system

Abstract

To provide a system that significantly reduces the time and labor required for creating documents and enables efficient creation of high-quality, consistent documents. [Solution] A system including: means for receiving purpose and target information of a material from a user; means for analyzing the purpose and target information and defining the required material structure and type of information; means for collecting the defined information from an internal database and external sources; means for organizing the collected information and converting it into appropriate text, table, graph, or image format; means for automatically generating a material layout based on the converted information; means for generating text based on the automatically generated layout; means for presenting the generated material to a user and receiving feedback; and means for automatically making corrections based on the feedback.

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] This invention relates to document creation tasks, which consume a large amount of time and resources in business environments. When salespeople and technical staff spend a lot of time creating documents, it reduces productivity and efficiency, preventing them from concentrating on the essential parts of their work. Furthermore, the strengths and weaknesses of document creation and their skill can affect the success or failure of a project. To address this situation, automation of document creation is needed. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including the following means.

[0006] means for receiving material purpose and subject information from the user;

[0007] means for analyzing the purpose and target information and defining the required material structure and information type;

[0008] means for collecting said defined information from internal databases and external sources;

[0009] means for organizing and converting the collected information into appropriate text, table, graph, or image formats;

[0010] means for automatically generating a layout of materials based on the converted information;

[0011] means for generating text based on the automatically generated layout;

[0012] means for presenting the generated materials to a user and receiving feedback;

[0013] The system includes means for automatically making corrections based on said feedback.

[0014] A "user" is an individual or organization that uses the document creation system.

[0015] "Information" refers to the specific content, such as data, text, tables, graphs, and images, that are necessary to achieve the purpose of the material.

[0016] "Purpose" refers to the primary use or intended goal of the material created by the user.

[0017] "Analysis" is the process of processing the input objectives and information to identify the components of the material and the types of information required.

[0018] An "internal database" is a system for managing data resources held within an organization.

[0019] "External sources" refers to information resources outside the organization, including APIs and market research reports.

[0020] "Collection" is the process of obtaining required information from internal databases and external sources.

[0021] "Organization" is the process of arranging collected information into an appropriate format and classifying it by subject.

[0022] "Conversion" is the process of preparing information into a format such as text, tables, graphs, or images.

[0023] "Layout" refers to the visual arrangement and structure of materials, including titles, section divisions, fonts, color schemes, etc.

[0024] "Auto-generation" refers to the automatic creation of material components by mechanical processes.

[0025] "Text generation" is the process of creating text in natural language based on collected and organized information.

[0026] "Feedback" is information that allows a user to evaluate the generated material and give instructions for improvement or correction.

[0027] "Revising" is the process of revising specific portions of material based on user feedback. [Brief explanation of the drawings]

[0028] [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

[0029] 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.

[0030] First, the terms used in the following description will be explained.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] [First embodiment]

[0037] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0038] 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.

[0039] 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).

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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.

[0044] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0045] 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.

[0046] 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.

[0047] 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.

[0048] 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."

[0049] The present invention is a system for improving the efficiency of document creation work, and includes various means for receiving document purpose and subject information from a user and automatically generating documents. This system can significantly reduce the time and effort required by users to create documents, and can also improve the quality and consistency of documents.

[0050] Input and analysis of needs

[0051] The user uses a terminal to input the purpose and target information of the document (e.g., sales presentation of a new product, target market, competitive information). The server receives this input information and begins analysis. Based on the results of the analysis, the server defines the necessary components of the document (e.g., product information, market analysis, competitive comparison, sales plan, budget graph).

[0052] Data collection and organization

[0053] The server collects the necessary information from internal databases and external sources. It obtains the company's product specifications and past sales data from internal databases, and market trends and competitive information from external sources. The server organizes the collected information and converts it into appropriate formats such as text, tables, graphs, and images. For example, new product specifications are organized in text and table format, and market trends are graphed.

[0054] Automatic layout generation of documents

[0055] The server determines the layout of each section of the document based on the organized information. Specifically, it automatically generates the order and color scheme templates for title slides, product information slides, market analysis slides, etc. The server then applies fonts, color schemes, page numbers, etc. based on the company's brand guidelines. For example, the company logo is placed in the bottom right corner of each slide based on a blue color scheme.

[0056] Automatic sentence generation

[0057] The server uses natural language processing technology to generate text based on the collected data. For example, for a product information slide, it generates a sentence such as "The new product offers a 20% performance improvement over the previous model" and adds it to the slide. It also adjusts the tone and style depending on the purpose of the document. For presentation materials, it uses a formal, business-oriented tone.

[0058] Accepting feedback and making corrections

[0059] The server can present the generated materials to the user and receive feedback. The user can check the materials through their terminal and input any necessary corrections (e.g., adjusting the size of graphs, correcting text). For example, they can input feedback such as "The graph for competitive comparison is small, so I would like it to be larger." The server will automatically make corrections based on the feedback and generate a new, revised material.

[0060] Final confirmation and document output

[0061] The user checks the revised document again and gives final approval. Check the final version of the document displayed on the terminal and, if satisfied, press the approval button. The server outputs the final version of the document in the user's desired format, such as PDF or PowerPoint. The output document is displayed on the terminal as a download link, which the user can use to distribute or present the document.

[0062] The present invention enables users to create documents efficiently and with high quality, significantly reducing the time and effort required for document creation, and also improves the consistency and quality of documents, thereby helping to improve business productivity.

[0063] The processing flow will be explained below.

[0064] Step 1:

[0065] The user uses the terminal to input the purpose and target information of the document. For example, the purpose is "sales presentation for a new product," and then adds details such as the target market and competitive information.

[0066] Step 2:

[0067] The server analyzes the entered purpose and target information and defines the necessary document components (e.g., product information, market analysis, competitor comparison, sales plan, budget graph). Based on this information, the server determines the type and amount of data required.

[0068] Step 3:

[0069] The server queries an internal database to gather relevant product information and past sales data, such as "product specifications" and "sales history."

[0070] Step 4:

[0071] The server gathers the necessary market trends and competitive information from external sources, for example, using a market research report API to get the latest market data.

[0072] Step 5:

[0073] The server organizes the collected data and converts it into text, tables, graphs, and images. Product specifications are converted into text and tables, and market trends are converted into graphs. For example, the specifications of a new product are compiled into a table, and market trends are converted into a line graph.

[0074] Step 6:

[0075] The server automatically generates a layout for the presentation materials based on this organized information. The layout includes a title slide, product information slide, market analysis slide, etc. For example, the first slide could contain the company logo and title, and the next slide could contain product information.

[0076] Step 7:

[0077] The server uses natural language processing technology to generate sentences based on the collected and organized information, such as "The new product offers 20% better performance than the previous model."

[0078] Step 8:

[0079] The server displays the generated document on the terminal and asks the user to confirm it. The user checks the contents of the document and enters feedback as necessary. For example, the user may enter feedback such as "I would like the size of the competitive comparison graph to be larger."

[0080] Step 9:

[0081] The server receives feedback from the user and automatically makes the specified modifications, for example, adjusting the size of the competitive comparison graph and regenerating the materials.

[0082] Step 10:

[0083] The user then reviews the revised documents and finally approves them. The approved documents are output by the server in PDF or PowerPoint format. The user can then download these documents from their device and use them for presentations or distribution.

[0084] By following the steps above, users can efficiently create high-quality materials in a short amount of time.

[0085] Example 1

[0086] 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."

[0087] In conventional document creation work, users spend a large amount of time and effort, and maintaining the quality and consistency of the documents is a challenge. In addition, many steps, such as collecting and organizing information for documents, setting layouts, and generating text, are done manually, so there is a need for efficiency improvements.

[0088] 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.

[0089] In this invention, the server includes means for receiving purpose and target information of the document from the user, means for analyzing the purpose and target information and defining the necessary components and types of information of the document, means for collecting the defined information from an internal database and external sources, means for organizing the collected information and converting it into appropriate text, table, graph, or image formats, means for automatically generating a layout of the document based on the converted information, means for generating text based on the automatically generated layout, means for presenting the generated document to the user and receiving feedback, means for automatically making corrections based on the feedback, and means for outputting the final version of the document in a format desired by the user. This significantly reduces the time and effort required for document creation and enables the efficient creation of high-quality, consistent documents.

[0090] A "user" is a person or organization that uses the system to create materials.

[0091] "Purpose" refers to the specific goal or intention of the user when creating the material.

[0092] "Target information" refers to data and information necessary for creating materials, such as product information, market analysis, and competitive information.

[0093] "Analysis" is the process of identifying the necessary components and types of information based on the input purpose and target information.

[0094] "Components" are the basic elements that make up the document, and specifically include product information, market analysis, competitive comparisons, sales plans, budget graphs, etc.

[0095] "Information" refers to the data and knowledge necessary to produce the materials. It is collected from internal databases and external sources.

[0096] An "internal database" is a collection of data managed within a company. For example, it may include product specifications and past sales data.

[0097] "External sources" are information sources obtained from outside the company, such as market trends and competitive information.

[0098] "Collection" is the process of obtaining required information from internal databases and external sources.

[0099] Organizing is the process of putting collected information into an appropriate format, such as text, tables, graphs, or images.

[0100] "Layout" refers to the arrangement and design of each section of the document, specifically including the order and color scheme of the title slide, product information slide, market analysis slide, etc.

[0101] "Natural language processing technology" is a technology that enables computers to understand and generate human language.

[0102] "Feedback" refers to evaluations and correction requests made by users regarding generated materials.

[0103] "Automatic correction" is the process by which the server automatically corrects the material based on user feedback.

[0104] "Final Version" means the completed version of the Material that has been finalized by the User.

[0105] "Format" refers to the format in which the materials are output. Examples include PDF and PowerPoint.

[0106] The present invention is a system that receives information on the purpose and target of a document from a user, automatically generates the document, and makes corrections based on the feedback. This system significantly reduces the time and effort required to create the document, enabling the efficient creation of high-quality, consistent documents.

[0107] First, the user uses a terminal to input the purpose and target information of the materials. For example, if you want to create a sales presentation for a new product, you would enter "new product information," "target market," "competitive information," etc. into the input form. The terminal then sends this information to the server.

[0108] The server then analyzes the received purpose and target information and defines the components and types of information required for the materials. This analysis is performed using a pre-trained generative AI model. For example, the components of a new product presentation material might include "product information," "market analysis," "competitive comparison," "sales plan," and "budget graph."

[0109] The server then collects the necessary information from internal databases and external sources. From the internal database, it obtains the company's product specifications and past sales data, and from external sources, it obtains market trends and competitive information. For example, the server uses web crawling technology to obtain the latest market trends.

[0110] The collected information is organized and converted into the appropriate format. For example, new product specifications are converted into text and tables, and market trends are graphed. Based on this organized information, the server automatically generates the layout for each section of the document. Specifically, it generates the order and color scheme templates for title slides, product information slides, market analysis slides, etc. Fonts, color schemes, page numbers, etc. are applied based on the company's brand guidelines.

[0111] The server then uses natural language processing technology to generate text based on the collected data. For example, a product information slide might say, "The new product offers 20% better performance than the previous model." The server also automatically adjusts tone and style depending on the purpose of the presentation. For business presentations, a formal tone is used.

[0112] The generated document is presented to the user, who can then input feedback via their terminal. For example, a request for corrections such as "The competitive comparison graph is too small, please make it larger" can be input. The server automatically makes corrections based on this feedback and regenerates the revised document.

[0113] Finally, the user checks the revised document on their device and, if satisfied, presses the approval button. The server outputs the final document in the user's desired format, such as PDF or PowerPoint. The output document is displayed on the device as a download link, which the user can use to distribute or present the document.

[0114] As a concrete example, consider the case where the following prompt is entered into a terminal:

[0115] Prompt statement:

[0116] I'd like to create a sales presentation for a new product. It should include information on the target market and competitors, as well as product specifications, market analysis, competitor comparisons, sales plans, and budget graphs. The presentation should use a blue color scheme, with the company logo placed in the bottom right corner of each slide.

[0117] Based on these prompts, the server collects and organizes the necessary information and automatically generates the layout and text. Once the user enters feedback and provides final approval, the completed document is output in PDF format. This series of processes enables users to quickly create efficient, high-quality documents, improving work productivity.

[0118] It can be seen that specific embodiments of the present invention streamline document creation and provide high quality, consistent documents.

[0119] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0120] Step 1:

[0121] The user uses the terminal to input the purpose and target information of the document. The input includes "new product information," "target market," and "competitive information" to create a sales presentation for a new product. The terminal sends this information to the server. The input data takes the form of text fields and drop-down menus, and is received by the server after it is sent.

[0122] Step 2:

[0123] The server analyzes the received purpose and target information using a generative AI model. Specifically, the server breaks down the purpose and target information and defines the components required for the document (product information, market analysis, competitive comparison, sales plan, budget graph, etc.). The output of this analysis is a requirements list for further specific information gathering and formatting.

[0124] Step 3:

[0125] The server collects the necessary information from internal databases and external sources. From the internal database, it obtains the company's product specifications and past sales data, and from external sources, it collects market trends and competitive information. For example, the server uses an API to obtain market trends from an external data provider. The collected data is organized into formats such as text, tables, graphs, and images.

[0126] Step 4:

[0127] The server organizes the collected information and converts it into various data formats. For example, new product specifications are converted into text and tables, and market trends are converted into graphs. Data formatting algorithms are used in this step. The output is a list of various types of data.

[0128] Step 5:

[0129] The server automatically generates the layout of the materials based on the organized information. Specifically, it generates the order and color scheme templates for each section (title slide, product information slide, market analysis slide, etc.). It also applies fonts, color schemes, page numbers, and other settings in accordance with the company's brand guidelines. For example, the server references a brand guideline database to determine the color scheme and applies it to each slide.

[0130] Step 6:

[0131] The server uses natural language processing technology to generate text based on the collected data. Using a generative AI model, it creates sentences such as "The new product offers 20% better performance than the previous model" for product information slides. The tone and style are automatically adjusted depending on the purpose of the document. The generated text is then placed in the appropriate place on each slide.

[0132] Step 7:

[0133] The server presents the generated document to the user. A preview of the document is displayed on the terminal, and the user checks it. The user can input feedback as needed. For example, the user may input a correction request such as "The competitive comparison graph is small, so I would like it to be larger." This feedback is sent to the server in real time.

[0134] Step 8:

[0135] The server automatically makes corrections based on user feedback. For example, it may enlarge the size of a competitive comparison graph. The corrected document is then regenerated and presented to the user. This feedback and correction process is repeated until the user is satisfied.

[0136] Step 9:

[0137] The user then checks the revised document again and gives final approval. When satisfied, they click the approval button displayed on their device. The server then outputs the final version of the document in PDF or PowerPoint format. The final version of the document is displayed on the device as a download link, which the user can use to distribute or present the document.

[0138] (Application example 1)

[0139] 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."

[0140] Conventional document creation systems require users to manually collect and organize a large amount of data, and then generate the content, which is extremely time-consuming and labor-intensive. It is also difficult to generate content optimized for smart devices, which can lead to a poor user experience. This can result in insufficient improvement in the consistency and quality of documents.

[0141] 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.

[0142] In this invention, the server includes means for receiving purpose and target information of materials from a user, means for analyzing the purpose and target information and defining the required structure of materials and the type of information, means for collecting the defined information from an internal database and external sources, means for organizing the collected information and converting it into an appropriate text, table, graph, or image format, means for automatically generating a layout of materials based on the converted information, means for generating text based on the automatically generated layout, means for automatically generating content for smart devices based on the generated text, means for displaying the generated content for smart devices, means for presenting the generated materials to a user and receiving feedback, and means for automatically making corrections based on the feedback, thereby enabling users to efficiently generate high-quality materials and content for smart devices.

[0143] The "means for receiving the purpose and target information of the material from the user" is an interface through which the user inputs the purpose and target information of the material to be provided.

[0144] "Means for analyzing the purpose and target information and defining the necessary material composition and type of information" refers to a system that determines the material composition and type of information to be collected based on the purpose and target information received from the user.

[0145] The "means for collecting the above-defined information from internal databases and external sources" refers to a function for collecting data from internal databases and external information sources based on the components of the material.

[0146] "Means for organizing the collected information and converting it into an appropriate text, table, graph, or image format" refers to the process of organizing the collected information and converting it into a format appropriate for the intended use.

[0147] The "means for automatically generating a layout of materials based on the converted information" is a system that automatically generates the appearance and arrangement of materials based on the converted information.

[0148] The "means for generating a sentence based on the automatically generated layout" is a function for generating a sentence using natural language processing technology based on the generated layout.

[0149] "Means for automatically generating content for smart devices based on the generated text" refers to a function that automatically generates content that is optimally displayed on devices such as smartphones and tablets based on the generated text.

[0150] The "means for displaying the generated content for smart devices" refers to a function for actually displaying the generated content for smart devices on the user's device.

[0151] The "means for presenting the generated materials to the user and receiving feedback" is an interface that shows the generated materials to the user and allows the user to input their opinions and corrections.

[0152] The "means for automatically correcting the material based on the feedback" is a function for receiving feedback from the user and automatically correcting the material based on the feedback.

[0153] This invention is a system for improving the efficiency of document creation work, and specifically includes various means for receiving purpose and target information of the document from a user and automatically generating, editing, and optimizing the document based on that information. Detailed embodiments of the invention are described below.

[0154] First, the user uses a smart device (e.g., smartphone, tablet, etc.) to input the purpose and target information of the document. The user interface is simple and designed to allow users to input information intuitively. Examples of input content include "presentation materials for new products," "target markets," and "competitive information."

[0155] The server analyzes the received information. This analysis involves defining the type of information needed (product information, market analysis, competitive comparison, etc.) based on the purpose and target information entered by the user. This analysis process uses natural language processing technology to accurately understand the user's request and identify the appropriate material components.

[0156] The server then collects the defined information from an internal database, such as the company's product specifications and past sales data, and from external sources, such as market trends and competitive information. The information collection process uses Python's requests and BeautifulSoup libraries.

[0157] The collected information is organized on the server and converted into appropriate formats such as text, tables, graphs, images, etc. Python's matplotlib and pandas libraries are used for text conversion and graph generation.

[0158] The server then automatically generates a layout for the document based on the converted information. This layout generation process includes font, color, and page number settings in accordance with the company's brand guidelines. It also includes a process to optimize the display on smart devices. The layout is constructed using an HTML template.

[0159] The server then generates text based on the automatically generated layout. The generated text is based on the collected data and has specific content. Using natural language processing technology, a sentence such as "The new product achieves a 20% performance improvement over the previous model" is generated.

[0160] After generating the text, the server automatically generates content for smart devices and displays it on the user's device. The user can review the generated content and enter any necessary feedback. An example of feedback might be, "The graph showing the competitive comparison is too small, so I'd like it to be larger."

[0161] The server automatically makes corrections based on the received feedback and regenerates the document, and the final version is output to the user in formats such as PDF or PowerPoint.

[0162] For example, if a user types "Generate a blog post about the AI ​​camera features of new smartphones," the server will gather market research data and generate an article about the features, market analysis, and future outlook of AI cameras. Here is an example prompt:

[0163] Generate a blog post about the latest trends in AI camera technology, including features, market analysis, and future prospects.

[0164] In this way, users can efficiently create high-quality materials and generate content for smart devices.

[0165] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0166] Step 1:

[0167] The user uses the terminal to input the purpose and target information of the document. The terminal provides a user interface, allowing the user to input the purpose of the document (e.g., "presentation materials for a new product") and target information (e.g., "target market" and "competitive information"). The input data is sent to the server.

[0168] Step 2:

[0169] The server analyzes the received purpose and target information and defines the components of the required materials and the type of information. The analysis process uses natural language processing technology to understand the information entered by the user and determine the appropriate material elements (e.g., "product information," "market analysis," "competitive comparison"), and the analysis results are output as a list.

[0170] Step 3:

[0171] The server collects defined information from an internal database and external sources. The internal database stores the company's product specifications and past sales data, and uses the requests and BeautifulSoup libraries to collect data from external sources (e.g., market trend sites and competitive information sites). The collected information is saved in text format.

[0172] Step 4:

[0173] The server organizes the collected information and converts it into the appropriate format (text, table, graph, image). For example, product information is organized into text and table format, and market trends are graphed. This process uses the pandas and matplotlib libraries. The converted data is then stored in temporary storage.

[0174] Step 5:

[0175] The server automatically generates a layout for the document based on the converted information. The layout is generated using an HTML template, and fonts, colors, and page numbers are set based on the company's brand guidelines. The generated layout is saved in HTML format.

[0176] Step 6:

[0177] The server uses natural language processing technology to generate text based on the automatically generated layout. For example, the generated text might include specific content such as "The new product achieves a 20% performance improvement over the previous model." The generated text is inserted into the HTML layout and saved in temporary storage as the final content.

[0178] Step 7:

[0179] The server automatically generates content for smart devices based on the generated text. For example, it applies responsive design that is optimally displayed on smartphones and tablets. The generated content for smart devices is then sent to the user's device.

