System

Abstract

To provide a system for enabling a user to quickly acquire materials in various styles, and for sharply reducing time and labor to be spent on material preparation.SOLUTION: The information processing apparatus includes an input unit configured to allow a user to input text, a receiving unit configured to receive the text input by the input unit, an analyzing unit configured to analyze the text received by the receiving unit, a generating unit configured to generate a plurality of materials based on the text analyzed by the analyzing unit, a setting unit configured to set a style of the materials generated by the generating unit, an automatic generating unit configured to automatically generate the plurality of materials based on the style set by the setting unit, a converting unit configured to convert the plurality of materials generated by the automatic generating unit into a file format, and a providing unit configured to provide the materials converted by the converting unit to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In the modern business environment, creating documents is an important task that requires time and effort. However, many business people are required to create documents in different patterns and styles, which can consume a lot of time. Therefore, there is a growing demand for a system that can quickly and efficiently generate documents in various styles. [Means for solving the problem]

[0005] In order to solve the above-mentioned problems, the present invention provides the following means: a system including input means for a user to input text, receiving means for receiving the text input by the input means, analysis means for analyzing the text received by the receiving means, generation means for generating a plurality of materials based on the text analyzed by the analysis means, setting means for setting a style of the materials generated by the generation means, automatic generation means for automatically generating a plurality of materials based on the style set by the setting means, conversion means for converting the plurality of materials generated by the automatic generation means into a file format, and provision means for providing the materials converted by the conversion means to a user. This allows a user to quickly obtain materials in a variety of styles, significantly reducing the time and effort required to create materials.

[0006] A "user" is an entity that operates the system to input text and receive the generated materials.

[0007] "Text" is document data that a user provides to the system using an input means.

[0008] "Input means" refers to an interface for a user to input text, and includes a keyboard, a mouse, a touch panel, and the like.

[0009] The "receiving means" is a component that allows the system to receive text input by the input means.

[0010] The "analysis means" is a function for analyzing the text received by the receiving means and extracting main topics and keywords.

[0011] The "generation means" is a function for creating materials based on the information extracted by the analysis means.

[0012] "Style settings" are settings that determine the appearance and format of the generated materials.

[0013] The "setting means" is an interface that allows the user to select the style of the document, and is a function that reflects the style setting.

[0014] The "automatic generation means" is a function for automatically generating a plurality of materials based on the style set by the setting means.

[0015] A "file format" is a standard data structure for storing document data, including PDF and PPT.

[0016] The "conversion means" is a function for converting the materials generated by the automatic generation means into a file format.

[0017] The "provision means" is a function for providing the user with the material converted by the conversion means. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] This invention is a system that instantly generates 100 patterns of materials by allowing the user to input text. This system includes the processes of text analysis, automatic material generation, style setting, file format conversion, and provision to the user.

[0040] Program processing overview

[0041] 1. The user inputs text via a dedicated application or web browser on the device. For example, the user can input text such as "About the sales strategy for a new product."

[0042] 2. The terminal sends the entered text to the server, which temporarily stores the received text in a database.

[0043] 3. The server launches the generation AI to retrieve text from the database. This text is analyzed by the analysis means, which extracts the main topics and keywords from the text.

[0044] 4. The user can use the device interface to set the style of the document, for example, black taste, POP, old style, etc.

[0045] 5. The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[0046] 6. The AI ​​automatically generates 100 different patterns of materials using text based on the set style. For the black theme, a simple design based on black is used. For the pop style, a colorful color scheme is used, and for the old-fashioned style, a traditional format is used. The generated materials are diverse, allowing users to choose according to their needs.

[0047] 7. The server converts the generated materials into a file format, such as PDF or PPT, making them easily accessible to users.

[0048] 8. The server sends the converted file to the user's device, where the user can check the list of provided materials and download the materials they need.

[0049] Specific examples

[0050] For example, if a user enters the text "Sales Strategy for a New Product" and selects the black theme, the server will instantly generate 100 different versions of the document. Specifically, the following documents will be generated:

[0051] Pattern 1: A black slide with key keywords highlighted in red.

[0052] Pattern 2: A slide with a dark background and bulleted main points in white text.

[0053] Pattern 3: Slides that make extensive use of graphs and charts and are visually easy to understand.

[0054] Users can select these patterns from the list of materials displayed on their terminal and download and use the materials they want.

[0055] This system greatly simplifies the process of creating documents and improves work efficiency for business people. In addition, AI-based automatic generation provides documents in a variety of styles, allowing users to select the most suitable document for their purpose.

[0056] The processing flow will be explained below.

[0057] Step 1:

[0058] The user opens a dedicated application or web browser on their device, enters the text of the document they want to create into the input form, and presses the submit button.

[0059] Step 2:

[0060] (Terminal) sends the entered text to the server, which passes the text to the server as text data.

[0061] Step 3:

[0062] The server temporarily stores the received text data in a database, which is then used for analysis.

[0063] Step 4:

[0064] The (server) starts the generation AI and retrieves the received text from the database, which is then analyzed by the analysis means.

[0065] Step 5:

[0066] The server instructs the AI ​​to analyze the text, which extracts key topics and keywords from the text.

[0067] Step 6:

[0068] The user uses the terminal interface to set the style of the document, for example, selecting a style such as black taste, POP, or old-fashioned.

[0069] Step 7:

[0070] The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[0071] Step 8:

[0072] The server instructs the AI ​​to automatically generate materials that reflect the set style. The AI ​​then automatically generates 100 different patterns of materials using text based on the set style.

[0073] Step 9:

[0074] The server converts the generated materials into a file format (PDF, PPT, etc.) and the conversion means prepares the materials in a format that can be used by the user.

[0075] Step 10:

[0076] The server sends the converted file to the user's terminal, and the document list is displayed on the terminal by the providing means.

[0077] Step 11:

[0078] The user selects the desired material from the list of materials displayed on the terminal and downloads it. The user then checks the downloaded material and modifies or uses it as necessary.

[0079] In this way, a system is realized that allows users to quickly obtain materials in a variety of styles through specific operations at each step.

[0080] Example 1

[0081] 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."

[0082] Conventional document creation systems have the problem that it takes a lot of time and effort for users to manually create a large number of documents. Furthermore, it is difficult to provide documents with the same content in various styles, making it impossible to quickly provide documents that meet specific needs. Therefore, there is a need for a system that can automatically generate documents in a variety of styles and is easy to use, while improving user efficiency.

[0083] 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.

[0084] In this invention, the server includes input means for a user to input text, transmission means for transmitting the text input by the input means from the terminal to the server, storage means for the server to store the text received by the transmission means in a database, analysis means for analyzing the text stored by the storage means, generation means for generating a plurality of materials based on main topics and keywords extracted by the analysis means, style setting means for the user to set a style for the materials, automatic generation means for the server to automatically generate a plurality of materials based on style parameters set by the style setting means, conversion means for converting the plurality of materials generated by the automatic generation means into a file format such as PDF or PPT, and provision means for the server to transmit the materials converted by the conversion means to the terminal. This allows users to easily automatically generate materials in a variety of styles and quickly use them.

[0085] An "input means" is a function or device that allows a user to input text.

[0086] "Transmission means" refers to a function or device for transmitting input text from a terminal to a server.

[0087] The "storage means" is a function or device for temporarily storing the text received by the server in a database.

[0088] "Analysis means" refers to a function or device for analyzing the stored text and extracting key topics and keywords.

[0089] The "generation means" is a function or device for generating a plurality of materials based on the information extracted by the analysis means.

[0090] "Style setting means" refers to a function or device that allows a user to select and set the style of a document.

[0091] The "automatic generation means" is a function or device for automatically generating materials based on set style parameters.

[0092] "Conversion means" refers to a function or device for converting the generated materials into a file format such as PDF or PPT.

[0093] The "provision means" is a function or device for transmitting the converted material to the user's terminal and making it available for use.

[0094] "Display means" refers to a function or device for displaying a list of converted materials.

[0095] The "downloading means" is a function or device that allows a user to download converted materials to a terminal.

[0096] MODE FOR CARRYING OUT THE INVENTION

[0097] This invention is a system that instantly generates 100 patterns of materials by inputting text from the user. This system can be used through a dedicated application or a web browser and consists of the following main processing steps:

[0098] Hardware and Software

[0099] 1. Input method:

[0100] The user uses a device such as a PC or smartphone to input text into a dedicated application or web browser. For example, the user might input text such as "Sales strategy for a new product."

[0101] 2. Means of transmission:

[0102] The device sends the entered text to the server using the HTTPS protocol, and this communication is done through a secure REST API.

[0103] 3. Preservation means:

[0104] The server temporarily stores the received text in a database (e.g., MySQL or PostgreSQL).

[0105] 4. Analysis method:

[0106] The server runs a generative AI model (e.g., OpenAI GPT-3) and retrieves the stored text from the database. This text is then analyzed by the generative AI to extract key topics and keywords.

[0107] 5. Styling tools:

[0108] Users can style their documents using a browser or application interface, choosing from style options such as "black," "POP," and "old-fashioned."

[0109] 6. Automatic generation means:

[0110] The server passes the style parameters set by the style setting means to the generation AI, which automatically generates 100 different patterns of materials based on these. In the case of a black taste, a design based on black is used.

[0111] 7. Conversion Method:

[0112] The server converts the generated documents into file formats such as PDF and PPT using libraries such as PDFKit and python-pptx.

[0113] 8. Means of provision:

[0114] The server sends the converted files to the user's device, where the user can view the list of generated files in the application or browser and download the desired files.

[0115] Specific examples

[0116] For example, if a user enters the text "Sales Strategy for a New Product" and selects the black theme, the server will instantly generate 100 different versions of the document. Specifically, the following documents will be generated:

[0117] Pattern 1: A black slide with key keywords highlighted in red.

[0118] Pattern 2: A slide with a dark background and bulleted main points in white text.

[0119] Pattern 3: Slides that make extensive use of graphs and charts and are visually easy to understand.

[0120] Prompt Sentence Example

[0121] "Generate 100 different materials using a black theme for a new product sales strategy."

[0122] This system greatly simplifies the process of creating documents and improves work efficiency for business people. In addition, the system automatically generates documents in a variety of styles using AI, allowing users to select the document that best suits their needs.

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

[0124] Step 1:

[0125] The user enters text

[0126] Input: A user uses a device (PC or smartphone) to enter text such as "About the sales strategy for a new product" into a dedicated application or web browser.

[0127] Specific behavior: The user enters text into the text input field and clicks the "Submit" button.

[0128] Output: The user's input text is stored in the device's memory and is ready to be sent to the next step.

[0129] Step 2:

[0130] The device sends the entered text to the server

[0131] Input: The text data entered in step 1.

[0132] Specific operation: The device uses the HTTPS protocol to call a REST API endpoint and send text data to the server.

[0133] Output: Text data is sent to the server.

[0134] Step 3:

[0135] The server receives the text and stores it in a database

[0136] Input: The text data sent to the server in step 2.

[0137] Specific operation: The server temporarily stores the received text in a database (MySQL, PostgreSQL, etc.).

[0138] Output: The text data is stored in a database and made available for analysis.

[0139] Step 4:

[0140] The server runs a generative AI and analyzes the text.

[0141] Input: Text data stored in a database.

[0142] How it works: The server launches a generative AI model (such as OpenAI GPT-3) to analyze the stored text data. The generative AI uses natural language processing techniques to extract key topics and keywords.

[0143] Output: The main topics and keywords are extracted as a result of the analysis.

[0144] Step 5:

[0145] User-defined style settings for materials

[0146] Input: Style options selected by the user, such as "Black Taste", "POP", "Old Style", etc.

[0147] What happens: The user selects a style option using the device interface. The browser or application remembers the selection.

[0148] Output: The user's style settings are saved on the device and ready to be sent to the server.

[0149] Step 6:

[0150] The device sends the selected style to the server.

[0151] Input: User selected styling data.

[0152] What happens: The device sends styling data to the server using the HTTPS protocol.

[0153] Output: The styling data is sent to the server.

[0154] Step 7:

[0155] The server automatically generates materials

[0156] Input: Styling data and parsed text data.

[0157] How it works: The server passes style parameters and text data to the AI, which then automatically generates 100 different patterns of materials based on these. For example, if the theme is black, a black-based design will be used.

[0158] Output: 100 patterns of generated data.

[0159] Step 8:

[0160] The server converts the file format

[0161] Input: Generated material data.

[0162] Specific operation: The server uses libraries such as PDFKit or python-pptx to convert to file formats such as PDF or PPT.

[0163] Output: PDF and PPT files.

[0164] Step 9:

[0165] The server sends the file to the user's device.

[0166] Input: PDF or PPT file created in step 8.

[0167] Specific operation: The server sends the file to the user's device using the HTTPS protocol. The device saves the received file and notifies the user.

[0168] Output: User downloadable PDF and PPT files.

[0169] Through the above process, users can automatically generate 100 different patterns of materials simply by entering text, and use them in a variety of styles.

[0170] (Application example 1)

[0171] 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."

[0172] In modern brick-and-mortar stores, effective product promotion and advertising is extremely important, but creating such promotions and advertising takes time and effort. Furthermore, there are limited means to quickly generate and display advertisements and materials with consistent design. This problem needs to be resolved, enabling store staff to easily and quickly generate attractive advertising materials and use them in-store.

[0173] 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.

[0174] In this invention, the server includes input means for a user to input text, receiving means for receiving the text input by the input means, analysis means for analyzing the text received by the receiving means, generation means for generating a plurality of materials based on the text analyzed by the analysis means, setting means for setting a style for the materials generated by the generation means, automatic generation means for automatically generating a plurality of materials based on the style set by the setting means, conversion means for converting the plurality of materials generated by the automatic generation means into a file format, provision means for providing the materials converted by the conversion means to users, and display means for displaying the materials on an electronic advertising board in a store. This allows promotional materials to be generated easily and quickly in a physical store and used in the store.

[0175] An "input means" is a means by which a user inputs text.

[0176] The "receiving means" is a means for receiving the text input by the input means.

[0177] The "analysis means" is a means for analyzing the text received by the receiving means.

[0178] The "generation means" is a means for generating a plurality of materials based on the text analyzed by the analysis means.

[0179] The "setting means" is a means for setting the style of the material generated by the generating means.

[0180] The "automatic generation means" is a means for automatically generating a plurality of materials based on the style set by the setting means.

[0181] The "conversion means" is a means for converting the plurality of materials generated by the automatic generation means into a file format.

[0182] The "providing means" is a means for providing the user with the material converted by the converting means.

[0183] "Display means" refers to means for displaying materials on an electronic advertising bulletin board within a store.

[0184] The system embodying this invention is designed to support effective in-store promotions, and can quickly generate materials based on text entered by the user and display them on an electronic billboard.

[0185] The main components of the system include user terminals, cloud servers, and in-store electronic billboards. These elements communicate with each other and exchange information to operate.

[0186] First, a user inputs text using a dedicated application or web browser on a device. Specific text can be entered, such as "About the sales strategy for a new product." This input is performed from a user device such as smart glasses or a management terminal.

[0187] The device then sends the input text to a cloud server, which temporarily stores the received text in a database and then launches a generative AI model to analyze the text. The analysis method extracts key topics and keywords from the input text.

[0188] The user then uses the device's user interface to style the document, choosing from a variety of styles including casual, modern, and traditional. The selected style is then sent back to the cloud server, which passes the style parameters to the generative AI model.

[0189] The generative AI model automatically generates 100 different patterns of materials based on the set style. In this process, it adopts a variety of styles, including black, pop, and old-fashioned. The generated materials are diverse, allowing users to choose according to their needs.

[0190] The generated materials are converted into file formats such as PDF and PPT on a cloud server, and are then sent to the user's device and displayed on the store's electronic billboard.

[0191] A specific example is a sales promotion for a new 4K TV at a consumer electronics retailer. When a user uses the smart glasses to speak a prompt such as, "Show me the best features of this new 4K TV. It has a modern style," a document is instantly generated. This document is then displayed in real time on digital signage in the store, enhancing its appeal to customers.

[0192] This system utilizes a generative AI model to instantly generate materials in a variety of styles based on prompt text, thereby revolutionizing the efficiency of promotional activities in physical stores.

[0193] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0194] Step 1:

[0195] The user inputs text using a device (smart glasses or a management device) via a dedicated application or web browser. This input includes prompts such as "New product sale promotion." The input text is stored in the device's internal temporary memory.

[0196] Step 2:

[0197] The device sends the entered text to the cloud server. This is done using an HTTP request, and the text data is passed to the server. The entered text is temporarily stored in a database on the server side.

[0198] Step 3:

[0199] The server analyzes the received text using its analysis tools. Specifically, it uses a natural language processing model (e.g., BERT or GPT) to extract key topics and keywords. As an output, a dataset of the analysis results is generated.

[0200] Step 4:

[0201] The user uses the device's user interface to set the style of the document, for example, by selecting from casual, modern, traditional, etc. The selected style information is stored in the device's internal temporary memory.

[0202] Step 5:

[0203] The device sends the user's selected style settings to the server using an HTTP request, and the style setting data is passed to the server. The entered style settings are temporarily stored in a database on the server side.

[0204] Step 6:

[0205] The server launches a generative AI model and automatically generates 100 patterns of materials based on the analyzed text data and style settings. Specifically, a generative AI model (such as DALL-E or GAN) is used to generate materials that conform to the specified style. The output is a dataset of diverse materials.

[0206] Step 7:

[0207] The server converts the generated materials into a file format using an appropriate library (e.g., a PDF generation library or a PPT generation library) and stores the converted files in temporary memory within the server.

[0208] Step 8:

[0209] The server sends the converted data to the store's electronic billboard. A dedicated API is used to send the data, and the data is displayed on the billboard.

[0210] Step 9:

[0211] The server sends the converted data to the user's device using an HTTP response, and the user receives a PDF or PPT file that can be downloaded and viewed on the device.

[0212] 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.

[0213] This invention combines a system that instantly generates 100 patterns of materials based on user input text with an emotion engine that recognizes the user's emotions. The emotion engine analyzes the user's emotional data and adjusts the style of the generated materials more appropriately.

