text information and extracting key points, means for analyzing the input image information and identifying the structure, means for inputting product information and service details for a physical store and displaying them in a comic format, and means for allowing the user to make corrections to the generated comic-format explanatory materials. This allows product explanations and service guides for physical stores to be provided in a visually easy-to-understand comic format, thereby enabling effective information transmission to customers.

[1462] "Business content" is information about the specific tasks and activities performed by a company or organization.

[1463] "Character information" is text data such as sentences and words.

[1464] "Image information" refers to visual data such as photographs and illustrations.

[1465] A "presentation file" is a document format that organizes and visually presents information in slide format.

[1466] "Input means" refers to devices or interfaces that input data such as text information, image information, and presentation files into the system.

[1467] "Means of analysis" refers to software or algorithms that break down and analyze input information to extract key points.

[1468] A "means for extracting key points" is a method or device for identifying the main information or content from input text information.

[1469] "Means for identifying structure" refers to technology or devices that recognize the elements and arrangement of input image information.

[1470] "Means for selecting optimal characters and scenarios" refers to techniques and methods for determining appropriate characters and story flow based on the analysis results.

[1471] "Means for generating explanatory materials in comic format" refers to technology or software that automatically generates the layout and content of a comic based on selected characters and a scenario.

[1472] "Means by which a user can make corrections to the generated comic-style explanatory material" refers to an interface or editing tool that allows a user to check the content of the generated comic and make any necessary changes.

[1473] A "brick and mortar store" is a store that has a physical location and where customers can visit in person to purchase goods or services.

[1474] "Product information" means data and descriptions about a product's characteristics, uses, benefits, etc.

[1475] "Service details" is information about the details of various services provided by the store and how to use them.

[1476] "Means for displaying in comic format" refers to technology or devices that display product information or service content in the form of comics that are visually easy to understand.

[1477] A specific embodiment of the present invention will be described in detail below. The present invention is a system for providing product explanations and service guides for brick-and-mortar stores in a visually easy-to-understand comic format.

[1478] System configuration

[1479] This system operates primarily using devices such as smartphones or tablets and a cloud server. Users install a dedicated application on their device and use it to input business details, product information, and service details. The input information is sent to the cloud server, where it is analyzed and processed to generate the manga.

[1480] Hardware and software used:

[1481] Hardware: Smartphone, tablet (iOS or Android)

[1482] Software: Dedicated applications, cloud servers, artificial intelligence (AI) models, natural language processing (NLP) models

[1483] The program proceeds as follows:

[1484] 1. Data entry method:

[1485] Users start a dedicated application and input product information and service details. Input methods include text input, image upload, and presentation file upload.

[1486] 2. Data analysis methods:

[1487] The cloud server receives the uploaded data and uses NLP models to analyze the text information and extract key points, while image recognition technology is used to identify the structure of the image information.

[1488] 3. Manga generation method:

[1489] The server selects the most suitable characters and scenario based on the analysis results and automatically generates explanatory materials in the form of a manga. The generated manga is temporarily saved and displayed as a preview on the user interface.

[1490] 4. Customization methods:

[1491] Users can use the interface to check the preview and make any necessary edits, such as modifying dialogue, changing character expressions, or adjusting the background.

[1492] 5. Output Method:

[1493] Finally, the revised comic-style explanatory material is generated as a PDF or image file, and a download link is provided to the user.

[1494] 6. Preservation means:

[1495] The cloud server stores the generated comics and related data, allowing users to re-edit them later.

[1496] Specific examples

[1497] For example, consider a scenario in which a user is explaining to a customer how to use a newly arrived electronic device. The user uploads a document containing the product's specifications and usage examples to the app. The app analyzes this using NLP and image recognition, selects characters and scenarios appropriate for each specification and usage example, and automatically generates a manga. The user then looks at the generated manga, fine-tunes the dialogue and facial expressions, and downloads the final version as a PDF to present to the customer. In this way, explanations can be provided in a visually easy-to-understand manner.

[1498] Example prompt sentence:

[1499] Documentation on how to use your new tablet:

[1500] 1. How to use the touch screen

[1501] 2. Installing and Using the App

[1502] 3. Internet connection settings

[1503] As described above, the system of the present invention provides product explanations and service guides in physical stores in a visually easy-to-understand comic format, thereby improving the quality of explanations given to customers.