[0180] Step 8:

[0181] The user checks the content generated for smart devices on their device and inputs any necessary feedback. An example of feedback might be, "The graph showing the competitive comparison is too small, so I'd like it to be larger." The feedback is then sent to the server.

[0182] Step 9:

[0183] The server automatically modifies the document based on the received feedback, adjusting the size of text and graphs, etc. The modified document is then saved again in HTML format.

[0184] Step 10:

[0185] The user checks the final version of the document again and presses the approval button. The server outputs the final version of the document in the user's desired format (e.g., PDF, PowerPoint) and generates a download link. The user can obtain the final version of the document via the link.

[0186] 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.

[0187] This invention is a system aimed at improving the efficiency and quality of document creation work, and combines an emotion engine that recognizes the user's emotions and dynamically adjusts the content and tone of the document. This system significantly reduces the time and effort required for users to create documents, and also enables customization according to individual needs and emotions.

[0188] Input and analysis of needs

[0189] The user uses a terminal to input the purpose and target information of the document (e.g., sales presentation of a new product, target market, competitive information). The server receives this input information and begins analysis. Based on the results of the analysis, the server defines the necessary components of the document (e.g., product information, market analysis, competitive comparison, sales plan, budget graph).

[0190] Data collection and organization

[0191] The server collects the necessary information from internal databases and external sources. It obtains the company's product specifications and past sales data from internal databases, and market trends and competitive information from external sources. The server organizes the collected information and converts it into appropriate formats such as text, tables, graphs, and images. For example, new product specifications are organized in text and table format, and market trends are graphed.

[0192] Automatic layout generation of documents

[0193] Based on the organized information, the server determines the layout of each section of the document, including the title slide, product information slide, and market analysis slide. The server then applies fonts, color schemes, page numbers, and other elements based on the company's brand guidelines. For example, the server uses a blue color scheme and places the company logo in the bottom right corner of each slide.

[0194] Automatic sentence generation

[0195] The server uses natural language processing technology to generate text based on the collected and organized information. For example, it creates a product information slide with a description such as, "The new product offers 20% better performance than the previous model." It also adjusts the tone and style depending on the purpose of the document. For presentation materials, it uses a formal, business-oriented tone.

[0196] Emotion engine accepts and corrects feedback

[0197] The server displays the generated materials on the terminal and asks the user to confirm them. The user then checks the contents of the materials and enters feedback as necessary. The emotion engine also analyzes the user's facial expressions and voice to recognize their emotions (such as surprise, joy, or dissatisfaction). The server then adjusts the content and tone of the materials according to the user's emotions identified by the emotion engine. For example, if the user shows a dissatisfied expression, the server modifies the design and text of that section to make it more specific and appealing.

[0198] Corrections based on feedback and final confirmation

[0199] The server automatically makes the specified modifications based on feedback from the user and the emotion engine. For example, based on feedback such as "Please make the size of the competitive comparison graph larger" and the emotion engine's analysis of the user's dissatisfaction, the server adjusts the size of the competitive comparison graph and regenerates the document. The user then checks the modified document again and finally approves it. The server outputs the approved document in PDF or PowerPoint format. The user can then download the document from their device and use it for presentations or distribution.

[0200] This invention allows users to create efficient, high-quality documents in a short time. It also enables customization according to the user's feelings, which is expected to improve the consistency and quality of documents and increase business productivity.

[0201] The processing flow will be explained below.

[0202] Step 1:

[0203] The user uses the terminal to input the purpose and target information of the document. Specifically, the user inputs the purpose as "sales presentation for a new product" and adds details such as the target market and competitive information.

[0204] Step 2:

[0205] The server analyzes the entered purpose and target information and defines the necessary document components (e.g., product information, market analysis, competitor comparison, sales plan, budget graph). Based on this information, the server determines the type and amount of data required.

[0206] Step 3:

[0207] The server queries the internal database to collect relevant product information and past sales data, and retrieves data such as "product specifications" and "sales history" from the internal database.

[0208] Step 4:

[0209] The server collects the necessary market trends and competitive information from external sources, and uses the market research report API to obtain the latest market data.

[0210] Step 5:

[0211] The server organizes the collected data and converts it into text, tables, graphs, and images. For example, it converts new product specifications into a table and market trends into a line graph.

[0212] Step 6:

[0213] The server automatically generates a layout for the presentation based on the organized information. The layout includes a title slide, product information slide, market analysis slide, etc. The server applies fonts, color schemes, page numbers, etc. based on the company's brand guidelines. For example, a blue color scheme is used and the company logo is placed in the bottom right corner of each slide.

[0214] Step 7:

[0215] The server uses natural language processing technology to generate text based on the collected and organized information, creating product information slides with descriptions such as "This new product offers 20% better performance than the previous model."

[0216] Step 8:

[0217] The server displays the generated document on the terminal and asks the user to confirm it. The user checks the contents of the document and enters feedback as necessary. For example, the user may enter a request such as "I would like the size of the competitive comparison graph to be larger."

[0218] Step 9:

[0219] When the user is confirmed, the server activates the emotion engine and analyzes the user's facial expressions and voice. The emotion engine identifies the user's emotion and sends the emotion data to the server. For example, if the user shows a dissatisfied expression, the server will receive the analysis result of the dissatisfaction.

[0220] Step 10:

[0221] Based on the analysis results of the emotion engine and user feedback, the server modifies specific parts of the document, for example, increasing the size of the competitive comparison graph and changing the color scheme to make it more appealing.

[0222] Step 11:

[0223] The user checks the revised document again on the terminal, and if the user is satisfied again, the server confirms the final version of the document at that point.

[0224] Step 12:

[0225] The server outputs the final, verified documents in PDF or PowerPoint format, and users can download these documents from their devices. Users can use these documents for presentations or distribution.

[0226] By following the steps above, the user can create efficient, high-quality materials in a short time, and furthermore, can customize the contents of the materials according to the user's feelings.

[0227] Example 2

[0228] 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."

[0229] Conventional document creation systems require users to manually collect and organize data, design layouts, and write documents, which is time-consuming, labor-intensive, and inefficient. Furthermore, if the content or tone of the document does not match the user's intentions or emotions, frequent revisions and additional work are required. This makes it difficult to maintain the quality and consistency of the document.

[0230] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0231] In this invention, the server includes: means for receiving purpose and target information for a document from a user; means for analyzing the purpose and target information and defining the necessary document components; means for collecting the defined information from an internal database and external sources; means for organizing the collected information and converting it into appropriate text, table, graph, or image formats; means for automatically generating a document layout based on the converted information; means for generating text based on the automatically generated layout; means for presenting the generated document to the user and receiving feedback; means for analyzing and recognizing the user's emotions regarding the document upon receiving feedback; means for dynamically adjusting the content and tone of the document based on the recognized emotional information; means for automatically making corrections based on the feedback and emotional information; and means for outputting the final document in PDF or presentation software format. This significantly reduces the time and effort required for document creation and enables dynamic adjustment of the content and tone of the document based on the user's emotions and feedback. As a result, efficient, high-quality documents can be created in a short time, enabling the provision of consistently high-quality documents.

[0232] "User" refers to a person who uses the system to create materials.

[0233] "Terminal" refers to a device through which a user inputs purpose and subject information for materials and provides feedback.

[0234] "Server" refers to a computer system that analyzes information input by users, collects and organizes data, generates layouts, and creates and edits text.

[0235] "Purpose and target information" refers to the information and target required for creating the document.

[0236] "Component" refers to the basic information unit that makes up a document.

[0237] An "internal database" refers to a collection of data that exists within a company.

[0238] "External sources" refers to information obtained from the Internet or other external resources.

[0239] "Text, tabular, graphical and image formats" refers to various formats for visually displaying information.

[0240] "Automatic layout generation" refers to the process of automatically determining the layout of slides and pages based on the elements that make up the document.

[0241] "Text generation" refers to the process of automatically creating the text contained in a document.

[0242] "Feedback" means suggestions for correction or improvement provided by a User after reviewing the Materials.

[0243] "Emotion engine" refers to a computer program that analyzes and recognizes a user's emotions.

[0244] "Dynamic adjustment" refers to changing the content and tone of material in real time based on feedback and emotional information.

[0245] "PDF or presentation software format" refers to the file format of the final output material.

[0246] This invention is a system aimed at improving the efficiency and quality of document creation work, and includes an emotion engine that recognizes the user's emotions and dynamically adjusts the content and tone of the document. This system significantly reduces the time and effort required for users to create documents, and also enables customization according to individual needs and emotions.

[0247] Input and analysis of needs

[0248] The user uses a terminal to input the purpose and target information of the document (e.g., sales presentation of a new product, target market, competitive information). The server receives this input information and performs semantic analysis using an NLP library (e.g., spaCy). This defines the necessary components of the document (e.g., product information, market analysis, competitive comparison, sales plan, budget graph).

[0249] Data collection and organization

[0250] The server collects the necessary information from an internal database (e.g., MySQL®) and external sources (e.g., RESTful API, web scraping). From the internal database, it obtains the company's product specifications and past sales data, and from external sources, it obtains market trends and competitive information. Next, the server organizes the collected information and converts it into an appropriate format (e.g., text, table, graph, image). At this stage, the data is processed using libraries such as Pandas and Matplotlib. For example, the specifications of a new product are organized into text and tables, and market trends are visualized as a line graph.

[0251] Automatic layout generation of documents

[0252] The server uses PowerPoint libraries (e.g., python-pptx) to automatically generate the layout of the materials based on the organized information. This includes the placement of slide titles, content, graphs, images, etc. The server customizes fonts, color schemes, page numbers, etc. based on the company's brand guidelines. For example, it uses a blue color scheme, places the company logo in the bottom right corner of each slide, and adds page numbers.

[0253] Automatic sentence generation

[0254] The server uses natural language processing technology (e.g., GPT-3 (registered trademark)) to generate text based on the collected and organized information. For product information slides, it automatically generates explanatory text such as, "The new product achieves a 20% performance improvement over the previous model." It also adjusts the tone and style according to the purpose of the document. For presentation materials, a formal, business-oriented tone is used.

[0255] Emotion engine accepts and corrects feedback

[0256] The server displays the generated materials on the terminal and asks the user to confirm them. The user can then review the contents of the materials and enter feedback. The emotion engine also analyzes the user's facial expressions and voice to recognize their emotions (such as surprise, joy, or dissatisfaction). The server then adjusts the content and tone of the materials according to the user's emotions identified by the emotion engine. For example, if the user shows a dissatisfied expression, the server will modify the design and text of that section to make it more specific and appealing.

[0257] Corrections based on feedback and final confirmation

[0258] The server automatically makes the specified modifications based on feedback from the user and the emotion engine. For example, based on feedback such as "Please make the size of the competitive comparison graph larger" and the emotion engine's analysis of the user's dissatisfaction, the server adjusts the size of the competitive comparison graph and regenerates the document. The user then reviews the modified document again and gives their final approval. The server outputs the approved document in PDF or presentation software format. The user can then download the document from their device and use it for presentations or distribution.

[0259] Specific examples

[0260] For example, a user might input the following prompt into a generative AI model:

[0261] Example prompt:

[0262] "I would like to create a sales presentation for a new product. The target market is working women in their 30s, and my competitors are Company A and Company B. The presentation content should include product specifications, market trends, a comparison with other competitors, and a sales plan."

[0263] Based on these prompts, the server performs analysis, collects the necessary data, automatically generates the layout of the document, and creates the text. Through feedback using an emotion engine, the content and tone of the document can be dynamically adjusted to match the user's emotions, ultimately enabling the creation of high-quality documents in a short amount of time.

[0264] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0265] Step 1:

[0266] Input and analysis of needs

[0267] The user uses the terminal to input the purpose and target information of the material (for example, a sales presentation for a new product, a target market, competitive information).

[0268] (Input) The prompt entered by the user (in text format).

[0269] (Output) The results of analyzing the purpose and subject information of the material (list of components).

[0270] The server analyzes the received prompt using an NLP library (e.g., spaCy) to extract keywords and intent. Specifically, it extracts important information from the prompt (e.g., "new product," "sales presentation," "target market," etc.) and defines the components.

[0271] Step 2:

[0272] Data collection and organization

[0273] Based on the defined information, the server performs the task of collecting the necessary data from an internal database (e.g. MySQL) and external sources (e.g. RESTful API, web scraping).

[0274] (Input) A list of components.

[0275] (Output) Collected information (text data, table data, graph data, image data).

[0276] Specifically, it obtains product specifications and past sales data from internal databases, and market trends and competitive information from external sources.

[0277] The server then organizes the collected data using libraries such as Pandas and converts it into text, tables, graphs, and images. For example, it organizes new product specifications into text and tables, and converts market trends into line graphs.

[0278] Step 3:

[0279] Automatic layout generation of documents

[0280] The server automatically generates the layout of the materials using a PowerPoint library (e.g., python-pptx) based on the organized information.

[0281] (Input) Organized information (text, tables, graphs, images).

[0282] (Output) Automatically generated layout document.

[0283] Specifically, you can arrange the slide titles, content, graphs, images, etc., and set fonts, color schemes, and page numbers based on your company's brand guidelines. For example, you can place the company logo in a blue color scheme in the bottom right corner of each slide and add page numbers.

[0284] Step 4:

[0285] Automatic sentence generation

[0286] The server uses natural language processing technology (e.g., GPT-3) to generate sentences based on the collected and organized information.

[0287] (Input) Automatically generated layout materials and organized information.

[0288] (Output) The generated document with text.

[0289] Specifically, for product information slides, the system automatically generates explanatory text such as, "The new product achieves a 20% performance improvement over the previous model." Furthermore, the system adjusts the tone and style depending on the purpose of the document. For example, for presentation materials, a formal business tone is used.

[0290] Step 5:

[0291] Emotion engine accepts and corrects feedback

[0292] The server displays the generated materials on the terminal and asks the user to confirm them.

[0293] The user checks the content of the materials and inputs feedback. The emotion engine also analyzes the user's facial expressions and voice to recognize their emotions (surprise, joy, dissatisfaction, etc.).

[0294] (Input) User feedback and emotional data (facial expression recognition, voice analysis).

[0295] (Output) Corrections based on emotional information and feedback.

[0296] The server dynamically adjusts the content and tone of the materials based on the user's emotions and feedback recognized by the emotion engine. For example, if the user shows a dissatisfied expression, the server will modify the design and text of that section to make it more specific and appealing.

[0297] Step 6:

[0298] Corrections based on feedback and final confirmation

[0299] The server automatically modifies the materials based on feedback from the user and the emotion engine.

[0300] (Input) Corrections based on emotional information and feedback.

[0301] (Output) The revised final document.

[0302] For example, based on feedback such as "Please increase the size of the competitive comparison graph" and the results of an analysis of user dissatisfaction using an emotion engine, the graph size is adjusted and the document is generated again.

[0303] The user then checks the revised document again and gives final approval.

[0304] The server outputs approved materials in PDF or presentation software format, which users can download from their devices for presentations or distribution.

[0305] (Application example 2)

[0306] 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."

[0307] The task of creating materials related to autonomous vehicles requires a great deal of time and effort, particularly in collecting and organizing information, and creating presentation materials and text. Furthermore, conventional document creation systems make it difficult to customize materials to reflect individual user needs and emotions, creating challenges in ensuring quality and consistency. Furthermore, while it is necessary to appropriately reflect the user's emotions while creating materials, there is no efficient way to do this.

[0308] 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.

[0309] In this invention, the server includes means for receiving purpose and target information of the materials from the user, means for analyzing the purpose and target information and defining the required structure and type of information of the materials, means for collecting the defined information from an internal database and external sources, means for organizing the collected information and converting it into an appropriate text, table, graph, or image format, means for automatically generating a layout of the materials based on the converted information, means for generating text based on the automatically generated layout, means for presenting the generated materials to the user and receiving feedback, and means for analyzing the user's emotions and dynamically adjusting the content and tone of the materials, thereby enabling dynamic customization of materials based on the user's emotions and the creation of high-quality materials.

[0310] "User" refers to any person or company that uses the System to create Materials.

[0311] "Materials" refers to documents that organize and visually present information, such as presentations and reports.

[0312] "Purpose" refers to the final goal or aim of the user when creating a document.

[0313] "Target information" refers to the collection of specific data and information required to create materials.

[0314] "Analysis" refers to the process of analyzing input information in detail and deriving its meaning and relevance.

[0315] "Structure" refers to how information is organized within a document.

[0316] "Type of information" refers to the format and nature of the data required to make up the material (e.g., text, tables, graphs, images).

[0317] An "internal database" refers to a collection of data managed within a company or organization.

[0318] "External sources" refers to information sources obtained from outside the company or organization (e.g., market research data, public statistics).

[0319] "Collection" refers to the process of gathering the necessary data and information.

[0320] "Organization" refers to the process of organizing collected information in a purposeful manner.

[0321] "Transformation" refers to the process of transforming organized information into a different format (e.g., turning text information into a graph).

[0322] "Layout" refers to the arrangement of information within a document and the design structure.

[0323] "Automatic generation" refers to the system automatically performing a specific process without human intervention.

[0324] "Text generation" refers to the process by which a system automatically creates text.

[0325] "Feedback" refers to reactions and opinions from users.

[0326] "Revising" refers to the process of changing the content or format of material for the purpose of improvement.

[0327] "Analyzing emotions" refers to the process of reading and understanding a user's emotions from their facial expressions and voice.

[0328] "Tone" refers to the overall atmosphere or style of a piece of writing or presentation.

[0329] "Dynamic adjustment" refers to changing the content and format of materials in real time according to the situation and conditions.

[0330] This invention is a system that improves the efficiency and quality of document creation related to autonomous vehicles. It clarifies the roles of the server, terminal, and user, and provides specific operating procedures.

[0331] Generating a Program

[0332] 1. The user enters the purpose and target information for creating the document via a device (e.g., a smartphone).

[0333] 2. The server receives the entered purpose and target information, analyzes it, and defines the components of the required materials and the type of information.

[0334] 3. The server collects the defined information from internal databases and external sources. Examples of internal databases include company product specifications and historical sales data, while examples of external sources include market trends and competitive information.

[0335] 4. The server organizes the collected information and converts it into appropriate text, table, graph, and image formats, using data analysis libraries such as Pandas and Matplotlib.

[0336] 5. The server automatically generates the layout of the materials based on the organized information. For example, it may use a blue color scheme and place the company logo in the bottom right corner of each slide.

[0337] 6. The server then uses natural language processing technology to generate sentences, such as "Our new product achieves a 20% performance improvement over the previous model," using a generative AI model (e.g., GPT-2).

[0338] 7. The server presents the generated materials to the user and receives feedback. The user uses a smartphone application to check the contents of the materials and enter feedback as needed. The user's facial expressions and voice are also captured through the device's camera and microphone and analyzed by the emotion engine.

[0339] 8. The server dynamically adjusts the content and tone of the materials based on this feedback and emotional data. For example, if the user shows a dissatisfied expression, the server will modify the design and text of that section to make it more specific and appealing.

[0340] 9. The server automatically makes the specified corrections and regenerates the document. The user then checks the corrected document again and finally approves it.

[0341] Hardware and Software

[0342] Hardware:

[0343] Devices such as smartphones and tablets

[0344] Cloud Server

[0345] Camera and microphone (for emotion analysis)

[0346] software:

[0347] Data collection and analysis: Pandas, Matplotlib

[0348] Natural Language Processing: GPT-2 (Hugging Face transformers library)

[0349] Sentiment analysis: BERT model (nlptown / bert-base-multilingual-uncased-sentiment)

[0350] Examples and prompts

[0351] For example, if a user types "I want to introduce a new navigation feature to my target market," the system will do the following:

[0352] The server collects details of new navigation features from an internal database, along with market trend information.

[0353] The automatically generated materials include sentences such as, "The new navigation function provides highly accurate location information services."

[0354] When a user inputs feedback that "information is insufficient," the server performs sentiment analysis and adds information about competitors' features.

[0355] Example prompt sentence:

[0356] "Get additional competitive comparison information for your customers and generate even more detailed graphs."

[0357] In this way, the system utilizes generative AI models and prompt sentences to create efficient, high-quality documents.

[0358] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0359] Step 1:

[0360] The user uses the terminal to input the purpose and target information of the material.

[0361] Input: Purpose of the material (e.g., introducing a new navigation feature) and subject information (target market, competitive information).

[0362] Output: The input data is sent to the cloud server.

[0363] Step 2:

[0364] The server analyzes the entered purpose and target information.

[0365] Input: Purpose and target information entered by the user.

[0366] Output: The components of the material and the type of information are defined.

[0367] Specific operation: The server performs natural language processing based on the input information and creates a list of the information required for the document.

[0368] Step 3:

[0369] The server collects the required information from an internal database and external sources.

[0370] Input: Material components and types of information.

[0371] Output: Information organized in a predetermined format.

[0372] What it does: The server uses SQL queries to extract data from its internal database and retrieves data from external sources through APIs.

