System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving an input of an idea or content from a user; means for transmitting the input idea or content to a server; means for analyzing the input idea or content in the server and extracting key points; means for generating a presentation material based on the key points; means for transmitting the generated presentation material to a terminal of the user; and means for displaying the generated presentation material in the terminal.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] Creating traditional business presentation materials depends not only on the quality of the idea, but also heavily on how it is presented. As a result, even if many businesspeople have great ideas, they lack the ability to communicate them effectively, resulting in their value not being fully appreciated. Creating presentation materials also requires specialized design skills and market research knowledge, which is time-consuming and labor-intensive. Therefore, there is a need for a method that allows anyone to easily create effective presentation materials that are easy to understand. [Means for solving the problem]

[0005] The present invention provides a system including: means for accepting input of ideas and content from a user; means for transmitting the input ideas and content to a server; means for analyzing the input ideas and content and extracting key points in the server; means for generating presentation materials based on the key points; means for transmitting the generated presentation materials to a user's terminal; and means for displaying the generated presentation materials on the terminal. Furthermore, the presentation material generating means includes means for creating slides, diagrams, flow charts, and videos, and the key point extracting means includes means for analyzing the ideas and content using natural language processing technology. This enables users to quickly create effective and attractive presentation materials without specialized skills.

[0006] "User" refers to an individual or corporation that uses this system.

[0007] "Idea" refers to the concept or idea that the user wants to convey in the presentation.

[0008] "Content" refers to the topics or information that the user wants to specifically explain in the presentation.

[0009] "Means" refers to a mechanism for performing a specific function or operation of this system.

[0010] "Server" refers to a computer system that receives and processes data sent by users.

[0011] "Analysis" refers to the process of understanding input ideas and content and extracting important information.

[0012] "Key points" refer to the main themes or important elements of a presentation extracted from ideas or content.

[0013] "Presentation materials" refers to content such as slides, diagrams, flow charts, and videos that are used to visually and audibly convey a user's ideas and content.

[0014] A "slide" refers to a static page used to visually convey information in a presentation.

[0015] "Diagram" refers to illustrations, graphs, charts, etc. that visually represent information.

[0016] "Flow" refers to a diagram that visually represents a process or procedure.

[0017] "Video" refers to a medium that dynamically conveys information using visual and auditory senses.

[0018] "Natural language processing technology" refers to technology that enables computers to understand and process human language.

[0019] "Terminal" refers to a device through which a user accesses and operates the system.

[0020] "Display" refers to visually presenting the generated presentation materials to a user.

[0021] "Transmission" refers to the transfer of data or information from one place to another. [Brief explanation of the drawings]

[0022] [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

[0023] 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.

[0024] First, the terms used in the following description will be explained.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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."

[0030] [First embodiment]

[0031] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0032] 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.

[0033] 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).

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] 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."

[0043] The AI ​​system for automatically creating presentation materials according to the present invention consists of three main components: a user, a terminal, and a server. This system is a technology that converts a user's ideas and content into easy-to-understand, effective presentation materials.

[0044] System Overview

[0045] The system begins by a user entering the idea and content of a presentation using a device. The entered data is sent from the device to a server, which analyzes the data and extracts key points. Presentation materials such as slides, diagrams, flow charts, and videos are then generated based on the key points. The generated presentation materials are then sent to the device and displayed to the user.

[0046] Detailed system description

[0047] 1. User idea input

[0048] The user uses the device to input the ideas and content of the presentation. Input is in text format. For example, the user might input something like, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[0049] 2. Data transmission

[0050] The device sends the user's input data to the server using an HTTP request or a dedicated API. The server receives this data and proceeds to the next step.

[0051] 3. Server analysis and keypoint extraction

[0052] The server analyzes the received data using natural language processing technology. As a result of the analysis, important key points are extracted from the data. For example, from the above input, key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24" are extracted.

[0053] 4. Generate presentation materials

[0054] The server generates presentation materials based on the extracted key points. Specifically, the following elements are generated:

[0055] Slides: Includes a title slide, an overview of your marketing strategy, details of your target market, the campaign implementation process, and success stories.