[1504] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1505] Step 1:

[1506] Data entry method:

[1507] Users launch a dedicated application on their smartphone or tablet and enter product information and service details. Specifically, they can enter text, upload images, and upload presentation files. Input data includes product features, usage instructions, and benefits.

[1508] input:

[1509] Product information (text, images, presentation files)

[1510] output:

[1511] Data transfer to cloud server

[1512] Step 2:

[1513] Data analysis methods:

[1514] The cloud server analyzes the received data. First, it analyzes the text information using a natural language processing (NLP) model to extract key points. Next, it analyzes the image information using image recognition technology to identify its structure.

[1515] input:

[1516] Product information received in step 1

[1517] output:

[1518] Keypoint Extraction (Text)

[1519] Identifying image structures

[1520] Specific behavior:

[1521] It uses NLP models to analyze the content of the input text and extract key information.

[1522] Image recognition software is used to analyze the structure of uploaded images and identify key elements.

[1523] Step 3:

[1524] Manga generation means:

[1525] The server selects the optimal characters and scenario based on the analysis results obtained in step 2. Using an artificial intelligence (AI) model, it automatically selects the optimal layout from pre-trained manga templates and generates explanatory materials in manga format.

[1526] input:

[1527] Keypoint extraction results

[1528] Image structure analysis results

[1529] output:

[1530] Comic book format explanatory material (for preview)

[1531] Specific behavior:

[1532] Using an AI model, the optimal characters and scenarios are selected from the analysis results.

[1533] Automatically create a manga layout based on selected elements.

[1534] Step 4:

[1535] Customization methods:

[1536] The generated manga-style explanatory material is displayed as a preview in the user interface. The user can check this preview and make any necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[1537] input:

[1538] Comic book format explanatory material (for preview)

[1539] output:

[1540] Final version with user modifications

[1541] Specific behavior:

[1542] Through the user interface, the user edits each part of the manga (dialogue, characters, background, etc.).

[1543] Edits are reflected in the preview in real time.

[1544] Step 5:

[1545] Output Method:

[1546] After the edits are complete, the cloud server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[1547] input:

[1548] Final version with user modifications

[1549] output:

[1550] Final version in PDF or image file format

[1551] Specific behavior:

[1552] The server saves and converts the final manga format description material and generates a download link.

[1553] Step 6:

[1554] Storage method:

[1555] The cloud server stores the generated comics and related data, allowing users to re-edit them later.

[1556] input:

[1557] Final version in PDF or image file format

[1558] output:

[1559] Saved manga data and related information

[1560] Specific behavior:

[1561] The server stores the generated explanatory material and related data in a database.

[1562] Data is managed and provided in a format that allows for re-editing.

[1563] 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.

[1564] A specific embodiment for carrying out the present invention will be described in detail below. This system includes means for inputting text information, image information, and presentation files for explaining business content, and means for analyzing this information. Furthermore, means for selecting characters and scenarios based on the analysis results and generating comic-style explanatory materials is provided. The generated comic-style explanatory materials can be edited by the user and output in PDF or image file format.

[1565] The system of the present invention further incorporates an emotion engine that recognizes the user's emotions. Based on the user's emotions recognized by the emotion engine, the selection of characters and scenarios can be automatically adjusted. The dialogue and character expressions of the cartoon are also adjusted to reflect the user's emotional state.

[1566] System Overview

[1567] The system operates as a web application. Users upload data related to their work through a dedicated interface. The server receives this data and analyzes it using artificial intelligence (AI) and natural language processing (NLP) models. Based on the analysis results, explanatory materials in comic form are automatically generated. An emotion engine then analyzes the user's emotions and adjusts the content of the generated comic before displaying it. Users can preview the generated materials and make any necessary corrections. The final explanatory materials in comic form can be downloaded as a PDF or image file.

[1568] Program processing

[1569] The program processing of the system will be specifically explained below.

[1570] Data entry and analysis

[1571] 1. Data entry method

[1572] The terminal displays an interface for users to input their business details, such as text information, rough sketches, or presentation files, and upload them through this interface.