[0373] Step 4:

[0374] The server converts the collected information into appropriate text, table, graph, and image formats.

[0375] Input: Organized information.

[0376] Output: Data converted into text, table, graph and image formats.

[0377] Specific operation: Process data with the Pandas library and generate graphs with Matplotlib.

[0378] Step 5:

[0379] The server automatically generates the layout of the materials based on the converted information.

[0380] Input: The transformed data.

[0381] Output: Auto-generated document layout.

[0382] What it does: Uses a template engine to assemble a layout into the specified format.

[0383] Step 6:

[0384] The server generates text based on the automatically generated layout.

[0385] Input: Document layout.

[0386] Output: The generated description.

[0387] Specific operation: Generate sentences using generative AI models such as GPT-2.

[0388] Step 7:

[0389] The server presents the generated materials to the user and receives feedback.

[0390] Input: Generated materials.

[0391] Output: User feedback and sentiment data.

[0392] Specific operation: Materials are displayed on the device screen, and the user's reactions are captured using the camera and microphone.

[0393] Step 8:

[0394] The server dynamically adjusts the content and tone of the material based on user feedback and emotional data.

[0395] Input: User feedback, emotion data.

[0396] Output: The corrected document.

[0397] What it does: Uses a sentiment analysis model (BERT) to modify text and layout based on sentiment scores.

[0398] Step 9:

[0399] The server regenerates the modified material and presents it to the user for final confirmation.

[0400] Input: Corrected material.

[0401] Output: Final approved materials.

[0402] Specific operation: After receiving final confirmation from the user, the materials are output in PDF or PowerPoint format.

[0403] Through the above process, the system can efficiently create high-quality materials that reflect the user's emotions.

[0404] 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.

[0405] 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.

[0406] 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.

[0407] [Second embodiment]

[0408] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0409] 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.

[0410] 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).

[0411] 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.

[0412] 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.

[0413] 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).

[0414] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0415] 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.

[0416] 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.

[0417] 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.

[0418] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0419] 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."

[0420] The present invention is a system for improving the efficiency of document creation work, and includes various means for receiving document purpose and subject information from a user and automatically generating documents. This system can significantly reduce the time and effort required by users to create documents, and can also improve the quality and consistency of documents.

[0421] Input and analysis of needs

[0422] The user uses a terminal to input the purpose and target information of the document (e.g., sales presentation of a new product, target market, competitive information). The server receives this input information and begins analysis. Based on the results of the analysis, the server defines the necessary components of the document (e.g., product information, market analysis, competitive comparison, sales plan, budget graph).

[0423] Data collection and organization

[0424] The server collects the necessary information from internal databases and external sources. It obtains the company's product specifications and past sales data from internal databases, and market trends and competitive information from external sources. The server organizes the collected information and converts it into appropriate formats such as text, tables, graphs, and images. For example, new product specifications are organized in text and table format, and market trends are graphed.

[0425] Automatic layout generation of documents

[0426] The server determines the layout of each section of the document based on the organized information. Specifically, it automatically generates the order and color scheme templates for title slides, product information slides, market analysis slides, etc. The server then applies fonts, color schemes, page numbers, etc. based on the company's brand guidelines. For example, the company logo is placed in the bottom right corner of each slide based on a blue color scheme.

[0427] Automatic sentence generation

[0428] The server uses natural language processing technology to generate text based on the collected data. For example, for a product information slide, it generates a sentence such as "The new product offers a 20% performance improvement over the previous model" and adds it to the slide. It also adjusts the tone and style depending on the purpose of the document. For presentation materials, it uses a formal, business-oriented tone.

[0429] Accepting feedback and making corrections

[0430] The server can present the generated materials to the user and receive feedback. The user can check the materials through their terminal and input any necessary corrections (e.g., adjusting the size of graphs, correcting text). For example, they can input feedback such as "The graph for competitive comparison is small, so I would like it to be larger." The server will automatically make corrections based on the feedback and generate a new, revised material.

[0431] Final confirmation and document output

[0432] The user checks the revised document again and gives final approval. Check the final version of the document displayed on the terminal and, if satisfied, press the approval button. The server outputs the final version of the document in the user's desired format, such as PDF or PowerPoint. The output document is displayed on the terminal as a download link, which the user can use to distribute or present the document.

[0433] The present invention enables users to create documents efficiently and with high quality, significantly reducing the time and effort required for document creation, and also improves the consistency and quality of documents, thereby helping to improve business productivity.

[0434] The processing flow will be explained below.

[0435] Step 1:

[0436] The user uses the terminal to input the purpose and target information of the document. For example, the purpose is "sales presentation for a new product," and then adds details such as the target market and competitive information.

[0437] Step 2:

[0438] The server analyzes the entered purpose and target information and defines the necessary document components (e.g., product information, market analysis, competitor comparison, sales plan, budget graph). Based on this information, the server determines the type and amount of data required.

[0439] Step 3:

[0440] The server queries an internal database to gather relevant product information and past sales data, such as "product specifications" and "sales history."

[0441] Step 4:

[0442] The server gathers the necessary market trends and competitive information from external sources, for example, using a market research report API to get the latest market data.

[0443] Step 5:

[0444] The server organizes the collected data and converts it into text, tables, graphs, and images. Product specifications are converted into text and tables, and market trends are converted into graphs. For example, the specifications of a new product are compiled into a table, and market trends are converted into a line graph.

[0445] Step 6:

[0446] The server automatically generates a layout for the presentation materials based on this organized information. The layout includes a title slide, product information slide, market analysis slide, etc. For example, the first slide could contain the company logo and title, and the next slide could contain product information.

[0447] Step 7:

[0448] The server uses natural language processing technology to generate sentences based on the collected and organized information, such as "The new product offers 20% better performance than the previous model."

[0449] Step 8:

[0450] The server displays the generated document on the terminal and asks the user to confirm it. The user checks the contents of the document and enters feedback as necessary. For example, the user may enter feedback such as "I would like the size of the competitive comparison graph to be larger."

[0451] Step 9:

[0452] The server receives feedback from the user and automatically makes the specified modifications, for example, adjusting the size of the competitive comparison graph and regenerating the materials.

[0453] Step 10:

[0454] The user then reviews the revised documents and finally approves them. The approved documents are output by the server in PDF or PowerPoint format. The user can then download these documents from their device and use them for presentations or distribution.

[0455] By following the steps above, users can efficiently create high-quality materials in a short amount of time.

[0456] Example 1

[0457] 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."

[0458] In conventional document creation work, users spend a large amount of time and effort, and maintaining the quality and consistency of the documents is a challenge. In addition, many steps, such as collecting and organizing information for documents, setting layouts, and generating text, are done manually, so there is a need for efficiency improvements.

[0459] 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.

[0460] In this invention, the server includes means for receiving purpose and target information of the document from the user, means for analyzing the purpose and target information and defining the necessary components and types of information of the document, means for collecting the defined information from an internal database and external sources, means for organizing the collected information and converting it into appropriate text, table, graph, or image formats, means for automatically generating a layout of the document based on the converted information, means for generating text based on the automatically generated layout, means for presenting the generated document to the user and receiving feedback, means for automatically making corrections based on the feedback, and means for outputting the final version of the document in a format desired by the user. This significantly reduces the time and effort required for document creation and enables the efficient creation of high-quality, consistent documents.

[0461] A "user" is a person or organization that uses the system to create materials.

[0462] "Purpose" refers to the specific goal or intention of the user when creating the material.

[0463] "Target information" refers to data and information necessary for creating materials, such as product information, market analysis, and competitive information.

[0464] "Analysis" is the process of identifying the necessary components and types of information based on the input purpose and target information.

[0465] "Components" are the basic elements that make up the document, and specifically include product information, market analysis, competitive comparisons, sales plans, budget graphs, etc.

[0466] "Information" refers to the data and knowledge necessary to produce the materials. It is collected from internal databases and external sources.

[0467] An "internal database" is a collection of data managed within a company. For example, it may include product specifications and past sales data.

[0468] "External sources" are information sources obtained from outside the company, such as market trends and competitive information.

[0469] "Collection" is the process of obtaining required information from internal databases and external sources.

[0470] Organizing is the process of putting collected information into an appropriate format, such as text, tables, graphs, or images.

[0471] "Layout" refers to the arrangement and design of each section of the document, specifically including the order and color scheme of the title slide, product information slide, market analysis slide, etc.

[0472] "Natural language processing technology" is a technology that enables computers to understand and generate human language.

[0473] "Feedback" refers to evaluations and correction requests made by users regarding generated materials.

[0474] "Automatic correction" is the process by which the server automatically corrects the material based on user feedback.

[0475] "Final Version" means the completed version of the Material that has been finalized by the User.

[0476] "Format" refers to the format in which the materials are output. Examples include PDF and PowerPoint.

[0477] The present invention is a system that receives information on the purpose and target of a document from a user, automatically generates the document, and makes corrections based on the feedback. This system significantly reduces the time and effort required to create the document, enabling the efficient creation of high-quality, consistent documents.

[0478] First, the user uses a terminal to input the purpose and target information of the materials. For example, if you want to create a sales presentation for a new product, you would enter "new product information," "target market," "competitive information," etc. into the input form. The terminal then sends this information to the server.

[0479] The server then analyzes the received purpose and target information and defines the components and types of information required for the materials. This analysis is performed using a pre-trained generative AI model. For example, the components of a new product presentation material might include "product information," "market analysis," "competitive comparison," "sales plan," and "budget graph."

[0480] The server then collects the necessary information from internal databases and external sources. From the internal database, it obtains the company's product specifications and past sales data, and from external sources, it obtains market trends and competitive information. For example, the server uses web crawling technology to obtain the latest market trends.

[0481] The collected information is organized and converted into the appropriate format. For example, new product specifications are converted into text and tables, and market trends are graphed. Based on this organized information, the server automatically generates the layout for each section of the document. Specifically, it generates the order and color scheme templates for title slides, product information slides, market analysis slides, etc. Fonts, color schemes, page numbers, etc. are applied based on the company's brand guidelines.

[0482] The server then uses natural language processing technology to generate text based on the collected data. For example, a product information slide might say, "The new product offers 20% better performance than the previous model." The server also automatically adjusts tone and style depending on the purpose of the presentation. For business presentations, a formal tone is used.

[0483] The generated document is presented to the user, who can then input feedback via their terminal. For example, a request for corrections such as "The competitive comparison graph is too small, please make it larger" can be input. The server automatically makes corrections based on this feedback and regenerates the revised document.

[0484] Finally, the user checks the revised document on their device and, if satisfied, presses the approval button. The server outputs the final document in the user's desired format, such as PDF or PowerPoint. The output document is displayed on the device as a download link, which the user can use to distribute or present the document.

[0485] As a concrete example, consider the case where the following prompt is entered into a terminal:

[0486] Prompt statement:

[0487] I'd like to create a sales presentation for a new product. It should include information on the target market and competitors, as well as product specifications, market analysis, competitor comparisons, sales plans, and budget graphs. The presentation should use a blue color scheme, with the company logo placed in the bottom right corner of each slide.

[0488] Based on these prompts, the server collects and organizes the necessary information and automatically generates the layout and text. Once the user enters feedback and provides final approval, the completed document is output in PDF format. This series of processes enables users to quickly create efficient, high-quality documents, improving work productivity.

[0489] It can be seen that specific embodiments of the present invention streamline document creation and provide high quality, consistent documents.

[0490] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0491] Step 1:

[0492] The user uses the terminal to input the purpose and target information of the document. The input includes "new product information," "target market," and "competitive information" to create a sales presentation for a new product. The terminal sends this information to the server. The input data takes the form of text fields and drop-down menus, and is received by the server after it is sent.

[0493] Step 2:

[0494] The server analyzes the received purpose and target information using a generative AI model. Specifically, the server breaks down the purpose and target information and defines the components required for the document (product information, market analysis, competitive comparison, sales plan, budget graph, etc.). The output of this analysis is a requirements list for further specific information gathering and formatting.

[0495] Step 3:

[0496] The server collects the necessary information from internal databases and external sources. From the internal database, it obtains the company's product specifications and past sales data, and from external sources, it collects market trends and competitive information. For example, the server uses an API to obtain market trends from an external data provider. The collected data is organized into formats such as text, tables, graphs, and images.

[0497] Step 4:

[0498] The server organizes the collected information and converts it into various data formats. For example, new product specifications are converted into text and tables, and market trends are converted into graphs. Data formatting algorithms are used in this step. The output is a list of various types of data.

[0499] Step 5:

[0500] The server automatically generates the layout of the materials based on the organized information. Specifically, it generates the order and color scheme templates for each section (title slide, product information slide, market analysis slide, etc.). It also applies fonts, color schemes, page numbers, and other settings in accordance with the company's brand guidelines. For example, the server references a brand guideline database to determine the color scheme and applies it to each slide.

[0501] Step 6:

[0502] The server uses natural language processing technology to generate text based on the collected data. Using a generative AI model, it creates sentences such as "The new product offers 20% better performance than the previous model" for product information slides. The tone and style are automatically adjusted depending on the purpose of the document. The generated text is then placed in the appropriate place on each slide.

[0503] Step 7:

[0504] The server presents the generated document to the user. A preview of the document is displayed on the terminal, and the user checks it. The user can input feedback as needed. For example, the user may input a correction request such as "The competitive comparison graph is small, so I would like it to be larger." This feedback is sent to the server in real time.

[0505] Step 8:

[0506] The server automatically makes corrections based on user feedback. For example, it may enlarge the size of a competitive comparison graph. The corrected document is then regenerated and presented to the user. This feedback and correction process is repeated until the user is satisfied.

[0507] Step 9:

[0508] The user then checks the revised document again and gives final approval. When satisfied, they click the approval button displayed on their device. The server then outputs the final version of the document in PDF or PowerPoint format. The final version of the document is displayed on the device as a download link, which the user can use to distribute or present the document.

[0509] (Application example 1)

[0510] 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."

[0511] Conventional document creation systems require users to manually collect and organize a large amount of data, and then generate the content, which is extremely time-consuming and labor-intensive. It is also difficult to generate content optimized for smart devices, which can lead to a poor user experience. This can result in insufficient improvement in the consistency and quality of documents.

[0512] 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.

[0513] In this invention, the server includes means for receiving purpose and target information of materials from a user, means for analyzing the purpose and target information and defining the required structure of materials and the type of information, means for collecting the defined information from an internal database and external sources, means for organizing the collected information and converting it into an appropriate text, table, graph, or image format, means for automatically generating a layout of materials based on the converted information, means for generating text based on the automatically generated layout, means for automatically generating content for smart devices based on the generated text, means for displaying the generated content for smart devices, means for presenting the generated materials to a user and receiving feedback, and means for automatically making corrections based on the feedback, thereby enabling users to efficiently generate high-quality materials and content for smart devices.

[0514] The "means for receiving the purpose and target information of the material from the user" is an interface through which the user inputs the purpose and target information of the material to be provided.

[0515] "Means for analyzing the purpose and target information and defining the necessary material composition and type of information" refers to a system that determines the material composition and type of information to be collected based on the purpose and target information received from the user.

[0516] The "means for collecting the above-defined information from internal databases and external sources" refers to a function for collecting data from internal databases and external information sources based on the components of the material.

[0517] "Means for organizing the collected information and converting it into an appropriate text, table, graph, or image format" refers to the process of organizing the collected information and converting it into a format appropriate for the intended use.

[0518] The "means for automatically generating a layout of materials based on the converted information" is a system that automatically generates the appearance and arrangement of materials based on the converted information.

[0519] The "means for generating a sentence based on the automatically generated layout" is a function for generating a sentence using natural language processing technology based on the generated layout.

[0520] "Means for automatically generating content for smart devices based on the generated text" refers to a function that automatically generates content that is optimally displayed on devices such as smartphones and tablets based on the generated text.

[0521] The "means for displaying the generated content for smart devices" refers to a function for actually displaying the generated content for smart devices on the user's device.

[0522] The "means for presenting the generated materials to the user and receiving feedback" is an interface that shows the generated materials to the user and allows the user to input their opinions and corrections.

[0523] The "means for automatically correcting the material based on the feedback" is a function for receiving feedback from the user and automatically correcting the material based on the feedback.

[0524] This invention is a system for improving the efficiency of document creation work, and specifically includes various means for receiving purpose and target information of the document from a user and automatically generating, editing, and optimizing the document based on that information. Detailed embodiments of the invention are described below.

[0525] First, the user uses a smart device (e.g., smartphone, tablet, etc.) to input the purpose and target information of the document. The user interface is simple and designed to allow users to input information intuitively. Examples of input content include "presentation materials for new products," "target markets," and "competitive information."

[0526] The server analyzes the received information. This analysis involves defining the type of information needed (product information, market analysis, competitive comparison, etc.) based on the purpose and target information entered by the user. This analysis process uses natural language processing technology to accurately understand the user's request and identify the appropriate material components.

[0527] The server then collects the defined information from an internal database, such as the company's product specifications and past sales data, and from external sources, such as market trends and competitive information. The information collection process uses Python's requests and BeautifulSoup libraries.

[0528] The collected information is organized on the server and converted into appropriate formats such as text, tables, graphs, images, etc. Python's matplotlib and pandas libraries are used for text conversion and graph generation.

[0529] The server then automatically generates a layout for the document based on the converted information. This layout generation process includes font, color, and page number settings in accordance with the company's brand guidelines. It also includes a process to optimize the display on smart devices. The layout is constructed using an HTML template.

[0530] The server then generates text based on the automatically generated layout. The generated text is based on the collected data and has specific content. Using natural language processing technology, a sentence such as "The new product achieves a 20% performance improvement over the previous model" is generated.

[0531] After generating the text, the server automatically generates content for smart devices and displays it on the user's device. The user can review the generated content and enter any necessary feedback. An example of feedback might be, "The graph showing the competitive comparison is too small, so I'd like it to be larger."

[0532] The server automatically makes corrections based on the received feedback and regenerates the document, and the final version is output to the user in formats such as PDF or PowerPoint.

[0533] For example, if a user types "Generate a blog post about the AI ​​camera features of new smartphones," the server will gather market research data and generate an article about the features, market analysis, and future outlook of AI cameras. Here is an example prompt:

[0534] Generate a blog post about the latest trends in AI camera technology, including features, market analysis, and future prospects.

[0535] In this way, users can efficiently create high-quality materials and generate content for smart devices.

[0536] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0537] Step 1:

[0538] The user uses the terminal to input the purpose and target information of the document. The terminal provides a user interface, allowing the user to input the purpose of the document (e.g., "presentation materials for a new product") and target information (e.g., "target market" and "competitive information"). The input data is sent to the server.

[0539] Step 2:

[0540] The server analyzes the received purpose and target information and defines the components of the required materials and the type of information. The analysis process uses natural language processing technology to understand the information entered by the user and determine the appropriate material elements (e.g., "product information," "market analysis," "competitive comparison"), and the analysis results are output as a list.

[0541] Step 3:

[0542] The server collects defined information from an internal database and external sources. The internal database stores the company's product specifications and past sales data, and uses the requests and BeautifulSoup libraries to collect data from external sources (e.g., market trend sites and competitive information sites). The collected information is saved in text format.

[0543] Step 4:

[0544] The server organizes the collected information and converts it into the appropriate format (text, table, graph, image). For example, product information is organized into text and table format, and market trends are graphed. This process uses the pandas and matplotlib libraries. The converted data is then stored in temporary storage.

[0545] Step 5:

[0546] The server automatically generates a layout for the document based on the converted information. The layout is generated using an HTML template, and fonts, colors, and page numbers are set based on the company's brand guidelines. The generated layout is saved in HTML format.

[0547] Step 6:

[0548] The server uses natural language processing technology to generate text based on the automatically generated layout. For example, the generated text might include specific content such as "The new product achieves a 20% performance improvement over the previous model." The generated text is inserted into the HTML layout and saved in temporary storage as the final content.

[0549] Step 7:

[0550] The server automatically generates content for smart devices based on the generated text. For example, it applies responsive design that is optimally displayed on smartphones and tablets. The generated content for smart devices is then sent to the user's device.

[0551] Step 8:

[0552] The user checks the content generated for smart devices on their device and inputs any necessary feedback. An example of feedback might be, "The graph showing the competitive comparison is too small, so I'd like it to be larger." The feedback is then sent to the server.

[0553] Step 9:

[0554] The server automatically modifies the document based on the received feedback, adjusting the size of text and graphs, etc. The modified document is then saved again in HTML format.

[0555] Step 10:

[0556] The user checks the final version of the document again and presses the approval button. The server outputs the final version of the document in the user's desired format (e.g., PDF, PowerPoint) and generates a download link. The user can obtain the final version of the document via the link.

[0557] 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.

[0558] This invention is a system aimed at improving the efficiency and quality of document creation work, and combines an emotion engine that recognizes the user's emotions and dynamically adjusts the content and tone of the document. This system significantly reduces the time and effort required for users to create documents, and also enables customization according to individual needs and emotions.