[0214] Program processing overview

[0215] 1. The user inputs text into a dedicated application or web browser on the device. For example, the user can input text such as "About the sales strategy for a new product."

[0216] 2. The terminal sends the entered text data to the server, which temporarily stores the received text in a database.

[0217] 3. The server launches the generation AI to retrieve text data from the database, and the analysis method extracts the main topics and keywords from the text.

[0218] 4. The user uses the device interface to set the style of the document, for example, select a style such as black, POP, or old-fashioned.

[0219] 5. The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[0220] 6. The emotion engine analyzes the user's text input and interactions to extract emotion data. The emotion analyzer determines the user's emotional state (e.g., happy, sad, excited, calm).

[0221] 7. The server passes the emotion data obtained from the emotion engine to the generation AI. The generation AI automatically generates 100 different patterns of materials based on the style settings and emotion data. For example, if the user is excited, an energetic, visually stimulating style will be selected based on the emotion data.

[0222] 8. The server converts the generated materials into a file format (PDF, PPT, etc.) that can be easily used by users.

[0223] 9. The server sends the converted file to the user's device, where a list of materials is displayed and the user can download the desired materials.

[0224] Specific examples

[0225] For example, if a user enters the text "Sales Strategy for a New Product" and selects a dark theme, the emotion engine analyzes the user's emotional state. If the user's emotion is determined to be "excited," the server passes the emotion data to the generation AI, which then generates energetic, visually stimulating materials in a dark theme.

[0226] For example, the following material is generated:

[0227] Pattern 1: A black slide with key keywords highlighted in red, reflecting the user's excitement.

[0228] Pattern 2: A dynamic design with visually striking graphs and charts placed on a dark background.

[0229] Pattern 3: Slides that make extensive use of visual effects that suit when the user is excited.

[0230] Users can select the desired material from a list displayed on their device, download it, and use it. This system greatly simplifies the process of creating materials, and quickly provides the most appropriate material based on the user's preferences.

[0231] The processing flow will be explained below.

[0232] Step 1:

[0233] The user opens a dedicated application or web browser on their device, enters the text of the document they want to create into the input form, and presses the submit button.

[0234] Step 2:

[0235] (Terminal) sends the entered text data to the server. The sent text is passed to the server as text data.

[0236] Step 3:

[0237] The server temporarily stores the received text data in a database, which is used for later analysis.

[0238] Step 4:

[0239] The (server) starts the generation AI and retrieves the received text from the database, which is then analyzed by the analysis means.

[0240] Step 5:

[0241] The server instructs the AI ​​to analyze the text, which extracts key topics and keywords from the text.

[0242] Step 6:

[0243] The user uses the terminal interface to set the style of the document, for example, selecting a style such as black taste, POP, or old-fashioned.

[0244] Step 7:

[0245] The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[0246] Step 8:

[0247] The emotion engine analyzes the user's text input and interactions to extract emotion data. The emotion analysis means determines the user's emotional state (e.g., happy, sad, excited, calm).

[0248] Step 9:

[0249] The server passes the emotion data obtained from the emotion engine to the generation AI, which then integrates the style settings and emotion data to adjust the parameters for generating materials.

[0250] Step 10:

[0251] The AI ​​automatically generates 100 different patterns of materials based on the set style and emotional data. For example, if the emotional data is "excited," an energetic and visually stimulating style will be selected.

[0252] Step 11:

[0253] The server converts the generated materials into a file format (PDF, PPT, etc.) and prepares them in a format that can be easily used by users.

[0254] Step 12:

[0255] The server sends the converted file to the user's terminal, where the list of materials is displayed.

[0256] Step 13:

[0257] The user selects the desired material from the list of materials displayed on the terminal and downloads it. The user then checks the downloaded material and modifies or uses it as necessary.

[0258] Example 2

[0259] 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."

[0260] Conventional document generation systems generate documents based on simple text input by the user, making it difficult to reflect the user's emotions and intentions. As a result, the generated documents may not match the user's expectations or emotions, which can lead to a poor user experience. In addition, the style settings of the generated documents are fixed, making it difficult to flexibly respond to individual user requests.

[0261] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: an input means for a user to input text; a receiving means for receiving the text input by the input means; an analysis means for analyzing the text received by the receiving means; a generation means for generating multiple materials based on the text analyzed by the analysis means; a setting means for setting a style of the materials generated by the generation means; an automatic generation means for automatically generating multiple materials based on the style set by the setting means; an emotion analysis means for analyzing a user's emotions; a style adjustment means for adjusting the style of the generated materials based on emotion data obtained by the emotion analysis means; a conversion means for converting the multiple materials generated by the automatic generation means into a file format; and a providing means for providing the materials converted by the conversion means to the user. This makes it possible to generate materials based on the user's emotions and intentions.

[0262] An "input means" is a device or software interface that allows a user to input text.

[0263] The "receiving means" is a system or function for receiving text sent from the input means.

[0264] An "analysis means" is a system or algorithm that analyzes received text and extracts key topics or keywords.

[0265] The "generation means" is a system or software for generating a plurality of materials based on the text analyzed by the analysis means.

[0266] The "setting means" is an interface or system for setting the style of the material generated by the generating means.

[0267] The "automatic generation means" is a system or algorithm for automatically generating multiple materials based on the style set by the setting means.

[0268] An "emotion analysis means" is a system or software that analyzes emotion data through user input text and user interaction with an interface.

[0269] The "style adjustment means" is a system or function for appropriately adjusting the style of the generated material based on the emotion data obtained by the emotion analysis means.

[0270] "Conversion means" refers to a system or software for converting multiple documents into a file format that is easy for users to use.

[0271] The "providing means" is a system or interface for providing the user with the material converted by the converting means.

[0272] The "display means" is a system or software that allows the providing means to display to the user a list of converted materials.

[0273] "Downloading means" means a system or interface that enables a user to download the converted material provided by the providing means.

[0274] This invention combines a system that instantly generates 100 patterns of materials based on user input text with an emotion engine that recognizes the user's emotions. The following describes in detail how to implement the program for this system.

[0275] First, a user uses a terminal to access a dedicated application or a web browser and input text. This input means allows the user to input text such as "Regarding sales strategies for new products." The input text data is sent from the terminal to a server, where it is received by the server's receiving means. The server temporarily stores the received text data in a database.

[0276] Within the server, the analysis tool retrieves text data from the database and uses a generative AI model (such as OpenAI's GPT-3) to analyze the text for key topics and keywords. After the analysis is complete, users can use the device interface to style the material, choosing from styles such as black, pop, and old-fashioned.

[0277] The device sends the user's selected style settings to the server, which then passes the style settings parameters to the generation AI. At the same time, a sentiment analysis tool analyzes the user's text input and interface interactions to extract emotional data. For example, it can use emotion engines such as Microsoft's Azure Cognitive Services or IBM Watson.

[0278] The emotion data acquired by the emotion analysis means is passed from the server to the generation AI. The generation AI automatically generates 100 different patterns of materials based on the user's emotion data and style settings. For example, if the user is determined to be "excited," an energetic and visually stimulating style is selected.

[0279] The generated documents are converted into a file format (e.g. PDF, PPT, etc.) by the server. This involves converting the documents into PDF format using Python's reportlab library, etc. The server then sends the converted files to the user's device via a delivery method. A list of documents is displayed on the device, and the user can download the documents they want.

[0280] As a concrete example, let's consider the case where a user inputs the text "Sales Strategy for a New Product," selects a black-and-white document style, and the emotion engine determines the user's emotion as "excited." In this case, the following document will be generated:

[0281] 1. Pattern 1: A black slide with key keywords highlighted in red, reflecting the user's excitement.

[0282] 2. Pattern 2: Visually striking graphs and charts are placed on a dark background, creating a dynamic design.

[0283] 3. Pattern 3: Slides that make extensive use of visual effects that suit the user's excited state.

[0284] Users can select the desired material from a list of materials displayed on their device, download it, and use it, which greatly simplifies the material creation process and quickly provides materials that are optimized to the user's emotions.

[0285] Example prompt sentence:

[0286] User: Enter the text "Sales strategy for new products"

[0287] System: "Please select the style of your materials. You can choose from black, pop, old-fashioned, etc."

[0288] User: Select "Black taste"

[0289] System: Analyzing user's emotional state...

[0290] System: Determined as "excited"

[0291] System: Generates 100 different patterns of materials.

[0292] System: Generation is complete. Please download the desired materials from the list below.

[0293] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0294] Step 1:

[0295] A user accesses a dedicated application or web browser on a terminal and inputs text such as "Sales strategy for a new product" into a text input field. Text data is acquired by an input means. The input is based on the user's intention, and the output is text data. Specific operations include the user inputting text using a keyboard.

[0296] Step 2:

[0297] The terminal transmits input text data to the server. The text data is encoded through a transmission means and transmitted to the server as a POST request. The input is the text data entered by the user, and the output is the text data transmitted to the server. Specific operations include the terminal transmitting data via an Internet connection.

[0298] Step 3:

[0299] The server analyzes the received text data using the analysis means and stores it in the database. The server receives the data using the reception means and extracts the main topics and keywords of the text using the analysis means. The data is reshaped and the format is optimized. The input is the text data received by the server, and the output is the analysis results and storage in the database. The specific operation is to perform an INSERT operation in the database.

[0300] Step 4:

[0301] The user styles the document through the terminal interface. For example, the user selects from options such as black, pop, and old-fashioned. The input is the user's style selection, and the output is the transmission of the style selection data to the server. Specific operations include the user selecting a style from a drop-down menu or radio buttons.

[0302] Step 5:

[0303] The terminal transmits style setting data to the server. This data is transmitted to the server as a POST request via the transmission means. The input is the style setting data selected by the user, and the output is the transmission of the style data to the server. Specific operations include an operation in which the terminal transmits the style data to the server via an HTTP request.

[0304] Step 6:

[0305] The server starts the emotion analysis means and analyzes the user's input text and interaction data to extract emotional data. The emotion analysis means determines the user's emotion as "happiness," "sadness," "excitement," etc. The input is text data and interaction data, and the output is the user's emotional data. Specifically, the server passes the data to an emotion analysis engine (e.g., Microsoft's Azure Cognitive Services) for analysis.

[0306] Step 7:

[0307] The server passes emotion data and style settings to a generative AI model, which then automatically generates 100 different patterns of materials based on this. The generative AI model (e.g., OpenAI's GPT-3) receives the emotion data and style settings as prompts and generates materials. The input is emotion data and style settings, and the output is 100 patterns of materials. Specific operations include the server sending prompt sentences to the generative AI model and receiving the generated results.

[0308] Step 8:

[0309] The server converts the generated document into a file format, for example, PDF format using the Python reportlab library. The input is the generated document, and the output is the document in the converted file format. Specific operations include the server calling a conversion means to convert the document into PDF or PPT format.

[0310] Step 9:

[0311] The server sends the converted file to the user's terminal. Using the provision means, a list of materials is displayed on the terminal, allowing the user to download the materials they desire. The input is the materials in the converted file format, and the output is the list of materials displayed on the terminal. Specific operations include the server sending the materials in an HTTP response and displaying the list on the terminal.

[0312] (Application example 2)

[0313] 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."

[0314] Conventional document generation systems do not take the user's emotional state into account, which means that the generated materials are not optimized for the emotions of the target audience. This is particularly true in the advertising field, where the inability to generate advertising materials that match the emotions of the target audience reduces the effectiveness of advertising. Furthermore, typical document generation systems lack flexibility in style settings, making it difficult to meet the diverse needs of users. A system that solves these problems is needed.

[0315] 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.

[0316] In this invention, the server includes input means for a user to input text, receiving means for receiving the text input by the input means, analysis means for analyzing the text received by the receiving means, generation means for generating a plurality of materials based on the text analyzed by the analysis means, setting means for setting a style of the materials generated by the generation means, emotion recognition means for recognizing the emotional state of the user, emotion data receiving means for receiving emotion data extracted by the emotion recognition means, automatic generation means for automatically generating a plurality of materials based on the style set by the setting means and the emotion data, conversion means for converting the plurality of materials generated by the automatic generation means into a file format, and provision means for providing the materials converted by the conversion means to the user. This makes it possible to generate materials that take the emotional state of the user into consideration, and to provide optimal materials to a target audience, particularly in fields such as advertising.

[0317] An "input means" is a means by which a user inputs text.

[0318] The "receiving means" is a means for receiving the text input by the input means.

[0319] "Analysis means" is a means for analyzing received text.

[0320] The "generation means" is a means for generating a plurality of materials based on the analyzed text.

[0321] The "setting means" is a means for setting the style of the generated document.

[0322] "Emotion recognition means" is a means for recognizing the emotional state of a user.

[0323] The "emotion data receiving means" is a means for receiving the emotion data extracted by the emotion recognition means.

[0324] The "automatic generation means" is a means for automatically generating a plurality of materials based on the set style and emotion data.

[0325] The "conversion means" is a means for converting multiple automatically generated materials into a file format.

[0326] The "means for providing" is a means for providing the converted material to the user.

[0327] The present invention is described in detail below with reference to an embodiment thereof. The system of the present invention comprises an input means for a user to input text, a receiving means, an analyzing means, a generating means, a setting means, an emotion recognition means, an emotion data receiving means, an automatic generating means, a converting means, and a providing means.

[0328] Program processing overview

[0329] The server provides a dedicated application or web browser for the user to input text. When the user inputs text, the input means receives the text and sends it to the server via the receiving means. The server temporarily stores the received text in a database. Next, the server uses the analyzing means to analyze the received text and extract major topics and keywords.

[0330] The user can set the style of the document using the interface of the terminal, for example, he can select a style such as black taste, pop, old style, etc. The setting means transmits the user's selected style setting to the server, and the server uses the emotion recognition means to analyze the user's text input and interaction.

[0331] The emotion data obtained by the emotion recognition means is passed to the server via the emotion data receiving means. The server passes the emotion data to the generation AI, which then automatically generates multiple materials based on the style settings and emotion data. The generation AI model uses OpenAI GPT-4, and its prompt sentences include the emotion data and style settings.

[0332] The generated materials are converted into a file format such as PDF or PPT by a conversion means. Finally, the converted files are sent to the user's terminal via a provision means, and the user can download the desired materials. An example of a prompt sentence is "User's emotional data: excitement. Style setting: pop style. Generate an advertisement based on the following topic: "New product campaign advertisement."

[0333] Hardware and software used

[0334] The server is hosted on Google Cloud Platform or AWS, the database is MySQL, IBM Watson or Microsoft Azure Emotion API is used for emotion recognition, OpenAI GPT-4 is used for generative AI modeling, and PDFlib is used for document conversion.

[0335] Specific examples

[0336] For example, if a user inputs the text "Sales Strategy for a New Product" and selects a dark theme, the emotion recognition means will analyze the user's emotional state. If the emotional data is determined to be "excited," the server will pass the emotional data to the generation AI, which will then generate energetic, visually stimulating, dark-themed materials. Specifically, this process will generate the following materials:

[0337] Pattern 1: A black slide with key keywords highlighted in red, reflecting the user's excitement.

[0338] Pattern 2: A dynamic design with visually striking graphs and charts placed on a dark background.

[0339] Pattern 3: Slides that make extensive use of visual effects that suit when the user is excited.

[0340] This allows users to select the desired material from a list of materials displayed on their device, and then download and use it. This system greatly simplifies the process of creating materials, and quickly provides the most appropriate material to suit the user's needs.

[0341] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0342] Step 1:

[0343] The user inputs text through a dedicated application or a web browser.

[0344] Input: Text data entered by the user (e.g., "Regarding sales strategies for new products").

[0345] Specific actions: The user enters text into the text box and presses the send button.

[0346] Step 2:

[0347] The terminal transmits the input text data to the server.

[0348] Input: Text data entered by the user.

[0349] Output: The text data received by the server.

[0350] Specific operation: The terminal application generates an HTTP request and sends text data to the server.

[0351] Step 3:

[0352] The server temporarily stores the received text in a database.

[0353] Input: Received text data.

[0354] Output: Text data stored in a database.

[0355] Specific operation: The SQL statement is executed on the server side and the text data is saved in the MySQL database.

[0356] Step 4:

[0357] The server uses an analysis means to analyze the text data and extract key topics and keywords.

[0358] Input: Text data stored in a database.

[0359] Output: Extracted main topics and keywords.

[0360] Specific operation: The server uses a natural language processing library (e.g., spaCy) to extract topics and keywords from the text data.

[0361] Step 5:

[0362] The user styles the document using the device interface.

[0363] Input: The style you choose (e.g., black taste, pop, old-fashioned, etc.).

[0364] Output: The selected style settings.

[0365] Specific action: The user selects a style from a drop-down menu or checkbox and presses the OK button.

[0366] Step 6:

[0367] The device sends the user's selected style settings to the server.

[0368] Input: The selected style setting.

[0369] Output: The style settings received by the server.

[0370] Specific operation: The application on the device generates an HTTP request and sends style setting data to the server.

[0371] Step 7:

[0372] The server uses emotion recognition means to analyze the user's text input and interactions and extract emotion data.

[0373] Input: Text data and user interaction data.

[0374] Output: Extracted emotion data.

[0375] Specific operation: The server uses an emotion recognition API (e.g., IBM Watson) to analyze the user's emotional state.

[0376] Step 8:

[0377] The server passes the emotion data to a generation AI, which automatically generates multiple materials based on the style settings and emotion data.

[0378] Input: emotion data and styling.

[0379] Output: The generated documents.

[0380] Specific operation: The server sends a prompt to the generative AI model (e.g., OpenAI GPT-4) to generate materials. Example prompt: "User emotion data: excitement. Style setting: pop style. Generate an advertisement based on the following topic: 'New product campaign advertisement'."

[0381] Step 9:

[0382] The server converts the automatically generated materials into a file format (PDF, PPT, etc.).

[0383] Input: Generated materials.

[0384] Output: The material converted into a file format.

[0385] Specific operation: The server uses PDFlib to convert the generated materials into PDF or PPT format.

[0386] Step 10:

[0387] The server provides the converted file to the user's terminal, allowing the user to download the desired material.

[0388] Input: The converted file.