[0056] Figures: Generate age distribution maps of your target market, social media usage statistics, and graphs showing campaign effectiveness.

[0057] Flow: A flow diagram is generated showing the steps to execute the campaign.

[0058] Video: A scenario for a promotional video for the campaign is generated and the actual video is created.

[0059] 5. Sending presentation materials

[0060] The generated presentation materials are sent from the server to the device, using HTTP responses and dedicated APIs.

[0061] 6. Displaying presentation materials

[0062] The terminal displays the received presentation materials to the user, who can then use the displayed materials to prepare and practice their presentation.

[0063] Specific examples

[0064] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[0065] 1. User idea input: User inputs, "As a new marketing strategy, we are thinking of introducing a social media campaign. Our main target is young people aged 18-24."

[0066] 2. Sending data: The device sends this information to the server.

[0067] 3. Server analysis and key point extraction: The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24."

[0068] 4. Presentation material generation: Based on the key points, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios.

[0069] 5. Sending the presentation materials: The server sends these artifacts to the terminal.

[0070] 6. Displaying presentation materials: The terminal displays these to the user, who then uses the materials to prepare the presentation.

[0071] This concludes the description of an embodiment of the AI ​​system for automatically creating presentation materials of the present invention. By using this system, users can save time and effort while giving effective and attractive presentations.

[0072] The processing flow will be explained below.

[0073] Step 1:

[0074] The user uses the device to enter the idea or content of the presentation in text format. For example, the user might enter, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[0075] Step 2:

[0076] The device sends the user's input data to the server using HTTP requests or dedicated APIs, where the text entered by the user is accurately transferred to the server.

[0077] Step 3:

[0078] The server processes the received user input data. First, it uses natural language processing technology to analyze the text data and understand the content of the sentence. This analysis uses techniques such as tokenization, POS tagging, and entity recognition.

[0079] Step 4:

[0080] The server extracts key points from the analysis results. Key point extraction uses an algorithm to identify important phrases and concepts. For example, key points such as "marketing strategy," "social media campaign," and "target: 18-24 years old" are extracted.

[0081] Step 5:

[0082] The server generates the presentation materials based on the extracted key points. In this process, the following elements are generated:

[0083] Slide generation: Automatically generate presentation slides by combining slide templates stored in the server with key points, such as "Title slide," "Target market overview," "Campaign details," and "Success stories."

[0084] Diagram and flow generation: Generate graphs, charts, and flowcharts based on data related to key points. For example, a "target age distribution map" or a "campaign implementation process flow" can be generated.

[0085] Video generation: Create promotional video scenarios and videos using scripts and video templates.

[0086] Step 6:

[0087] The server sends the generated presentation materials to the device. This transmission is also done using HTTP responses or a dedicated API. The materials sent include slides, diagrams, flow charts, videos, etc.

[0088] Step 7:

[0089] The device displays the received presentation materials to the user, who can then use them to prepare and practice their presentation. The user can also edit and customize the materials as needed.

[0090] These are the processing steps of the generative AI system that automatically creates presentation materials. This specific processing flow enables users to quickly create high-quality presentation materials.

[0091] Example 1

[0092] 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."

[0093] In today's world, creating effective and engaging presentation materials in a short amount of time is an important challenge. However, many users find creating presentation materials time-consuming and laborious, and often fail to achieve satisfactory results due to a lack of technical knowledge. Furthermore, advanced analysis and generation techniques are required to effectively organize the content of presentation materials. Therefore, an efficient and effective method to solve these problems is needed.

[0094] 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.

[0095] In this invention, the server includes means for accepting input of ideas and content from a user, means for transmitting the input ideas and content to the server, means for analyzing the input ideas and content in the server using natural language processing technology and extracting key points, means for generating presentation materials using a generative AI model based on the key points, means for transmitting the generated presentation materials to a user's terminal, and means for displaying the generated presentation materials on the terminal, thereby enabling a user to automatically create effective presentation materials in a short amount of time.

[0096] "User" refers to an individual or organization that uses the system to create presentation materials.

[0097] "Ideas" refer to thoughts and ideas that a user inputs as content for presentation materials.