[1573] 2. Data analysis methods

[1574] The server receives the uploaded data and temporarily stores it.

[1575] The server analyzes the received text information using a natural language processing (NLP) model to extract key points and important phrases, such as stages such as "planning," "implementation," and "evaluation."

[1576] The server analyzes the received image information (rough sketch) using image recognition technology, identifies elements such as diagrams and characters, and determines their relationships.

[1577] Manga generation means

[1578] 1. Character and scenario selection method

[1579] The server then selects the most suitable characters and scenario based on the analysis results, referencing pre-trained manga templates. For example, a template explaining the progress of a project may be selected.

[1580] 2. Emotion Engine

[1581] The device analyzes the user's facial expressions and tone of voice to collect emotional data and send it to the server. The server then uses an emotion engine to analyze this data and determine the user's emotional state. For example, if the user is nervous, the server will set a relaxed expression and dialogue for the character accordingly.

[1582] 3. Manga generation means

[1583] The server automatically generates a cartoon based on the selected characters and scenario. The generated cartoon is adjusted based on the results of the emotion engine. For example, if the user has a happy expression, a smiling face is added to the character.

[1584] User customization

[1585] 1. Customization methods

[1586] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[1587] Final output and saving

[1588] 1. Output Method

[1589] After the revisions are complete, the server generates the final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[1590] 2. Preservation means

[1591] The server stores the generated comics and related data, allowing users to re-edit them later.

[1592] Specific examples

[1593] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes this rough sketch and identifies each step in the process. It then selects a product development scenario and an appropriate character, and automatically generates a comic-style explanatory document. The emotion engine analyzes the user's emotions and adds a character with a relaxed expression and encouraging words to a nervous user. The user can review this document and, if necessary, change "prototype testing" to "quality testing," and finally download it in PDF format for use in internal presentations.

[1594] As described above, the system of the present invention efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and by adjusting them according to the user's emotions, it provides a form of presentation that enhances its effectiveness.

[1595] The processing flow will be explained below.

[1596] Step 1:

[1597] The terminal displays an interface for the user to input business details, and the user can upload text information, rough sketches, or presentation files through this interface.

[1598] Step 2:

[1599] The server receives the uploaded data and temporarily stores it.

[1600] Step 3:

[1601] The server analyzes the received text using a natural language processing (NLP) model to extract key points and important phrases, such as major stages such as "new product planning" and "market research."

[1602] Step 4:

[1603] The server uses image recognition technology to analyze the received image information (rough sketches), identify elements such as diagrams and characters, and determine their relationships. For example, it recognizes each step in a flow diagram as a box or arrow.

[1604] Step 5:

[1605] The server selects the most suitable characters and scenarios based on the results of NLP analysis and image recognition. This is done by referencing pre-trained manga templates. For example, a scenario in which the "development team leader" "presents a product idea" may be selected.

[1606] Step 6:

[1607] The device analyzes the user's facial expressions and tone of voice in real time to collect emotional data, which is then sent to a server.

[1608] Step 7:

[1609] The server uses an emotion engine to analyze the user's emotion data and identify the emotion the user is currently feeling. For example, if the user is nervous, the server analyzes the emotion data.

[1610] Step 8:

[1611] The server then adjusts the character's facial expression and dialogue based on the recognized emotion data. For example, if the user is nervous, a character with a relaxed expression and encouraging dialogue will be placed.

[1612] Step 9:

[1613] The server automatically generates a manga based on the selected characters and the adjusted scenario. The generated manga is temporarily saved and displayed as a preview on the user interface.

[1614] Step 10:

[1615] The device provides an interface for the user to check the preview and make necessary edits, such as modifying dialogue, changing character expressions, and adjusting the background.

[1616] Step 11:

[1617] The server updates the final comic book-style instruction material to reflect the modifications made by the user.

[1618] Step 12:

[1619] The server generates the updated and final comic-style explanatory material in PDF or image file format and provides the user with a download link.

[1620] Step 13:

[1621] The server stores the generated comics and related data, allowing users to re-edit them later.

[1622] Example 2

[1623] 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."