[0389] Output: A file that users can download.

[0390] Specific operation: The server sends the file to the user's device through the Express server and provides a download link.

[0391] 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.

[0392] 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.

[0393] 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.

[0394] [Second embodiment]

[0395] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0396] 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.

[0397] 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).

[0398] 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.

[0399] 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.

[0400] 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).

[0401] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0402] 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.

[0403] 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.

[0404] 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.

[0405] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0406] 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."

[0407] This invention is a system that instantly generates 100 patterns of materials by allowing the user to input text. This system includes the processes of text analysis, automatic material generation, style setting, file format conversion, and provision to the user.

[0408] Program processing overview

[0409] 1. The user inputs text via a dedicated application or web browser on the device. For example, the user can input text such as "About the sales strategy for a new product."

[0410] 2. The terminal sends the entered text to the server, which temporarily stores the received text in a database.

[0411] 3. The server launches the generation AI to retrieve text from the database. This text is analyzed by the analysis means, which extracts the main topics and keywords from the text.

[0412] 4. The user can use the device interface to set the style of the document, for example, black taste, POP, old style, etc.

[0413] 5. The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[0414] 6. The AI ​​automatically generates 100 different patterns of materials using text based on the set style. For the black theme, a simple design based on black is used. For the pop style, a colorful color scheme is used, and for the old-fashioned style, a traditional format is used. The generated materials are diverse, allowing users to choose according to their needs.

[0415] 7. The server converts the generated materials into a file format, such as PDF or PPT, making them easily accessible to users.

[0416] 8. The server sends the converted file to the user's device, where the user can check the list of provided materials and download the materials they need.

[0417] Specific examples

[0418] For example, if a user enters the text "Sales Strategy for a New Product" and selects the black theme, the server will instantly generate 100 different versions of the document. Specifically, the following documents will be generated:

[0419] Pattern 1: A black slide with key keywords highlighted in red.

[0420] Pattern 2: A slide with a dark background and bulleted main points in white text.

[0421] Pattern 3: Slides that make extensive use of graphs and charts and are visually easy to understand.

[0422] Users can select these patterns from the list of materials displayed on their terminal and download and use the materials they want.

[0423] This system greatly simplifies the process of creating documents and improves work efficiency for business people. In addition, AI-based automatic generation provides documents in a variety of styles, allowing users to select the most suitable document for their purpose.

[0424] The processing flow will be explained below.

[0425] Step 1:

[0426] The user opens a dedicated application or web browser on their device, enters the text of the document they want to create into the input form, and presses the submit button.

[0427] Step 2:

[0428] (Terminal) sends the entered text to the server, which passes the text to the server as text data.

[0429] Step 3:

[0430] The server temporarily stores the received text data in a database, which is then used for analysis.

[0431] Step 4:

[0432] The (server) starts the generation AI and retrieves the received text from the database, which is then analyzed by the analysis means.

[0433] Step 5:

[0434] The server instructs the AI ​​to analyze the text, which extracts key topics and keywords from the text.

[0435] Step 6:

[0436] The user uses the terminal interface to set the style of the document, for example, selecting a style such as black taste, POP, or old-fashioned.

[0437] Step 7:

[0438] The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[0439] Step 8:

[0440] The server instructs the AI ​​to automatically generate materials that reflect the set style. The AI ​​then automatically generates 100 different patterns of materials using text based on the set style.

[0441] Step 9:

[0442] The server converts the generated materials into a file format (PDF, PPT, etc.) and the conversion means prepares the materials in a format that can be used by the user.

[0443] Step 10:

[0444] The server sends the converted file to the user's terminal, and the document list is displayed on the terminal by the providing means.

[0445] Step 11:

[0446] The user selects the desired material from the list of materials displayed on the terminal and downloads it. The user then checks the downloaded material and modifies or uses it as necessary.

[0447] In this way, a system is realized that allows users to quickly obtain materials in a variety of styles through specific operations at each step.

[0448] Example 1

[0449] 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."

[0450] Conventional document creation systems have the problem that it takes a lot of time and effort for users to manually create a large number of documents. Furthermore, it is difficult to provide documents with the same content in various styles, making it impossible to quickly provide documents that meet specific needs. Therefore, there is a need for a system that can automatically generate documents in a variety of styles and is easy to use, while improving user efficiency.

[0451] 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.

[0452] In this invention, the server includes input means for a user to input text, transmission means for transmitting the text input by the input means from the terminal to the server, storage means for the server to store the text received by the transmission means in a database, analysis means for analyzing the text stored by the storage means, generation means for generating a plurality of materials based on main topics and keywords extracted by the analysis means, style setting means for the user to set a style for the materials, automatic generation means for the server to automatically generate a plurality of materials based on style parameters set by the style setting means, conversion means for converting the plurality of materials generated by the automatic generation means into a file format such as PDF or PPT, and provision means for the server to transmit the materials converted by the conversion means to the terminal. This allows users to easily automatically generate materials in a variety of styles and quickly use them.

[0453] An "input means" is a function or device that allows a user to input text.

[0454] "Transmission means" refers to a function or device for transmitting input text from a terminal to a server.

[0455] The "storage means" is a function or device for temporarily storing the text received by the server in a database.

[0456] "Analysis means" refers to a function or device for analyzing the stored text and extracting key topics and keywords.

[0457] The "generation means" is a function or device for generating a plurality of materials based on the information extracted by the analysis means.

[0458] "Style setting means" refers to a function or device that allows a user to select and set the style of a document.

[0459] The "automatic generation means" is a function or device for automatically generating materials based on set style parameters.

[0460] "Conversion means" refers to a function or device for converting the generated materials into a file format such as PDF or PPT.

[0461] The "provision means" is a function or device for transmitting the converted material to the user's terminal and making it available for use.

[0462] "Display means" refers to a function or device for displaying a list of converted materials.

[0463] The "downloading means" is a function or device that allows a user to download converted materials to a terminal.

[0464] MODE FOR CARRYING OUT THE INVENTION

[0465] This invention is a system that instantly generates 100 patterns of materials by inputting text from the user. This system can be used through a dedicated application or a web browser and consists of the following main processing steps:

[0466] Hardware and Software

[0467] 1. Input method:

[0468] The user uses a device such as a PC or smartphone to input text into a dedicated application or web browser. For example, the user might input text such as "Sales strategy for a new product."

[0469] 2. Means of transmission:

[0470] The device sends the entered text to the server using the HTTPS protocol, and this communication is done through a secure REST API.

[0471] 3. Preservation means:

[0472] The server temporarily stores the received text in a database (e.g., MySQL or PostgreSQL).

[0473] 4. Analysis method:

[0474] The server runs a generative AI model (e.g., OpenAI GPT-3) and retrieves the stored text from the database. This text is then analyzed by the generative AI to extract key topics and keywords.

[0475] 5. Styling tools:

[0476] Users can style their documents using a browser or application interface, choosing from style options such as "black," "POP," and "old-fashioned."

[0477] 6. Automatic generation means:

[0478] The server passes the style parameters set by the style setting means to the generation AI, which automatically generates 100 different patterns of materials based on these. In the case of a black taste, a design based on black is used.

[0479] 7. Conversion Method:

[0480] The server converts the generated documents into file formats such as PDF and PPT using libraries such as PDFKit and python-pptx.

[0481] 8. Means of provision:

[0482] The server sends the converted files to the user's device, where the user can view the list of generated files in the application or browser and download the desired files.

[0483] Specific examples

[0484] For example, if a user enters the text "Sales Strategy for a New Product" and selects the black theme, the server will instantly generate 100 different versions of the document. Specifically, the following documents will be generated:

[0485] Pattern 1: A black slide with key keywords highlighted in red.

[0486] Pattern 2: A slide with a dark background and bulleted main points in white text.

[0487] Pattern 3: Slides that make extensive use of graphs and charts and are visually easy to understand.

[0488] Prompt Sentence Example

[0489] "Generate 100 different materials using a black theme for a new product sales strategy."

[0490] This system greatly simplifies the process of creating documents and improves work efficiency for business people. In addition, the system automatically generates documents in a variety of styles using AI, allowing users to select the document that best suits their needs.

[0491] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0492] Step 1:

[0493] The user enters text

[0494] Input: A user uses a device (PC or smartphone) to enter text such as "About the sales strategy for a new product" into a dedicated application or web browser.

[0495] Specific behavior: The user enters text into the text input field and clicks the "Submit" button.

[0496] Output: The user's input text is stored in the device's memory and is ready to be sent to the next step.

[0497] Step 2:

[0498] The device sends the entered text to the server

[0499] Input: The text data entered in step 1.

[0500] Specific operation: The device uses the HTTPS protocol to call a REST API endpoint and send text data to the server.

[0501] Output: Text data is sent to the server.

[0502] Step 3:

[0503] The server receives the text and stores it in a database

[0504] Input: The text data sent to the server in step 2.

[0505] Specific operation: The server temporarily stores the received text in a database (MySQL, PostgreSQL, etc.).

[0506] Output: The text data is stored in a database and made available for analysis.

[0507] Step 4:

[0508] The server runs a generative AI and analyzes the text.

[0509] Input: Text data stored in a database.

[0510] How it works: The server launches a generative AI model (such as OpenAI GPT-3) to analyze the stored text data. The generative AI uses natural language processing techniques to extract key topics and keywords.

[0511] Output: The main topics and keywords are extracted as a result of the analysis.

[0512] Step 5:

[0513] User-defined style settings for materials

[0514] Input: Style options selected by the user, such as "Black Taste", "POP", "Old Style", etc.

[0515] What happens: The user selects a style option using the device interface. The browser or application remembers the selection.

[0516] Output: The user's style settings are saved on the device and ready to be sent to the server.

[0517] Step 6:

[0518] The device sends the selected style to the server.

[0519] Input: User selected styling data.

[0520] What happens: The device sends styling data to the server using the HTTPS protocol.

[0521] Output: The styling data is sent to the server.

[0522] Step 7:

[0523] The server automatically generates materials

[0524] Input: Styling data and parsed text data.

[0525] How it works: The server passes style parameters and text data to the AI, which then automatically generates 100 different patterns of materials based on these. For example, if the theme is black, a black-based design will be used.

[0526] Output: 100 patterns of generated data.

[0527] Step 8:

[0528] The server converts the file format

[0529] Input: Generated material data.

[0530] Specific operation: The server uses libraries such as PDFKit or python-pptx to convert to file formats such as PDF or PPT.

[0531] Output: PDF and PPT files.

[0532] Step 9:

[0533] The server sends the file to the user's device.

[0534] Input: PDF or PPT file created in step 8.

[0535] Specific operation: The server sends the file to the user's device using the HTTPS protocol. The device saves the received file and notifies the user.

[0536] Output: User downloadable PDF and PPT files.

[0537] Through the above process, users can automatically generate 100 different patterns of materials simply by entering text, and use them in a variety of styles.

[0538] (Application example 1)

[0539] 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."

[0540] In modern brick-and-mortar stores, effective product promotion and advertising is extremely important, but creating such promotions and advertising takes time and effort. Furthermore, there are limited means to quickly generate and display advertisements and materials with consistent design. This problem needs to be resolved, enabling store staff to easily and quickly generate attractive advertising materials and use them in-store.

[0541] 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.

[0542] In this invention, the server includes input means for a user to input text, receiving means for receiving the text input by the input means, analysis means for analyzing the text received by the receiving means, generation means for generating a plurality of materials based on the text analyzed by the analysis means, setting means for setting a style for the materials generated by the generation means, automatic generation means for automatically generating a plurality of materials based on the style set by the setting means, conversion means for converting the plurality of materials generated by the automatic generation means into a file format, provision means for providing the materials converted by the conversion means to users, and display means for displaying the materials on an electronic advertising board in a store. This allows promotional materials to be generated easily and quickly in a physical store and used in the store.

[0543] An "input means" is a means by which a user inputs text.

[0544] The "receiving means" is a means for receiving the text input by the input means.

[0545] The "analysis means" is a means for analyzing the text received by the receiving means.

[0546] The "generation means" is a means for generating a plurality of materials based on the text analyzed by the analysis means.

[0547] The "setting means" is a means for setting the style of the material generated by the generating means.

[0548] The "automatic generation means" is a means for automatically generating a plurality of materials based on the style set by the setting means.

[0549] The "conversion means" is a means for converting the plurality of materials generated by the automatic generation means into a file format.

[0550] The "providing means" is a means for providing the user with the material converted by the converting means.

[0551] "Display means" refers to means for displaying materials on an electronic advertising bulletin board within a store.

[0552] The system embodying this invention is designed to support effective in-store promotions, and can quickly generate materials based on text entered by the user and display them on an electronic billboard.

[0553] The main components of the system include user terminals, cloud servers, and in-store electronic billboards. These elements communicate with each other and exchange information to operate.

[0554] First, a user inputs text using a dedicated application or web browser on a device. Specific text can be entered, such as "About the sales strategy for a new product." This input is performed from a user device such as smart glasses or a management terminal.

[0555] The device then sends the input text to a cloud server, which temporarily stores the received text in a database and then launches a generative AI model to analyze the text. The analysis method extracts key topics and keywords from the input text.

[0556] The user then uses the device's user interface to style the document, choosing from a variety of styles including casual, modern, and traditional. The selected style is then sent back to the cloud server, which passes the style parameters to the generative AI model.

[0557] The generative AI model automatically generates 100 different patterns of materials based on the set style. In this process, it adopts a variety of styles, including black, pop, and old-fashioned. The generated materials are diverse, allowing users to choose according to their needs.

[0558] The generated materials are converted into file formats such as PDF and PPT on a cloud server, and are then sent to the user's device and displayed on the store's electronic billboard.

[0559] A specific example is a sales promotion for a new 4K TV at a consumer electronics retailer. When a user uses the smart glasses to speak a prompt such as, "Show me the best features of this new 4K TV. It has a modern style," a document is instantly generated. This document is then displayed in real time on digital signage in the store, enhancing its appeal to customers.

[0560] This system utilizes a generative AI model to instantly generate materials in a variety of styles based on prompt text, thereby revolutionizing the efficiency of promotional activities in physical stores.

[0561] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0562] Step 1:

[0563] The user inputs text using a device (smart glasses or a management device) via a dedicated application or web browser. This input includes prompts such as "New product sale promotion." The input text is stored in the device's internal temporary memory.

[0564] Step 2:

[0565] The device sends the entered text to the cloud server. This is done using an HTTP request, and the text data is passed to the server. The entered text is temporarily stored in a database on the server side.

[0566] Step 3:

[0567] The server analyzes the received text using its analysis tools. Specifically, it uses a natural language processing model (e.g., BERT or GPT) to extract key topics and keywords. As an output, a dataset of the analysis results is generated.

[0568] Step 4:

[0569] The user uses the device's user interface to set the style of the document, for example, by selecting from casual, modern, traditional, etc. The selected style information is stored in the device's internal temporary memory.

[0570] Step 5:

[0571] The device sends the user's selected style settings to the server using an HTTP request, and the style setting data is passed to the server. The entered style settings are temporarily stored in a database on the server side.

[0572] Step 6:

[0573] The server launches a generative AI model and automatically generates 100 patterns of materials based on the analyzed text data and style settings. Specifically, a generative AI model (such as DALL-E or GAN) is used to generate materials that conform to the specified style. The output is a dataset of diverse materials.

[0574] Step 7:

[0575] The server converts the generated materials into a file format using an appropriate library (e.g., a PDF generation library or a PPT generation library) and stores the converted files in temporary memory within the server.

[0576] Step 8:

[0577] The server sends the converted data to the store's electronic billboard. A dedicated API is used to send the data, and the data is displayed on the billboard.

[0578] Step 9:

[0579] The server sends the converted data to the user's device using an HTTP response, and the user receives a PDF or PPT file that can be downloaded and viewed on the device.

[0580] 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.

[0581] This invention combines a system that instantly generates 100 patterns of materials based on user input text with an emotion engine that recognizes the user's emotions. The emotion engine analyzes the user's emotional data and adjusts the style of the generated materials more appropriately.

[0582] Program processing overview

[0583] 1. The user inputs text into a dedicated application or web browser on the device. For example, the user can input text such as "About the sales strategy for a new product."

[0584] 2. The terminal sends the entered text data to the server, which temporarily stores the received text in a database.

[0585] 3. The server launches the generation AI to retrieve text data from the database, and the analysis method extracts the main topics and keywords from the text.

[0586] 4. The user uses the device interface to set the style of the document, for example, select a style such as black, POP, or old-fashioned.

[0587] 5. The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[0588] 6. The emotion engine analyzes the user's text input and interactions to extract emotion data. The emotion analyzer determines the user's emotional state (e.g., happy, sad, excited, calm).

[0589] 7. The server passes the emotion data obtained from the emotion engine to the generation AI. The generation AI automatically generates 100 different patterns of materials based on the style settings and emotion data. For example, if the user is excited, an energetic, visually stimulating style will be selected based on the emotion data.

[0590] 8. The server converts the generated materials into a file format (PDF, PPT, etc.) that can be easily used by users.

[0591] 9. The server sends the converted file to the user's device, where a list of materials is displayed and the user can download the desired materials.

[0592] Specific examples

[0593] For example, if a user enters the text "Sales Strategy for a New Product" and selects a dark theme, the emotion engine analyzes the user's emotional state. If the user's emotion is determined to be "excited," the server passes the emotion data to the generation AI, which then generates energetic, visually stimulating materials in a dark theme.

[0594] For example, the following material is generated:

[0595] Pattern 1: A black slide with key keywords highlighted in red, reflecting the user's excitement.

[0596] Pattern 2: A dynamic design with visually striking graphs and charts placed on a dark background.

[0597] Pattern 3: Slides that make extensive use of visual effects that suit when the user is excited.

[0598] Users can select the desired material from a list displayed on their device, download it, and use it. This system greatly simplifies the process of creating materials, and quickly provides the most appropriate material based on the user's preferences.

[0599] The processing flow will be explained below.

[0600] Step 1:

[0601] The user opens a dedicated application or web browser on their device, enters the text of the document they want to create into the input form, and presses the submit button.

[0602] Step 2:

[0603] (Terminal) sends the entered text data to the server. The sent text is passed to the server as text data.