[0098] "Content" refers to the specific information or data that a user enters for inclusion in a presentation.

[0099] "Terminal" refers to an electronic device used by a user, such as a computer, smartphone, or tablet.

[0100] "Server" refers to a computer system that analyzes user input data and generates presentation materials.

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

[0102] "Key points" refer to important elements or information extracted from input ideas or content.

[0103] A "generative AI model" refers to an algorithm that uses artificial intelligence to automatically generate content such as text, images, and videos.

[0104] "Presentation materials" refers to materials in the form of slides, diagrams, flow charts, videos, etc. that are generated based on user input data.

[0105] An "HTTP request" is a type of protocol for sending data from a client to a server.

[0106] "API" is an abbreviation for Application Programming Interface, and refers to an interface that allows different software programs to communicate with each other.

[0107] MODE FOR CARRYING OUT THE INVENTION

[0108] The AI ​​system for automatically creating presentation materials according to the present invention is composed of three main components: a user, a terminal, and a server. The system of the present invention is a technology for converting a user's ideas and content into easy-to-understand, effective presentation materials.

[0109] The system begins operation when the user uses a device to input the idea and content of the presentation. For example, the user might input, "We are considering introducing a social media campaign as a new marketing strategy. Our main target is young people aged 18-24." The input data is sent from the device to a server, which analyzes the data and extracts key points. The server then implements natural language processing technology using spaCy and NLTK, natural language processing libraries for Python. As a result of the analysis, important key points are extracted from the data. For example, "new marketing strategy," "social media campaign," and "main target is young people aged 18-24."

[0110] The server then uses a generative AI model (e.g., OpenAI's GPT-4) to generate a presentation based on the extracted key points, including the following elements:

[0111] Slides: Title slide, marketing strategy overview, target market details, campaign implementation process, success stories, etc.

[0112] Figures: Age distribution of your target market, social media usage statistics, graphs showing campaign effectiveness, etc.

[0113] Flow: A flow diagram showing the steps to execute the campaign.

[0114] Video: A scenario for a promotional video for the campaign is generated, and the actual video may be created using FFmpeg and OpenCV.

[0115] The generated presentation materials are sent from the server to the device using HTTP responses or a dedicated API. The device displays the received presentation materials to the user, who can then use the displayed materials to prepare and practice their presentation.

[0116] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[0117] 1. User idea input:

[0118] The user types, "We're looking to launch a social media campaign as a new marketing strategy. Our primary target audience will be young people aged 18-24."

[0119] 2. Data transmission:

[0120] The terminal sends this information to the server.

[0121] 3. Server analysis and keypoint extraction:

[0122] The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24."

[0123] 4. Generate presentation materials:

[0124] Based on the key points, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios.

[0125] 5. Submitting presentation materials:

[0126] The server sends these products to the terminal.

[0127] 6. Viewing Presentation Materials:

[0128] The terminal displays this to the user, who then prepares a presentation based on the materials.

[0129] This system allows users to save time and effort while delivering effective and engaging presentations. It also utilizes generative AI models and natural language processing technology to automatically generate high-quality presentation materials.

[0130] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0131] Step 1:

[0132] The user uses the device to input the idea or content of the presentation in text format, for example, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[0133] Input: Presentation ideas and content

[0134] Output: Text data as user input

[0135] Step 2:

[0136] The terminal sends the text data entered by the user to the server using an HTTP request or a dedicated API. The transmission is triggered when the user clicks the "Send" button.

[0137] Input: Text data as user input

[0138] Output: Text data sent to the server

[0139] Step 3:

[0140] The server analyzes the received text data using natural language processing techniques, such as spaCy or NLTK, a Python natural language processing library, to extract key points from the text.

[0141] During the analysis process, important phrases and sentences are identified and listed as key points.

[0142] Input: Text data sent to the server

[0143] Output: List of key points (e.g., "New marketing strategy," "Social media campaign," "Primary target is young people aged 18-24")

[0144] Step 4:

[0145] The server generates presentation materials using a generative AI model (e.g., OpenAI's GPT-4) based on the extracted keypoints. The generation of presentation materials includes the following elements:

[0146] Slides: Title slide, marketing strategy overview, target market details, campaign implementation process, success stories, etc.