[0559] Input and analysis of needs

[0560] The user uses a terminal to input the purpose and target information of the document (e.g., sales presentation of a new product, target market, competitive information). The server receives this input information and begins analysis. Based on the results of the analysis, the server defines the necessary components of the document (e.g., product information, market analysis, competitive comparison, sales plan, budget graph).

[0561] Data collection and organization

[0562] The server collects the necessary information from internal databases and external sources. It obtains the company's product specifications and past sales data from internal databases, and market trends and competitive information from external sources. The server organizes the collected information and converts it into appropriate formats such as text, tables, graphs, and images. For example, new product specifications are organized in text and table format, and market trends are graphed.

[0563] Automatic layout generation of documents

[0564] Based on the organized information, the server determines the layout of each section of the document, including the title slide, product information slide, and market analysis slide. The server then applies fonts, color schemes, page numbers, and other elements based on the company's brand guidelines. For example, the server uses a blue color scheme and places the company logo in the bottom right corner of each slide.

[0565] Automatic sentence generation

[0566] The server uses natural language processing technology to generate text based on the collected and organized information. For example, it creates a product information slide with a description such as, "The new product offers 20% better performance than the previous model." It also adjusts the tone and style depending on the purpose of the document. For presentation materials, it uses a formal, business-oriented tone.

[0567] Emotion engine accepts and corrects feedback

[0568] The server displays the generated materials on the terminal and asks the user to confirm them. The user then checks the contents of the materials and enters feedback as necessary. The emotion engine also analyzes the user's facial expressions and voice to recognize their emotions (such as surprise, joy, or dissatisfaction). The server then adjusts the content and tone of the materials according to the user's emotions identified by the emotion engine. For example, if the user shows a dissatisfied expression, the server modifies the design and text of that section to make it more specific and appealing.

[0569] Corrections based on feedback and final confirmation

[0570] The server automatically makes the specified modifications based on feedback from the user and the emotion engine. For example, based on feedback such as "Please make the size of the competitive comparison graph larger" and the emotion engine's analysis of the user's dissatisfaction, the server adjusts the size of the competitive comparison graph and regenerates the document. The user then checks the modified document again and finally approves it. The server outputs the approved document in PDF or PowerPoint format. The user can then download the document from their device and use it for presentations or distribution.

[0571] This invention allows users to create efficient, high-quality documents in a short time. It also enables customization according to the user's feelings, which is expected to improve the consistency and quality of documents and increase business productivity.

[0572] The processing flow will be explained below.

[0573] Step 1:

[0574] The user uses the terminal to input the purpose and target information of the document. Specifically, the user inputs the purpose as "sales presentation for a new product" and adds details such as the target market and competitive information.

[0575] Step 2:

[0576] The server analyzes the entered purpose and target information and defines the necessary document components (e.g., product information, market analysis, competitor comparison, sales plan, budget graph). Based on this information, the server determines the type and amount of data required.

[0577] Step 3:

[0578] The server queries the internal database to collect relevant product information and past sales data, and retrieves data such as "product specifications" and "sales history" from the internal database.

[0579] Step 4:

[0580] The server collects the necessary market trends and competitive information from external sources, and uses the market research report API to obtain the latest market data.

[0581] Step 5:

[0582] The server organizes the collected data and converts it into text, tables, graphs, and images. For example, it converts new product specifications into a table and market trends into a line graph.

[0583] Step 6:

[0584] The server automatically generates a layout for the presentation based on the organized information. The layout includes a title slide, product information slide, market analysis slide, etc. The server applies fonts, color schemes, page numbers, etc. based on the company's brand guidelines. For example, a blue color scheme is used and the company logo is placed in the bottom right corner of each slide.

[0585] Step 7:

[0586] The server uses natural language processing technology to generate text based on the collected and organized information, creating product information slides with descriptions such as "This new product offers 20% better performance than the previous model."

[0587] Step 8:

[0588] The server displays the generated document on the terminal and asks the user to confirm it. The user checks the contents of the document and enters feedback as necessary. For example, the user may enter a request such as "I would like the size of the competitive comparison graph to be larger."

[0589] Step 9:

[0590] When the user is confirmed, the server activates the emotion engine and analyzes the user's facial expressions and voice. The emotion engine identifies the user's emotion and sends the emotion data to the server. For example, if the user shows a dissatisfied expression, the server will receive the analysis result of the dissatisfaction.

[0591] Step 10:

[0592] Based on the analysis results of the emotion engine and user feedback, the server modifies specific parts of the document, for example, increasing the size of the competitive comparison graph and changing the color scheme to make it more appealing.

[0593] Step 11:

[0594] The user checks the revised document again on the terminal, and if the user is satisfied again, the server confirms the final version of the document at that point.

[0595] Step 12:

[0596] The server outputs the final, verified documents in PDF or PowerPoint format, and users can download these documents from their devices. Users can use these documents for presentations or distribution.

[0597] By following the steps above, the user can create efficient, high-quality materials in a short time, and furthermore, can customize the contents of the materials according to the user's feelings.

[0598] Example 2

[0599] 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."

[0600] Conventional document creation systems require users to manually collect and organize data, design layouts, and write documents, which is time-consuming, labor-intensive, and inefficient. Furthermore, if the content or tone of the document does not match the user's intentions or emotions, frequent revisions and additional work are required. This makes it difficult to maintain the quality and consistency of the document.

[0601] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0602] In this invention, the server includes: means for receiving purpose and target information for a document from a user; means for analyzing the purpose and target information and defining the necessary document components; means for collecting the defined information from an internal database and external sources; means for organizing the collected information and converting it into appropriate text, table, graph, or image formats; means for automatically generating a document layout based on the converted information; means for generating text based on the automatically generated layout; means for presenting the generated document to the user and receiving feedback; means for analyzing and recognizing the user's emotions regarding the document upon receiving feedback; means for dynamically adjusting the content and tone of the document based on the recognized emotional information; means for automatically making corrections based on the feedback and emotional information; and means for outputting the final document in PDF or presentation software format. This significantly reduces the time and effort required for document creation and enables dynamic adjustment of the content and tone of the document based on the user's emotions and feedback. As a result, efficient, high-quality documents can be created in a short time, enabling the provision of consistently high-quality documents.

[0603] "User" refers to a person who uses the system to create materials.

[0604] "Terminal" refers to a device through which a user inputs purpose and subject information for materials and provides feedback.

[0605] "Server" refers to a computer system that analyzes information input by users, collects and organizes data, generates layouts, and creates and edits text.

[0606] "Purpose and target information" refers to the information and target required for creating the document.

[0607] "Component" refers to the basic information unit that makes up a document.

[0608] An "internal database" refers to a collection of data that exists within a company.

[0609] "External sources" refers to information obtained from the Internet or other external resources.

[0610] "Text, tabular, graphical and image formats" refers to various formats for visually displaying information.

[0611] "Automatic layout generation" refers to the process of automatically determining the layout of slides and pages based on the elements that make up the document.

[0612] "Text generation" refers to the process of automatically creating the text contained in a document.

[0613] "Feedback" means suggestions for correction or improvement provided by a User after reviewing the Materials.

[0614] "Emotion engine" refers to a computer program that analyzes and recognizes a user's emotions.

[0615] "Dynamic adjustment" refers to changing the content and tone of material in real time based on feedback and emotional information.

[0616] "PDF or presentation software format" refers to the file format of the final output material.

[0617] This invention is a system aimed at improving the efficiency and quality of document creation work, and includes an emotion engine that recognizes the user's emotions and dynamically adjusts the content and tone of the document. This system significantly reduces the time and effort required for users to create documents, and also enables customization according to individual needs and emotions.

[0618] Input and analysis of needs

[0619] The user uses a terminal to input the purpose and target information of the document (e.g., sales presentation of a new product, target market, competitive information). The server receives this input information and performs semantic analysis using an NLP library (e.g., spaCy). This determines the necessary components of the document (e.g., product information, market analysis, competitive comparison, sales plan, budget graph).

[0620] Data collection and organization

[0621] The server collects the necessary information from an internal database (e.g., MySQL) and external sources (e.g., RESTful API, web scraping). From the internal database, it obtains the company's product specifications and past sales data, and from external sources, it obtains market trends and competitive information. Next, the server organizes the collected information and converts it into an appropriate format (e.g., text, table, graph, image). At this stage, the data is processed using libraries such as Pandas and Matplotlib. For example, the specifications of a new product are organized into text and tables, and market trends are visualized as a line graph.

[0622] Automatic layout generation of documents

[0623] The server uses PowerPoint libraries (e.g., python-pptx) to automatically generate the layout of the materials based on the organized information. This includes the placement of slide titles, content, graphs, images, etc. The server customizes fonts, color schemes, page numbers, etc. based on the company's brand guidelines. For example, it uses a blue color scheme, places the company logo in the bottom right corner of each slide, and adds page numbers.

[0624] Automatic sentence generation

[0625] The server uses natural language processing technology (e.g., GPT-3) to generate text based on the collected and organized information. For product information slides, it automatically generates explanatory text such as, "The new product achieves a 20% performance improvement over the previous model." It also adjusts the tone and style according to the purpose of the document. For presentation materials, a formal, business-oriented tone is used.

[0626] Emotion engine accepts and corrects feedback

[0627] The server displays the generated materials on the terminal and asks the user to confirm them. The user can then review the contents of the materials and enter feedback. The emotion engine also analyzes the user's facial expressions and voice to recognize their emotions (such as surprise, joy, or dissatisfaction). The server then adjusts the content and tone of the materials according to the user's emotions identified by the emotion engine. For example, if the user shows a dissatisfied expression, the server will modify the design and text of that section to make it more specific and appealing.

[0628] Corrections based on feedback and final confirmation

[0629] The server automatically makes the specified modifications based on feedback from the user and the emotion engine. For example, based on feedback such as "Please make the size of the competitive comparison graph larger" and the emotion engine's analysis of the user's dissatisfaction, the server adjusts the size of the competitive comparison graph and regenerates the document. The user then reviews the modified document again and gives their final approval. The server outputs the approved document in PDF or presentation software format. The user can then download the document from their device and use it for presentations or distribution.

[0630] Specific examples

[0631] For example, a user might input the following prompt into a generative AI model:

[0632] Example prompt:

[0633] "I would like to create a sales presentation for a new product. The target market is working women in their 30s, and my competitors are Company A and Company B. The presentation content should include product specifications, market trends, a comparison with other competitors, and a sales plan."

[0634] Based on these prompts, the server performs analysis, collects the necessary data, automatically generates the layout of the document, and creates the text. Through feedback using an emotion engine, the content and tone of the document can be dynamically adjusted to match the user's emotions, ultimately enabling the creation of high-quality documents in a short amount of time.

[0635] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0636] Step 1:

[0637] Input and analysis of needs

[0638] The user uses the terminal to input the purpose and target information of the material (for example, a sales presentation for a new product, a target market, competitive information).

[0639] (Input) The prompt entered by the user (in text format).

[0640] (Output) The results of analyzing the purpose and subject information of the material (list of components).

[0641] The server analyzes the received prompt using an NLP library (e.g., spaCy) to extract keywords and intent. Specifically, it extracts important information from the prompt (e.g., "new product," "sales presentation," "target market," etc.) and defines the components.

[0642] Step 2:

[0643] Data collection and organization

[0644] Based on the defined information, the server performs the task of collecting the necessary data from an internal database (e.g. MySQL) and external sources (e.g. RESTful API, web scraping).

[0645] (Input) A list of components.

[0646] (Output) Collected information (text data, table data, graph data, image data).

[0647] Specifically, it obtains product specifications and past sales data from internal databases, and market trends and competitive information from external sources.

[0648] The server then organizes the collected data using libraries such as Pandas and converts it into text, tables, graphs, and images. For example, it organizes new product specifications into text and tables, and converts market trends into line graphs.

[0649] Step 3:

[0650] Automatic layout generation of documents

[0651] The server automatically generates the layout of the materials using a PowerPoint library (e.g., python-pptx) based on the organized information.

[0652] (Input) Organized information (text, tables, graphs, images).

[0653] (Output) Automatically generated layout document.

[0654] Specifically, you can arrange the slide titles, content, graphs, images, etc., and set fonts, color schemes, and page numbers based on your company's brand guidelines. For example, you can place the company logo in a blue color scheme in the bottom right corner of each slide and add page numbers.

[0655] Step 4:

[0656] Automatic sentence generation

[0657] The server uses natural language processing technology (e.g., GPT-3) to generate sentences based on the collected and organized information.

[0658] (Input) Automatically generated layout materials and organized information.

[0659] (Output) The generated document with text.

[0660] Specifically, for product information slides, the system automatically generates explanatory text such as, "The new product achieves a 20% performance improvement over the previous model." Furthermore, the system adjusts the tone and style depending on the purpose of the document. For example, for presentation materials, a formal business tone is used.

[0661] Step 5:

[0662] Emotion engine accepts and corrects feedback

[0663] The server displays the generated materials on the terminal and asks the user to confirm them.

[0664] The user checks the content of the materials and inputs feedback. The emotion engine also analyzes the user's facial expressions and voice to recognize their emotions (surprise, joy, dissatisfaction, etc.).

[0665] (Input) User feedback and emotional data (facial expression recognition, voice analysis).

[0666] (Output) Corrections based on emotional information and feedback.

[0667] The server dynamically adjusts the content and tone of the materials based on the user's emotions and feedback recognized by the emotion engine. For example, if the user shows a dissatisfied expression, the server will modify the design and text of that section to make it more specific and appealing.

[0668] Step 6:

[0669] Corrections based on feedback and final confirmation

[0670] The server automatically modifies the materials based on feedback from the user and the emotion engine.

[0671] (Input) Corrections based on emotional information and feedback.

[0672] (Output) The revised final document.

[0673] For example, based on feedback such as "Please increase the size of the competitive comparison graph" and the results of an analysis of user dissatisfaction using an emotion engine, the graph size is adjusted and the document is generated again.

[0674] The user then checks the revised document again and gives final approval.

[0675] The server outputs approved materials in PDF or presentation software format, which users can download from their devices for presentations or distribution.

[0676] (Application example 2)

[0677] 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."

[0678] The task of creating materials related to autonomous vehicles requires a great deal of time and effort, particularly in collecting and organizing information, and creating presentation materials and text. Furthermore, conventional document creation systems make it difficult to customize materials to reflect individual user needs and emotions, creating challenges in ensuring quality and consistency. Furthermore, while it is necessary to appropriately reflect the user's emotions while creating materials, there is no efficient way to do this.

[0679] 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.

[0680] In this invention, the server includes means for receiving purpose and target information of the materials from the user, means for analyzing the purpose and target information and defining the required structure and type of information of the materials, means for collecting the defined information from an internal database and external sources, means for organizing the collected information and converting it into an appropriate text, table, graph, or image format, means for automatically generating a layout of the materials based on the converted information, means for generating text based on the automatically generated layout, means for presenting the generated materials to the user and receiving feedback, and means for analyzing the user's emotions and dynamically adjusting the content and tone of the materials, thereby enabling dynamic customization of materials based on the user's emotions and the creation of high-quality materials.

[0681] "User" refers to any person or company that uses the System to create Materials.

[0682] "Materials" refers to documents that organize and visually present information, such as presentations and reports.

[0683] "Purpose" refers to the final goal or aim of the user when creating a document.

[0684] "Target information" refers to the collection of specific data and information required to create materials.

[0685] "Analysis" refers to the process of analyzing input information in detail and deriving its meaning and relevance.

[0686] "Structure" refers to how information is organized within a document.

[0687] "Type of information" refers to the format and nature of the data required to make up the material (e.g., text, tables, graphs, images).

[0688] An "internal database" refers to a collection of data managed within a company or organization.

[0689] "External sources" refers to information sources obtained from outside the company or organization (e.g., market research data, public statistics).

[0690] "Collection" refers to the process of gathering the necessary data and information.

[0691] "Organization" refers to the process of organizing collected information in a purposeful manner.

[0692] "Transformation" refers to the process of transforming organized information into a different format (e.g., turning text information into a graph).

[0693] "Layout" refers to the arrangement of information within a document and the design structure.

[0694] "Automatic generation" refers to the system automatically performing a specific process without human intervention.

[0695] "Text generation" refers to the process by which a system automatically creates text.

[0696] "Feedback" refers to reactions and opinions from users.

[0697] "Revising" refers to the process of changing the content or format of material for the purpose of improvement.

[0698] "Analyzing emotions" refers to the process of reading and understanding a user's emotions from their facial expressions and voice.

[0699] "Tone" refers to the overall atmosphere or style of a piece of writing or presentation.

[0700] "Dynamic adjustment" refers to changing the content and format of materials in real time according to the situation and conditions.

[0701] This invention is a system that improves the efficiency and quality of document creation related to autonomous vehicles. It clarifies the roles of the server, terminal, and user, and provides specific operating procedures.

[0702] Program Generation

[0703] 1. The user enters the purpose and target information for creating the document via a device (e.g., a smartphone).

[0704] 2. The server receives the entered purpose and target information, analyzes it, and defines the components of the required materials and the type of information.

[0705] 3. The server collects the defined information from internal databases and external sources. Examples of internal databases include company product specifications and historical sales data, while examples of external sources include market trends and competitive information.

[0706] 4. The server organizes the collected information and converts it into appropriate text, table, graph, and image formats, using data analysis libraries such as Pandas and Matplotlib.

[0707] 5. The server automatically generates the layout of the materials based on the organized information. For example, it may use a blue color scheme and place the company logo in the bottom right corner of each slide.

[0708] 6. The server then uses natural language processing technology to generate sentences, such as "Our new product achieves a 20% performance improvement over the previous model," using a generative AI model (e.g., GPT-2).

[0709] 7. The server presents the generated materials to the user and receives feedback. The user uses a smartphone application to check the contents of the materials and enter feedback as needed. The user's facial expressions and voice are also captured through the device's camera and microphone and analyzed by the emotion engine.

[0710] 8. The server dynamically adjusts the content and tone of the materials based on this feedback and emotional data. For example, if the user shows a dissatisfied expression, the server will modify the design and text of that section to make it more specific and appealing.

[0711] 9. The server automatically makes the specified corrections and regenerates the document. The user then checks the corrected document again and finally approves it.

[0712] Hardware and Software

[0713] Hardware:

[0714] Devices such as smartphones and tablets

[0715] Cloud Server

[0716] Camera and microphone (for emotion analysis)

[0717] software:

[0718] Data collection and analysis: Pandas, Matplotlib

[0719] Natural Language Processing: GPT-2 (Hugging Face transformers library)

[0720] Sentiment analysis: BERT model (nlptown / bert-base-multilingual-uncased-sentiment)

[0721] Examples and prompts

[0722] For example, if a user types "I want to introduce a new navigation feature to my target market," the system will do the following:

[0723] The server collects details of new navigation features from an internal database, along with market trend information.

[0724] The automatically generated materials include sentences such as, "The new navigation function provides highly accurate location information services."

[0725] When a user inputs feedback that "information is insufficient," the server performs sentiment analysis and adds information about competitors' features.

[0726] Example prompt sentence:

[0727] "Get additional competitive comparison information for your customers and generate even more detailed graphs."

[0728] In this way, the system utilizes generative AI models and prompt sentences to create efficient, high-quality documents.

[0729] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0730] Step 1:

[0731] The user uses the terminal to input the purpose and target information of the material.

[0732] Input: Purpose of the material (e.g., introducing a new navigation feature) and subject information (target market, competitive information).

[0733] Output: The input data is sent to the cloud server.

[0734] Step 2:

[0735] The server analyzes the entered purpose and target information.

[0736] Input: Purpose and target information entered by the user.

[0737] Output: The components of the material and the type of information are defined.

[0738] Specific operation: The server performs natural language processing based on the input information and creates a list of the information required for the document.

[0739] Step 3:

[0740] The server collects the required information from an internal database and external sources.

[0741] Input: Material components and types of information.

[0742] Output: Information organized in a predetermined format.

[0743] What it does: The server uses SQL queries to extract data from its internal database and retrieves data from external sources through APIs.

[0744] Step 4:

[0745] The server converts the collected information into appropriate text, table, graph, and image formats.

[0746] Input: Organized information.

[0747] Output: Data converted into text, table, graph and image formats.

[0748] Specific operation: Process data with the Pandas library and generate graphs with Matplotlib.

[0749] Step 5:

[0750] The server automatically generates the layout of the materials based on the converted information.

[0751] Input: The transformed data.

[0752] Output: Auto-generated document layout.

[0753] What it does: Uses a template engine to assemble a layout into the specified format.

[0754] Step 6:

[0755] The server generates text based on the automatically generated layout.

[0756] Input: Document layout.

[0757] Output: The generated description.

[0758] Specific operation: Generate sentences using generative AI models such as GPT-2.

[0759] Step 7:

[0760] The server presents the generated materials to the user and receives feedback.

[0761] Input: Generated materials.

[0762] Output: User feedback and sentiment data.

[0763] Specific operation: Materials are displayed on the device screen, and the user's reactions are captured using the camera and microphone.