[0604] Step 3:

[0605] The server temporarily stores the received text data in a database, which is used for later analysis.

[0606] Step 4:

[0607] The (server) starts the generation AI and retrieves the received text from the database, which is then analyzed by the analysis means.

[0608] Step 5:

[0609] The server instructs the AI ​​to analyze the text, which extracts key topics and keywords from the text.

[0610] Step 6:

[0611] The user uses the terminal interface to set the style of the document, for example, selecting a style such as black taste, POP, or old-fashioned.

[0612] Step 7:

[0613] The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[0614] Step 8:

[0615] The emotion engine analyzes the user's text input and interactions to extract emotion data. The emotion analysis means determines the user's emotional state (e.g., happy, sad, excited, calm).

[0616] Step 9:

[0617] The server passes the emotion data obtained from the emotion engine to the generation AI, which then integrates the style settings and emotion data to adjust the parameters for generating materials.

[0618] Step 10:

[0619] The AI ​​automatically generates 100 different patterns of materials based on the set style and emotional data. For example, if the emotional data is "excited," an energetic and visually stimulating style will be selected.

[0620] Step 11:

[0621] The server converts the generated materials into a file format (PDF, PPT, etc.) and prepares them in a format that can be easily used by users.

[0622] Step 12:

[0623] The server sends the converted file to the user's terminal, where the list of materials is displayed.

[0624] Step 13:

[0625] The user selects the desired material from the list of materials displayed on the terminal and downloads it. The user then checks the downloaded material and modifies or uses it as necessary.

[0626] Example 2

[0627] 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."

[0628] Conventional document generation systems generate documents based on simple text input by the user, making it difficult to reflect the user's emotions and intentions. As a result, the generated documents may not match the user's expectations or emotions, which can lead to a poor user experience. In addition, the style settings of the generated documents are fixed, making it difficult to flexibly respond to individual user requests.

[0629] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: an input means for a user to input text; a receiving means for receiving the text input by the input means; an analysis means for analyzing the text received by the receiving means; a generation means for generating multiple materials based on the text analyzed by the analysis means; a setting means for setting a style of the materials generated by the generation means; an automatic generation means for automatically generating multiple materials based on the style set by the setting means; an emotion analysis means for analyzing a user's emotions; a style adjustment means for adjusting the style of the generated materials based on emotion data obtained by the emotion analysis means; a conversion means for converting the multiple materials generated by the automatic generation means into a file format; and a providing means for providing the materials converted by the conversion means to the user. This makes it possible to generate materials based on the user's emotions and intentions.

[0630] An "input means" is a device or software interface that allows a user to input text.

[0631] The "receiving means" is a system or function for receiving text sent from the input means.

[0632] An "analysis means" is a system or algorithm that analyzes received text and extracts key topics or keywords.

[0633] The "generation means" is a system or software for generating a plurality of materials based on the text analyzed by the analysis means.

[0634] The "setting means" is an interface or system for setting the style of the material generated by the generating means.

[0635] The "automatic generation means" is a system or algorithm for automatically generating multiple materials based on the style set by the setting means.

[0636] An "emotion analysis means" is a system or software that analyzes emotion data through user input text and user interaction with an interface.

[0637] The "style adjustment means" is a system or function for appropriately adjusting the style of the generated material based on the emotion data obtained by the emotion analysis means.

[0638] "Conversion means" refers to a system or software for converting multiple documents into a file format that is easy for users to use.

[0639] The "providing means" is a system or interface for providing the user with the material converted by the converting means.

[0640] The "display means" is a system or software that allows the providing means to display to the user a list of converted materials.

[0641] "Downloading means" means a system or interface that enables a user to download the converted material provided by the providing means.

[0642] This invention combines a system that instantly generates 100 patterns of materials based on user input text with an emotion engine that recognizes the user's emotions. The following describes in detail how to implement the program for this system.

[0643] First, a user uses a terminal to access a dedicated application or a web browser and input text. This input means allows the user to input text such as "Regarding sales strategies for new products." The input text data is sent from the terminal to a server, where it is received by the server's receiving means. The server temporarily stores the received text data in a database.

[0644] Within the server, the analysis tool retrieves text data from the database and uses a generative AI model (such as OpenAI's GPT-3) to analyze the text for key topics and keywords. After the analysis is complete, users can use the device interface to style the material, choosing from styles such as black, pop, and old-fashioned.

[0645] The device sends the user's selected style settings to the server, which then passes the style settings parameters to the generation AI. At the same time, a sentiment analysis tool analyzes the user's text input and interface interactions to extract emotional data. For example, it can use emotion engines such as Microsoft's Azure Cognitive Services or IBM Watson.

[0646] The emotion data acquired by the emotion analysis means is passed from the server to the generation AI. The generation AI automatically generates 100 different patterns of materials based on the user's emotion data and style settings. For example, if the user is determined to be "excited," an energetic and visually stimulating style is selected.

[0647] The generated documents are converted into a file format (e.g. PDF, PPT, etc.) by the server. This involves converting the documents into PDF format using Python's reportlab library, etc. The server then sends the converted files to the user's device via a delivery method. A list of documents is displayed on the device, and the user can download the documents they want.

[0648] As a concrete example, let's consider the case where a user inputs the text "Sales Strategy for a New Product," selects a black-and-white document style, and the emotion engine determines the user's emotion as "excited." In this case, the following document will be generated:

[0649] 1. Pattern 1: A black slide with key keywords highlighted in red, reflecting the user's excitement.

[0650] 2. Pattern 2: Visually striking graphs and charts are placed on a dark background, creating a dynamic design.

[0651] 3. Pattern 3: Slides that make extensive use of visual effects that suit the user's excited state.

[0652] Users can select the desired material from a list of materials displayed on their device, download it, and use it, which greatly simplifies the material creation process and quickly provides materials that are optimized to the user's emotions.

[0653] Example prompt sentence:

[0654] User: Enter the text "Sales strategy for new products"

[0655] System: "Please select the style of your materials. You can choose from black, pop, old-fashioned, etc."

[0656] User: Select "Black taste"

[0657] System: Analyzing user's emotional state...

[0658] System: Determined as "excited"

[0659] System: Generates 100 different patterns of materials.

[0660] System: Generation is complete. Please download the desired materials from the list below.

[0661] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0662] Step 1:

[0663] A user accesses a dedicated application or web browser on a terminal and inputs text such as "Sales strategy for a new product" into a text input field. Text data is acquired by an input means. The input is based on the user's intention, and the output is text data. Specific operations include the user inputting text using a keyboard.

[0664] Step 2:

[0665] The terminal transmits input text data to the server. The text data is encoded through a transmission means and transmitted to the server as a POST request. The input is the text data entered by the user, and the output is the text data transmitted to the server. Specific operations include the terminal transmitting data via an Internet connection.

[0666] Step 3:

[0667] The server analyzes the received text data using the analysis means and stores it in the database. The server receives the data using the reception means and extracts the main topics and keywords of the text using the analysis means. The data is reshaped and the format is optimized. The input is the text data received by the server, and the output is the analysis results and storage in the database. The specific operation is to perform an INSERT operation in the database.

[0668] Step 4:

[0669] The user styles the document through the terminal interface. For example, the user selects from options such as black, pop, and old-fashioned. The input is the user's style selection, and the output is the transmission of the style selection data to the server. Specific operations include the user selecting a style from a drop-down menu or radio buttons.

[0670] Step 5:

[0671] The terminal transmits style setting data to the server. This data is transmitted to the server as a POST request via the transmission means. The input is the style setting data selected by the user, and the output is the transmission of the style data to the server. Specific operations include an operation in which the terminal transmits the style data to the server via an HTTP request.

[0672] Step 6:

[0673] The server starts the emotion analysis means and analyzes the user's input text and interaction data to extract emotional data. The emotion analysis means determines the user's emotion as "happiness," "sadness," "excitement," etc. The input is text data and interaction data, and the output is the user's emotional data. Specifically, the server passes the data to an emotion analysis engine (e.g., Microsoft's Azure Cognitive Services) for analysis.

[0674] Step 7:

[0675] The server passes emotion data and style settings to a generative AI model, which then automatically generates 100 different patterns of materials based on this. The generative AI model (e.g., OpenAI's GPT-3) receives the emotion data and style settings as prompts and generates materials. The input is emotion data and style settings, and the output is 100 patterns of materials. Specific operations include the server sending prompt sentences to the generative AI model and receiving the generated results.

[0676] Step 8:

[0677] The server converts the generated document into a file format, for example, PDF format using the Python reportlab library. The input is the generated document, and the output is the document in the converted file format. Specific operations include the server calling a conversion means to convert the document into PDF or PPT format.

[0678] Step 9:

[0679] The server sends the converted file to the user's terminal. Using the provision means, a list of materials is displayed on the terminal, allowing the user to download the materials they desire. The input is the materials in the converted file format, and the output is the list of materials displayed on the terminal. Specific operations include the server sending the materials in an HTTP response and displaying the list on the terminal.

[0680] (Application example 2)

[0681] 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."

[0682] Conventional document generation systems do not take the user's emotional state into account, which means that the generated materials are not optimized for the emotions of the target audience. This is particularly true in the advertising field, where the inability to generate advertising materials that match the emotions of the target audience reduces the effectiveness of advertising. Furthermore, typical document generation systems lack flexibility in style settings, making it difficult to meet the diverse needs of users. A system that solves these problems is needed.

[0683] 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.

[0684] In this invention, the server includes input means for a user to input text, receiving means for receiving the text input by the input means, analysis means for analyzing the text received by the receiving means, generation means for generating a plurality of materials based on the text analyzed by the analysis means, setting means for setting a style of the materials generated by the generation means, emotion recognition means for recognizing the emotional state of the user, emotion data receiving means for receiving emotion data extracted by the emotion recognition means, automatic generation means for automatically generating a plurality of materials based on the style set by the setting means and the emotion data, conversion means for converting the plurality of materials generated by the automatic generation means into a file format, and provision means for providing the materials converted by the conversion means to the user. This makes it possible to generate materials that take the emotional state of the user into consideration, and to provide optimal materials to a target audience, particularly in fields such as advertising.

[0685] An "input means" is a means by which a user inputs text.

[0686] The "receiving means" is a means for receiving the text input by the input means.

[0687] "Analysis means" is a means for analyzing received text.

[0688] The "generation means" is a means for generating a plurality of materials based on the analyzed text.

[0689] The "setting means" is a means for setting the style of the generated document.

[0690] "Emotion recognition means" is a means for recognizing the emotional state of a user.

[0691] The "emotion data receiving means" is a means for receiving the emotion data extracted by the emotion recognition means.

[0692] The "automatic generation means" is a means for automatically generating a plurality of materials based on the set style and emotion data.

[0693] The "conversion means" is a means for converting multiple automatically generated materials into a file format.

[0694] The "means for providing" is a means for providing the converted material to the user.

[0695] The present invention is described in detail below with reference to an embodiment thereof. The system of the present invention comprises an input means for a user to input text, a receiving means, an analyzing means, a generating means, a setting means, an emotion recognition means, an emotion data receiving means, an automatic generating means, a converting means, and a providing means.

[0696] Program processing overview

[0697] The server provides a dedicated application or web browser for the user to input text. When the user inputs text, the input means receives the text and sends it to the server via the receiving means. The server temporarily stores the received text in a database. Next, the server uses the analyzing means to analyze the received text and extract major topics and keywords.

[0698] The user can set the style of the document using the interface of the terminal, for example, he can select a style such as black taste, pop, old style, etc. The setting means transmits the user's selected style setting to the server, and the server uses the emotion recognition means to analyze the user's text input and interaction.

[0699] The emotion data obtained by the emotion recognition means is passed to the server via the emotion data receiving means. The server passes the emotion data to the generation AI, which then automatically generates multiple materials based on the style settings and emotion data. The generation AI model uses OpenAI GPT-4, and its prompt sentences include the emotion data and style settings.

[0700] The generated materials are converted into a file format such as PDF or PPT by a conversion means. Finally, the converted files are sent to the user's terminal via a provision means, and the user can download the desired materials. An example of a prompt sentence is "User's emotional data: excitement. Style setting: pop style. Generate an advertisement based on the following topic: "New product campaign advertisement."

[0701] Hardware and software used

[0702] The server is hosted on Google Cloud Platform or AWS, the database is MySQL, IBM Watson or Microsoft Azure Emotion API is used for emotion recognition, OpenAI GPT-4 is used for generative AI modeling, and PDFlib is used for document conversion.

[0703] Specific examples

[0704] For example, if a user inputs the text "Sales Strategy for a New Product" and selects a dark theme, the emotion recognition means will analyze the user's emotional state. If the emotional data is determined to be "excited," the server will pass the emotional data to the generation AI, which will then generate energetic, visually stimulating, dark-themed materials. Specifically, this process will generate the following materials:

[0705] Pattern 1: A black slide with key keywords highlighted in red, reflecting the user's excitement.

[0706] Pattern 2: A dynamic design with visually striking graphs and charts placed on a dark background.

[0707] Pattern 3: Slides that make extensive use of visual effects that suit when the user is excited.

[0708] This allows users to select the desired material from a list of materials displayed on their device, and then download and use it. This system greatly simplifies the process of creating materials, and quickly provides the most appropriate material to suit the user's needs.

[0709] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0710] Step 1:

[0711] The user inputs text through a dedicated application or a web browser.

[0712] Input: Text data entered by the user (e.g., "Regarding sales strategies for new products").

[0713] Specific actions: The user enters text into the text box and presses the send button.

[0714] Step 2:

[0715] The terminal transmits the input text data to the server.

[0716] Input: Text data entered by the user.

[0717] Output: The text data received by the server.

[0718] Specific operation: The terminal application generates an HTTP request and sends text data to the server.

[0719] Step 3:

[0720] The server temporarily stores the received text in a database.

[0721] Input: Received text data.

[0722] Output: Text data stored in a database.

[0723] Specific operation: The SQL statement is executed on the server side and the text data is saved in the MySQL database.

[0724] Step 4:

[0725] The server uses an analysis means to analyze the text data and extract key topics and keywords.

[0726] Input: Text data stored in a database.

[0727] Output: Extracted main topics and keywords.

[0728] Specific operation: The server uses a natural language processing library (e.g., spaCy) to extract topics and keywords from the text data.

[0729] Step 5:

[0730] The user styles the document using the device interface.

[0731] Input: The style you choose (e.g., black taste, pop, old-fashioned, etc.).

[0732] Output: The selected style settings.

[0733] Specific action: The user selects a style from a drop-down menu or checkbox and presses the OK button.

[0734] Step 6:

[0735] The device sends the user's selected style settings to the server.

[0736] Input: The selected style setting.

[0737] Output: The style settings received by the server.

[0738] Specific operation: The application on the device generates an HTTP request and sends style setting data to the server.

[0739] Step 7:

[0740] The server uses emotion recognition means to analyze the user's text input and interactions and extract emotion data.

[0741] Input: Text data and user interaction data.

[0742] Output: Extracted emotion data.

[0743] Specific operation: The server uses an emotion recognition API (e.g., IBM Watson) to analyze the user's emotional state.

[0744] Step 8:

[0745] The server passes the emotion data to a generation AI, which automatically generates multiple materials based on the style settings and emotion data.

[0746] Input: emotion data and styling.

[0747] Output: The generated documents.

[0748] Specific operation: The server sends a prompt to the generative AI model (e.g., OpenAI GPT-4) to generate materials. Example prompt: "User emotion data: excitement. Style setting: pop style. Generate an advertisement based on the following topic: 'New product campaign advertisement'."

[0749] Step 9:

[0750] The server converts the automatically generated materials into a file format (PDF, PPT, etc.).

[0751] Input: Generated materials.

[0752] Output: The material converted into a file format.

[0753] Specific operation: The server uses PDFlib to convert the generated materials into PDF or PPT format.

[0754] Step 10:

[0755] The server provides the converted file to the user's terminal, allowing the user to download the desired material.

[0756] Input: The converted file.

[0757] Output: A file that users can download.

[0758] Specific operation: The server sends the file to the user's device through the Express server and provides a download link.

[0759] 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.

[0760] 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.

[0761] 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.

[0762] [Third embodiment]

[0763] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0764] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0765] 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).

[0766] 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.

[0767] 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.

[0768] 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).

[0769] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0770] 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.

[0771] 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.

[0772] 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.

[0773] 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.

[0774] 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."

[0775] This invention is a system that instantly generates 100 patterns of materials by allowing the user to input text. This system includes the processes of text analysis, automatic material generation, style setting, file format conversion, and provision to the user.

[0776] Program processing overview

[0777] 1. The user inputs text via a dedicated application or web browser on the device. For example, the user can input text such as "About the sales strategy for a new product."

[0778] 2. The terminal sends the entered text to the server, which temporarily stores the received text in a database.

[0779] 3. The server launches the generation AI to retrieve text from the database. This text is analyzed by the analysis means, which extracts the main topics and keywords from the text.

[0780] 4. The user can use the device interface to set the style of the document, for example, black taste, POP, old style, etc.

[0781] 5. The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[0782] 6. The AI ​​automatically generates 100 different patterns of materials using text based on the set style. For the black theme, a simple design based on black is used. For the pop style, a colorful color scheme is used, and for the old-fashioned style, a traditional format is used. The generated materials are diverse, allowing users to choose according to their needs.

[0783] 7. The server converts the generated materials into a file format, such as PDF or PPT, making them easily accessible to users.

[0784] 8. The server sends the converted file to the user's device, where the user can check the list of provided materials and download the materials they need.

[0785] Specific examples

[0786] For example, if a user enters the text "Sales Strategy for a New Product" and selects the black theme, the server will instantly generate 100 different versions of the document. Specifically, the following documents will be generated:

[0787] Pattern 1: A black slide with key keywords highlighted in red.

[0788] Pattern 2: A slide with a dark background and bulleted main points in white text.

[0789] Pattern 3: Slides that make extensive use of graphs and charts and are visually easy to understand.

[0790] Users can select these patterns from the list of materials displayed on their terminal and download and use the materials they want.