[0147] Figures: Age distribution of your target market, social media usage statistics, graphs showing campaign effectiveness, etc.

[0148] Flow: A flow diagram showing the steps to execute the campaign.

[0149] Video: A scenario for a promotional video for the campaign is generated, and the actual video may be created using FFmpeg and OpenCV.

[0150] Input: List of keypoints

[0151] Output: Generated presentation materials (slides, diagrams, flow charts, videos)

[0152] Step 5:

[0153] The server sends the generated presentation materials to the terminal via HTTP responses or a dedicated API. The materials are compressed and sent in JSON or XML format.

[0154] Input: Generated presentation materials

[0155] Output: Presentation materials sent to the device

[0156] Step 6:

[0157] The device displays the received presentation materials to the user, either using a dedicated viewer or through a web browser, where the user can review the materials and make corrections or additions as needed.

[0158] Input: Presentation materials received from the server

[0159] Output: Presentation material displayed to the user

[0160] The above are the specific processing steps of this system, which enables users to automatically generate high-quality presentation materials in a short amount of time.

[0161] (Application example 1)

[0162] 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."

[0163] Creating effective materials for advertising campaigns requires specialized knowledge and time, which places a significant burden on small businesses in particular. It is also difficult to consistently create high-quality materials that are appropriate for the target audience and key messages. Furthermore, it is often difficult to devote human resources and time to solving these problems, so automated methods are needed.

[0164] 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.

[0165] In this invention, the server includes means for accepting input of ideas and content from a user, means for transmitting the entered ideas and content to the server, means for analyzing the entered ideas and content in the server and extracting key points, means for accepting a target demographic, main messages, and a promotion plan from the user, means for automatically generating advertising campaign materials based on the accepted data, means for transmitting the generated presentation materials to the user's terminal, and means for displaying the generated presentation materials on the terminal, thereby enabling the automatic generation of advertising campaign materials and the provision of effective presentation materials.

[0166] "User" refers to any individual or legal entity that uses the System.

[0167] "Ideas" refer to ideas, concepts, and suggestions provided by users.

[0168] "Content" refers to information, data, theme settings, etc. provided by users.

[0169] "Server" refers to a computer system for processing data.

[0170] "Key points" refer to important items or main points extracted from ideas or content.

[0171] "Presentation materials" refers to materials that include slides, diagrams, flow charts, videos, etc., that allow users to visually convey information.

[0172] "Terminal" refers to an electronic device such as a computer, smartphone, or tablet that can be directly operated by a user.

[0173] "Target demographic" refers to the specific group of the population that a particular ad or campaign is aimed at.

[0174] "Key messages" are the most important information or concepts you want to communicate in your ad or campaign.

[0175] A "promotion plan" refers to a detailed strategy and execution plan for effectively promoting a product or service.

[0176] "Advertising Campaign Materials" means presentation materials and related materials generated for use for advertising purposes.

[0177] "Automatic generation" refers to the system autonomously creating materials with minimal human intervention.

[0178] "Natural language processing technology" refers to technology that enables computers to understand and analyze human language.

[0179] The system of the present invention consists of three main components: a user, a terminal, and a server, which enable the automatic generation of presentation materials for advertising campaigns.

[0180] User Input

[0181] The user uses the terminal to input the idea, content, target audience, main message, and promotion plan for the advertising campaign in text format. For example, they might input, "I'm thinking of creating an advertising campaign for the market launch of a new product. The main target audience is urban residents aged 25-35. The main message of the product is 'environmentally friendly.'"

[0182] Sending data

[0183] The terminal sends the user's input data to the server as an HTTP request using TLS (Transport Layer Security). This transmission method ensures data security and communication reliability.

[0184] Keypoint Extraction

[0185] The server analyzes the received data using natural language processing technology and extracts key points. The generative AI model used is OpenAI's "text-davinci-003," which extracts key points from the input data, such as "new product launch," "urban dwellers aged 25-35," and "environmentally friendly." Specifically, the following prompt sentences are used:

[0186] Extract the main key points from the following passage: "You are considering an advertising campaign for the launch of a new product. The primary target audience is urban dwellers aged 25-35. The key message of the product is 'environmentally friendly'."