[0764] Step 8:

[0765] The server dynamically adjusts the content and tone of the material based on user feedback and emotional data.

[0766] Input: User feedback, emotion data.

[0767] Output: The corrected document.

[0768] What it does: Uses a sentiment analysis model (BERT) to modify text and layout based on sentiment scores.

[0769] Step 9:

[0770] The server regenerates the modified material and presents it to the user for final confirmation.

[0771] Input: Corrected material.

[0772] Output: Final approved materials.

[0773] Specific operation: After receiving final confirmation from the user, the materials are output in PDF or PowerPoint format.

[0774] Through the above process, the system can efficiently create high-quality materials that reflect the user's emotions.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] [Third embodiment]

[0779] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0780] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0781] 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).

[0782] 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.

[0783] 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.

[0784] 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).

[0785] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0786] 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.

[0787] 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.

[0788] 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.

[0789] 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.

[0790] 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."

[0791] The present invention is a system for improving the efficiency of document creation work, and includes various means for receiving document purpose and subject information from a user and automatically generating documents. This system can significantly reduce the time and effort required by users to create documents, and can also improve the quality and consistency of documents.

[0792] Input and analysis of needs

[0793] The user uses a terminal to input the purpose and target information of the document (e.g., sales presentation of a new product, target market, competitive information). The server receives this input information and begins analysis. Based on the results of the analysis, the server defines the necessary components of the document (e.g., product information, market analysis, competitive comparison, sales plan, budget graph).

[0794] Data collection and organization

[0795] The server collects the necessary information from internal databases and external sources. It obtains the company's product specifications and past sales data from internal databases, and market trends and competitive information from external sources. The server organizes the collected information and converts it into appropriate formats such as text, tables, graphs, and images. For example, new product specifications are organized in text and table format, and market trends are graphed.

[0796] Automatic layout generation of documents

[0797] The server determines the layout of each section of the document based on the organized information. Specifically, it automatically generates the order and color scheme templates for title slides, product information slides, market analysis slides, etc. The server then applies fonts, color schemes, page numbers, etc. based on the company's brand guidelines. For example, the company logo is placed in the bottom right corner of each slide based on a blue color scheme.

[0798] Automatic sentence generation

[0799] The server uses natural language processing technology to generate text based on the collected data. For example, for a product information slide, it generates a sentence such as "The new product offers a 20% performance improvement over the previous model" and adds it to the slide. It also adjusts the tone and style depending on the purpose of the document. For presentation materials, it uses a formal, business-oriented tone.

[0800] Accepting feedback and making corrections

[0801] The server can present the generated materials to the user and receive feedback. The user can check the materials through their terminal and input any necessary corrections (e.g., adjusting the size of graphs, correcting text). For example, they can input feedback such as "The graph for competitive comparison is small, so I would like it to be larger." The server will automatically make corrections based on the feedback and generate a new, revised material.

[0802] Final confirmation and document output

[0803] The user checks the revised document again and gives final approval. Check the final version of the document displayed on the terminal and, if satisfied, press the approval button. The server outputs the final version of the document in the user's desired format, such as PDF or PowerPoint. The output document is displayed on the terminal as a download link, which the user can use to distribute or present the document.

[0804] The present invention enables users to create documents efficiently and with high quality, significantly reducing the time and effort required for document creation, and also improves the consistency and quality of documents, thereby helping to improve business productivity.

[0805] The processing flow will be explained below.

[0806] Step 1:

[0807] The user uses the terminal to input the purpose and target information of the document. For example, the purpose is "sales presentation for a new product," and then adds details such as the target market and competitive information.

[0808] Step 2:

[0809] The server analyzes the entered purpose and target information and defines the necessary document components (e.g., product information, market analysis, competitor comparison, sales plan, budget graph). Based on this information, the server determines the type and amount of data required.

[0810] Step 3:

[0811] The server queries an internal database to gather relevant product information and past sales data, such as "product specifications" and "sales history."

[0812] Step 4:

[0813] The server gathers the necessary market trends and competitive information from external sources, for example, using a market research report API to get the latest market data.

[0814] Step 5:

[0815] The server organizes the collected data and converts it into text, tables, graphs, and images. Product specifications are converted into text and tables, and market trends are converted into graphs. For example, the specifications of a new product are compiled into a table, and market trends are converted into a line graph.

[0816] Step 6:

[0817] The server automatically generates a layout for the presentation materials based on this organized information. The layout includes a title slide, product information slide, market analysis slide, etc. For example, the first slide could contain the company logo and title, and the next slide could contain product information.

[0818] Step 7:

[0819] The server uses natural language processing technology to generate sentences based on the collected and organized information, such as "The new product offers 20% better performance than the previous model."

[0820] Step 8:

[0821] The server displays the generated document on the terminal and asks the user to confirm it. The user checks the contents of the document and enters feedback as necessary. For example, the user may enter feedback such as "I would like the size of the competitive comparison graph to be larger."

[0822] Step 9:

[0823] The server receives feedback from the user and automatically makes the specified modifications, for example, adjusting the size of the competitive comparison graph and regenerating the materials.

[0824] Step 10:

[0825] The user then reviews the revised documents and finally approves them. The approved documents are output by the server in PDF or PowerPoint format. The user can then download these documents from their device and use them for presentations or distribution.

[0826] By following the steps above, users can efficiently create high-quality materials in a short amount of time.

[0827] Example 1

[0828] 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."

[0829] In conventional document creation work, users spend a large amount of time and effort, and maintaining the quality and consistency of the documents is a challenge. In addition, many steps, such as collecting and organizing information for documents, setting layouts, and generating text, are done manually, so there is a need for efficiency improvements.

[0830] 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.

[0831] In this invention, the server includes means for receiving purpose and target information of the document from the user, means for analyzing the purpose and target information and defining the necessary components and types of information of the document, means for collecting the defined information from an internal database and external sources, means for organizing the collected information and converting it into appropriate text, table, graph, or image formats, means for automatically generating a layout of the document based on the converted information, means for generating text based on the automatically generated layout, means for presenting the generated document to the user and receiving feedback, means for automatically making corrections based on the feedback, and means for outputting the final version of the document in a format desired by the user. This significantly reduces the time and effort required for document creation and enables the efficient creation of high-quality, consistent documents.

[0832] A "user" is a person or organization that uses the system to create materials.

[0833] "Purpose" refers to the specific goal or intention of the user when creating the material.

[0834] "Target information" refers to data and information necessary for creating materials, such as product information, market analysis, and competitive information.

[0835] "Analysis" is the process of identifying the necessary components and types of information based on the input purpose and target information.

[0836] "Components" are the basic elements that make up the document, and specifically include product information, market analysis, competitive comparisons, sales plans, budget graphs, etc.

[0837] "Information" refers to the data and knowledge necessary to produce the materials. It is collected from internal databases and external sources.

[0838] An "internal database" is a collection of data managed within a company. For example, it may include product specifications and past sales data.

[0839] "External sources" are information sources obtained from outside the company, such as market trends and competitive information.

[0840] "Collection" is the process of obtaining required information from internal databases and external sources.

[0841] Organizing is the process of putting collected information into an appropriate format, such as text, tables, graphs, or images.

[0842] "Layout" refers to the arrangement and design of each section of the document, specifically including the order and color scheme of the title slide, product information slide, market analysis slide, etc.

[0843] "Natural language processing technology" is a technology that enables computers to understand and generate human language.

[0844] "Feedback" refers to evaluations and correction requests made by users regarding generated materials.

[0845] "Automatic correction" is the process by which the server automatically corrects the material based on user feedback.

[0846] "Final Version" means the completed version of the Material that has been finalized by the User.

[0847] "Format" refers to the format in which the materials are output. Examples include PDF and PowerPoint.

[0848] The present invention is a system that receives information on the purpose and target of a document from a user, automatically generates the document, and makes corrections based on the feedback. This system significantly reduces the time and effort required to create the document, enabling the efficient creation of high-quality, consistent documents.

[0849] First, the user uses a terminal to input the purpose and target information of the materials. For example, if you want to create a sales presentation for a new product, you would enter "new product information," "target market," "competitive information," etc. into the input form. The terminal then sends this information to the server.

[0850] The server then analyzes the received purpose and target information and defines the components and types of information required for the materials. This analysis is performed using a pre-trained generative AI model. For example, the components of a new product presentation material might include "product information," "market analysis," "competitive comparison," "sales plan," and "budget graph."

[0851] The server then collects the necessary information from internal databases and external sources. From the internal database, it obtains the company's product specifications and past sales data, and from external sources, it obtains market trends and competitive information. For example, the server uses web crawling technology to obtain the latest market trends.

[0852] The collected information is organized and converted into the appropriate format. For example, new product specifications are converted into text and tables, and market trends are graphed. Based on this organized information, the server automatically generates the layout for each section of the document. Specifically, it generates the order and color scheme templates for title slides, product information slides, market analysis slides, etc. Fonts, color schemes, page numbers, etc. are applied based on the company's brand guidelines.

[0853] The server then uses natural language processing technology to generate text based on the collected data. For example, a product information slide might say, "The new product offers 20% better performance than the previous model." The server also automatically adjusts tone and style depending on the purpose of the presentation. For business presentations, a formal tone is used.

[0854] The generated document is presented to the user, who can then input feedback via their terminal. For example, a request for corrections such as "The competitive comparison graph is too small, please make it larger" can be input. The server automatically makes corrections based on this feedback and regenerates the revised document.

[0855] Finally, the user checks the revised document on their device and, if satisfied, presses the approval button. The server outputs the final document in the user's desired format, such as PDF or PowerPoint. The output document is displayed on the device as a download link, which the user can use to distribute or present the document.

[0856] As a concrete example, consider the case where the following prompt is entered into a terminal:

[0857] Prompt statement:

[0858] I'd like to create a sales presentation for a new product. It should include information on the target market and competitors, as well as product specifications, market analysis, competitor comparisons, sales plans, and budget graphs. The presentation should use a blue color scheme, with the company logo placed in the bottom right corner of each slide.

[0859] Based on these prompts, the server collects and organizes the necessary information and automatically generates the layout and text. Once the user enters feedback and provides final approval, the completed document is output in PDF format. This series of processes enables users to quickly create efficient, high-quality documents, improving work productivity.

[0860] It can be seen that specific embodiments of the present invention streamline document creation and provide high quality, consistent documents.

[0861] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0862] Step 1:

[0863] The user uses the terminal to input the purpose and target information of the document. The input includes "new product information," "target market," and "competitive information" to create a sales presentation for a new product. The terminal sends this information to the server. The input data takes the form of text fields and drop-down menus, and is received by the server after it is sent.

[0864] Step 2:

[0865] The server analyzes the received purpose and target information using a generative AI model. Specifically, the server breaks down the purpose and target information and defines the components required for the document (product information, market analysis, competitive comparison, sales plan, budget graph, etc.). The output of this analysis is a requirements list for further specific information gathering and formatting.

[0866] Step 3:

[0867] The server collects the necessary information from internal databases and external sources. From the internal database, it obtains the company's product specifications and past sales data, and from external sources, it collects market trends and competitive information. For example, the server uses an API to obtain market trends from an external data provider. The collected data is organized into formats such as text, tables, graphs, and images.

[0868] Step 4:

[0869] The server organizes the collected information and converts it into various data formats. For example, new product specifications are converted into text and tables, and market trends are converted into graphs. Data formatting algorithms are used in this step. The output is a list of various types of data.

[0870] Step 5:

[0871] The server automatically generates the layout of the materials based on the organized information. Specifically, it generates the order and color scheme templates for each section (title slide, product information slide, market analysis slide, etc.). It also applies fonts, color schemes, page numbers, and other settings in accordance with the company's brand guidelines. For example, the server references a brand guideline database to determine the color scheme and applies it to each slide.

[0872] Step 6:

[0873] The server uses natural language processing technology to generate text based on the collected data. Using a generative AI model, it creates sentences such as "The new product offers 20% better performance than the previous model" for product information slides. The tone and style are automatically adjusted depending on the purpose of the document. The generated text is then placed in the appropriate place on each slide.

[0874] Step 7:

[0875] The server presents the generated document to the user. A preview of the document is displayed on the terminal, and the user checks it. The user can input feedback as needed. For example, the user may input a correction request such as "The competitive comparison graph is small, so I would like it to be larger." This feedback is sent to the server in real time.

[0876] Step 8:

[0877] The server automatically makes corrections based on user feedback. For example, it may enlarge the size of a competitive comparison graph. The corrected document is then regenerated and presented to the user. This feedback and correction process is repeated until the user is satisfied.

[0878] Step 9:

[0879] The user then checks the revised document again and gives final approval. When satisfied, they click the approval button displayed on their device. The server then outputs the final version of the document in PDF or PowerPoint format. The final version of the document is displayed on the device as a download link, which the user can use to distribute or present the document.

[0880] (Application example 1)

[0881] 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."

[0882] Conventional document creation systems require users to manually collect and organize a large amount of data, and then generate the content, which is extremely time-consuming and labor-intensive. It is also difficult to generate content optimized for smart devices, which can lead to a poor user experience. This can result in insufficient improvement in the consistency and quality of documents.

[0883] 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.

[0884] In this invention, the server includes means for receiving purpose and target information of materials from a user, means for analyzing the purpose and target information and defining the required structure of materials and the type of information, means for collecting the defined information from an internal database and external sources, means for organizing the collected information and converting it into an appropriate text, table, graph, or image format, means for automatically generating a layout of materials based on the converted information, means for generating text based on the automatically generated layout, means for automatically generating content for smart devices based on the generated text, means for displaying the generated content for smart devices, means for presenting the generated materials to a user and receiving feedback, and means for automatically making corrections based on the feedback, thereby enabling users to efficiently generate high-quality materials and content for smart devices.

[0885] The "means for receiving the purpose and target information of the material from the user" is an interface through which the user inputs the purpose and target information of the material to be provided.

[0886] "Means for analyzing the purpose and target information and defining the necessary material composition and type of information" refers to a system that determines the material composition and type of information to be collected based on the purpose and target information received from the user.

[0887] The "means for collecting the above-defined information from internal databases and external sources" refers to a function for collecting data from internal databases and external information sources based on the components of the material.

[0888] "Means for organizing the collected information and converting it into an appropriate text, table, graph, or image format" refers to the process of organizing the collected information and converting it into a format appropriate for the intended use.

[0889] The "means for automatically generating a layout of materials based on the converted information" is a system that automatically generates the appearance and arrangement of materials based on the converted information.

[0890] The "means for generating a sentence based on the automatically generated layout" is a function for generating a sentence using natural language processing technology based on the generated layout.

[0891] "Means for automatically generating content for smart devices based on the generated text" refers to a function that automatically generates content that is optimally displayed on devices such as smartphones and tablets based on the generated text.

[0892] The "means for displaying the generated content for smart devices" refers to a function for actually displaying the generated content for smart devices on the user's device.

[0893] The "means for presenting the generated materials to the user and receiving feedback" is an interface that shows the generated materials to the user and allows the user to input their opinions and corrections.

[0894] The "means for automatically correcting the material based on the feedback" is a function for receiving feedback from the user and automatically correcting the material based on the feedback.

[0895] This invention is a system for improving the efficiency of document creation work, and specifically includes various means for receiving purpose and target information of the document from a user and automatically generating, editing, and optimizing the document based on that information. Detailed embodiments of the invention are described below.

[0896] First, the user uses a smart device (e.g., smartphone, tablet, etc.) to input the purpose and target information of the document. The user interface is simple and designed to allow users to input information intuitively. Examples of input content include "presentation materials for new products," "target markets," and "competitive information."

[0897] The server analyzes the received information. This analysis involves defining the type of information needed (product information, market analysis, competitive comparison, etc.) based on the purpose and target information entered by the user. This analysis process uses natural language processing technology to accurately understand the user's request and identify the appropriate material components.

[0898] The server then collects the defined information from an internal database, such as the company's product specifications and past sales data, and from external sources, such as market trends and competitive information. The information collection process uses Python's requests and BeautifulSoup libraries.

[0899] The collected information is organized on the server and converted into appropriate formats such as text, tables, graphs, images, etc. Python's matplotlib and pandas libraries are used for text conversion and graph generation.

[0900] The server then automatically generates a layout for the document based on the converted information. This layout generation process includes font, color, and page number settings in accordance with the company's brand guidelines. It also includes a process to optimize the display on smart devices. The layout is constructed using an HTML template.

[0901] The server then generates text based on the automatically generated layout. The generated text is based on the collected data and has specific content. Using natural language processing technology, a sentence such as "The new product achieves a 20% performance improvement over the previous model" is generated.

[0902] After generating the text, the server automatically generates content for smart devices and displays it on the user's device. The user can review the generated content and enter any necessary feedback. An example of feedback might be, "The graph showing the competitive comparison is too small, so I'd like it to be larger."

[0903] The server automatically makes corrections based on the received feedback and regenerates the document, and the final version is output to the user in formats such as PDF or PowerPoint.

[0904] For example, if a user types "Generate a blog post about the AI ​​camera features of new smartphones," the server will gather market research data and generate an article about the features, market analysis, and future outlook of AI cameras. Here is an example prompt:

[0905] Generate a blog post about the latest trends in AI camera technology, including features, market analysis, and future prospects.

[0906] In this way, users can efficiently create high-quality materials and generate content for smart devices.

[0907] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0908] Step 1:

[0909] The user uses the terminal to input the purpose and target information of the document. The terminal provides a user interface, allowing the user to input the purpose of the document (e.g., "presentation materials for a new product") and target information (e.g., "target market" and "competitive information"). The input data is sent to the server.

[0910] Step 2:

[0911] The server analyzes the received purpose and target information and defines the components of the required materials and the type of information. The analysis process uses natural language processing technology to understand the information entered by the user and determine the appropriate material elements (e.g., "product information," "market analysis," "competitive comparison"), and the analysis results are output as a list.

[0912] Step 3:

[0913] The server collects defined information from an internal database and external sources. The internal database stores the company's product specifications and past sales data, and uses the requests and BeautifulSoup libraries to collect data from external sources (e.g., market trend sites and competitive information sites). The collected information is saved in text format.

[0914] Step 4:

[0915] The server organizes the collected information and converts it into the appropriate format (text, table, graph, image). For example, product information is organized into text and table format, and market trends are graphed. This process uses the pandas and matplotlib libraries. The converted data is then stored in temporary storage.

[0916] Step 5:

[0917] The server automatically generates a layout for the document based on the converted information. The layout is generated using an HTML template, and fonts, colors, and page numbers are set based on the company's brand guidelines. The generated layout is saved in HTML format.

[0918] Step 6:

[0919] The server uses natural language processing technology to generate text based on the automatically generated layout. For example, the generated text might include specific content such as "The new product achieves a 20% performance improvement over the previous model." The generated text is inserted into the HTML layout and saved in temporary storage as the final content.

[0920] Step 7:

[0921] The server automatically generates content for smart devices based on the generated text. For example, it applies responsive design that is optimally displayed on smartphones and tablets. The generated content for smart devices is then sent to the user's device.

[0922] Step 8:

[0923] The user checks the content generated for smart devices on their device and inputs any necessary feedback. An example of feedback might be, "The graph showing the competitive comparison is too small, so I'd like it to be larger." The feedback is then sent to the server.

[0924] Step 9:

[0925] The server automatically modifies the document based on the received feedback, adjusting the size of text and graphs, etc. The modified document is then saved again in HTML format.

[0926] Step 10:

[0927] The user checks the final version of the document again and presses the approval button. The server outputs the final version of the document in the user's desired format (e.g., PDF, PowerPoint) and generates a download link. The user can obtain the final version of the document via the link.

[0928] 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.

[0929] This invention is a system aimed at improving the efficiency and quality of document creation work, and combines an emotion engine that recognizes the user's emotions and dynamically adjusts the content and tone of the document. This system significantly reduces the time and effort required for users to create documents, and also enables customization according to individual needs and emotions.

[0930] Input and analysis of needs

[0931] The user uses a terminal to input the purpose and target information of the document (e.g., sales presentation of a new product, target market, competitive information). The server receives this input information and begins analysis. Based on the results of the analysis, the server defines the necessary components of the document (e.g., product information, market analysis, competitive comparison, sales plan, budget graph).

[0932] Data collection and organization

[0933] The server collects the necessary information from internal databases and external sources. It obtains the company's product specifications and past sales data from internal databases, and market trends and competitive information from external sources. The server organizes the collected information and converts it into appropriate formats such as text, tables, graphs, and images. For example, new product specifications are organized in text and table format, and market trends are graphed.

[0934] Automatic layout generation of documents

[0935] Based on the organized information, the server determines the layout of each section of the document, including the title slide, product information slide, and market analysis slide. The server then applies fonts, color schemes, page numbers, and other elements based on the company's brand guidelines. For example, the server uses a blue color scheme and places the company logo in the bottom right corner of each slide.