[1624] When explaining business operations, it is important to convey information visually, but conventional methods require time and effort. It is also difficult to create materials that take the user's emotions into account, limiting the effectiveness of communication. Another issue is the difficulty of re-editing or customizing materials once they have been created.

[1625] 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 a means for inputting data for explaining business operations, a means for temporarily saving the input data, a means for analyzing text information and extracting key points, a means for analyzing image information and identifying a structure, a means for selecting optimal characters and scenarios based on the extracted and identified information and generating a comic-style explanatory material, a means for analyzing a user's emotions regarding the generated comic-style explanatory material and adjusting the content, a means for allowing a user to make corrections to the generated comic-style explanatory material, and a means for saving the generated comic-style explanatory material and enabling re-editing. This allows for efficient creation of materials for explaining business operations visually and intuitively and allows adjustments based on the user's emotions. Furthermore, re-editing and customization can be easily performed, thereby enhancing the effectiveness of communication.

[1626] "Means for inputting data" refers to an interface that allows a user to provide text information, image information, or a presentation file to explain the content of a business to the system.

[1627] "Means for temporarily storing input data" refers to a storage or memory area for temporarily storing user-provided data before analysis or processing.

[1628] "Means for analyzing textual information and extracting key points" refers to a program that uses natural language processing technology to analyze textual information and identify important phrases and keywords.

[1629] "Means for analyzing image information and identifying its structure" refers to a program that uses computer vision technology to analyze image information and identify the elements of diagrams and characters and their relationships.

[1630] "Means for selecting optimal characters and scenarios" refers to an algorithm for selecting optimal characters and scenarios from pre-trained templates and databases based on the analyzed information.

[1631] "Means for generating explanatory materials in comic format" refers to programs and tools for automatically creating materials in comic format based on selected characters and scenarios.

[1632] "Means for analyzing user emotions and adjusting content" refers to an algorithm that analyzes the user's facial expressions and tone of voice to determine the user's emotions and adjust the manga characters and scenario accordingly.

[1633] "Means for making edits to the generated comic-style explanatory materials" refers to an interface that allows users to edit and adjust the content of the generated comic (such as lines, character expressions, backgrounds, etc.).

[1634] "Means for saving the generated comic-format explanatory materials and enabling them to be re-edited" refers to a system that allows comic-format materials to be saved in cloud storage or a database once they have been generated, allowing them to be re-edited or updated later.

[1635] "Means to enable output in PDF or image file format" refers to the function for outputting the final comic-format explanatory materials as a PDF file or image file (JPEG, PNG, etc.).

[1636] The system for implementing this invention operates as a web application. This system is composed of a user, a terminal, and a server. The specific operation of each element will be described in detail below.

[1637] System Overview

[1638] Users upload data related to their work through a dedicated interface, typically using a form or file upload function displayed on a web page. The server receives this data and temporarily stores it in cloud storage.

[1639] Data entry and analysis

[1640] Data Entry Method

[1641] The terminal displays an interface for users to input their business details, using which they can upload text information, rough sketches, or presentation files.

[1642] Data Analysis Methods

[1643] The server receives the uploaded data and temporarily stores it. This is done using cloud storage. The server then uses an NLP (natural language processing) model to analyze the text information. This model uses a Python NLP library (such as spacy or nltk). Through the analysis, key points and important phrases are extracted. For example, stages such as "planning," "implementation," and "evaluation" are identified.

[1644] The server analyzes the received image information (rough sketches) using image recognition technology. Specifically, it uses computer vision libraries (such as OpenCV and TensorFlow) to identify elements such as diagrams and characters and determine their relationships.

[1645] Manga generation means

[1646] Character and scenario selection method

[1647] The server selects the most suitable characters and scenarios based on the analysis results. This selection is made by referring to pre-trained manga templates. These templates are trained by a generative AI model (e.g., GPT-4). For example, a template describing the progress of a project is selected.

[1648] Emotion Engine

[1649] The device uses a camera and microphone to collect data to analyze the user's facial expressions and tone of voice. The collected data is sent to a server. The server then analyzes the collected data using an emotion engine. For example, it uses a machine learning model (SVM or neural network) to classify the user's emotions. If the user is nervous, the character's facial expression and lines are set accordingly.