[0187] Generate presentation materials

[0188] The server automatically generates presentation materials based on the extracted key points, including slides, diagrams, flow charts, videos, etc. Based on the generated presentation content, it generates detailed materials using the following prompt sentences:

[0189] Create a presentation for an advertising campaign based on the following key points: "New product launch, urban dwellers aged 25-35, environmentally friendly."

[0190] Sending and Displaying Data

[0191] The generated presentation materials are sent to the terminal via an HTTP response, and the terminal displays the received materials to the user, allowing the user to prepare for the presentation.

[0192] This system allows users to automatically generate presentation materials for advertising campaigns efficiently and with high quality. For example, based on the input data mentioned above, presentation materials emphasizing messages such as "new product launch" and "environmental friendliness" are displayed on the terminal.

[0193] This completes the description of the embodiment of the invention. By using this system, it is possible to automatically generate advertising campaign materials and provide effective presentation materials.

[0194] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0195] Step 1:

[0196] The user uses the terminal to input the idea, content, target audience, main message, and promotion plan for the advertising campaign in text format. The input information is, "We are thinking of an advertising campaign for the market launch of a new product. The main target audience is urban residents aged 25-35. The main message of the product is 'environmentally friendly'." The input data is prepared.

[0197] Step 2:

[0198] The terminal sends the input data to the server using an HTTP request. At this time, TLS (Transport Layer Security) is used to ensure the security and reliability of the data. The sent data is then received by the server.

[0199] Step 3:

[0200] The server analyzes the received data and extracts key points using natural language processing techniques. It uses OpenAI's "text-davinci-003" as a generative AI model and executes prompts.

[0201] Extract the main key points from the following passage: "You are considering an advertising campaign for the launch of a new product. The primary target audience is urban dwellers aged 25-35. The key message of the product is 'environmentally friendly'."

[0202] From the input data, key points such as "new product launch," "urban residents aged 25-35," and "environmentally friendly" are extracted.

[0203] Step 4:

[0204] The server generates a presentation based on the extracted key points, again using the OpenAI API and the following prompt:

[0205] Create a presentation for an advertising campaign based on the following key points: "New product launch, urban dwellers aged 25-35, environmentally friendly."

[0206] The generative AI model takes the key points as input and generates presentation materials including slides, diagrams, flow charts, and videos. The generated materials are prepared.

[0207] Step 5:

[0208] The server sends the generated presentation materials to the terminal via an HTTP response. The materials are packaged in JSON format and transmitted via a secure communication method.

[0209] Step 6:

[0210] The terminal displays the received presentation materials on a user interface, allowing the user to review the displayed materials and prepare for the presentation. The displayed content includes generated slides, diagrams, flow charts, and videos.

[0211] 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.

[0212] The AI ​​system for automatically creating presentation materials according to the present invention consists of four main components: a user, a terminal, a server, and an emotion engine. This system is a technology that converts the user's ideas and content into easy-to-understand and effective presentation materials, and also combines an emotion engine that recognizes and reflects the user's emotions.

[0213] System Overview

[0214] When a user uses a device to input ideas and content for a presentation, the emotion engine recognizes the user's emotions. The input data is sent from the device to a server, which analyzes the data and extracts key points. Presentation materials such as slides, diagrams, flow charts, and videos are generated based on the key points and edited to match the user's emotions. The generated presentation materials are then sent to the device and displayed to the user.

[0215] Detailed system description

[0216] 1. User idea input and emotion recognition

[0217] The user uses the device to input the idea and content of the presentation. At this time, the emotion engine analyzes the user's facial expressions, voice, and input content to identify their emotions. For example, if the user inputs, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target is young people aged 18-24," the engine will determine whether the user is excited or nervous.

[0218] 2. Data transmission

[0219] The device sends the user's input data and emotion information to the server using HTTP requests and dedicated APIs. The text and emotion data entered by the user are accurately transferred to the server.