[0936] Automatic sentence generation

[0937] The server uses natural language processing technology to generate text based on the collected and organized information. For example, it creates a product information slide with a description such as, "The new product offers 20% better performance than the previous model." It also adjusts the tone and style depending on the purpose of the document. For presentation materials, it uses a formal, business-oriented tone.

[0938] Emotion engine accepts and corrects feedback

[0939] The server displays the generated materials on the terminal and asks the user to confirm them. The user then checks the contents of the materials and enters feedback as necessary. The emotion engine also analyzes the user's facial expressions and voice to recognize their emotions (such as surprise, joy, or dissatisfaction). The server then adjusts the content and tone of the materials according to the user's emotions identified by the emotion engine. For example, if the user shows a dissatisfied expression, the server modifies the design and text of that section to make it more specific and appealing.

[0940] Corrections based on feedback and final confirmation

[0941] The server automatically makes the specified modifications based on feedback from the user and the emotion engine. For example, based on feedback such as "Please make the size of the competitive comparison graph larger" and the emotion engine's analysis of the user's dissatisfaction, the server adjusts the size of the competitive comparison graph and regenerates the document. The user then checks the modified document again and finally approves it. The server outputs the approved document in PDF or PowerPoint format. The user can then download the document from their device and use it for presentations or distribution.

[0942] This invention allows users to create efficient, high-quality documents in a short time. It also enables customization according to the user's feelings, which is expected to improve the consistency and quality of documents and increase business productivity.

[0943] The processing flow will be explained below.

[0944] Step 1:

[0945] The user uses the terminal to input the purpose and target information of the document. Specifically, the user inputs the purpose as "sales presentation for a new product" and adds details such as the target market and competitive information.

[0946] Step 2:

[0947] The server analyzes the entered purpose and target information and defines the necessary document components (e.g., product information, market analysis, competitor comparison, sales plan, budget graph). Based on this information, the server determines the type and amount of data required.

[0948] Step 3:

[0949] The server queries the internal database to collect relevant product information and past sales data, and retrieves data such as "product specifications" and "sales history" from the internal database.

[0950] Step 4:

[0951] The server collects the necessary market trends and competitive information from external sources, and uses the market research report API to obtain the latest market data.

[0952] Step 5:

[0953] The server organizes the collected data and converts it into text, tables, graphs, and images. For example, it converts new product specifications into a table and market trends into a line graph.

[0954] Step 6:

[0955] The server automatically generates a layout for the presentation based on the organized information. The layout includes a title slide, product information slide, market analysis slide, etc. The server applies fonts, color schemes, page numbers, etc. based on the company's brand guidelines. For example, a blue color scheme is used and the company logo is placed in the bottom right corner of each slide.

[0956] Step 7:

[0957] The server uses natural language processing technology to generate text based on the collected and organized information, creating product information slides with descriptions such as "This new product offers 20% better performance than the previous model."

[0958] Step 8:

[0959] The server displays the generated document on the terminal and asks the user to confirm it. The user checks the contents of the document and enters feedback as necessary. For example, the user may enter a request such as "I would like the size of the competitive comparison graph to be larger."

[0960] Step 9:

[0961] When the user is confirmed, the server activates the emotion engine and analyzes the user's facial expressions and voice. The emotion engine identifies the user's emotion and sends the emotion data to the server. For example, if the user shows a dissatisfied expression, the server will receive the analysis result of the dissatisfaction.

[0962] Step 10:

[0963] Based on the analysis results of the emotion engine and user feedback, the server modifies specific parts of the document, for example, increasing the size of the competitive comparison graph and changing the color scheme to make it more appealing.

[0964] Step 11:

[0965] The user checks the revised document again on the terminal, and if the user is satisfied again, the server confirms the final version of the document at that point.

[0966] Step 12:

[0967] The server outputs the final, verified documents in PDF or PowerPoint format, and users can download these documents from their devices. Users can use these documents for presentations or distribution.

[0968] By following the steps above, the user can create efficient, high-quality materials in a short time, and furthermore, can customize the contents of the materials according to the user's feelings.

[0969] Example 2

[0970] 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."

[0971] Conventional document creation systems require users to manually collect and organize data, design layouts, and write documents, which is time-consuming, labor-intensive, and inefficient. Furthermore, if the content or tone of the document does not match the user's intentions or emotions, frequent revisions and additional work are required. This makes it difficult to maintain the quality and consistency of the document.

[0972] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0973] In this invention, the server includes: means for receiving purpose and target information for a document from a user; means for analyzing the purpose and target information and defining the necessary document components; means for collecting the defined information from an internal database and external sources; means for organizing the collected information and converting it into appropriate text, table, graph, or image formats; means for automatically generating a document layout based on the converted information; means for generating text based on the automatically generated layout; means for presenting the generated document to the user and receiving feedback; means for analyzing and recognizing the user's emotions regarding the document upon receiving feedback; means for dynamically adjusting the content and tone of the document based on the recognized emotional information; means for automatically making corrections based on the feedback and emotional information; and means for outputting the final document in PDF or presentation software format. This significantly reduces the time and effort required for document creation and enables dynamic adjustment of the content and tone of the document based on the user's emotions and feedback. As a result, efficient, high-quality documents can be created in a short time, enabling the provision of consistently high-quality documents.

[0974] "User" refers to a person who uses the system to create materials.

[0975] "Terminal" refers to a device through which a user inputs purpose and subject information for materials and provides feedback.

[0976] "Server" refers to a computer system that analyzes information input by users, collects and organizes data, generates layouts, and creates and edits text.

[0977] "Purpose and target information" refers to the information and target required for creating the document.

[0978] "Component" refers to the basic information unit that makes up a document.

[0979] An "internal database" refers to a collection of data that exists within a company.

[0980] "External sources" refers to information obtained from the Internet or other external resources.

[0981] "Text, tabular, graphical and image formats" refers to various formats for visually displaying information.

[0982] "Automatic layout generation" refers to the process of automatically determining the layout of slides and pages based on the elements that make up the document.

[0983] "Text generation" refers to the process of automatically creating the text contained in a document.

[0984] "Feedback" means suggestions for correction or improvement provided by a User after reviewing the Materials.

[0985] "Emotion engine" refers to a computer program that analyzes and recognizes a user's emotions.

[0986] "Dynamic adjustment" refers to changing the content and tone of material in real time based on feedback and emotional information.

[0987] "PDF or presentation software format" refers to the file format of the final output material.

[0988] This invention is a system aimed at improving the efficiency and quality of document creation work, and includes an emotion engine that recognizes the user's emotions and dynamically adjusts the content and tone of the document. This system significantly reduces the time and effort required for users to create documents, and also enables customization according to individual needs and emotions.

[0989] Input and analysis of needs

[0990] The user uses a terminal to input the purpose and target information of the document (e.g., sales presentation of a new product, target market, competitive information). The server receives this input information and performs semantic analysis using an NLP library (e.g., spaCy). This determines the necessary components of the document (e.g., product information, market analysis, competitive comparison, sales plan, budget graph).

[0991] Data collection and organization

[0992] The server collects the necessary information from an internal database (e.g., MySQL) and external sources (e.g., RESTful API, web scraping). From the internal database, it obtains the company's product specifications and past sales data, and from external sources, it obtains market trends and competitive information. Next, the server organizes the collected information and converts it into an appropriate format (e.g., text, table, graph, image). At this stage, the data is processed using libraries such as Pandas and Matplotlib. For example, the specifications of a new product are organized into text and tables, and market trends are visualized as a line graph.

[0993] Automatic layout generation of documents

[0994] The server uses PowerPoint libraries (e.g., python-pptx) to automatically generate the layout of the materials based on the organized information. This includes the placement of slide titles, content, graphs, images, etc. The server customizes fonts, color schemes, page numbers, etc. based on the company's brand guidelines. For example, it uses a blue color scheme, places the company logo in the bottom right corner of each slide, and adds page numbers.

[0995] Automatic sentence generation

[0996] The server uses natural language processing technology (e.g., GPT-3) to generate text based on the collected and organized information. For product information slides, it automatically generates explanatory text such as, "The new product achieves a 20% performance improvement over the previous model." It also adjusts the tone and style according to the purpose of the document. For presentation materials, a formal, business-oriented tone is used.

[0997] Emotion engine accepts and corrects feedback

[0998] The server displays the generated materials on the terminal and asks the user to confirm them. The user can then review the contents of the materials and enter feedback. The emotion engine also analyzes the user's facial expressions and voice to recognize their emotions (such as surprise, joy, or dissatisfaction). The server then adjusts the content and tone of the materials according to the user's emotions identified by the emotion engine. For example, if the user shows a dissatisfied expression, the server will modify the design and text of that section to make it more specific and appealing.

[0999] Corrections based on feedback and final confirmation

[1000] The server automatically makes the specified modifications based on feedback from the user and the emotion engine. For example, based on feedback such as "Please make the size of the competitive comparison graph larger" and the emotion engine's analysis of the user's dissatisfaction, the server adjusts the size of the competitive comparison graph and regenerates the document. The user then reviews the modified document again and gives their final approval. The server outputs the approved document in PDF or presentation software format. The user can then download the document from their device and use it for presentations or distribution.

[1001] Specific examples

[1002] For example, a user might input the following prompt into a generative AI model:

[1003] Example prompt:

[1004] "I would like to create a sales presentation for a new product. The target market is working women in their 30s, and my competitors are Company A and Company B. The presentation content should include product specifications, market trends, a comparison with other competitors, and a sales plan."

[1005] Based on these prompts, the server performs analysis, collects the necessary data, automatically generates the layout of the document, and creates the text. Through feedback using an emotion engine, the content and tone of the document can be dynamically adjusted to match the user's emotions, ultimately enabling the creation of high-quality documents in a short amount of time.

[1006] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1007] Step 1:

[1008] Input and analysis of needs

[1009] The user uses the terminal to input the purpose and target information of the material (for example, a sales presentation for a new product, a target market, competitive information).

[1010] (Input) The prompt entered by the user (in text format).

[1011] (Output) The results of analyzing the purpose and subject information of the material (list of components).

[1012] The server analyzes the received prompt using an NLP library (e.g., spaCy) to extract keywords and intent. Specifically, it extracts important information from the prompt (e.g., "new product," "sales presentation," "target market," etc.) and defines the components.

[1013] Step 2:

[1014] Data collection and organization

[1015] Based on the defined information, the server performs the task of collecting the necessary data from an internal database (e.g. MySQL) and external sources (e.g. RESTful API, web scraping).

[1016] (Input) A list of components.

[1017] (Output) Collected information (text data, table data, graph data, image data).

[1018] Specifically, it obtains product specifications and past sales data from internal databases, and market trends and competitive information from external sources.

[1019] The server then organizes the collected data using libraries such as Pandas and converts it into text, tables, graphs, and images. For example, it organizes new product specifications into text and tables, and converts market trends into line graphs.

[1020] Step 3:

[1021] Automatic layout generation of documents

[1022] The server automatically generates the layout of the materials using a PowerPoint library (e.g., python-pptx) based on the organized information.

[1023] (Input) Organized information (text, tables, graphs, images).

[1024] (Output) Automatically generated layout document.

[1025] Specifically, you can arrange the slide titles, content, graphs, images, etc., and set fonts, color schemes, and page numbers based on your company's brand guidelines. For example, you can place the company logo in a blue color scheme in the bottom right corner of each slide and add page numbers.

[1026] Step 4:

[1027] Automatic sentence generation

[1028] The server uses natural language processing technology (e.g., GPT-3) to generate sentences based on the collected and organized information.

[1029] (Input) Automatically generated layout materials and organized information.

[1030] (Output) The generated document with text.

[1031] Specifically, for product information slides, the system automatically generates explanatory text such as, "The new product achieves a 20% performance improvement over the previous model." Furthermore, the system adjusts the tone and style depending on the purpose of the document. For example, for presentation materials, a formal business tone is used.

[1032] Step 5:

[1033] Emotion engine accepts and corrects feedback

[1034] The server displays the generated materials on the terminal and asks the user to confirm them.

[1035] The user checks the content of the materials and inputs feedback. The emotion engine also analyzes the user's facial expressions and voice to recognize their emotions (surprise, joy, dissatisfaction, etc.).

[1036] (Input) User feedback and emotional data (facial expression recognition, voice analysis).

[1037] (Output) Corrections based on emotional information and feedback.

[1038] The server dynamically adjusts the content and tone of the materials based on the user's emotions and feedback recognized by the emotion engine. For example, if the user shows a dissatisfied expression, the server will modify the design and text of that section to make it more specific and appealing.

[1039] Step 6:

[1040] Corrections based on feedback and final confirmation

[1041] The server automatically modifies the materials based on feedback from the user and the emotion engine.

[1042] (Input) Corrections based on emotional information and feedback.

[1043] (Output) The revised final document.

[1044] For example, based on feedback such as "Please increase the size of the competitive comparison graph" and the results of an analysis of user dissatisfaction using an emotion engine, the graph size is adjusted and the document is generated again.

[1045] The user then checks the revised document again and gives final approval.

[1046] The server outputs approved materials in PDF or presentation software format, which users can download from their devices for presentations or distribution.

[1047] (Application example 2)

[1048] 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."

[1049] The task of creating materials related to autonomous vehicles requires a great deal of time and effort, particularly in collecting and organizing information, and creating presentation materials and text. Furthermore, conventional document creation systems make it difficult to customize materials to reflect individual user needs and emotions, creating challenges in ensuring quality and consistency. Furthermore, while it is necessary to appropriately reflect the user's emotions while creating materials, there is no efficient way to do this.

[1050] 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.

[1051] In this invention, the server includes means for receiving purpose and target information of the materials from the user, means for analyzing the purpose and target information and defining the required structure and type of information of the materials, means for collecting the defined information from an internal database and external sources, means for organizing the collected information and converting it into an appropriate text, table, graph, or image format, means for automatically generating a layout of the materials based on the converted information, means for generating text based on the automatically generated layout, means for presenting the generated materials to the user and receiving feedback, and means for analyzing the user's emotions and dynamically adjusting the content and tone of the materials, thereby enabling dynamic customization of materials based on the user's emotions and the creation of high-quality materials.

[1052] "User" refers to any person or company that uses the System to create Materials.

[1053] "Materials" refers to documents that organize and visually present information, such as presentations and reports.

[1054] "Purpose" refers to the final goal or aim of the user when creating a document.

[1055] "Target information" refers to the collection of specific data and information required to create materials.

[1056] "Analysis" refers to the process of analyzing input information in detail and deriving its meaning and relevance.

[1057] "Structure" refers to how information is organized within a document.

[1058] "Type of information" refers to the format and nature of the data required to make up the material (e.g., text, tables, graphs, images).

[1059] An "internal database" refers to a collection of data managed within a company or organization.

[1060] "External sources" refers to information sources obtained from outside the company or organization (e.g., market research data, public statistics).

[1061] "Collection" refers to the process of gathering the necessary data and information.

[1062] "Organization" refers to the process of organizing collected information in a purposeful manner.

[1063] "Transformation" refers to the process of transforming organized information into a different format (e.g., turning text information into a graph).

[1064] "Layout" refers to the arrangement of information within a document and the design structure.

[1065] "Automatic generation" refers to the system automatically performing a specific process without human intervention.

[1066] "Text generation" refers to the process by which a system automatically creates text.

[1067] "Feedback" refers to reactions and opinions from users.

[1068] "Revising" refers to the process of changing the content or format of material for the purpose of improvement.

[1069] "Analyzing emotions" refers to the process of reading and understanding a user's emotions from their facial expressions and voice.

[1070] "Tone" refers to the overall atmosphere or style of a piece of writing or presentation.

[1071] "Dynamic adjustment" refers to changing the content and format of materials in real time according to the situation and conditions.

[1072] This invention is a system that improves the efficiency and quality of document creation related to autonomous vehicles. It clarifies the roles of the server, terminal, and user, and provides specific operating procedures.

[1073] Program Generation

[1074] 1. The user enters the purpose and target information for creating the document via a device (e.g., a smartphone).

[1075] 2. The server receives the entered purpose and target information, analyzes it, and defines the components of the required materials and the type of information.

[1076] 3. The server collects the defined information from internal databases and external sources. Examples of internal databases include company product specifications and historical sales data, while examples of external sources include market trends and competitive information.

[1077] 4. The server organizes the collected information and converts it into appropriate text, table, graph, and image formats, using data analysis libraries such as Pandas and Matplotlib.

[1078] 5. The server automatically generates the layout of the materials based on the organized information. For example, it may use a blue color scheme and place the company logo in the bottom right corner of each slide.

[1079] 6. The server then uses natural language processing technology to generate sentences, such as "Our new product achieves a 20% performance improvement over the previous model," using a generative AI model (e.g., GPT-2).

[1080] 7. The server presents the generated materials to the user and receives feedback. The user uses a smartphone application to check the contents of the materials and enter feedback as needed. The user's facial expressions and voice are also captured through the device's camera and microphone and analyzed by the emotion engine.

[1081] 8. The server dynamically adjusts the content and tone of the materials based on this feedback and emotional data. For example, if the user shows a dissatisfied expression, the server will modify the design and text of that section to make it more specific and appealing.

[1082] 9. The server automatically makes the specified corrections and regenerates the document. The user then checks the corrected document again and finally approves it.

[1083] Hardware and Software

[1084] Hardware:

[1085] Devices such as smartphones and tablets

[1086] Cloud Server

[1087] Camera and microphone (for emotion analysis)

[1088] software:

[1089] Data collection and analysis: Pandas, Matplotlib

[1090] Natural Language Processing: GPT-2 (Hugging Face transformers library)

[1091] Sentiment analysis: BERT model (nlptown / bert-base-multilingual-uncased-sentiment)

[1092] Examples and prompts

[1093] For example, if a user types "I want to introduce a new navigation feature to my target market," the system will do the following:

[1094] The server collects details of new navigation features from an internal database, along with market trend information.

[1095] The automatically generated materials include sentences such as, "The new navigation function provides highly accurate location information services."

[1096] When a user inputs feedback that "information is insufficient," the server performs sentiment analysis and adds information about competitors' features.

[1097] Example prompt sentence:

[1098] "Get additional competitive comparison information for your customers and generate even more detailed graphs."

[1099] In this way, the system utilizes generative AI models and prompt sentences to create efficient, high-quality documents.

[1100] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1101] Step 1:

[1102] The user uses the terminal to input the purpose and target information of the material.

[1103] Input: Purpose of the material (e.g., introducing a new navigation feature) and subject information (target market, competitive information).

[1104] Output: The input data is sent to the cloud server.

[1105] Step 2:

[1106] The server analyzes the entered purpose and target information.

[1107] Input: Purpose and target information entered by the user.

[1108] Output: The components of the material and the type of information are defined.

[1109] Specific operation: The server performs natural language processing based on the input information and creates a list of the information required for the document.

[1110] Step 3:

[1111] The server collects the required information from an internal database and external sources.

[1112] Input: Material components and types of information.

[1113] Output: Information organized in a predetermined format.

[1114] What it does: The server uses SQL queries to extract data from its internal database and retrieves data from external sources through APIs.

[1115] Step 4:

[1116] The server converts the collected information into appropriate text, table, graph, and image formats.

[1117] Input: Organized information.

[1118] Output: Data converted into text, table, graph and image formats.

[1119] Specific operation: Process data with the Pandas library and generate graphs with Matplotlib.

[1120] Step 5:

[1121] The server automatically generates the layout of the materials based on the converted information.

[1122] Input: The transformed data.

[1123] Output: Auto-generated document layout.

[1124] What it does: Uses a template engine to assemble a layout into the specified format.

[1125] Step 6:

[1126] The server generates text based on the automatically generated layout.

[1127] Input: Document layout.

[1128] Output: The generated description.

[1129] Specific operation: Generate sentences using generative AI models such as GPT-2.

[1130] Step 7:

[1131] The server presents the generated materials to the user and receives feedback.

[1132] Input: Generated materials.

[1133] Output: User feedback and sentiment data.

[1134] Specific operation: Materials are displayed on the device screen, and the user's reactions are captured using the camera and microphone.

[1135] Step 8:

[1136] The server dynamically adjusts the content and tone of the material based on user feedback and emotional data.

[1137] Input: User feedback, emotion data.

[1138] Output: The corrected document.

[1139] What it does: Uses a sentiment analysis model (BERT) to modify text and layout based on sentiment scores.

[1140] Step 9:

[1141] The server regenerates the modified material and presents it to the user for final confirmation.

[1142] Input: Corrected material.

[1143] Output: Final approved materials.

[1144] Specific operation: After receiving final confirmation from the user, the materials are output in PDF or PowerPoint format.

[1145] Through the above process, the system can efficiently create high-quality materials that reflect the user's emotions.

[1146] 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.

[1147] 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.

[1148] 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.

[1149] [Fourth embodiment]

[1150] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1151] 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.

[1152] 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).

[1153] 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.

[1154] 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.

[1155] 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).

[1156] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1157] 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.

[1158] 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.

[1159] 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.

[1160] 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.

[1161] 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.

[1162] 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."