[1650] Manga generation means

[1651] The server automatically generates a comic based on the selected characters and scenario. This uses a generative AI model (such as DALL-E or MidJourney). The generated comic is adjusted based on the results of the emotion engine. For example, if the user has a happy expression, a smiling face is added to the character.

[1652] User customization

[1653] The device provides an interface for users to preview the generated manga and make any necessary edits. Specifically, it has drag-and-drop and text editing functions. Users can edit dialogue, change character expressions, adjust backgrounds, and more.

[1654] Final output and saving

[1655] Output Method

[1656] After the revisions are complete, the server generates the final comic-style explanatory material in PDF or image file format using a library (such as ReportLab or Pillow) and provides the user with a download link for the generated file.

[1657] Preservation means

[1658] The server saves the generated comics and related data. The data is stored in a database (e.g., PostgreSQL or MongoDB). This allows users to re-edit the data later and allows history management.

[1659] Specific examples

[1660] For example, suppose a user uploads a rough sketch to explain the process of developing a new product. The server analyzes the rough sketch and identifies each step in the process. It then selects a product development scenario and an appropriate character, automatically generating a comic-style explanatory document. The emotion engine analyzes the user's emotions and adds a character with a relaxed expression and encouraging words to a nervous user. The user can review the document and, if necessary, change "prototype testing" to "quality testing," and finally download it as a PDF for use in internal presentations.

[1661] Examples of prompt statements

[1662] - "Please upload a rough sketch to create a comic-style document that explains the new product development process. Which stage is the most important in terms of trends?"

[1663] - "Enable the emotion engine and adjust the character's facial expressions. Tell us their current emotional state."

[1664] In this way, this system efficiently generates explanatory materials in comic format to visually and intuitively convey business content, and by adjusting them according to the user's emotions, it enhances the effectiveness of presentations.

[1665] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1666] Step 1: Enter your data

[1667] The terminal displays an interface for the user to input data related to the business content. This interface includes a text input field, a rough sketch upload function, and a presentation file upload function. The input data can be text information, a rough sketch, or a presentation file. The input data can be provided by the user by direct input or file upload.

[1668] Step 2: Save your data

[1669] The terminal sends the data entered by the user to the server, which then temporarily stores the received data in cloud storage. For example, text information, image information (rough sketches), and presentation files are temporarily stored in the cloud storage.

[1670] Step 3: Analyzing the text

[1671] The server analyzes the temporarily stored text information using an NLP (natural language processing) model. In this process, Python NLP libraries (e.g., spacy, nltk) are used to extract key points and important phrases from the text information. As a result, important phrases such as "planning," "implementation," and "evaluation" are output.

[1672] Step 4: Analyze image information

[1673] The server analyzes the temporarily stored image information (rough sketches) using computer vision technology. This analysis uses libraries such as OpenCV and TensorFlow. The server identifies elements such as diagrams and characters from the rough sketches and determines their relationships. For example, the server identifies diagrams showing each stage of a project and determines their interrelationships.

[1674] Step 5: Character and scenario selection

[1675] The server selects the most suitable characters and scenarios based on key points and elements extracted from text and image information. This selection is performed by referring to pre-trained manga templates. For example, a template explaining the progress of a project may be selected.

[1676] Step 6: Sentiment Analysis

[1677] The device uses a camera and microphone to analyze the user's facial expressions and voice, and the collected emotional data is sent to a server.

[1678] The server analyzes the collected data using an emotion engine, which determines what emotions the user is feeling. For example, it can determine if the user is nervous. The results of the emotion analysis are output and used to adjust the character's facial expressions and dialogue.

[1679] Step 7: Generate the comic

[1680] The server automatically generates a manga based on the selected characters and scenario. This generation uses generative AI models such as DALL-E and MidJourney. The character's facial expressions and lines are adjusted based on the results of the emotion analysis. The generated manga is output, reflecting the results of the emotion analysis.

[1681] Step 8: Providing customizations

[1682] The device provides an interface for users to preview and modify the generated manga. This interface includes drag-and-drop and text editing functions. Users can modify dialogue, change character expressions, adjust backgrounds, and more. The modified and adjusted manga is output based on the user's input.