[0220] 3. Server analysis and keypoint extraction

[0221] The server processes the received user input data and emotional information. First, it uses natural language processing technology to analyze the text data and understand the content of the sentences. This analysis uses techniques such as tokenization, POS tagging, and entity recognition. Next, it extracts important key points from the data, including the emotions identified by the emotion engine. For example, key points such as "marketing strategy," "social media campaign," and "target: 18-24 years old" are extracted, and the user's emotions are also recorded.

[0222] 4. Generate presentation materials

[0223] The server generates the presentation materials based on the extracted key points and emotion information. Specifically, the following elements are generated:

[0224] Slide generation: Automatically generate presentation slides by combining slide templates stored on the server with key points. For example, slides such as "title slide," "target market overview," "campaign details," and "success stories" are generated. The tone and style are adjusted to match the user's emotions.

[0225] Diagram and flow generation: Graphs, charts, and flowcharts are generated based on data related to key points. For example, a "target age distribution map" or a "campaign implementation process flow" can be generated. The design of the diagrams and flows is also adjusted according to the user's emotions to reflect their feelings.

[0226] Video Generation: Scripts and video templates are used to create promotional video scripts and animations, with the tone and style of the scripts and animations tailored to the emotions identified by the emotion engine.

[0227] 5. Sending presentation materials

[0228] The generated presentation materials are sent from the server to the device using HTTP responses or a dedicated API. The materials sent include slides, diagrams, flow charts, videos, and more.

[0229] 6. Displaying presentation materials

[0230] The device displays the received presentation materials to the user. The user can use the displayed materials to prepare and practice their presentation. They can also edit and customize the materials as needed. Materials generated based on the emotions identified by the emotion engine can more effectively convey the user's intentions.

[0231] Specific examples

[0232] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[0233] 1. User idea input and emotion recognition: The user inputs, "As a new marketing strategy, we are thinking of introducing a social media campaign. Our main target is young people aged 18-24." The emotion engine recognizes the user's excitement.

[0234] 2. Data transmission: The device transmits this information and emotion data to the server.

[0235] 3. Server analysis and key point extraction: The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24," while recording what the user is excited about.

[0236] 4. Presentation generation: Based on key points and emotion data, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios. The tone and style of the materials are adjusted to reflect the user's excitement and create a lively presentation.

[0237] 5. Sending the presentation materials: The server sends these artifacts to the terminal.

[0238] 6. Displaying presentation materials: The terminal displays these to the user, who then uses the materials to prepare the presentation.

[0239] The above is an embodiment of the present invention, which combines an emotion engine with a generative AI system for automatically creating presentation materials. By using this system, users can quickly create high-quality presentation materials that reflect their own emotions.

[0240] The processing flow will be explained below.

[0241] Step 1:

[0242] The user uses the device to enter the idea or content of the presentation in text format. For example, the user might enter, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[0243] Step 2:

[0244] The device's built-in emotion engine analyzes the user's facial expressions, voice, and input content while they are typing. For example, it can determine whether the user is excited or calm by capturing facial expressions with a camera and recording audio with a microphone.

[0245] Step 3:

[0246] The device sends the analyzed emotion data and the user's input text data to the server. This transmission uses data formatting and an HTTP request. The emotion data and text data are accurately transferred to the server.

[0247] Step 4:

[0248] The server analyzes the received text data using natural language processing technology to understand the content of the text. Specific analysis steps include tokenization, POS tagging, and entity recognition.

[0249] Step 5:

[0250] The server extracts key points from the analysis results. This process identifies and summarizes important phrases and concepts. For example, key points such as "marketing strategy," "social media campaign," and "target age group: 18-24 years old" are extracted.

[0251] Step 6:

[0252] The server analyzes the received emotional data and identifies the user's emotional state. The emotion engine determines whether the user is excited or calm based on data obtained from facial expression and voice analysis.

[0253] Step 7:

[0254] The server generates presentation materials based on the extracted key points and emotion data. The specific generation process includes the following elements:

[0255] Slide generation: The server automatically generates presentation slides using slide templates that reflect key points, including title slides, target market overviews, campaign details, and success stories. The tone and style are also adjusted to match the user's emotions.