[1163] The present invention is a system for improving the efficiency of document creation work, and includes various means for receiving document purpose and subject information from a user and automatically generating documents. This system can significantly reduce the time and effort required by users to create documents, and can also improve the quality and consistency of documents.

[1164] Input and analysis of needs

[1165] The user uses a terminal to input the purpose and target information of the document (e.g., sales presentation of a new product, target market, competitive information). The server receives this input information and begins analysis. Based on the results of the analysis, the server defines the necessary components of the document (e.g., product information, market analysis, competitive comparison, sales plan, budget graph).

[1166] Data collection and organization

[1167] The server collects the necessary information from internal databases and external sources. It obtains the company's product specifications and past sales data from internal databases, and market trends and competitive information from external sources. The server organizes the collected information and converts it into appropriate formats such as text, tables, graphs, and images. For example, new product specifications are organized in text and table format, and market trends are graphed.

[1168] Automatic layout generation of documents

[1169] The server determines the layout of each section of the document based on the organized information. Specifically, it automatically generates the order and color scheme templates for title slides, product information slides, market analysis slides, etc. The server then applies fonts, color schemes, page numbers, etc. based on the company's brand guidelines. For example, the company logo is placed in the bottom right corner of each slide based on a blue color scheme.

[1170] Automatic sentence generation

[1171] The server uses natural language processing technology to generate text based on the collected data. For example, for a product information slide, it generates a sentence such as "The new product offers a 20% performance improvement over the previous model" and adds it to the slide. It also adjusts the tone and style depending on the purpose of the document. For presentation materials, it uses a formal, business-oriented tone.

[1172] Accepting feedback and making corrections

[1173] The server can present the generated materials to the user and receive feedback. The user can check the materials through their terminal and input any necessary corrections (e.g., adjusting the size of graphs, correcting text). For example, they can input feedback such as "The graph for competitive comparison is small, so I would like it to be larger." The server will automatically make corrections based on the feedback and generate a new, revised material.

[1174] Final confirmation and document output

[1175] The user checks the revised document again and gives final approval. Check the final version of the document displayed on the terminal and, if satisfied, press the approval button. The server outputs the final version of the document in the user's desired format, such as PDF or PowerPoint. The output document is displayed on the terminal as a download link, which the user can use to distribute or present the document.

[1176] The present invention enables users to create documents efficiently and with high quality, significantly reducing the time and effort required for document creation, and also improves the consistency and quality of documents, thereby helping to improve business productivity.

[1177] The processing flow will be explained below.

[1178] Step 1:

[1179] The user uses the terminal to input the purpose and target information of the document. For example, the purpose is "sales presentation for a new product," and then adds details such as the target market and competitive information.

[1180] Step 2:

[1181] The server analyzes the entered purpose and target information and defines the necessary document components (e.g., product information, market analysis, competitor comparison, sales plan, budget graph). Based on this information, the server determines the type and amount of data required.

[1182] Step 3:

[1183] The server queries an internal database to gather relevant product information and past sales data, such as "product specifications" and "sales history."

[1184] Step 4:

[1185] The server gathers the necessary market trends and competitive information from external sources, for example, using a market research report API to get the latest market data.

[1186] Step 5:

[1187] The server organizes the collected data and converts it into text, tables, graphs, and images. Product specifications are converted into text and tables, and market trends are converted into graphs. For example, the specifications of a new product are compiled into a table, and market trends are converted into a line graph.

[1188] Step 6:

[1189] The server automatically generates a layout for the presentation materials based on this organized information. The layout includes a title slide, product information slide, market analysis slide, etc. For example, the first slide could contain the company logo and title, and the next slide could contain product information.

[1190] Step 7:

[1191] The server uses natural language processing technology to generate sentences based on the collected and organized information, such as "The new product offers 20% better performance than the previous model."

[1192] Step 8:

[1193] The server displays the generated document on the terminal and asks the user to confirm it. The user checks the contents of the document and enters feedback as necessary. For example, the user may enter feedback such as "I would like the size of the competitive comparison graph to be larger."

[1194] Step 9:

[1195] The server receives feedback from the user and automatically makes the specified modifications, for example, adjusting the size of the competitive comparison graph and regenerating the materials.

[1196] Step 10:

[1197] The user then reviews the revised documents and finally approves them. The approved documents are output by the server in PDF or PowerPoint format. The user can then download these documents from their device and use them for presentations or distribution.

[1198] By following the steps above, users can efficiently create high-quality materials in a short amount of time.

[1199] Example 1

[1200] 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."

[1201] In conventional document creation work, users spend a large amount of time and effort, and maintaining the quality and consistency of the documents is a challenge. In addition, many steps, such as collecting and organizing information for documents, setting layouts, and generating text, are done manually, so there is a need for efficiency improvements.

[1202] 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.

[1203] In this invention, the server includes means for receiving purpose and target information of the document from the user, means for analyzing the purpose and target information and defining the necessary components and types of information of the document, means for collecting the defined information from an internal database and external sources, means for organizing the collected information and converting it into appropriate text, table, graph, or image formats, means for automatically generating a layout of the document based on the converted information, means for generating text based on the automatically generated layout, means for presenting the generated document to the user and receiving feedback, means for automatically making corrections based on the feedback, and means for outputting the final version of the document in a format desired by the user. This significantly reduces the time and effort required for document creation and enables the efficient creation of high-quality, consistent documents.

[1204] A "user" is a person or organization that uses the system to create materials.

[1205] "Purpose" refers to the specific goal or intention of the user when creating the material.

[1206] "Target information" refers to data and information necessary for creating materials, such as product information, market analysis, and competitive information.

[1207] "Analysis" is the process of identifying the necessary components and types of information based on the input purpose and target information.

[1208] "Components" are the basic elements that make up the document, and specifically include product information, market analysis, competitive comparisons, sales plans, budget graphs, etc.

[1209] "Information" refers to the data and knowledge necessary to produce the materials. It is collected from internal databases and external sources.

[1210] An "internal database" is a collection of data managed within a company. For example, it may include product specifications and past sales data.

[1211] "External sources" are information sources obtained from outside the company, such as market trends and competitive information.

[1212] "Collection" is the process of obtaining required information from internal databases and external sources.

[1213] Organizing is the process of putting collected information into an appropriate format, such as text, tables, graphs, or images.

[1214] "Layout" refers to the arrangement and design of each section of the document, specifically including the order and color scheme of the title slide, product information slide, market analysis slide, etc.

[1215] "Natural language processing technology" is a technology that enables computers to understand and generate human language.

[1216] "Feedback" refers to evaluations and correction requests made by users regarding generated materials.

[1217] "Automatic correction" is the process by which the server automatically corrects the material based on user feedback.

[1218] "Final Version" means the completed version of the Material that has been finalized by the User.

[1219] "Format" refers to the format in which the materials are output. Examples include PDF and PowerPoint.

[1220] The present invention is a system that receives information on the purpose and target of a document from a user, automatically generates the document, and makes corrections based on the feedback. This system significantly reduces the time and effort required to create the document, enabling the efficient creation of high-quality, consistent documents.

[1221] First, the user uses a terminal to input the purpose and target information of the materials. For example, if you want to create a sales presentation for a new product, you would enter "new product information," "target market," "competitive information," etc. into the input form. The terminal then sends this information to the server.

[1222] The server then analyzes the received purpose and target information and defines the components and types of information required for the materials. This analysis is performed using a pre-trained generative AI model. For example, the components of a new product presentation material might include "product information," "market analysis," "competitive comparison," "sales plan," and "budget graph."

[1223] The server then collects the necessary information from internal databases and external sources. From the internal database, it obtains the company's product specifications and past sales data, and from external sources, it obtains market trends and competitive information. For example, the server uses web crawling technology to obtain the latest market trends.

[1224] The collected information is organized and converted into the appropriate format. For example, new product specifications are converted into text and tables, and market trends are graphed. Based on this organized information, the server automatically generates the layout for each section of the document. Specifically, it generates the order and color scheme templates for title slides, product information slides, market analysis slides, etc. Fonts, color schemes, page numbers, etc. are applied based on the company's brand guidelines.

[1225] The server then uses natural language processing technology to generate text based on the collected data. For example, a product information slide might say, "The new product offers 20% better performance than the previous model." The server also automatically adjusts tone and style depending on the purpose of the presentation. For business presentations, a formal tone is used.

[1226] The generated document is presented to the user, who can then input feedback via their terminal. For example, a request for corrections such as "The competitive comparison graph is too small, please make it larger" can be input. The server automatically makes corrections based on this feedback and regenerates the revised document.

[1227] Finally, the user checks the revised document on their device and, if satisfied, presses the approval button. The server outputs the final document in the user's desired format, such as PDF or PowerPoint. The output document is displayed on the device as a download link, which the user can use to distribute or present the document.

[1228] As a concrete example, consider the case where the following prompt is entered into a terminal:

[1229] Prompt statement:

[1230] I'd like to create a sales presentation for a new product. It should include information on the target market and competitors, as well as product specifications, market analysis, competitor comparisons, sales plans, and budget graphs. The presentation should use a blue color scheme, with the company logo placed in the bottom right corner of each slide.

[1231] Based on these prompts, the server collects and organizes the necessary information and automatically generates the layout and text. Once the user enters feedback and provides final approval, the completed document is output in PDF format. This series of processes enables users to quickly create efficient, high-quality documents, improving work productivity.

[1232] It can be seen that specific embodiments of the present invention streamline document creation and provide high quality, consistent documents.

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

[1234] Step 1:

[1235] The user uses the terminal to input the purpose and target information of the document. The input includes "new product information," "target market," and "competitive information" to create a sales presentation for a new product. The terminal sends this information to the server. The input data takes the form of text fields and drop-down menus, and is received by the server after it is sent.

[1236] Step 2:

[1237] The server analyzes the received purpose and target information using a generative AI model. Specifically, the server breaks down the purpose and target information and defines the components required for the document (product information, market analysis, competitive comparison, sales plan, budget graph, etc.). The output of this analysis is a requirements list for further specific information gathering and formatting.

[1238] Step 3:

[1239] The server collects the necessary information from internal databases and external sources. From the internal database, it obtains the company's product specifications and past sales data, and from external sources, it collects market trends and competitive information. For example, the server uses an API to obtain market trends from an external data provider. The collected data is organized into formats such as text, tables, graphs, and images.

[1240] Step 4:

[1241] The server organizes the collected information and converts it into various data formats. For example, new product specifications are converted into text and tables, and market trends are converted into graphs. Data formatting algorithms are used in this step. The output is a list of various types of data.

[1242] Step 5:

[1243] The server automatically generates the layout of the materials based on the organized information. Specifically, it generates the order and color scheme templates for each section (title slide, product information slide, market analysis slide, etc.). It also applies fonts, color schemes, page numbers, and other settings in accordance with the company's brand guidelines. For example, the server references a brand guideline database to determine the color scheme and applies it to each slide.

[1244] Step 6:

[1245] The server uses natural language processing technology to generate text based on the collected data. Using a generative AI model, it creates sentences such as "The new product offers 20% better performance than the previous model" for product information slides. The tone and style are automatically adjusted depending on the purpose of the document. The generated text is then placed in the appropriate place on each slide.

[1246] Step 7:

[1247] The server presents the generated document to the user. A preview of the document is displayed on the terminal, and the user checks it. The user can input feedback as needed. For example, the user may input a correction request such as "The competitive comparison graph is small, so I would like it to be larger." This feedback is sent to the server in real time.

[1248] Step 8:

[1249] The server automatically makes corrections based on user feedback. For example, it may enlarge the size of a competitive comparison graph. The corrected document is then regenerated and presented to the user. This feedback and correction process is repeated until the user is satisfied.

[1250] Step 9:

[1251] The user then checks the revised document again and gives final approval. When satisfied, they click the approval button displayed on their device. The server then outputs the final version of the document in PDF or PowerPoint format. The final version of the document is displayed on the device as a download link, which the user can use to distribute or present the document.

[1252] (Application example 1)

[1253] 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."

[1254] Conventional document creation systems require users to manually collect and organize a large amount of data, and then generate the content, which is extremely time-consuming and labor-intensive. It is also difficult to generate content optimized for smart devices, which can lead to a poor user experience. This can result in insufficient improvement in the consistency and quality of documents.

[1255] 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.

[1256] In this invention, the server includes means for receiving purpose and target information of materials from a user, means for analyzing the purpose and target information and defining the required structure of materials and the type of information, means for collecting the defined information from an internal database and external sources, means for organizing the collected information and converting it into an appropriate text, table, graph, or image format, means for automatically generating a layout of materials based on the converted information, means for generating text based on the automatically generated layout, means for automatically generating content for smart devices based on the generated text, means for displaying the generated content for smart devices, means for presenting the generated materials to a user and receiving feedback, and means for automatically making corrections based on the feedback, thereby enabling users to efficiently generate high-quality materials and content for smart devices.

[1257] The "means for receiving the purpose and target information of the material from the user" is an interface through which the user inputs the purpose and target information of the material to be provided.

[1258] "Means for analyzing the purpose and target information and defining the necessary material composition and type of information" refers to a system that determines the material composition and type of information to be collected based on the purpose and target information received from the user.

[1259] The "means for collecting the above-defined information from internal databases and external sources" refers to a function for collecting data from internal databases and external information sources based on the components of the material.

[1260] "Means for organizing the collected information and converting it into an appropriate text, table, graph, or image format" refers to the process of organizing the collected information and converting it into a format appropriate for the intended use.

[1261] The "means for automatically generating a layout of materials based on the converted information" is a system that automatically generates the appearance and arrangement of materials based on the converted information.

[1262] The "means for generating a sentence based on the automatically generated layout" is a function for generating a sentence using natural language processing technology based on the generated layout.

[1263] "Means for automatically generating content for smart devices based on the generated text" refers to a function that automatically generates content that is optimally displayed on devices such as smartphones and tablets based on the generated text.

[1264] The "means for displaying the generated content for smart devices" refers to a function for actually displaying the generated content for smart devices on the user's device.

[1265] The "means for presenting the generated materials to the user and receiving feedback" is an interface that shows the generated materials to the user and allows the user to input their opinions and corrections.

[1266] The "means for automatically correcting the material based on the feedback" is a function for receiving feedback from the user and automatically correcting the material based on the feedback.

[1267] This invention is a system for improving the efficiency of document creation work, and specifically includes various means for receiving purpose and target information of the document from a user and automatically generating, editing, and optimizing the document based on that information. Detailed embodiments of the invention are described below.

[1268] First, the user uses a smart device (e.g., smartphone, tablet, etc.) to input the purpose and target information of the document. The user interface is simple and designed to allow users to input information intuitively. Examples of input content include "presentation materials for new products," "target markets," and "competitive information."

[1269] The server analyzes the received information. This analysis involves defining the type of information needed (product information, market analysis, competitive comparison, etc.) based on the purpose and target information entered by the user. This analysis process uses natural language processing technology to accurately understand the user's request and identify the appropriate material components.

[1270] The server then collects the defined information from an internal database, such as the company's product specifications and past sales data, and from external sources, such as market trends and competitive information. The information collection process uses Python's requests and BeautifulSoup libraries.

[1271] The collected information is organized on the server and converted into appropriate formats such as text, tables, graphs, images, etc. Python's matplotlib and pandas libraries are used for text conversion and graph generation.

[1272] The server then automatically generates a layout for the document based on the converted information. This layout generation process includes font, color, and page number settings in accordance with the company's brand guidelines. It also includes a process to optimize the display on smart devices. The layout is constructed using an HTML template.

[1273] The server then generates text based on the automatically generated layout. The generated text is based on the collected data and has specific content. Using natural language processing technology, a sentence such as "The new product achieves a 20% performance improvement over the previous model" is generated.

[1274] After generating the text, the server automatically generates content for smart devices and displays it on the user's device. The user can review the generated content and enter any necessary feedback. An example of feedback might be, "The graph showing the competitive comparison is too small, so I'd like it to be larger."

[1275] The server automatically makes corrections based on the received feedback and regenerates the document, and the final version is output to the user in formats such as PDF or PowerPoint.

[1276] For example, if a user types "Generate a blog post about the AI ​​camera features of new smartphones," the server will gather market research data and generate an article about the features, market analysis, and future outlook of AI cameras. Here is an example prompt:

[1277] Generate a blog post about the latest trends in AI camera technology, including features, market analysis, and future prospects.

[1278] In this way, users can efficiently create high-quality materials and generate content for smart devices.

[1279] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1280] Step 1:

[1281] The user uses the terminal to input the purpose and target information of the document. The terminal provides a user interface, allowing the user to input the purpose of the document (e.g., "presentation materials for a new product") and target information (e.g., "target market" and "competitive information"). The input data is sent to the server.

[1282] Step 2:

[1283] The server analyzes the received purpose and target information and defines the components of the required materials and the type of information. The analysis process uses natural language processing technology to understand the information entered by the user and determine the appropriate material elements (e.g., "product information," "market analysis," "competitive comparison"), and the analysis results are output as a list.

[1284] Step 3:

[1285] The server collects defined information from an internal database and external sources. The internal database stores the company's product specifications and past sales data, and uses the requests and BeautifulSoup libraries to collect data from external sources (e.g., market trend sites and competitive information sites). The collected information is saved in text format.

[1286] Step 4:

[1287] The server organizes the collected information and converts it into the appropriate format (text, table, graph, image). For example, product information is organized into text and table format, and market trends are graphed. This process uses the pandas and matplotlib libraries. The converted data is then stored in temporary storage.

[1288] Step 5:

[1289] The server automatically generates a layout for the document based on the converted information. The layout is generated using an HTML template, and fonts, colors, and page numbers are set based on the company's brand guidelines. The generated layout is saved in HTML format.

[1290] Step 6:

[1291] The server uses natural language processing technology to generate text based on the automatically generated layout. For example, the generated text might include specific content such as "The new product achieves a 20% performance improvement over the previous model." The generated text is inserted into the HTML layout and saved in temporary storage as the final content.

[1292] Step 7:

[1293] The server automatically generates content for smart devices based on the generated text. For example, it applies responsive design that is optimally displayed on smartphones and tablets. The generated content for smart devices is then sent to the user's device.

[1294] Step 8:

[1295] The user checks the content generated for smart devices on their device and inputs any necessary feedback. An example of feedback might be, "The graph showing the competitive comparison is too small, so I'd like it to be larger." The feedback is then sent to the server.

[1296] Step 9:

[1297] The server automatically modifies the document based on the received feedback, adjusting the size of text and graphs, etc. The modified document is then saved again in HTML format.

[1298] Step 10:

[1299] The user checks the final version of the document again and presses the approval button. The server outputs the final version of the document in the user's desired format (e.g., PDF, PowerPoint) and generates a download link. The user can obtain the final version of the document via the link.

[1300] 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.

[1301] This invention is a system aimed at improving the efficiency and quality of document creation work, and combines an emotion engine that recognizes the user's emotions and dynamically adjusts the content and tone of the document. This system significantly reduces the time and effort required for users to create documents, and also enables customization according to individual needs and emotions.

[1302] Input and analysis of needs

[1303] The user uses a terminal to input the purpose and target information of the document (e.g., sales presentation of a new product, target market, competitive information). The server receives this input information and begins analysis. Based on the results of the analysis, the server defines the necessary components of the document (e.g., product information, market analysis, competitive comparison, sales plan, budget graph).

[1304] Data collection and organization

[1305] The server collects the necessary information from internal databases and external sources. It obtains the company's product specifications and past sales data from internal databases, and market trends and competitive information from external sources. The server organizes the collected information and converts it into appropriate formats such as text, tables, graphs, and images. For example, new product specifications are organized in text and table format, and market trends are graphed.

[1306] Automatic layout generation of documents

[1307] Based on the organized information, the server determines the layout of each section of the document, including the title slide, product information slide, and market analysis slide. The server then applies fonts, color schemes, page numbers, and other elements based on the company's brand guidelines. For example, the server uses a blue color scheme and places the company logo in the bottom right corner of each slide.

[1308] Automatic sentence generation

[1309] The server uses natural language processing technology to generate text based on the collected and organized information. For example, it creates a product information slide with a description such as, "The new product offers 20% better performance than the previous model." It also adjusts the tone and style depending on the purpose of the document. For presentation materials, it uses a formal, business-oriented tone.

[1310] Emotion engine accepts and corrects feedback

[1311] The server displays the generated materials on the terminal and asks the user to confirm them. The user then checks the contents of the materials and enters feedback as necessary. The emotion engine also analyzes the user's facial expressions and voice to recognize their emotions (such as surprise, joy, or dissatisfaction). The server then adjusts the content and tone of the materials according to the user's emotions identified by the emotion engine. For example, if the user shows a dissatisfied expression, the server modifies the design and text of that section to make it more specific and appealing.

[1312] Corrections based on feedback and final confirmation

[1313] The server automatically makes the specified modifications based on feedback from the user and the emotion engine. For example, based on feedback such as "Please make the size of the competitive comparison graph larger" and the emotion engine's analysis of the user's dissatisfaction, the server adjusts the size of the competitive comparison graph and regenerates the document. The user then checks the modified document again and finally approves it. The server outputs the approved document in PDF or PowerPoint format. The user can then download the document from their device and use it for presentations or distribution.