[1683] Step 9: Final Output

[1684] The server generates the final, edited version of the comic-style explanatory material in PDF or image file format using libraries such as ReportLab or Pillow. A download link for the generated file is provided to the user. The final output PDF or image file is provided to the user.

[1685] Step 10: Save your data

[1686] The server stores the generated manga and related data in a database (e.g., PostgreSQL, MongoDB), allowing users to re-edit the data later. The saved data is output in a format that allows for re-editing and history management.

[1687] Through the above processing steps, the system can efficiently generate comic-style materials that allow users to visually and intuitively communicate their work content, and can adjust the content according to the user's emotions.

[1688] (Application example 2)

[1689] 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."

[1690] Conventional work explanation materials generally use text or simple illustrations, making it difficult to present information in a visually understandable format. Furthermore, there is no means of providing appropriate information based on employees' emotions, which reduces the effectiveness of training and reduces work efficiency. To address these issues, the present invention aims to provide a system that explains work content in comic form and automatically adjusts based on emotions.

[1691] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1692] In this invention, the server includes means for inputting text information, image information, or a presentation file for explaining the content of work, means for analyzing the input text information and extracting key points, means for analyzing the input image information and identifying a structure, means for selecting optimal characters and scenarios based on the extracted and identified information and generating explanatory materials in comic form, means for automatically adjusting the characters and scenarios using an emotion engine that recognizes the user's emotions, and means for the user to make corrections to the generated explanatory materials in comic form. This makes it possible to provide information in a visually easy-to-understand format and provide optimal information according to the emotions of employees.

[1693] "Job Description" refers to detailed information about a specified task or process.

[1694] "Textual information" refers to data provided in text format.

[1695] "Image information" means data provided in a visual format, such as a photograph, illustration, or diagram.

[1696] A "presentation file" is a digital document created to explain business content in slide format.

[1697] The "emotion engine" is a system that analyzes a user's facial expressions, tone of voice, etc. to identify emotions.

[1698] "Means for extracting key points" is a function for identifying and extracting important information and phrases from input text information.

[1699] The "means for identifying structure" is a function for analyzing input image information and identifying its contents and relationships.

[1700] The "means for selecting characters and scenarios" is a function for selecting the most suitable characters and scenarios based on the extracted and identified information.

[1701] "Means for generating explanatory materials in comic format" is a function for creating materials that visually explain business details in comic format based on selected characters and scenarios.

[1702] "Means for automatic adjustment" is a function that automatically changes the content of characters and scenarios based on the user's emotions identified by the emotion engine.

[1703] "Means by which users can make modifications" is a function that provides an interface that allows users to freely edit and modify the generated comic-style explanatory material.

[1704] MODE FOR CARRYING OUT THE INVENTION

[1705] The following describes in detail a specific embodiment of the present invention. This system generates job explanation materials in cartoon format and automatically adjusts the content using an emotion engine. The entire system is designed to enable effective employee training and job explanations in factories using smart glasses.

[1706] Hardware and Software Configuration

[1707] Hardware:

[1708] Smart glasses (e.g. Microsoft HoloLens)

[1709] Server (Cloud or On-Premise)

[1710] software:

[1711] Natural Language Processing (NLP) models (e.g., Google BERT)

[1712] Image recognition technology (e.g., OpenCV)

[1713] Sentiment analysis engine (e.g. Microsoft Azure Emotion API)

[1714] Processing flow

[1715] 1. Data Entry

[1716] The terminal (smart glasses) provides an interface for inputting text information and presentation files related to business content. Users use the smart glasses to scan or upload data related to business materials.

[1717] 2. Data Analysis

[1718] The server analyzes the input text information using an NLP model to extract key business points, and also analyzes image information using image recognition technology to identify structure and important elements.

[1719] 3. Manga generation

[1720] The server selects the most suitable characters and scenario based on the key points and the identified structure, and generates explanatory materials in comic form. At the same time, an emotion analysis engine analyzes the user's facial expressions and tone of voice to set appropriate character expressions and lines.

[1721] 4. User Modifications

[1722] The generated comic-style explanatory materials can be previewed on the smart glasses and edited as needed, such as changing dialogue, adjusting character expressions, and adding backgrounds.