[0791] This system greatly simplifies the process of creating documents and improves work efficiency for business people. In addition, AI-based automatic generation provides documents in a variety of styles, allowing users to select the most suitable document for their purpose.

[0792] The processing flow will be explained below.

[0793] Step 1:

[0794] The user opens a dedicated application or web browser on their device, enters the text of the document they want to create into the input form, and presses the submit button.

[0795] Step 2:

[0796] (Terminal) sends the entered text to the server, which passes the text to the server as text data.

[0797] Step 3:

[0798] The server temporarily stores the received text data in a database, which is then used for analysis.

[0799] Step 4:

[0800] The (server) starts the generation AI and retrieves the received text from the database, which is then analyzed by the analysis means.

[0801] Step 5:

[0802] The server instructs the AI ​​to analyze the text, which extracts key topics and keywords from the text.

[0803] Step 6:

[0804] The user uses the terminal interface to set the style of the document, for example, selecting a style such as black taste, POP, or old-fashioned.

[0805] Step 7:

[0806] The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[0807] Step 8:

[0808] The server instructs the AI ​​to automatically generate materials that reflect the set style. The AI ​​then automatically generates 100 different patterns of materials using text based on the set style.

[0809] Step 9:

[0810] The server converts the generated materials into a file format (PDF, PPT, etc.) and the conversion means prepares the materials in a format that can be used by the user.

[0811] Step 10:

[0812] The server sends the converted file to the user's terminal, and the document list is displayed on the terminal by the providing means.

[0813] Step 11:

[0814] The user selects the desired material from the list of materials displayed on the terminal and downloads it. The user then checks the downloaded material and modifies or uses it as necessary.

[0815] In this way, a system is realized that allows users to quickly obtain materials in a variety of styles through specific operations at each step.

[0816] Example 1

[0817] 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."

[0818] Conventional document creation systems have the problem that it takes a lot of time and effort for users to manually create a large number of documents. Furthermore, it is difficult to provide documents with the same content in various styles, making it impossible to quickly provide documents that meet specific needs. Therefore, there is a need for a system that can automatically generate documents in a variety of styles and is easy to use, while improving user efficiency.

[0819] 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.

[0820] In this invention, the server includes input means for a user to input text, transmission means for transmitting the text input by the input means from the terminal to the server, storage means for the server to store the text received by the transmission means in a database, analysis means for analyzing the text stored by the storage means, generation means for generating a plurality of materials based on main topics and keywords extracted by the analysis means, style setting means for the user to set a style for the materials, automatic generation means for the server to automatically generate a plurality of materials based on style parameters set by the style setting means, conversion means for converting the plurality of materials generated by the automatic generation means into a file format such as PDF or PPT, and provision means for the server to transmit the materials converted by the conversion means to the terminal. This allows users to easily automatically generate materials in a variety of styles and quickly use them.

[0821] An "input means" is a function or device that allows a user to input text.

[0822] "Transmission means" refers to a function or device for transmitting input text from a terminal to a server.

[0823] The "storage means" is a function or device for temporarily storing the text received by the server in a database.

[0824] "Analysis means" refers to a function or device for analyzing the stored text and extracting key topics and keywords.

[0825] The "generation means" is a function or device for generating a plurality of materials based on the information extracted by the analysis means.

[0826] "Style setting means" refers to a function or device that allows a user to select and set the style of a document.

[0827] The "automatic generation means" is a function or device for automatically generating materials based on set style parameters.

[0828] "Conversion means" refers to a function or device for converting the generated materials into a file format such as PDF or PPT.

[0829] The "provision means" is a function or device for transmitting the converted material to the user's terminal and making it available for use.

[0830] "Display means" refers to a function or device for displaying a list of converted materials.

[0831] The "downloading means" is a function or device that allows a user to download converted materials to a terminal.

[0832] MODE FOR CARRYING OUT THE INVENTION

[0833] This invention is a system that instantly generates 100 patterns of materials by inputting text from the user. This system can be used through a dedicated application or a web browser and consists of the following main processing steps:

[0834] Hardware and Software

[0835] 1. Input method:

[0836] The user uses a device such as a PC or smartphone to input text into a dedicated application or web browser. For example, the user might input text such as "Sales strategy for a new product."

[0837] 2. Means of transmission:

[0838] The device sends the entered text to the server using the HTTPS protocol, and this communication is done through a secure REST API.

[0839] 3. Preservation means:

[0840] The server temporarily stores the received text in a database (e.g., MySQL or PostgreSQL).

[0841] 4. Analysis method:

[0842] The server runs a generative AI model (e.g., OpenAI GPT-3) and retrieves the stored text from the database. This text is then analyzed by the generative AI to extract key topics and keywords.

[0843] 5. Styling tools:

[0844] Users can style their documents using a browser or application interface, choosing from style options such as "black," "POP," and "old-fashioned."

[0845] 6. Automatic generation means:

[0846] The server passes the style parameters set by the style setting means to the generation AI, which automatically generates 100 different patterns of materials based on these. In the case of a black taste, a design based on black is used.

[0847] 7. Conversion Method:

[0848] The server converts the generated documents into file formats such as PDF and PPT using libraries such as PDFKit and python-pptx.

[0849] 8. Means of provision:

[0850] The server sends the converted files to the user's device, where the user can view the list of generated files in the application or browser and download the desired files.

[0851] Specific examples

[0852] For example, if a user enters the text "Sales Strategy for a New Product" and selects the black theme, the server will instantly generate 100 different versions of the document. Specifically, the following documents will be generated:

[0853] Pattern 1: A black slide with key keywords highlighted in red.

[0854] Pattern 2: A slide with a dark background and bulleted main points in white text.

[0855] Pattern 3: Slides that make extensive use of graphs and charts and are visually easy to understand.

[0856] Prompt Sentence Example

[0857] "Generate 100 different materials using a black theme for a new product sales strategy."

[0858] This system greatly simplifies the process of creating documents and improves work efficiency for business people. In addition, the system automatically generates documents in a variety of styles using AI, allowing users to select the document that best suits their needs.

[0859] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0860] Step 1:

[0861] The user enters text

[0862] Input: A user uses a device (PC or smartphone) to enter text such as "About the sales strategy for a new product" into a dedicated application or web browser.

[0863] Specific behavior: The user enters text into the text input field and clicks the "Submit" button.

[0864] Output: The user's input text is stored in the device's memory and is ready to be sent to the next step.

[0865] Step 2:

[0866] The device sends the entered text to the server

[0867] Input: The text data entered in step 1.

[0868] Specific operation: The device uses the HTTPS protocol to call a REST API endpoint and send text data to the server.

[0869] Output: Text data is sent to the server.

[0870] Step 3:

[0871] The server receives the text and stores it in a database

[0872] Input: The text data sent to the server in step 2.

[0873] Specific operation: The server temporarily stores the received text in a database (MySQL, PostgreSQL, etc.).

[0874] Output: The text data is stored in a database and made available for analysis.

[0875] Step 4:

[0876] The server runs a generative AI and analyzes the text.

[0877] Input: Text data stored in a database.

[0878] How it works: The server launches a generative AI model (such as OpenAI GPT-3) to analyze the stored text data. The generative AI uses natural language processing techniques to extract key topics and keywords.

[0879] Output: The main topics and keywords are extracted as a result of the analysis.

[0880] Step 5:

[0881] User-defined style settings for materials

[0882] Input: Style options selected by the user, such as "Black Taste", "POP", "Old Style", etc.

[0883] What happens: The user selects a style option using the device interface. The browser or application remembers the selection.

[0884] Output: The user's style settings are saved on the device and ready to be sent to the server.

[0885] Step 6:

[0886] The device sends the selected style to the server.

[0887] Input: User selected styling data.

[0888] What happens: The device sends styling data to the server using the HTTPS protocol.

[0889] Output: The styling data is sent to the server.

[0890] Step 7:

[0891] The server automatically generates materials

[0892] Input: Styling data and parsed text data.

[0893] How it works: The server passes style parameters and text data to the AI, which then automatically generates 100 different patterns of materials based on these. For example, if the theme is black, a black-based design will be used.

[0894] Output: 100 patterns of generated data.

[0895] Step 8:

[0896] The server converts the file format

[0897] Input: Generated material data.

[0898] Specific operation: The server uses libraries such as PDFKit or python-pptx to convert to file formats such as PDF or PPT.

[0899] Output: PDF and PPT files.

[0900] Step 9:

[0901] The server sends the file to the user's device.

[0902] Input: PDF or PPT file created in step 8.

[0903] Specific operation: The server sends the file to the user's device using the HTTPS protocol. The device saves the received file and notifies the user.

[0904] Output: User downloadable PDF and PPT files.

[0905] Through the above process, users can automatically generate 100 different patterns of materials simply by entering text, and use them in a variety of styles.

[0906] (Application example 1)

[0907] 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."

[0908] In modern brick-and-mortar stores, effective product promotion and advertising is extremely important, but creating such promotions and advertising takes time and effort. Furthermore, there are limited means to quickly generate and display advertisements and materials with consistent design. This problem needs to be resolved, enabling store staff to easily and quickly generate attractive advertising materials and use them in-store.

[0909] 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.

[0910] In this invention, the server includes input means for a user to input text, receiving means for receiving the text input by the input means, analysis means for analyzing the text received by the receiving means, generation means for generating a plurality of materials based on the text analyzed by the analysis means, setting means for setting a style for the materials generated by the generation means, automatic generation means for automatically generating a plurality of materials based on the style set by the setting means, conversion means for converting the plurality of materials generated by the automatic generation means into a file format, provision means for providing the materials converted by the conversion means to users, and display means for displaying the materials on an electronic advertising board in a store. This allows promotional materials to be generated easily and quickly in a physical store and used in the store.

[0911] An "input means" is a means by which a user inputs text.

[0912] The "receiving means" is a means for receiving the text input by the input means.

[0913] The "analysis means" is a means for analyzing the text received by the receiving means.

[0914] The "generation means" is a means for generating a plurality of materials based on the text analyzed by the analysis means.

[0915] The "setting means" is a means for setting the style of the material generated by the generating means.

[0916] The "automatic generation means" is a means for automatically generating a plurality of materials based on the style set by the setting means.

[0917] The "conversion means" is a means for converting the plurality of materials generated by the automatic generation means into a file format.

[0918] The "providing means" is a means for providing the user with the material converted by the converting means.

[0919] "Display means" refers to means for displaying materials on an electronic advertising bulletin board within a store.

[0920] The system embodying this invention is designed to support effective in-store promotions, and can quickly generate materials based on text entered by the user and display them on an electronic billboard.

[0921] The main components of the system include user terminals, cloud servers, and in-store electronic billboards. These elements communicate with each other and exchange information to operate.

[0922] First, a user inputs text using a dedicated application or web browser on a device. Specific text can be entered, such as "About the sales strategy for a new product." This input is performed from a user device such as smart glasses or a management terminal.

[0923] The device then sends the input text to a cloud server, which temporarily stores the received text in a database and then launches a generative AI model to analyze the text. The analysis method extracts key topics and keywords from the input text.

[0924] The user then uses the device's user interface to style the document, choosing from a variety of styles including casual, modern, and traditional. The selected style is then sent back to the cloud server, which passes the style parameters to the generative AI model.

[0925] The generative AI model automatically generates 100 different patterns of materials based on the set style. In this process, it adopts a variety of styles, including black, pop, and old-fashioned. The generated materials are diverse, allowing users to choose according to their needs.

[0926] The generated materials are converted into file formats such as PDF and PPT on a cloud server, and are then sent to the user's device and displayed on the store's electronic billboard.

[0927] A specific example is a sales promotion for a new 4K TV at a consumer electronics retailer. When a user uses the smart glasses to speak a prompt such as, "Show me the best features of this new 4K TV. It has a modern style," a document is instantly generated. This document is then displayed in real time on digital signage in the store, enhancing its appeal to customers.

[0928] This system utilizes a generative AI model to instantly generate materials in a variety of styles based on prompt text, thereby revolutionizing the efficiency of promotional activities in physical stores.

[0929] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0930] Step 1:

[0931] The user inputs text using a device (smart glasses or a management device) via a dedicated application or web browser. This input includes prompts such as "New product sale promotion." The input text is stored in the device's internal temporary memory.

[0932] Step 2:

[0933] The device sends the entered text to the cloud server. This is done using an HTTP request, and the text data is passed to the server. The entered text is temporarily stored in a database on the server side.

[0934] Step 3:

[0935] The server analyzes the received text using its analysis tools. Specifically, it uses a natural language processing model (e.g., BERT or GPT) to extract key topics and keywords. As an output, a dataset of the analysis results is generated.

[0936] Step 4:

[0937] The user uses the device's user interface to set the style of the document, for example, by selecting from casual, modern, traditional, etc. The selected style information is stored in the device's internal temporary memory.

[0938] Step 5:

[0939] The device sends the user's selected style settings to the server using an HTTP request, and the style setting data is passed to the server. The entered style settings are temporarily stored in a database on the server side.

[0940] Step 6:

[0941] The server launches a generative AI model and automatically generates 100 patterns of materials based on the analyzed text data and style settings. Specifically, a generative AI model (such as DALL-E or GAN) is used to generate materials that conform to the specified style. The output is a dataset of diverse materials.

[0942] Step 7:

[0943] The server converts the generated materials into a file format using an appropriate library (e.g., a PDF generation library or a PPT generation library) and stores the converted files in temporary memory within the server.

[0944] Step 8:

[0945] The server sends the converted data to the store's electronic billboard. A dedicated API is used to send the data, and the data is displayed on the billboard.

[0946] Step 9:

[0947] The server sends the converted data to the user's device using an HTTP response, and the user receives a PDF or PPT file that can be downloaded and viewed on the device.

[0948] 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.

[0949] This invention combines a system that instantly generates 100 patterns of materials based on user input text with an emotion engine that recognizes the user's emotions. The emotion engine analyzes the user's emotional data and adjusts the style of the generated materials more appropriately.

[0950] Program processing overview

[0951] 1. The user inputs text into a dedicated application or web browser on the device. For example, the user can input text such as "About the sales strategy for a new product."

[0952] 2. The terminal sends the entered text data to the server, which temporarily stores the received text in a database.

[0953] 3. The server launches the generation AI to retrieve text data from the database, and the analysis method extracts the main topics and keywords from the text.

[0954] 4. The user uses the device interface to set the style of the document, for example, select a style such as black, POP, or old-fashioned.

[0955] 5. The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[0956] 6. The emotion engine analyzes the user's text input and interactions to extract emotion data. The emotion analyzer determines the user's emotional state (e.g., happy, sad, excited, calm).

[0957] 7. The server passes the emotion data obtained from the emotion engine to the generation AI. The generation AI automatically generates 100 different patterns of materials based on the style settings and emotion data. For example, if the user is excited, an energetic, visually stimulating style will be selected based on the emotion data.

[0958] 8. The server converts the generated materials into a file format (PDF, PPT, etc.) that can be easily used by users.

[0959] 9. The server sends the converted file to the user's device, where a list of materials is displayed and the user can download the desired materials.

[0960] Specific examples

[0961] For example, if a user enters the text "Sales Strategy for a New Product" and selects a dark theme, the emotion engine analyzes the user's emotional state. If the user's emotion is determined to be "excited," the server passes the emotion data to the generation AI, which then generates energetic, visually stimulating materials in a dark theme.

[0962] For example, the following material is generated:

[0963] Pattern 1: A black slide with key keywords highlighted in red, reflecting the user's excitement.

[0964] Pattern 2: A dynamic design with visually striking graphs and charts placed on a dark background.

[0965] Pattern 3: Slides that make extensive use of visual effects that suit when the user is excited.

[0966] Users can select the desired material from a list displayed on their device, download it, and use it. This system greatly simplifies the process of creating materials, and quickly provides the most appropriate material based on the user's preferences.

[0967] The processing flow will be explained below.

[0968] Step 1:

[0969] The user opens a dedicated application or web browser on their device, enters the text of the document they want to create into the input form, and presses the submit button.

[0970] Step 2:

[0971] (Terminal) sends the entered text data to the server. The sent text is passed to the server as text data.

[0972] Step 3:

[0973] The server temporarily stores the received text data in a database, which is used for later analysis.

[0974] Step 4:

[0975] The (server) starts the generation AI and retrieves the received text from the database, which is then analyzed by the analysis means.

[0976] Step 5:

[0977] The server instructs the AI ​​to analyze the text, which extracts key topics and keywords from the text.

[0978] Step 6:

[0979] The user uses the terminal interface to set the style of the document, for example, selecting a style such as black taste, POP, or old-fashioned.

[0980] Step 7:

[0981] The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[0982] Step 8:

[0983] The emotion engine analyzes the user's text input and interactions to extract emotion data. The emotion analysis means determines the user's emotional state (e.g., happy, sad, excited, calm).

[0984] Step 9:

[0985] The server passes the emotion data obtained from the emotion engine to the generation AI, which then integrates the style settings and emotion data to adjust the parameters for generating materials.

[0986] Step 10:

[0987] The AI ​​automatically generates 100 different patterns of materials based on the set style and emotional data. For example, if the emotional data is "excited," an energetic and visually stimulating style will be selected.

[0988] Step 11:

[0989] The server converts the generated materials into a file format (PDF, PPT, etc.) and prepares them in a format that can be easily used by users.

[0990] Step 12:

[0991] The server sends the converted file to the user's terminal, where the list of materials is displayed.

[0992] Step 13:

[0993] The user selects the desired material from the list of materials displayed on the terminal and downloads it. The user then checks the downloaded material and modifies or uses it as necessary.

[0994] Example 2

[0995] 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."

[0996] Conventional document generation systems generate documents based on simple text input by the user, making it difficult to reflect the user's emotions and intentions. As a result, the generated documents may not match the user's expectations or emotions, which can lead to a poor user experience. In addition, the style settings of the generated documents are fixed, making it difficult to flexibly respond to individual user requests.