[1314] This invention allows users to create efficient, high-quality documents in a short time. It also enables customization according to the user's feelings, which is expected to improve the consistency and quality of documents and increase business productivity.

[1315] The processing flow will be explained below.

[1316] Step 1:

[1317] The user uses the terminal to input the purpose and target information of the document. Specifically, the user inputs the purpose as "sales presentation for a new product" and adds details such as the target market and competitive information.

[1318] Step 2:

[1319] The server analyzes the entered purpose and target information and defines the necessary document components (e.g., product information, market analysis, competitor comparison, sales plan, budget graph). Based on this information, the server determines the type and amount of data required.

[1320] Step 3:

[1321] The server queries the internal database to collect relevant product information and past sales data, and retrieves data such as "product specifications" and "sales history" from the internal database.

[1322] Step 4:

[1323] The server collects the necessary market trends and competitive information from external sources, and uses the market research report API to obtain the latest market data.

[1324] Step 5:

[1325] The server organizes the collected data and converts it into text, tables, graphs, and images. For example, it converts new product specifications into a table and market trends into a line graph.

[1326] Step 6:

[1327] The server automatically generates a layout for the presentation based on the organized information. The layout includes a title slide, product information slide, market analysis slide, etc. The server applies fonts, color schemes, page numbers, etc. based on the company's brand guidelines. For example, a blue color scheme is used and the company logo is placed in the bottom right corner of each slide.

[1328] Step 7:

[1329] The server uses natural language processing technology to generate text based on the collected and organized information, creating product information slides with descriptions such as "This new product offers 20% better performance than the previous model."

[1330] Step 8:

[1331] The server displays the generated document on the terminal and asks the user to confirm it. The user checks the contents of the document and enters feedback as necessary. For example, the user may enter a request such as "I would like the size of the competitive comparison graph to be larger."

[1332] Step 9:

[1333] When the user is confirmed, the server activates the emotion engine and analyzes the user's facial expressions and voice. The emotion engine identifies the user's emotion and sends the emotion data to the server. For example, if the user shows a dissatisfied expression, the server will receive the analysis result of the dissatisfaction.

[1334] Step 10:

[1335] Based on the analysis results of the emotion engine and user feedback, the server modifies specific parts of the document, for example, increasing the size of the competitive comparison graph and changing the color scheme to make it more appealing.

[1336] Step 11:

[1337] The user checks the revised document again on the terminal, and if the user is satisfied again, the server confirms the final version of the document at that point.

[1338] Step 12:

[1339] The server outputs the final, verified documents in PDF or PowerPoint format, and users can download these documents from their devices. Users can use these documents for presentations or distribution.

[1340] By following the steps above, the user can create efficient, high-quality materials in a short time, and furthermore, can customize the contents of the materials according to the user's feelings.

[1341] Example 2

[1342] 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."

[1343] Conventional document creation systems require users to manually collect and organize data, design layouts, and write documents, which is time-consuming, labor-intensive, and inefficient. Furthermore, if the content or tone of the document does not match the user's intentions or emotions, frequent revisions and additional work are required. This makes it difficult to maintain the quality and consistency of the document.

[1344] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1345] In this invention, the server includes: means for receiving purpose and target information for a document from a user; means for analyzing the purpose and target information and defining the necessary document components; means for collecting the defined information from an internal database and external sources; means for organizing the collected information and converting it into appropriate text, table, graph, or image formats; means for automatically generating a document layout based on the converted information; means for generating text based on the automatically generated layout; means for presenting the generated document to the user and receiving feedback; means for analyzing and recognizing the user's emotions regarding the document upon receiving feedback; means for dynamically adjusting the content and tone of the document based on the recognized emotional information; means for automatically making corrections based on the feedback and emotional information; and means for outputting the final document in PDF or presentation software format. This significantly reduces the time and effort required for document creation and enables dynamic adjustment of the content and tone of the document based on the user's emotions and feedback. As a result, efficient, high-quality documents can be created in a short time, enabling the provision of consistently high-quality documents.

[1346] "User" refers to a person who uses the system to create materials.

[1347] "Terminal" refers to a device through which a user inputs purpose and subject information for materials and provides feedback.

[1348] "Server" refers to a computer system that analyzes information input by users, collects and organizes data, generates layouts, and creates and edits text.

[1349] "Purpose and target information" refers to the information and target required for creating the document.

[1350] "Component" refers to the basic information unit that makes up a document.

[1351] An "internal database" refers to a collection of data that exists within a company.

[1352] "External sources" refers to information obtained from the Internet or other external resources.

[1353] "Text, tabular, graphical and image formats" refers to various formats for visually displaying information.

[1354] "Automatic layout generation" refers to the process of automatically determining the layout of slides and pages based on the elements that make up the document.

[1355] "Text generation" refers to the process of automatically creating the text contained in a document.

[1356] "Feedback" means suggestions for correction or improvement provided by a User after reviewing the Materials.

[1357] "Emotion engine" refers to a computer program that analyzes and recognizes a user's emotions.

[1358] "Dynamic adjustment" refers to changing the content and tone of material in real time based on feedback and emotional information.

[1359] "PDF or presentation software format" refers to the file format of the final output material.

[1360] This invention is a system aimed at improving the efficiency and quality of document creation work, and includes an emotion engine that recognizes the user's emotions and dynamically adjusts the content and tone of the document. This system significantly reduces the time and effort required for users to create documents, and also enables customization according to individual needs and emotions.

[1361] Input and analysis of needs

[1362] The user uses a terminal to input the purpose and target information of the document (e.g., sales presentation of a new product, target market, competitive information). The server receives this input information and performs semantic analysis using an NLP library (e.g., spaCy). This determines the necessary components of the document (e.g., product information, market analysis, competitive comparison, sales plan, budget graph).

[1363] Data collection and organization

[1364] The server collects the necessary information from an internal database (e.g., MySQL) and external sources (e.g., RESTful API, web scraping). From the internal database, it obtains the company's product specifications and past sales data, and from external sources, it obtains market trends and competitive information. Next, the server organizes the collected information and converts it into an appropriate format (e.g., text, table, graph, image). At this stage, the data is processed using libraries such as Pandas and Matplotlib. For example, the specifications of a new product are organized into text and tables, and market trends are visualized as a line graph.

[1365] Automatic layout generation of documents

[1366] The server uses PowerPoint libraries (e.g., python-pptx) to automatically generate the layout of the materials based on the organized information. This includes the placement of slide titles, content, graphs, images, etc. The server customizes fonts, color schemes, page numbers, etc. based on the company's brand guidelines. For example, it uses a blue color scheme, places the company logo in the bottom right corner of each slide, and adds page numbers.

[1367] Automatic sentence generation

[1368] The server uses natural language processing technology (e.g., GPT-3) to generate text based on the collected and organized information. For product information slides, it automatically generates explanatory text such as, "The new product achieves a 20% performance improvement over the previous model." It also adjusts the tone and style according to the purpose of the document. For presentation materials, a formal, business-oriented tone is used.

[1369] Emotion engine accepts and corrects feedback

[1370] The server displays the generated materials on the terminal and asks the user to confirm them. The user can then review the contents of the materials and enter feedback. The emotion engine also analyzes the user's facial expressions and voice to recognize their emotions (such as surprise, joy, or dissatisfaction). The server then adjusts the content and tone of the materials according to the user's emotions identified by the emotion engine. For example, if the user shows a dissatisfied expression, the server will modify the design and text of that section to make it more specific and appealing.

[1371] Corrections based on feedback and final confirmation

[1372] The server automatically makes the specified modifications based on feedback from the user and the emotion engine. For example, based on feedback such as "Please make the size of the competitive comparison graph larger" and the emotion engine's analysis of the user's dissatisfaction, the server adjusts the size of the competitive comparison graph and regenerates the document. The user then reviews the modified document again and gives their final approval. The server outputs the approved document in PDF or presentation software format. The user can then download the document from their device and use it for presentations or distribution.

[1373] Specific examples

[1374] For example, a user might input the following prompt into a generative AI model:

[1375] Example prompt:

[1376] "I would like to create a sales presentation for a new product. The target market is working women in their 30s, and my competitors are Company A and Company B. The presentation content should include product specifications, market trends, a comparison with other competitors, and a sales plan."

[1377] Based on these prompts, the server performs analysis, collects the necessary data, automatically generates the layout of the document, and creates the text. Through feedback using an emotion engine, the content and tone of the document can be dynamically adjusted to match the user's emotions, ultimately enabling the creation of high-quality documents in a short amount of time.

[1378] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1379] Step 1:

[1380] Input and analysis of needs

[1381] The user uses the terminal to input the purpose and target information of the material (for example, a sales presentation for a new product, a target market, competitive information).

[1382] (Input) The prompt entered by the user (in text format).

[1383] (Output) The results of analyzing the purpose and subject information of the material (list of components).

[1384] The server analyzes the received prompt using an NLP library (e.g., spaCy) to extract keywords and intent. Specifically, it extracts important information from the prompt (e.g., "new product," "sales presentation," "target market," etc.) and defines the components.

[1385] Step 2:

[1386] Data collection and organization

[1387] Based on the defined information, the server performs the task of collecting the necessary data from an internal database (e.g. MySQL) and external sources (e.g. RESTful API, web scraping).

[1388] (Input) A list of components.

[1389] (Output) Collected information (text data, table data, graph data, image data).

[1390] Specifically, it obtains product specifications and past sales data from internal databases, and market trends and competitive information from external sources.

[1391] The server then organizes the collected data using libraries such as Pandas and converts it into text, tables, graphs, and images. For example, it organizes new product specifications into text and tables, and converts market trends into line graphs.

[1392] Step 3:

[1393] Automatic layout generation of documents

[1394] The server automatically generates the layout of the materials using a PowerPoint library (e.g., python-pptx) based on the organized information.

[1395] (Input) Organized information (text, tables, graphs, images).

[1396] (Output) Automatically generated layout document.

[1397] Specifically, you can arrange the slide titles, content, graphs, images, etc., and set fonts, color schemes, and page numbers based on your company's brand guidelines. For example, you can place the company logo in a blue color scheme in the bottom right corner of each slide and add page numbers.

[1398] Step 4:

[1399] Automatic sentence generation

[1400] The server uses natural language processing technology (e.g., GPT-3) to generate sentences based on the collected and organized information.

[1401] (Input) Automatically generated layout materials and organized information.

[1402] (Output) The generated document with text.

[1403] Specifically, for product information slides, the system automatically generates explanatory text such as, "The new product achieves a 20% performance improvement over the previous model." Furthermore, the system adjusts the tone and style depending on the purpose of the document. For example, for presentation materials, a formal business tone is used.

[1404] Step 5:

[1405] Emotion engine accepts and corrects feedback

[1406] The server displays the generated materials on the terminal and asks the user to confirm them.

[1407] The user checks the content of the materials and inputs feedback. The emotion engine also analyzes the user's facial expressions and voice to recognize their emotions (surprise, joy, dissatisfaction, etc.).

[1408] (Input) User feedback and emotional data (facial expression recognition, voice analysis).

[1409] (Output) Corrections based on emotional information and feedback.

[1410] The server dynamically adjusts the content and tone of the materials based on the user's emotions and feedback recognized by the emotion engine. For example, if the user shows a dissatisfied expression, the server will modify the design and text of that section to make it more specific and appealing.

[1411] Step 6:

[1412] Corrections based on feedback and final confirmation

[1413] The server automatically modifies the materials based on feedback from the user and the emotion engine.

[1414] (Input) Corrections based on emotional information and feedback.

[1415] (Output) The revised final document.

[1416] For example, based on feedback such as "Please increase the size of the competitive comparison graph" and the results of an analysis of user dissatisfaction using an emotion engine, the graph size is adjusted and the document is generated again.

[1417] The user then checks the revised document again and gives final approval.

[1418] The server outputs approved materials in PDF or presentation software format, which users can download from their devices for presentations or distribution.

[1419] (Application example 2)

[1420] 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."

[1421] The task of creating materials related to autonomous vehicles requires a great deal of time and effort, particularly in collecting and organizing information, and creating presentation materials and text. Furthermore, conventional document creation systems make it difficult to customize materials to reflect individual user needs and emotions, creating challenges in ensuring quality and consistency. Furthermore, while it is necessary to appropriately reflect the user's emotions while creating materials, there is no efficient way to do this.

[1422] 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.

[1423] In this invention, the server includes means for receiving purpose and target information of the materials from the user, means for analyzing the purpose and target information and defining the required structure and type of information of the materials, means for collecting the defined information from an internal database and external sources, means for organizing the collected information and converting it into an appropriate text, table, graph, or image format, means for automatically generating a layout of the materials based on the converted information, means for generating text based on the automatically generated layout, means for presenting the generated materials to the user and receiving feedback, and means for analyzing the user's emotions and dynamically adjusting the content and tone of the materials, thereby enabling dynamic customization of materials based on the user's emotions and the creation of high-quality materials.

[1424] "User" refers to any person or company that uses the System to create Materials.

[1425] "Materials" refers to documents that organize and visually present information, such as presentations and reports.

[1426] "Purpose" refers to the final goal or aim of the user when creating a document.

[1427] "Target information" refers to the collection of specific data and information required to create materials.

[1428] "Analysis" refers to the process of analyzing input information in detail and deriving its meaning and relevance.

[1429] "Structure" refers to how information is organized within a document.

[1430] "Type of information" refers to the format and nature of the data required to make up the material (e.g., text, tables, graphs, images).

[1431] An "internal database" refers to a collection of data managed within a company or organization.

[1432] "External sources" refers to information sources obtained from outside the company or organization (e.g., market research data, public statistics).

[1433] "Collection" refers to the process of gathering the necessary data and information.

[1434] "Organization" refers to the process of organizing collected information in a purposeful manner.

[1435] "Transformation" refers to the process of transforming organized information into a different format (e.g., turning text information into a graph).

[1436] "Layout" refers to the arrangement of information within a document and the design structure.

[1437] "Automatic generation" refers to the system automatically performing a specific process without human intervention.

[1438] "Text generation" refers to the process by which a system automatically creates text.

[1439] "Feedback" refers to reactions and opinions from users.

[1440] "Revising" refers to the process of changing the content or format of material for the purpose of improvement.

[1441] "Analyzing emotions" refers to the process of reading and understanding a user's emotions from their facial expressions and voice.

[1442] "Tone" refers to the overall atmosphere or style of a piece of writing or presentation.

[1443] "Dynamic adjustment" refers to changing the content and format of materials in real time according to the situation and conditions.

[1444] This invention is a system that improves the efficiency and quality of document creation related to autonomous vehicles. It clarifies the roles of the server, terminal, and user, and provides specific operating procedures.

[1445] Program Generation

[1446] 1. The user enters the purpose and target information for creating the document via a device (e.g., a smartphone).

[1447] 2. The server receives the entered purpose and target information, analyzes it, and defines the components of the required materials and the type of information.

[1448] 3. The server collects the defined information from internal databases and external sources. Examples of internal databases include company product specifications and historical sales data, while examples of external sources include market trends and competitive information.

[1449] 4. The server organizes the collected information and converts it into appropriate text, table, graph, and image formats, using data analysis libraries such as Pandas and Matplotlib.

[1450] 5. The server automatically generates the layout of the materials based on the organized information. For example, it may use a blue color scheme and place the company logo in the bottom right corner of each slide.

[1451] 6. The server then uses natural language processing technology to generate sentences, such as "Our new product achieves a 20% performance improvement over the previous model," using a generative AI model (e.g., GPT-2).

[1452] 7. The server presents the generated materials to the user and receives feedback. The user uses a smartphone application to check the contents of the materials and enter feedback as needed. The user's facial expressions and voice are also captured through the device's camera and microphone and analyzed by the emotion engine.

[1453] 8. The server dynamically adjusts the content and tone of the materials based on this feedback and emotional data. For example, if the user shows a dissatisfied expression, the server will modify the design and text of that section to make it more specific and appealing.

[1454] 9. The server automatically makes the specified corrections and regenerates the document. The user then checks the corrected document again and finally approves it.

[1455] Hardware and Software

[1456] Hardware:

[1457] Devices such as smartphones and tablets

[1458] Cloud Server

[1459] Camera and microphone (for emotion analysis)

[1460] software:

[1461] Data collection and analysis: Pandas, Matplotlib

[1462] Natural Language Processing: GPT-2 (Hugging Face transformers library)

[1463] Sentiment analysis: BERT model (nlptown / bert-base-multilingual-uncased-sentiment)

[1464] Examples and prompts

[1465] For example, if a user types "I want to introduce a new navigation feature to my target market," the system will do the following:

[1466] The server collects details of new navigation features from an internal database, along with market trend information.

[1467] The automatically generated materials include sentences such as, "The new navigation function provides highly accurate location information services."

[1468] When a user inputs feedback that "information is insufficient," the server performs sentiment analysis and adds information about competitors' features.

[1469] Example prompt sentence:

[1470] "Get additional competitive comparison information for your customers and generate even more detailed graphs."

[1471] In this way, the system utilizes generative AI models and prompt sentences to create efficient, high-quality documents.

[1472] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1473] Step 1:

[1474] The user uses the terminal to input the purpose and target information of the material.

[1475] Input: Purpose of the material (e.g., introducing a new navigation feature) and subject information (target market, competitive information).

[1476] Output: The input data is sent to the cloud server.

[1477] Step 2:

[1478] The server analyzes the entered purpose and target information.

[1479] Input: Purpose and target information entered by the user.

[1480] Output: The components of the material and the type of information are defined.

[1481] Specific operation: The server performs natural language processing based on the input information and creates a list of the information required for the document.

[1482] Step 3:

[1483] The server collects the required information from an internal database and external sources.

[1484] Input: Material components and types of information.

[1485] Output: Information organized in a predetermined format.

[1486] What it does: The server uses SQL queries to extract data from its internal database and retrieves data from external sources through APIs.

[1487] Step 4:

[1488] The server converts the collected information into appropriate text, table, graph, and image formats.

[1489] Input: Organized information.

[1490] Output: Data converted into text, table, graph and image formats.

[1491] Specific operation: Process data with the Pandas library and generate graphs with Matplotlib.

[1492] Step 5:

[1493] The server automatically generates the layout of the materials based on the converted information.

[1494] Input: The transformed data.

[1495] Output: Auto-generated document layout.

[1496] What it does: Uses a template engine to assemble a layout into the specified format.

[1497] Step 6:

[1498] The server generates text based on the automatically generated layout.

[1499] Input: Document layout.

[1500] Output: The generated description.

[1501] Specific operation: Generate sentences using generative AI models such as GPT-2.

[1502] Step 7:

[1503] The server presents the generated materials to the user and receives feedback.

[1504] Input: Generated materials.

[1505] Output: User feedback and sentiment data.

[1506] Specific operation: Materials are displayed on the device screen, and the user's reactions are captured using the camera and microphone.

[1507] Step 8:

[1508] The server dynamically adjusts the content and tone of the material based on user feedback and emotional data.

[1509] Input: User feedback, emotion data.

[1510] Output: The corrected document.

[1511] What it does: Uses a sentiment analysis model (BERT) to modify text and layout based on sentiment scores.

[1512] Step 9:

[1513] The server regenerates the modified material and presents it to the user for final confirmation.

[1514] Input: Corrected material.

[1515] Output: Final approved materials.

[1516] Specific operation: After receiving final confirmation from the user, the materials are output in PDF or PowerPoint format.

[1517] Through the above process, the system can efficiently create high-quality materials that reflect the user's emotions.

[1518] 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.

[1519] 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.

[1520] 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.

[1521] 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.

[1522] 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.

[1523] 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.

[1524] 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).

[1525] 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.

[1526] 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."

[1527] 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.

[1528] 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).

[1529] 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.

[1530] 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.

[1531] 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.

[1532] 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.

[1533] 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.

[1534] 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.

[1535] 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.

[1536] 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.

[1537] 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.

[1538] 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.

[1539] The following is further disclosed regarding the above embodiment.

[1540] (Claim 1)

[1541] means for receiving material purpose and subject info...

Claims

1. means for receiving material purpose and subject information from the user; means for analyzing the purpose and target information and defining the required material structure and information type; means for collecting said defined information from internal databases and external sources; means for organizing and converting the collected information into appropriate text, table, graph, or image formats; means for automatically generating a layout of materials based on the converted information; means for generating text based on the automatically generated layout; means for presenting the generated materials to a user and receiving feedback; The system includes means for automatically making corrections based on said feedback.

2. 10. The system of claim 1, further comprising means for automatically modifying specific portions of the material (e.g., graphs, tables, text, etc.) based on feedback from the user.

3. 2. The system according to claim 1, wherein the means for generating a layout of the document further includes means for setting fonts, colors, and page numbers in accordance with a company's brand guidelines.

Images