[0256] Diagram and flow generation: Graphs, charts, and flowcharts are generated based on key points and related data. For example, a "target age distribution map" or a "campaign process flow" can be generated. Furthermore, the design tone and coloring can be adjusted based on the user's emotions.

[0257] Video Generation: Create promotional video scenarios and animations using scripts and video templates. The tone and style of the video are also adjusted based on user sentiment data.

[0258] Step 8:

[0259] The server sends the generated presentation materials to the device using HTTP responses or a dedicated API. The materials sent include slides, diagrams, flow charts, videos, etc.

[0260] Step 9:

[0261] The terminal displays the received presentation materials to the user, who can then practice and prepare for the presentation. The displayed materials can also be edited as needed. Materials that reflect the user's emotions will help them give more effective presentations.

[0262] These are the specific processing steps of the automatic presentation material generation system that combines an emotion engine that recognizes the user's emotions. These steps enable users to quickly create high-quality presentation materials that reflect their own emotions.

[0263] Example 2

[0264] 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."

[0265] Conventional presentation material creation systems require a great deal of time and effort for users to create their own materials, and it is difficult to create effective materials that reflect the user's emotions. Furthermore, materials that do not reflect emotions often fail to make an appropriate impact on the audience.

[0266] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting input of ideas or content from a user, means for analyzing the input idea or content and identifying the user's emotion, and means for transmitting the input idea or content and emotion information to the server. This enables the user to quickly create high-quality presentation materials that reflect his or her own emotions.

[0267] "User" refers to any individual or entity that uses this system to input ideas or content.

[0268] "Emotion engine" refers to a software component that analyzes input ideas and content and identifies the user's emotions.

[0269] "Terminal" refers to an electronic device that a user uses to input ideas or content and transmit that data to a server.

[0270] "Server" refers to a computer system that analyzes received data and generates presentation materials.

[0271] "Ideas" refer to thoughts and plans that users come up with and input into the system.

[0272] "Key points" refer to important information or key points extracted from input ideas or content.

[0273] "Presentation materials" refers to materials including slides, diagrams, flows, videos, etc. that are generated based on the user's ideas, content, and emotional information.

[0274] "Natural language processing technology" refers to technology that enables computers to understand, interpret, and generate human language.

[0275] "Slide generation" refers to the process of automatically creating slides based on key points and emotional information as part of a presentation deck.

[0276] "Diagram and flow generation" refers to the process of automatically creating graphs, charts, and flowcharts using data related to key points as part of a presentation deck.

[0277] The AI ​​system for automatically creating presentation materials according to the present invention consists of four main components: a user, a terminal, a server, and an emotion engine. This system is a technology that converts the user's ideas and content into easy-to-understand and effective presentation materials, and also combines an emotion engine that recognizes and reflects the user's emotions.

[0278] System Overview

[0279] When a user uses a device to input ideas and content for a presentation, the emotion engine recognizes the user's emotions. The input data is sent from the device to a server, which analyzes the data and extracts key points. Presentation materials such as slides, diagrams, flow charts, and videos are generated based on the key points and edited to match the user's emotions. The generated presentation materials are then sent to the device and displayed to the user.

[0280] Detailed system description

[0281] 1. User idea input and emotion recognition

[0282] The user uses the device to input ideas and content for the presentation. The device then uses a camera and microphone and an emotion engine to analyze the user's facial expressions, voice, and input to identify emotions. For example, if the user inputs, "As a new marketing strategy, we are considering introducing a social media campaign. Our primary target is young people aged 18-24," the device will analyze the user's emotions (such as excitement or nervousness) in real time.

[0283] 2. Data transmission

[0284] The device sends the user's input data and emotion information to the server using an HTTP request or a dedicated API. The device converts the emotion data into JSON format and sends it along with the user's text data. For example, the device sends the data to the endpoint using a POST request.