[1723] 5. Final output

[1724] Once the edits are complete, the document is generated as a PDF or image file and saved on the server. The final product can then be downloaded by the user via a download link.

[1725] Specific examples

[1726] For example, consider a case where an employee learning how to set up a new production line uses smart glasses to scan their work, and AI analyzes the content to generate a comic-style document. If the emotion engine detects that the user is nervous, it adds a character with a relaxed expression and reassuring words. The user can then review and edit the document, and finally save it as a PDF to use as training material.

[1727] Prompt Sentence Examples

[1728] "Scan the job description and generate a cartoon-style document, with characters that have relaxed expressions to make it easier for employees to understand."

[1729] By combining the above elements, the present invention makes it possible to quickly generate visually easy-to-understand work explanation materials and provide appropriate information according to the emotions of employees.

[1730] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1731] Step 1: Data entry

[1732] The terminal (smart glasses) provides an interface for inputting text information and presentation files related to work content. Users use the smart glasses to scan or upload data related to work materials. The input data is text-based work instructions and image-based presentation files.

[1733] Step 2: Data analysis

[1734] The server receives the text information sent from the device and analyzes it using a natural language processing (NLP) model (e.g., Google BERT). During the analysis, important steps and key points of the business (e.g., "work preparation," "equipment setup," and "quality check") are extracted. At the same time, image information is analyzed using image recognition technology (e.g., OpenCV) to identify structure and important elements (e.g., diagrams, equipment layout). These analysis results are used in the next step.

[1735] Step 3: Character and scenario selection

[1736] The server automatically selects the most suitable characters and scenarios based on the keypoints extracted and the structure identified in step 2. This selection uses pre-trained manga templates. For example, a scenario and its characters that explain the setup procedure for a manufacturing line are selected.

[1737] Step 4: Sentiment Analysis

[1738] The device analyzes the user's facial expressions and tone of voice using an emotion analysis engine (e.g., Microsoft Azure Emotion API) and sends the user's emotional data to the server. The emotional data (e.g., "tense," "relaxed," "excited") is used to adjust the content of the comic in a later step.

[1739] Step 5: Manga Generation

[1740] The server generates explanatory materials in comic form based on the characters and scenario selected in step 3. Furthermore, the character's facial expressions and lines are automatically adjusted based on the results of the emotion analysis engine. For example, if the user is nervous, a character with a relaxed expression and encouraging lines will be set.

[1741] Step 6: User Modifications

[1742] The generated comic-style explanatory materials are previewed on the device. The user can use smart glasses to check the preview and make any necessary corrections (e.g., changing dialogue, adjusting character expressions, adding backgrounds). The corrected data is then saved on the server.

[1743] Step 7: Final output

[1744] Once the edits are complete, the document is generated as a PDF or image file on the server, and a download link is provided to the user. The final product is then saved in the cloud, allowing for future editing.

[1745] Each step of this system presents work details in a visually easy-to-understand format, enabling appropriate information to be provided based on the employee's emotions.

[1746] 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.

[1747] 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.

[1748] 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.

[1749] 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.

[1750] 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.

[1751] 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.

[1752] 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).

[1753] 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.

[1754] 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."

[1755] 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.

[1756] 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).

[1757] 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.

[1758] 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.

[1759] 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.

[1760] 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.

[1761] 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.

[1762] 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.

[1763] 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.

[1764] 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.

[1765] 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.

[1766] 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.

[1767] The following is further disclosed regarding the above embodiment.

[1768] (Claim 1)

[1769] A means for inputting text information, image information, or a presentation file to explain the business content;

[1770] A means for analyzing input character information and extracting key points;

[1771] A means for analyzing input image information and identifying a structure;

[1772] A means for selecting optimal characters and scenarios based on the extracted and identified information and generating explanatory materials in comic form;

[1773] A means for allowing a user to make corrections to the generated comic-style explanatory material;

[1774] A system including:

[1775] (Claim 2)

[1776] 10. The system of claim 1, further comprising means for automatically generating a layout of the manga based on selected characters and scenarios.