[0997] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: an input means for a user to input text; a receiving means for receiving the text input by the input means; an analysis means for analyzing the text received by the receiving means; a generation means for generating multiple materials based on the text analyzed by the analysis means; a setting means for setting a style of the materials generated by the generation means; an automatic generation means for automatically generating multiple materials based on the style set by the setting means; an emotion analysis means for analyzing a user's emotions; a style adjustment means for adjusting the style of the generated materials based on emotion data obtained by the emotion analysis means; a conversion means for converting the multiple materials generated by the automatic generation means into a file format; and a providing means for providing the materials converted by the conversion means to the user. This makes it possible to generate materials based on the user's emotions and intentions.

[0998] An "input means" is a device or software interface that allows a user to input text.

[0999] The "receiving means" is a system or function for receiving text sent from the input means.

[1000] An "analysis means" is a system or algorithm that analyzes received text and extracts key topics or keywords.

[1001] The "generation means" is a system or software for generating a plurality of materials based on the text analyzed by the analysis means.

[1002] The "setting means" is an interface or system for setting the style of the material generated by the generating means.

[1003] The "automatic generation means" is a system or algorithm for automatically generating multiple materials based on the style set by the setting means.

[1004] An "emotion analysis means" is a system or software that analyzes emotion data through user input text and user interaction with an interface.

[1005] The "style adjustment means" is a system or function for appropriately adjusting the style of the generated material based on the emotion data obtained by the emotion analysis means.

[1006] "Conversion means" refers to a system or software for converting multiple documents into a file format that is easy for users to use.

[1007] The "providing means" is a system or interface for providing the user with the material converted by the converting means.

[1008] The "display means" is a system or software that allows the providing means to display to the user a list of converted materials.

[1009] "Downloading means" means a system or interface that enables a user to download the converted material provided by the providing means.

[1010] This invention combines a system that instantly generates 100 patterns of materials based on user input text with an emotion engine that recognizes the user's emotions. The following describes in detail how to implement the program for this system.

[1011] First, a user uses a terminal to access a dedicated application or a web browser and input text. This input means allows the user to input text such as "Regarding sales strategies for new products." The input text data is sent from the terminal to a server, where it is received by the server's receiving means. The server temporarily stores the received text data in a database.

[1012] Within the server, the analysis tool retrieves text data from the database and uses a generative AI model (such as OpenAI's GPT-3) to analyze the text for key topics and keywords. After the analysis is complete, users can use the device interface to style the material, choosing from styles such as black, pop, and old-fashioned.

[1013] The device sends the user's selected style settings to the server, which then passes the style settings parameters to the generation AI. At the same time, a sentiment analysis tool analyzes the user's text input and interface interactions to extract emotional data. For example, it can use emotion engines such as Microsoft's Azure Cognitive Services or IBM Watson.

[1014] The emotion data acquired by the emotion analysis means is passed from the server to the generation AI. The generation AI automatically generates 100 different patterns of materials based on the user's emotion data and style settings. For example, if the user is determined to be "excited," an energetic and visually stimulating style is selected.

[1015] The generated documents are converted into a file format (e.g. PDF, PPT, etc.) by the server. This involves converting the documents into PDF format using Python's reportlab library, etc. The server then sends the converted files to the user's device via a delivery method. A list of documents is displayed on the device, and the user can download the documents they want.

[1016] As a concrete example, let's consider the case where a user inputs the text "Sales Strategy for a New Product," selects a black-and-white document style, and the emotion engine determines the user's emotion as "excited." In this case, the following document will be generated:

[1017] 1. Pattern 1: A black slide with key keywords highlighted in red, reflecting the user's excitement.

[1018] 2. Pattern 2: Visually striking graphs and charts are placed on a dark background, creating a dynamic design.

[1019] 3. Pattern 3: Slides that make extensive use of visual effects that suit the user's excited state.

[1020] Users can select the desired material from a list of materials displayed on their device, download it, and use it, which greatly simplifies the material creation process and quickly provides materials that are optimized to the user's emotions.

[1021] Example prompt sentence:

[1022] User: Enter the text "Sales strategy for new products"

[1023] System: "Please select the style of your materials. You can choose from black, pop, old-fashioned, etc."

[1024] User: Select "Black taste"

[1025] System: Analyzing user's emotional state...

[1026] System: Determined as "excited"

[1027] System: Generates 100 different patterns of materials.

[1028] System: Generation is complete. Please download the desired materials from the list below.

[1029] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1030] Step 1:

[1031] A user accesses a dedicated application or web browser on a terminal and inputs text such as "Sales strategy for a new product" into a text input field. Text data is acquired by an input means. The input is based on the user's intention, and the output is text data. Specific operations include the user inputting text using a keyboard.

[1032] Step 2:

[1033] The terminal transmits input text data to the server. The text data is encoded through a transmission means and transmitted to the server as a POST request. The input is the text data entered by the user, and the output is the text data transmitted to the server. Specific operations include the terminal transmitting data via an Internet connection.

[1034] Step 3:

[1035] The server analyzes the received text data using the analysis means and stores it in the database. The server receives the data using the reception means and extracts the main topics and keywords of the text using the analysis means. The data is reshaped and the format is optimized. The input is the text data received by the server, and the output is the analysis results and storage in the database. The specific operation is to perform an INSERT operation in the database.

[1036] Step 4:

[1037] The user styles the document through the terminal interface. For example, the user selects from options such as black, pop, and old-fashioned. The input is the user's style selection, and the output is the transmission of the style selection data to the server. Specific operations include the user selecting a style from a drop-down menu or radio buttons.

[1038] Step 5:

[1039] The terminal transmits style setting data to the server. This data is transmitted to the server as a POST request via the transmission means. The input is the style setting data selected by the user, and the output is the transmission of the style data to the server. Specific operations include an operation in which the terminal transmits the style data to the server via an HTTP request.

[1040] Step 6:

[1041] The server starts the emotion analysis means and analyzes the user's input text and interaction data to extract emotional data. The emotion analysis means determines the user's emotion as "happiness," "sadness," "excitement," etc. The input is text data and interaction data, and the output is the user's emotional data. Specifically, the server passes the data to an emotion analysis engine (e.g., Microsoft's Azure Cognitive Services) for analysis.

[1042] Step 7:

[1043] The server passes emotion data and style settings to a generative AI model, which then automatically generates 100 different patterns of materials based on this. The generative AI model (e.g., OpenAI's GPT-3) receives the emotion data and style settings as prompts and generates materials. The input is emotion data and style settings, and the output is 100 patterns of materials. Specific operations include the server sending prompt sentences to the generative AI model and receiving the generated results.

[1044] Step 8:

[1045] The server converts the generated document into a file format, for example, PDF format using the Python reportlab library. The input is the generated document, and the output is the document in the converted file format. Specific operations include the server calling a conversion means to convert the document into PDF or PPT format.

[1046] Step 9:

[1047] The server sends the converted file to the user's terminal. Using the provision means, a list of materials is displayed on the terminal, allowing the user to download the materials they desire. The input is the materials in the converted file format, and the output is the list of materials displayed on the terminal. Specific operations include the server sending the materials in an HTTP response and displaying the list on the terminal.

[1048] (Application example 2)

[1049] 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."

[1050] Conventional document generation systems do not take the user's emotional state into account, which means that the generated materials are not optimized for the emotions of the target audience. This is particularly true in the advertising field, where the inability to generate advertising materials that match the emotions of the target audience reduces the effectiveness of advertising. Furthermore, typical document generation systems lack flexibility in style settings, making it difficult to meet the diverse needs of users. A system that solves these problems is needed.

[1051] 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.

[1052] In this invention, the server includes input means for a user to input text, receiving means for receiving the text input by the input means, analysis means for analyzing the text received by the receiving means, generation means for generating a plurality of materials based on the text analyzed by the analysis means, setting means for setting a style of the materials generated by the generation means, emotion recognition means for recognizing the emotional state of the user, emotion data receiving means for receiving emotion data extracted by the emotion recognition means, automatic generation means for automatically generating a plurality of materials based on the style set by the setting means and the emotion data, conversion means for converting the plurality of materials generated by the automatic generation means into a file format, and provision means for providing the materials converted by the conversion means to the user. This makes it possible to generate materials that take the emotional state of the user into consideration, and to provide optimal materials to a target audience, particularly in fields such as advertising.

[1053] An "input means" is a means by which a user inputs text.

[1054] The "receiving means" is a means for receiving the text input by the input means.

[1055] "Analysis means" is a means for analyzing received text.

[1056] The "generation means" is a means for generating a plurality of materials based on the analyzed text.

[1057] The "setting means" is a means for setting the style of the generated document.

[1058] "Emotion recognition means" is a means for recognizing the emotional state of a user.

[1059] The "emotion data receiving means" is a means for receiving the emotion data extracted by the emotion recognition means.

[1060] The "automatic generation means" is a means for automatically generating a plurality of materials based on the set style and emotion data.

[1061] The "conversion means" is a means for converting multiple automatically generated materials into a file format.

[1062] The "means for providing" is a means for providing the converted material to the user.

[1063] The present invention is described in detail below with reference to an embodiment thereof. The system of the present invention comprises an input means for a user to input text, a receiving means, an analyzing means, a generating means, a setting means, an emotion recognition means, an emotion data receiving means, an automatic generating means, a converting means, and a providing means.

[1064] Program processing overview

[1065] The server provides a dedicated application or web browser for the user to input text. When the user inputs text, the input means receives the text and sends it to the server via the receiving means. The server temporarily stores the received text in a database. Next, the server uses the analyzing means to analyze the received text and extract major topics and keywords.

[1066] The user can set the style of the document using the interface of the terminal, for example, he can select a style such as black taste, pop, old style, etc. The setting means transmits the user's selected style setting to the server, and the server uses the emotion recognition means to analyze the user's text input and interaction.

[1067] The emotion data obtained by the emotion recognition means is passed to the server via the emotion data receiving means. The server passes the emotion data to the generation AI, which then automatically generates multiple materials based on the style settings and emotion data. The generation AI model uses OpenAI GPT-4, and its prompt sentences include the emotion data and style settings.

[1068] The generated materials are converted into a file format such as PDF or PPT by a conversion means. Finally, the converted files are sent to the user's terminal via a provision means, and the user can download the desired materials. An example of a prompt sentence is "User's emotional data: excitement. Style setting: pop style. Generate an advertisement based on the following topic: "New product campaign advertisement."

[1069] Hardware and software used

[1070] The server is hosted on Google Cloud Platform or AWS, the database is MySQL, IBM Watson or Microsoft Azure Emotion API is used for emotion recognition, OpenAI GPT-4 is used for generative AI modeling, and PDFlib is used for document conversion.

[1071] Specific examples

[1072] For example, if a user inputs the text "Sales Strategy for a New Product" and selects a dark theme, the emotion recognition means will analyze the user's emotional state. If the emotional data is determined to be "excited," the server will pass the emotional data to the generation AI, which will then generate energetic, visually stimulating, dark-themed materials. Specifically, this process will generate the following materials:

[1073] Pattern 1: A black slide with key keywords highlighted in red, reflecting the user's excitement.

[1074] Pattern 2: A dynamic design with visually striking graphs and charts placed on a dark background.

[1075] Pattern 3: Slides that make extensive use of visual effects that suit when the user is excited.

[1076] This allows users to select the desired material from a list of materials displayed on their device, and then download and use it. This system greatly simplifies the process of creating materials, and quickly provides the most appropriate material to suit the user's needs.

[1077] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1078] Step 1:

[1079] The user inputs text through a dedicated application or a web browser.

[1080] Input: Text data entered by the user (e.g., "Regarding sales strategies for new products").

[1081] Specific actions: The user enters text into the text box and presses the send button.

[1082] Step 2:

[1083] The terminal transmits the input text data to the server.

[1084] Input: Text data entered by the user.

[1085] Output: The text data received by the server.

[1086] Specific operation: The terminal application generates an HTTP request and sends text data to the server.

[1087] Step 3:

[1088] The server temporarily stores the received text in a database.

[1089] Input: Received text data.

[1090] Output: Text data stored in a database.

[1091] Specific operation: The SQL statement is executed on the server side and the text data is saved in the MySQL database.

[1092] Step 4:

[1093] The server uses an analysis means to analyze the text data and extract key topics and keywords.

[1094] Input: Text data stored in a database.

[1095] Output: Extracted main topics and keywords.

[1096] Specific operation: The server uses a natural language processing library (e.g., spaCy) to extract topics and keywords from the text data.

[1097] Step 5:

[1098] The user styles the document using the device interface.

[1099] Input: The style you choose (e.g., black taste, pop, old-fashioned, etc.).

[1100] Output: The selected style settings.

[1101] Specific action: The user selects a style from a drop-down menu or checkbox and presses the OK button.

[1102] Step 6:

[1103] The device sends the user's selected style settings to the server.

[1104] Input: The selected style setting.

[1105] Output: The style settings received by the server.

[1106] Specific operation: The application on the device generates an HTTP request and sends style setting data to the server.

[1107] Step 7:

[1108] The server uses emotion recognition means to analyze the user's text input and interactions and extract emotion data.

[1109] Input: Text data and user interaction data.

[1110] Output: Extracted emotion data.

[1111] Specific operation: The server uses an emotion recognition API (e.g., IBM Watson) to analyze the user's emotional state.

[1112] Step 8:

[1113] The server passes the emotion data to a generation AI, which automatically generates multiple materials based on the style settings and emotion data.

[1114] Input: emotion data and styling.

[1115] Output: The generated documents.

[1116] Specific operation: The server sends a prompt to the generative AI model (e.g., OpenAI GPT-4) to generate materials. Example prompt: "User emotion data: excitement. Style setting: pop style. Generate an advertisement based on the following topic: 'New product campaign advertisement'."

[1117] Step 9:

[1118] The server converts the automatically generated materials into a file format (PDF, PPT, etc.).

[1119] Input: Generated materials.

[1120] Output: The material converted into a file format.

[1121] Specific operation: The server uses PDFlib to convert the generated materials into PDF or PPT format.

[1122] Step 10:

[1123] The server provides the converted file to the user's terminal, allowing the user to download the desired material.

[1124] Input: The converted file.

[1125] Output: A file that users can download.

[1126] Specific operation: The server sends the file to the user's device through the Express server and provides a download link.

[1127] 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.

[1128] 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.

[1129] 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.

[1130] [Fourth embodiment]

[1131] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1132] 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.

[1133] 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).

[1134] 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.

[1135] 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.

[1136] 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).

[1137] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1138] 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.

[1139] 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.

[1140] 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.

[1141] 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.

[1142] 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.

[1143] 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."

[1144] This invention is a system that instantly generates 100 patterns of materials by allowing the user to input text. This system includes the processes of text analysis, automatic material generation, style setting, file format conversion, and provision to the user.

[1145] Program processing overview

[1146] 1. The user inputs text via a dedicated application or web browser on the device. For example, the user can input text such as "About the sales strategy for a new product."

[1147] 2. The terminal sends the entered text to the server, which temporarily stores the received text in a database.

[1148] 3. The server launches the generation AI to retrieve text from the database. This text is analyzed by the analysis means, which extracts the main topics and keywords from the text.

[1149] 4. The user can use the device interface to set the style of the document, for example, black taste, POP, old style, etc.

[1150] 5. The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[1151] 6. The AI ​​automatically generates 100 different patterns of materials using text based on the set style. For the black theme, a simple design based on black is used. For the pop style, a colorful color scheme is used, and for the old-fashioned style, a traditional format is used. The generated materials are diverse, allowing users to choose according to their needs.

[1152] 7. The server converts the generated materials into a file format, such as PDF or PPT, making them easily accessible to users.

[1153] 8. The server sends the converted file to the user's device, where the user can check the list of provided materials and download the materials they need.

[1154] Specific examples

[1155] For example, if a user enters the text "Sales Strategy for a New Product" and selects the black theme, the server will instantly generate 100 different versions of the document. Specifically, the following documents will be generated:

[1156] Pattern 1: A black slide with key keywords highlighted in red.

[1157] Pattern 2: A slide with a dark background and bulleted main points in white text.

[1158] Pattern 3: Slides that make extensive use of graphs and charts and are visually easy to understand.

[1159] Users can select these patterns from the list of materials displayed on their terminal and download and use the materials they want.

[1160] This system greatly simplifies the process of creating documents and improves work efficiency for business people. In addition, AI-based automatic generation provides documents in a variety of styles, allowing users to select the most suitable document for their purpose.

[1161] The processing flow will be explained below.

[1162] Step 1:

[1163] The user opens a dedicated application or web browser on their device, enters the text of the document they want to create into the input form, and presses the submit button.

[1164] Step 2:

[1165] (Terminal) sends the entered text to the server, which passes the text to the server as text data.

[1166] Step 3:

[1167] The server temporarily stores the received text data in a database, which is then used for analysis.

[1168] Step 4:

[1169] The (server) starts the generation AI and retrieves the received text from the database, which is then analyzed by the analysis means.

[1170] Step 5:

[1171] The server instructs the AI ​​to analyze the text, which extracts key topics and keywords from the text.

[1172] Step 6:

[1173] The user uses the terminal interface to set the style of the document, for example, selecting a style such as black taste, POP, or old-fashioned.

[1174] Step 7:

[1175] The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[1176] Step 8:

[1177] The server instructs the AI ​​to automatically generate materials that reflect the set style. The AI ​​then automatically generates 100 different patterns of materials using text based on the set style.

[1178] Step 9:

[1179] The server converts the generated materials into a file format (PDF, PPT, etc.) and the conversion means prepares the materials in a format that can be used by the user.

[1180] Step 10:

[1181] The server sends the converted file to the user's terminal, and the document list is displayed on the terminal by the providing means.

[1182] Step 11:

[1183] The user selects the desired material from the list of materials displayed on the terminal and downloads it. The user then checks the downloaded material and modifies or uses it as necessary.

[1184] In this way, a system is realized that allows users to quickly obtain materials in a variety of styles through specific operations at each step.

[1185] Example 1

[1186] 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."

[1187] Conventional document creation systems have the problem that it takes a lot of time and effort for users to manually create a large number of documents. Furthermore, it is difficult to provide documents with the same content in various styles, making it impossible to quickly provide documents that meet specific needs. Therefore, there is a need for a system that can automatically generate documents in a variety of styles and is easy to use, while improving user efficiency.

[1188] 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.