[1777] (Claim 3)

[1778] The system according to claim 1, further comprising means for outputting the generated comic-style explanatory material in PDF or image file format.

[1779] "Example 1"

[1780] (Claim 1)

[1781] A means for inputting text information, image information, or a presentation file to explain the business content;

[1782] A means for analyzing input character information and extracting key points;

[1783] A means for analyzing input image information and identifying a structure;

[1784] A means for selecting optimal characters and scenarios based on the extracted and identified information and generating explanatory materials in comic form;

[1785] A means for allowing a user to make corrections to the generated comic-style explanatory material;

[1786] A means to save the generated comic-style explanatory materials so that they can be re-edited later, and

[1787] A system including:

[1788] (Claim 2)

[1789] 10. The system of claim 1, further comprising means for providing an interface for modifying selected lines, changing character facial expressions, and adjusting backgrounds.

[1790] (Claim 3)

[1791] The system according to claim 1, further comprising means for outputting the generated comic-style explanatory material in PDF or image file format.

[1792] "Application Example 1"

[1793] (Claim 1)

[1794] A means for inputting text information, image information, or a presentation file to explain the business content;

[1795] A means for analyzing input character information and extracting key points;

[1796] A means for analyzing input image information and identifying a structure;

[1797] A means for selecting optimal characters and scenarios based on the extracted and identified information and generating explanatory materials in comic form;

[1798] A means for allowing a user to make corrections to the generated comic-style explanatory material;

[1799] A system that includes a means to input product information and service details for physical stores and display them in comic form.

[1800] (Claim 2)

[1801] 10. The system of claim 1, further comprising means for automatically generating a layout of the manga based on selected characters and scenarios.

[1802] (Claim 3)

[1803] The system according to claim 1, further comprising means for outputting the generated comic-style explanatory material in PDF or image file format.

[1804] "Example 2: Combining Emotion Engines"

[1805] (Claim 1)

[1806] a means for inputting data describing the business;

[1807] A means for temporarily saving input data;

[1808] A means for analyzing text information and extracting key points;

[1809] A means for analyzing image information and identifying a structure;

[1810] A means for selecting optimal characters and scenarios based on the extracted and identified information and generating explanatory materials in comic form;

[1811] A means for analyzing a user's emotions regarding the generated comic-style explanatory material and adjusting the content;

[1812] A means for allowing a user to make corrections to the generated comic-style explanatory material;

[1813] A means for saving the generated comic-style explanatory material and enabling it to be re-edited;

[1814] A system including:

[1815] (Claim 2)

[1816] 10. The system of claim 1, further comprising means for automatically generating a layout of the manga based on selected characters and scenarios.

[1817] (Claim 3)

[1818] The system according to claim 1, further comprising means for outputting the generated comic-style explanatory material in PDF or image file format.

[1819] "Application example 2 when combining emotion engines"

[1820] (Claim 1)

[1821] A means for inputting text information, image information, or a presentation file to explain the business content;

[1822] A means for analyzing input character information and extracting key points;

[1823] A means for analyzing input image information and identifying a structure;

[1824] A means for selecting optimal characters and scenarios based on the extracted and identified information and generating explanatory materials in comic form;

[1825] means for automatically adjusting characters and scenarios using an emotion engine that recognizes user emotions;

[1826] A means for allowing a user to make corrections to the generated comic-style explanatory material;

[1827] A system including:

[1828] (Claim 2)

[1829] 10. The system of claim 1, further comprising means for automatically generating a layout of the manga based on selected characters and scenarios.

[1830] (Claim 3)

[1831] The system according to claim 1, further comprising means for outputting the generated comic-style explanatory material in PDF or image file format. [Explanation of symbols]

[1832] 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 inputting text information, image information, or a presentation file to explain the business content; A means for analyzing input character information and extracting key points; A means for analyzing input image information and identifying a structure; A means for selecting optimal characters and scenarios based on the extracted and identified information and generating explanatory materials in comic form; A means for allowing a user to make corrections to the generated comic-style explanatory material; A system including:

2. The system of claim 1 further comprising means for automatically generating a layout of the manga based on selected characters and scenarios.

3. The system according to claim 1, further comprising means for outputting the generated comic-style explanatory material in PDF or image file format.

Images