[1189] In this invention, the server includes input means for a user to input text, transmission means for transmitting the text input by the input means from the terminal to the server, storage means for the server to store the text received by the transmission means in a database, analysis means for analyzing the text stored by the storage means, generation means for generating a plurality of materials based on main topics and keywords extracted by the analysis means, style setting means for the user to set a style for the materials, automatic generation means for the server to automatically generate a plurality of materials based on style parameters set by the style setting means, conversion means for converting the plurality of materials generated by the automatic generation means into a file format such as PDF or PPT, and provision means for the server to transmit the materials converted by the conversion means to the terminal. This allows users to easily automatically generate materials in a variety of styles and quickly use them.

[1190] An "input means" is a function or device that allows a user to input text.

[1191] "Transmission means" refers to a function or device for transmitting input text from a terminal to a server.

[1192] The "storage means" is a function or device for temporarily storing the text received by the server in a database.

[1193] "Analysis means" refers to a function or device for analyzing the stored text and extracting key topics and keywords.

[1194] The "generation means" is a function or device for generating a plurality of materials based on the information extracted by the analysis means.

[1195] "Style setting means" refers to a function or device that allows a user to select and set the style of a document.

[1196] The "automatic generation means" is a function or device for automatically generating materials based on set style parameters.

[1197] "Conversion means" refers to a function or device for converting the generated materials into a file format such as PDF or PPT.

[1198] The "provision means" is a function or device for transmitting the converted material to the user's terminal and making it available for use.

[1199] "Display means" refers to a function or device for displaying a list of converted materials.

[1200] The "downloading means" is a function or device that allows a user to download converted materials to a terminal.

[1201] MODE FOR CARRYING OUT THE INVENTION

[1202] This invention is a system that instantly generates 100 patterns of materials by inputting text from the user. This system can be used through a dedicated application or a web browser and consists of the following main processing steps:

[1203] Hardware and Software

[1204] 1. Input method:

[1205] The user uses a device such as a PC or smartphone to input text into a dedicated application or web browser. For example, the user might input text such as "Sales strategy for a new product."

[1206] 2. Means of transmission:

[1207] The device sends the entered text to the server using the HTTPS protocol, and this communication is done through a secure REST API.

[1208] 3. Preservation means:

[1209] The server temporarily stores the received text in a database (e.g., MySQL or PostgreSQL).

[1210] 4. Analysis method:

[1211] The server runs a generative AI model (e.g., OpenAI GPT-3) and retrieves the stored text from the database. This text is then analyzed by the generative AI to extract key topics and keywords.

[1212] 5. Styling tools:

[1213] Users can style their documents using a browser or application interface, choosing from style options such as "black," "POP," and "old-fashioned."

[1214] 6. Automatic generation means:

[1215] The server passes the style parameters set by the style setting means to the generation AI, which automatically generates 100 different patterns of materials based on these. In the case of a black taste, a design based on black is used.

[1216] 7. Conversion Method:

[1217] The server converts the generated documents into file formats such as PDF and PPT using libraries such as PDFKit and python-pptx.

[1218] 8. Means of provision:

[1219] The server sends the converted files to the user's device, where the user can view the list of generated files in the application or browser and download the desired files.

[1220] Specific examples

[1221] For example, if a user enters the text "Sales Strategy for a New Product" and selects the black theme, the server will instantly generate 100 different versions of the document. Specifically, the following documents will be generated:

[1222] Pattern 1: A black slide with key keywords highlighted in red.

[1223] Pattern 2: A slide with a dark background and bulleted main points in white text.

[1224] Pattern 3: Slides that make extensive use of graphs and charts and are visually easy to understand.

[1225] Prompt Sentence Example

[1226] "Generate 100 different materials using a black theme for a new product sales strategy."

[1227] This system greatly simplifies the process of creating documents and improves work efficiency for business people. In addition, the system automatically generates documents in a variety of styles using AI, allowing users to select the document that best suits their needs.

[1228] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1229] Step 1:

[1230] The user enters text

[1231] Input: A user uses a device (PC or smartphone) to enter text such as "About the sales strategy for a new product" into a dedicated application or web browser.

[1232] Specific behavior: The user enters text into the text input field and clicks the "Submit" button.

[1233] Output: The user's input text is stored in the device's memory and is ready to be sent to the next step.

[1234] Step 2:

[1235] The device sends the entered text to the server

[1236] Input: The text data entered in step 1.

[1237] Specific operation: The device uses the HTTPS protocol to call a REST API endpoint and send text data to the server.

[1238] Output: Text data is sent to the server.

[1239] Step 3:

[1240] The server receives the text and stores it in a database

[1241] Input: The text data sent to the server in step 2.

[1242] Specific operation: The server temporarily stores the received text in a database (MySQL, PostgreSQL, etc.).

[1243] Output: The text data is stored in a database and made available for analysis.

[1244] Step 4:

[1245] The server runs a generative AI and analyzes the text.

[1246] Input: Text data stored in a database.

[1247] How it works: The server launches a generative AI model (such as OpenAI GPT-3) to analyze the stored text data. The generative AI uses natural language processing techniques to extract key topics and keywords.

[1248] Output: The main topics and keywords are extracted as a result of the analysis.

[1249] Step 5:

[1250] User-defined style settings for materials

[1251] Input: Style options selected by the user, such as "Black Taste", "POP", "Old Style", etc.

[1252] What happens: The user selects a style option using the device interface. The browser or application remembers the selection.

[1253] Output: The user's style settings are saved on the device and ready to be sent to the server.

[1254] Step 6:

[1255] The device sends the selected style to the server.

[1256] Input: User selected styling data.

[1257] What happens: The device sends styling data to the server using the HTTPS protocol.

[1258] Output: The styling data is sent to the server.

[1259] Step 7:

[1260] The server automatically generates materials

[1261] Input: Styling data and parsed text data.

[1262] How it works: The server passes style parameters and text data to the AI, which then automatically generates 100 different patterns of materials based on these. For example, if the theme is black, a black-based design will be used.

[1263] Output: 100 patterns of generated data.

[1264] Step 8:

[1265] The server converts the file format

[1266] Input: Generated material data.

[1267] Specific operation: The server uses libraries such as PDFKit or python-pptx to convert to file formats such as PDF or PPT.

[1268] Output: PDF and PPT files.

[1269] Step 9:

[1270] The server sends the file to the user's device.

[1271] Input: PDF or PPT file created in step 8.

[1272] Specific operation: The server sends the file to the user's device using the HTTPS protocol. The device saves the received file and notifies the user.

[1273] Output: User downloadable PDF and PPT files.

[1274] Through the above process, users can automatically generate 100 different patterns of materials simply by entering text, and use them in a variety of styles.

[1275] (Application example 1)

[1276] 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."

[1277] In modern brick-and-mortar stores, effective product promotion and advertising is extremely important, but creating such promotions and advertising takes time and effort. Furthermore, there are limited means to quickly generate and display advertisements and materials with consistent design. This problem needs to be resolved, enabling store staff to easily and quickly generate attractive advertising materials and use them in-store.

[1278] 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.

[1279] In this invention, the server includes input means for a user to input text, receiving means for receiving the text input by the input means, analysis means for analyzing the text received by the receiving means, generation means for generating a plurality of materials based on the text analyzed by the analysis means, setting means for setting a style for the materials generated by the generation means, automatic generation means for automatically generating a plurality of materials based on the style set by the setting means, conversion means for converting the plurality of materials generated by the automatic generation means into a file format, provision means for providing the materials converted by the conversion means to users, and display means for displaying the materials on an electronic advertising board in a store. This allows promotional materials to be generated easily and quickly in a physical store and used in the store.

[1280] An "input means" is a means by which a user inputs text.

[1281] The "receiving means" is a means for receiving the text input by the input means.

[1282] The "analysis means" is a means for analyzing the text received by the receiving means.

[1283] The "generation means" is a means for generating a plurality of materials based on the text analyzed by the analysis means.

[1284] The "setting means" is a means for setting the style of the material generated by the generating means.

[1285] The "automatic generation means" is a means for automatically generating a plurality of materials based on the style set by the setting means.

[1286] The "conversion means" is a means for converting the plurality of materials generated by the automatic generation means into a file format.

[1287] The "providing means" is a means for providing the user with the material converted by the converting means.

[1288] "Display means" refers to means for displaying materials on an electronic advertising bulletin board within a store.

[1289] The system embodying this invention is designed to support effective in-store promotions, and can quickly generate materials based on text entered by the user and display them on an electronic billboard.

[1290] The main components of the system include user terminals, cloud servers, and in-store electronic billboards. These elements communicate with each other and exchange information to operate.

[1291] First, a user inputs text using a dedicated application or web browser on a device. Specific text can be entered, such as "About the sales strategy for a new product." This input is performed from a user device such as smart glasses or a management terminal.

[1292] The device then sends the input text to a cloud server, which temporarily stores the received text in a database and then launches a generative AI model to analyze the text. The analysis method extracts key topics and keywords from the input text.

[1293] The user then uses the device's user interface to style the document, choosing from a variety of styles including casual, modern, and traditional. The selected style is then sent back to the cloud server, which passes the style parameters to the generative AI model.

[1294] The generative AI model automatically generates 100 different patterns of materials based on the set style. In this process, it adopts a variety of styles, including black, pop, and old-fashioned. The generated materials are diverse, allowing users to choose according to their needs.

[1295] The generated materials are converted into file formats such as PDF and PPT on a cloud server, and are then sent to the user's device and displayed on the store's electronic billboard.

[1296] A specific example is a sales promotion for a new 4K TV at a consumer electronics retailer. When a user uses the smart glasses to speak a prompt such as, "Show me the best features of this new 4K TV. It has a modern style," a document is instantly generated. This document is then displayed in real time on digital signage in the store, enhancing its appeal to customers.

[1297] This system utilizes a generative AI model to instantly generate materials in a variety of styles based on prompt text, thereby revolutionizing the efficiency of promotional activities in physical stores.

[1298] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1299] Step 1:

[1300] The user inputs text using a device (smart glasses or a management device) via a dedicated application or web browser. This input includes prompts such as "New product sale promotion." The input text is stored in the device's internal temporary memory.

[1301] Step 2:

[1302] The device sends the entered text to the cloud server. This is done using an HTTP request, and the text data is passed to the server. The entered text is temporarily stored in a database on the server side.

[1303] Step 3:

[1304] The server analyzes the received text using its analysis tools. Specifically, it uses a natural language processing model (e.g., BERT or GPT) to extract key topics and keywords. As an output, a dataset of the analysis results is generated.

[1305] Step 4:

[1306] The user uses the device's user interface to set the style of the document, for example, by selecting from casual, modern, traditional, etc. The selected style information is stored in the device's internal temporary memory.

[1307] Step 5:

[1308] The device sends the user's selected style settings to the server using an HTTP request, and the style setting data is passed to the server. The entered style settings are temporarily stored in a database on the server side.

[1309] Step 6:

[1310] The server launches a generative AI model and automatically generates 100 patterns of materials based on the analyzed text data and style settings. Specifically, a generative AI model (such as DALL-E or GAN) is used to generate materials that conform to the specified style. The output is a dataset of diverse materials.

[1311] Step 7:

[1312] The server converts the generated materials into a file format using an appropriate library (e.g., a PDF generation library or a PPT generation library) and stores the converted files in temporary memory within the server.

[1313] Step 8:

[1314] The server sends the converted data to the store's electronic billboard. A dedicated API is used to send the data, and the data is displayed on the billboard.

[1315] Step 9:

[1316] The server sends the converted data to the user's device using an HTTP response, and the user receives a PDF or PPT file that can be downloaded and viewed on the device.

[1317] 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.

[1318] This invention combines a system that instantly generates 100 patterns of materials based on user input text with an emotion engine that recognizes the user's emotions. The emotion engine analyzes the user's emotional data and adjusts the style of the generated materials more appropriately.

[1319] Program processing overview

[1320] 1. The user inputs text into a dedicated application or web browser on the device. For example, the user can input text such as "About the sales strategy for a new product."

[1321] 2. The terminal sends the entered text data to the server, which temporarily stores the received text in a database.

[1322] 3. The server launches the generation AI to retrieve text data from the database, and the analysis method extracts the main topics and keywords from the text.

[1323] 4. The user uses the device interface to set the style of the document, for example, select a style such as black, POP, or old-fashioned.

[1324] 5. The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[1325] 6. The emotion engine analyzes the user's text input and interactions to extract emotion data. The emotion analyzer determines the user's emotional state (e.g., happy, sad, excited, calm).

[1326] 7. The server passes the emotion data obtained from the emotion engine to the generation AI. The generation AI automatically generates 100 different patterns of materials based on the style settings and emotion data. For example, if the user is excited, an energetic, visually stimulating style will be selected based on the emotion data.

[1327] 8. The server converts the generated materials into a file format (PDF, PPT, etc.) that can be easily used by users.

[1328] 9. The server sends the converted file to the user's device, where a list of materials is displayed and the user can download the desired materials.

[1329] Specific examples

[1330] For example, if a user enters the text "Sales Strategy for a New Product" and selects a dark theme, the emotion engine analyzes the user's emotional state. If the user's emotion is determined to be "excited," the server passes the emotion data to the generation AI, which then generates energetic, visually stimulating materials in a dark theme.

[1331] For example, the following material is generated:

[1332] Pattern 1: A black slide with key keywords highlighted in red, reflecting the user's excitement.

[1333] Pattern 2: A dynamic design with visually striking graphs and charts placed on a dark background.

[1334] Pattern 3: Slides that make extensive use of visual effects that suit when the user is excited.

[1335] Users can select the desired material from a list displayed on their device, download it, and use it. This system greatly simplifies the process of creating materials, and quickly provides the most appropriate material based on the user's preferences.

[1336] The processing flow will be explained below.

[1337] Step 1:

[1338] The user opens a dedicated application or web browser on their device, enters the text of the document they want to create into the input form, and presses the submit button.

[1339] Step 2:

[1340] (Terminal) sends the entered text data to the server. The sent text is passed to the server as text data.

[1341] Step 3:

[1342] The server temporarily stores the received text data in a database, which is used for later analysis.

[1343] Step 4:

[1344] The (server) starts the generation AI and retrieves the received text from the database, which is then analyzed by the analysis means.

[1345] Step 5:

[1346] The server instructs the AI ​​to analyze the text, which extracts key topics and keywords from the text.

[1347] Step 6:

[1348] The user uses the terminal interface to set the style of the document, for example, selecting a style such as black taste, POP, or old-fashioned.

[1349] Step 7:

[1350] The device sends the user's selected style settings to the server, which receives them and passes the style setting parameters to the generation AI.

[1351] Step 8:

[1352] The emotion engine analyzes the user's text input and interactions to extract emotion data. The emotion analysis means determines the user's emotional state (e.g., happy, sad, excited, calm).

[1353] Step 9:

[1354] The server passes the emotion data obtained from the emotion engine to the generation AI, which then integrates the style settings and emotion data to adjust the parameters for generating materials.

[1355] Step 10:

[1356] The AI ​​automatically generates 100 different patterns of materials based on the set style and emotional data. For example, if the emotional data is "excited," an energetic and visually stimulating style will be selected.

[1357] Step 11:

[1358] The server converts the generated materials into a file format (PDF, PPT, etc.) and prepares them in a format that can be easily used by users.

[1359] Step 12:

[1360] The server sends the converted file to the user's terminal, where the list of materials is displayed.

[1361] Step 13:

[1362] The user selects the desired material from the list of materials displayed on the terminal and downloads it. The user then checks the downloaded material and modifies or uses it as necessary.

[1363] Example 2

[1364] 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."

[1365] Conventional document generation systems generate documents based on simple text input by the user, making it difficult to reflect the user's emotions and intentions. As a result, the generated documents may not match the user's expectations or emotions, which can lead to a poor user experience. In addition, the style settings of the generated documents are fixed, making it difficult to flexibly respond to individual user requests.

[1366] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: an input means for a user to input text; a receiving means for receiving the text input by the input means; an analysis means for analyzing the text received by the receiving means; a generation means for generating multiple materials based on the text analyzed by the analysis means; a setting means for setting a style of the materials generated by the generation means; an automatic generation means for automatically generating multiple materials based on the style set by the setting means; an emotion analysis means for analyzing a user's emotions; a style adjustment means for adjusting the style of the generated materials based on emotion data obtained by the emotion analysis means; a conversion means for converting the multiple materials generated by the automatic generation means into a file format; and a providing means for providing the materials converted by the conversion means to the user. This makes it possible to generate materials based on the user's emotions and intentions.

[1367] An "input means" is a device or software interface that allows a user to input text.

[1368] The "receiving means" is a system or function for receiving text sent from the input means.

[1369] An "analysis means" is a system or algorithm that analyzes received text and extracts key topics or keywords.

[1370] The "generation means" is a system or software for generating a plurality of materials based on the text analyzed by the analysis means.

[1371] The "setting means" is an interface or system for setting the style of the material generated by the generating means.

[1372] The "automatic generation means" is a system or algorithm for automatically generating multiple materials based on the style set by the setting means.

[1373] An "emotion analysis means" is a system or software that analyzes emotion data through user input text and user interaction with an interface.

[1374] The "style adjustment means" is a system or function for appropriately adjusting the style of the generated material based on the emotion data obtained by the emotion analysis means.

[1375] "Conversion means" refers to a system or software for converting multiple documents into a file format that is easy for users to use.

[1376] The "providing means" is a system or interface for providing the user with the material converted by the converting means.

[1377] The "display means" is a system or software that allows the providing means to display to the user a list of converted materials.

[1378] "Downloading means" means a system or interface that enables a user to download the converted material provided by the providing means.

[1379] This invention combines a system that instantly generates 100 patterns of materials based on user input text with an emotion engine that recognizes the user's emotions. The following describes in detail how to implement the program for this system.

[1380] First, a user uses a terminal to access a dedicated application or a web browser and input text. This input means allows the user to input text such as "Regarding sales strategies for new products." The input text data is sent from the terminal to a server, where it is received by the server's receiving means. The server temporarily stores the received text data in a database.

[1381] Within the server, the analysis tool retrieves text data from the database and uses a generative AI model (such as OpenAI's GPT-3) to analyze the text for key topics and keywords. After the analysis is complete, users can use the device interface to style the material, choosing from styles such as black, pop, and old-fashioned.

[1382] The device sends the user's selected style settings to the server, which then passes the style settings parameters to the generation AI. At the same time, a sentiment analysis tool analyzes the user's text input and interface interactions to extract emotional data. For example, it can use emotion engines such as Microsoft's Azure Cognitive Services or IBM Watson.

[1383] The emotion data acquired by the emotion analysis means is passed from the server to the generation AI. The generation AI automatically generates 100 different patterns of materials based on the user's emotion data and style settings. For example, if the user is determined to be "excited," an energetic and visually stimulating style is selected.

[1384] The generated documents are converted into a file format (e.g. PDF, PPT, etc.) by the server. This involves converting the documents into PDF format using Python's reportlab library, etc. The server then sends the converted files to the user's device via a delivery method. A list of documents is displayed on the device, and the user can download the documents they want.

[1385] As a concrete example, let's consider the case where a user inputs the text "Sales Strategy for a New Product," selects a black-and-white document style, and the emotion engine determines the user's emotion as "excited." In this case, the following document will be generated:

[1386] 1. Pattern 1: A black slide with key keywords highlighted in red, reflecting the user's excitement.

[1387] 2. Pattern 2: Visually striking graphs and charts are placed on a dark background, creating a dynamic design.

[1388] 3. Pattern 3: Slides that make extensive use of visual effects that suit the user's excited state.

[1389] Users can select the desired material from a list of materials displayed on their device, download it, and use it, which greatly simplifies the material creation process and quickly provides materials that are optimized to the user's emotions.

[1390] Example prompt sentence:

[1391] User: Enter the text "Sales strategy for new products"

[1392] System: "Please select the style of your materials. You can choose from black, pop, old-fashioned, etc."

[1393] User: Select "Black taste"

[1394] System: Analyzing user's emotional state...

[1395] System: Determined as "excited"

[1396] System: Generates 100 different patterns of materials.

[1397] System: Generation is complete. Please download the desired materials from the list below.

[1398] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1399] Step 1:

[1400] A user accesses a dedicated application or web browser on a terminal and inputs text such as "Sales strategy for a new product" into a text input field. Text data is acquired by an input means. The input is based on the user's intention, and the output is text data. Specific operations include the user inputting text using a keyboard.

[1401] Step 2:

[1402] The terminal transmits input text data to the server. The text data is encoded through a transmission means and transmitted to the server as a POST request. The input is the text data entered by the user, and the output is the text data transmitted to the server. Specific operations include the terminal transmitting data via an Internet connection.

[1403] Step 3:

[1404] The server analyzes the received text data using the analysis means and stores it in the database. The server receives the data using the reception means and extracts the main topics and keywords of the text using the analysis means. The data is reshaped and the format is optimized. The input is the text data received by the server, and the output is the analysis results and storage in the database. The specific operation is to perform an INSERT operation in the database.

[1405] Step 4:

[1406] The user styles the document through the terminal interface. For example, the user selects from options such as black, pop, and old-fashioned. The input is the user's style selection, and the output is the transmission of the style selection data to the server. Specific operations include the user selecting a style from a drop-down menu or radio buttons.

[1407] Step 5:

[1408] The terminal transmits style setting data to the server. This data is transmitted to the server as a POST request via the transmission means. The input is the style setting data selected by the user, and the output is the transmission of the style data to the server. Specific operations include an operation in which the terminal transmits the style data to the server via an HTTP request.

[1409] Step 6:

[1410] The server starts the emotion analysis means and analyzes the user's input text and interaction data to extract emotional data. The emotion analysis means determines the user's emotion as "happiness," "sadness," "excitement," etc. The input is text data and interaction data, and the output is the user's emotional data. Specifically, the server passes the data to an emotion analysis engine (e.g., Microsoft's Azure Cognitive Services) for analysis.

[1411] Step 7:

[1412] The server passes emotion data and style settings to a generative AI model, which then automatically generates 100 different patterns of materials based on this. The generative AI model (e.g., OpenAI's GPT-3) receives the emotion data and style settings as prompts and generates materials. The input is emotion data and style settings, and the output is 100 patterns of materials. Specific operations include the server sending prompt sentences to the generative AI model and receiving the generated results.

[1413] Step 8:

[1414] The server converts the generated document into a file format, for example, PDF format using the Python reportlab library. The input is the generated document, and the output is the document in the converted file format. Specific operations include the server calling a conversion means to convert the document into PDF or PPT format.

[1415] Step 9:

[1416] The server sends the converted file to the user's terminal. Using the provision means, a list of materials is displayed on the terminal, allowing the user to download the materials they desire. The input is the materials in the converted file format, and the output is the list of materials displayed on the terminal. Specific operations include the server sending the materials in an HTTP response and displaying the list on the terminal.

[1417] (Application example 2)

[1418] 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."

[1419] Conventional document generation systems do not take the user's emotional state into account, which means that the generated materials are not optimized for the emotions of the target audience. This is particularly true in the advertising field, where the inability to generate advertising materials that match the emotions of the target audience reduces the effectiveness of advertising. Furthermore, typical document generation systems lack flexibility in style settings, making it difficult to meet the diverse needs of users. A system that solves these problems is needed.

[1420] 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.

[1421] In this invention, the server includes input means for a user to input text, receiving means for receiving the text input by the input means, analysis means for analyzing the text received by the receiving means, generation means for generating a plurality of materials based on the text analyzed by the analysis means, setting means for setting a style of the materials generated by the generation means, emotion recognition means for recognizing the emotional state of the user, emotion data receiving means for receiving emotion data extracted by the emotion recognition means, automatic generation means for automatically generating a plurality of materials based on the style set by the setting means and the emotion data, conversion means for converting the plurality of materials generated by the automatic generation means into a file format, and provision means for providing the materials converted by the conversion means to the user. This makes it possible to generate materials that take the emotional state of the user into consideration, and to provide optimal materials to a target audience, particularly in fields such as advertising.

[1422] An "input means" is a means by which a user inputs text.

[1423] The "receiving means" is a means for receiving the text input by the input means.

[1424] "Analysis means" is a means for analyzing received text.

[1425] The "generation means" is a means for generating a plurality of materials based on the analyzed text.

[1426] The "setting means" is a means for setting the style of the generated document.

[1427] "Emotion recognition means" is a means for recognizing the emotional state of a user.

[1428] The "emotion data receiving means" is a means for receiving the emotion data extracted by the emotion recognition means.

[1429] The "automatic generation means" is a means for automatically generating a plurality of materials based on the set style and emotion data.

[1430] The "conversion means" is a means for converting multiple automatically generated materials into a file format.

[1431] The "means for providing" is a means for providing the converted material to the user.

[1432] The present invention is described in detail below with reference to an embodiment thereof. The system of the present invention comprises an input means for a user to input text, a receiving means, an analyzing means, a generating means, a setting means, an emotion recognition means, an emotion data receiving means, an automatic generating means, a converting means, and a providing means.

[1433] Program processing overview

[1434] The server provides a dedicated application or web browser for the user to input text. When the user inputs text, the input means receives the text and sends it to the server via the receiving means. The server temporarily stores the received text in a database. Next, the server uses the analyzing means to analyze the received text and extract major topics and keywords.

[1435] The user can set the style of the document using the interface of the terminal, for example, he can select a style such as black taste, pop, old style, etc. The setting means transmits the user's selected style setting to the server, and the server uses the emotion recognition means to analyze the user's text input and interaction.

[1436] The emotion data obtained by the emotion recognition means is passed to the server via the emotion data receiving means. The server passes the emotion data to the generation AI, which then automatically generates multiple materials based on the style settings and emotion data. The generation AI model uses OpenAI GPT-4, and its prompt sentences include the emotion data and style settings.

[1437] The generated materials are converted into a file format such as PDF or PPT by a conversion means. Finally, the converted files are sent to the user's terminal via a provision means, and the user can download the desired materials. An example of a prompt sentence is "User's emotional data: excitement. Style setting: pop style. Generate an advertisement based on the following topic: "New product campaign advertisement."

[1438] Hardware and software used

[1439] The server is hosted on Google Cloud Platform or AWS, the database is MySQL, IBM Watson or Microsoft Azure Emotion API is used for emotion recognition, OpenAI GPT-4 is used for generative AI modeling, and PDFlib is used for document conversion.

[1440] Specific examples

[1441] For example, if a user inputs the text "Sales Strategy for a New Product" and selects a dark theme, the emotion recognition means will analyze the user's emotional state. If the emotional data is determined to be "excited," the server will pass the emotional data to the generation AI, which will then generate energetic, visually stimulating, dark-themed materials. Specifically, this process will generate the following materials:

[1442] Pattern 1: A black slide with key keywords highlighted in red, reflecting the user's excitement.

[1443] Pattern 2: A dynamic design with visually striking graphs and charts placed on a dark background.

[1444] Pattern 3: Slides that make extensive use of visual effects that suit when the user is excited.

[1445] This allows users to select the desired material from a list of materials displayed on their device, and then download and use it. This system greatly simplifies the process of creating materials, and quickly provides the most appropriate material to suit the user's needs.

[1446] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1447] Step 1:

[1448] The user inputs text through a dedicated application or a web browser.

[1449] Input: Text data entered by the user (e.g., "Regarding sales strategies for new products").

[1450] Specific actions: The user enters text into the text box and presses the send button.

[1451] Step 2:

[1452] The terminal transmits the input text data to the server.

[1453] Input: Text data entered by the user.

[1454] Output: The text data received by the server.

[1455] Specific operation: The terminal application generates an HTTP request and sends text data to the server.

[1456] Step 3:

[1457] The server temporarily stores the received text in a database.

[1458] Input: Received text data.

[1459] Output: Text data stored in a database.

[1460] Specific operation: The SQL statement is executed on the server side and the text data is saved in the MySQL database.

[1461] Step 4:

[1462] The server uses an analysis means to analyze the text data and extract key topics and keywords.

[1463] Input: Text data stored in a database.

[1464] Output: Extracted main topics and keywords.

[1465] Specific operation: The server uses a natural language processing library (e.g., spaCy) to extract topics and keywords from the text data.

[1466] Step 5:

[1467] The user styles the document using the device interface.

[1468] Input: The style you choose (e.g., black taste, pop, old-fashioned, etc.).

[1469] Output: The selected style settings.

[1470] Specific action: The user selects a style from a drop-down menu or checkbox and presses the OK button.

[1471] Step 6:

[1472] The device sends the user's selected style settings to the server.

[1473] Input: The selected style setting.

[1474] Output: The style settings received by the server.

[1475] Specific operation: The application on the device generates an HTTP request and sends style setting data to the server.

[1476] Step 7:

[1477] The server uses emotion recognition means to analyze the user's text input and interactions and extract emotion data.

[1478] Input: Text data and user interaction data.

[1479] Output: Extracted emotion data.

[1480] Specific operation: The server uses an emotion recognition API (e.g., IBM Watson) to analyze the user's emotional state.

[1481] Step 8:

[1482] The server passes the emotion data to a generation AI, which automatically generates multiple materials based on the style settings and emotion data.

[1483] Input: emotion data and styling.

[1484] Output: The generated documents.

[1485] Specific operation: The server sends a prompt to the generative AI model (e.g., OpenAI GPT-4) to generate materials. Example prompt: "User emotion data: excitement. Style setting: pop style. Generate an advertisement based on the following topic: 'New product campaign advertisement'."

[1486] Step 9:

[1487] The server converts the automatically generated materials into a file format (PDF, PPT, etc.).

[1488] Input: Generated materials.

[1489] Output: The material converted into a file format.

[1490] Specific operation: The server uses PDFlib to convert the generated materials into PDF or PPT format.

[1491] Step 10:

[1492] The server provides the converted file to the user's terminal, allowing the user to download the desired material.

[1493] Input: The converted file.

[1494] Output: A file that users can download.

[1495] Specific operation: The server sends the file to the user's device through the Express server and provides a download link.

[1496] 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.

[1497] 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.

[1498] 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.

[1499] 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.

[1500] 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.

[1501] 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.

[1502] 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).

[1503] 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.

[1504] 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."

[1505] 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.

[1506] 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).

[1507] 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.

[1508] 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.

[1509] 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.

[1510] 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.

[1511] 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.

[1512] 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.

[1513] 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.

[1514] 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.

[1515] 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.

[1516] 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.

[1517] The following is further disclosed regarding the above embodiment.

[1518] (Claim 1)

[1519] an input means for a user to input text;

[1520] receiving means for receiving the text input by the input means;

[1521] analysis means for analyzing the text received by the receiving means;

[1522] a generation means for generating a plurality of materials based on the text analyzed by the analysis means;

[1523] a setting means for setting a style of the material generated by the generating means;

[1524] an automatic generation means for automatically generating a plurality of materials based on the style set by the setting means;

[1525] a conversion means for converting the plurality of materials generated by the automatic generation means into a file format;

[1526] providing means for providing the user with the material converted by the conversion means;

[1527] A system including:

[1528] (Claim 2)

[1529] 2. The system according to claim 1, wherein the providing means includes display means for displaying a list of materials converted by the converting means.

[1530] (Claim 3)

[1531] 2. The system according to claim 1, wherein the providing means includes downloading means for enabling a user to download the material converted by the converting means.

[1532] "Example 1"

[1533] (Claim 1)

[1534] an input means for a user to input text;

[1535] a transmitting means for transmitting the text input by the input means from the terminal to a server;

[1536] a storage means for storing the text received by the sending means in a database;

[1537] an analysis means for analyzing the text stored by the storage means;

[1538] a generating means for generating a plurality of materials based on the main topics and keywords extracted by the analyzing means;

[1539] a style setting means for allowing a user to style a document;

[1540] an automatic generation means for automatically generating a plurality of materials by the server based on the style parameters set by the style setting means;

[1541] A conversion means for converting the plurality of materials generated by the automatic generation means into a file format such as PDF or PPT;

[1542] providing means for the server to transmit the material converted by the conversion means to the terminal;

[1543] A system including:

[1544] (Claim 2)

[1545] 2. The system according to claim 1, wherein the providing means includes display means for displaying a list of materials converted by the converting means.

[1546] (Claim 3)

[1547] 2. The system according to claim 1, wherein the providing means includes downloading means for enabling a user to download the material converted by the converting means.

[1548] "Application Example 1"

[1549] (Claim 1)

[1550] an input means for a user to input text;

[1551] receiving means for receiving the text input by the input means;

[1552] analysis means for analyzing the text received by the receiving means;

[1553] a generation means for generating a plurality of materials based on the text analyzed by the analysis means;

[1554] a setting means for setting a style of the material generated by the generating means;

[1555] an automatic generation means for automatically generating a plurality of materials based on the style set by the setting means;

[1556] a conversion means for converting the plurality of materials generated by the automatic generation means into a file format;

[1557] providing means for providing the user with the material converted by the conversion means;

[1558] a display means for displaying the material on an electronic billboard in the store;

[1559] A system including:

[1560] (Claim 2)

[1561] 2. The system according to claim 1, wherein the providing means includes display means for displaying a list of materials converted by the converting means.

[1562] (Claim 3)

[1563] 2. The system according to claim 1, wherein the providing means includes downloading means for enabling a user to download the material converted by the converting means.

[1564] "Example 2: Combining Emotion Engines"

[1565] (Claim 1)

[1566] an input means for a user to input text;

[1567] receiving means for receiving the text input by the input means;

[1568] analysis means for analyzing the text received by the receiving means;

[1569] a generation means for generating a plurality of materials based on the text analyzed by the analysis means;

[1570] a setting means for setting a style of the material generated by the generating means;

[1571] an automatic generation means for automatically generating a plurality of materials based on the style set by the setting means;

[1572] emotion analysis means for analyzing the emotions of a user;

[1573] a style adjustment means for adjusting the style of the generated material based on the emotion data obtained by the emotion analysis means;

[1574] a conversion means for converting the plurality of materials generated by the automatic generation means into a file format;

[1575] providing means for providing the user with the material converted by the conversion means;

[1576] A system including:

[1577] (Claim 2)

[1578] 2. The system according to claim 1, wherein the providing means includes display means for displaying a list of materials converted by the converting means.

[1579] (Claim 3)

[1580] 2. The system according to claim 1, wherein the providing means includes downloading means for enabling a user to download the material converted by the converting means.

[1581] "Application example 2 when combining emotion engines"

[1582] (Claim 1)

[1583] an input means for a user to input text;

[1584] receiving means for receiving the text input by the input means;

[1585] analysis means for analyzing the text received by the receiving means;

[1586] a generation means for generating a plurality of materials based on the text analyzed by the analysis means;

[1587] a setting means for setting a style of the material generated by the generating means;

[1588] emotion recognition means for recognizing an emotional state of a user;

[1589] emotion data receiving means for receiving emotion data extracted by the emotion recognition means;

[1590] an automatic generation means for automatically generating a plurality of materials based on the style set by the setting means and the emotion data;

[1591] a conversion means for converting the plurality of materials generated by the automatic generation means into a file format;

[1592] providing means for providing the user with the material converted by the conversion means;

[1593] A system including:

[1594] (Claim 2)

[1595] 2. The system according to claim 1, wherein the providing means includes display means for displaying a list of materials converted by the converting means.

[1596] (Claim 3)

[1597] 2. The system according to claim 1, wherein the providing means includes downloading means for enabling a user to download the material converted by the converting means. [Explanation of symbols]

[1598] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. an input means for a user to input text; receiving means for receiving the text input by the input means; analysis means for analyzing the text received by the receiving means; a generation means for generating a plurality of materials based on the text analyzed by the analysis means; a setting means for setting a style of the material generated by the generating means; an automatic generation means for automatically generating a plurality of materials based on the style set by the setting means; a conversion means for converting the plurality of materials generated by the automatic generation means into a file format; providing means for providing the user with the material converted by the conversion means; A system including:

2. 2. The system according to claim 1, wherein said providing means includes display means for displaying a list of materials converted by said converting means.

3. 2. The system according to claim 1, wherein said providing means includes downloading means for enabling a user to download the material converted by said converting means.

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