[0285] 3. Server analysis and keypoint extraction

[0286] The server processes the received user input data and emotional information. First, it uses natural language processing (NLP) techniques to analyze the text data. Python NLP libraries (such as SpaCy and NLTK) are used for this analysis. The server then integrates the emotions identified by the emotion engine and extracts important key points from the data. For example, key points such as "marketing strategy," "social media campaign," and "target age group: 18-24 years old" are extracted, and the user's emotions are also recorded.

[0287] 4. Generate presentation materials

[0288] The server generates a presentation based on the extracted key points and emotion information. The following elements are generated:

[0289] Slide generation: The server selects an appropriate template from multiple saved templates and arranges content based on key points. For example, slides such as "title slide," "target market overview," "campaign details," and "success stories" are generated. In this process, the server considers the user's emotional state (e.g., excitement) to select a lively design.

[0290] Figure and flow generation: The server automatically generates graphs, charts, and flowcharts based on data related to key points. Specifically, the server draws graphs based on the data using Python libraries such as Matplotlib and Plotly.

[0291] Video generation: The server uses scripts and video templates to generate promotional videos for presentations. The server uses video generation software (e.g., Adobe Premiere API or FFmpeg) based on emotion information to edit and create videos.

[0292] 5. Sending presentation materials

[0293] The server sends the generated presentation materials to the terminal. This is done using HTTP responses or a dedicated API. The server compresses the generated materials (PDF, PPT, video files, etc.) into a ZIP file and sends it as an HTTP response.

[0294] 6. Displaying presentation materials

[0295] The device displays the received presentation materials to the user. To display the materials in the appropriate format, the device uses tools such as a PDF viewer or video player. Specifically, the device unzips the received files and displays them in the interface so that the user can easily view and edit them.

[0296] Specific examples

[0297] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[0298] 1. User idea input and emotion recognition: When a user inputs, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target is young people aged 18-24," the device uses its emotion engine to recognize the user's state of excitement.

[0299] 2. Data transmission: The device transmits this information and emotion data to the server.

[0300] 3. Server analysis and key point extraction: The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24," while also recording what the user is excited about.

[0301] 4. Presentation generation: Based on key points and emotion data, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios. The tone and style of the presentation materials are adjusted to reflect the user's excitement and make them more lively.

[0302] 5. Sending presentation materials: The server sends the generated materials to the terminal.

[0303] 6. Displaying presentation materials: The terminal displays the materials to the user, who then prepares the presentation based on them.

[0304] The above is a detailed description of an embodiment of the AI ​​system for automatically creating presentation materials of the present invention. By using this system, users can quickly create high-quality presentation materials that reflect their own emotions.

[0305] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0306] Step 1: User idea input and emotion recognition

[0307] The user uses the device to input the ideas and content of the presentation. Specifically, they input text information using the device's keyboard or voice input function. At the same time, the device uses its built-in camera and microphone to capture the user's facial expressions and voice. Based on this, the device uses an emotion engine to perform facial expression recognition and voice analysis to identify the user's emotions (excitement, nervousness, etc.) in real time. Input data (text information) and emotional data (excitement, nervousness, etc.) are generated.

[0308] Step 2: Sending data

[0309] The device sends the input data (text information) and emotion data obtained in step 1 to the server. Specifically, this data is converted into JSON format and sent to the server's API endpoint via an HTTP POST request. The input includes text data and emotion data, and the output is the accurate transfer of this data to the server.

[0310] Step 3: Server analysis and keypoint extraction

[0311] The server analyzes the data received in step 2. First, the server uses natural language processing (NLP) techniques to analyze the text data. Specifically, the server uses a Python NLP library (such as SpaCy or NLTK) to perform tokenization, POS tagging, and entity recognition. This analyzes the content of the text and extracts key points. In parallel, the server also analyzes the sentiment data and records the user's sentiment information. The inputs are text data and sentiment data, and the output is key points and sentiment information.

[0312] Step 4: Generate presentation materials

[0313] The server generates the presentation materials based on the key points and emotion information obtained in step 3. Specifically, the following elements are generated:

[0314] Slide generation: The server selects an appropriate template from multiple stored templates and arranges content based on key points. The template and design are selected taking into account the user's emotional state.

[0315] Figure and flow generation: The server uses data related to key points to automatically generate graphs, charts, and flowcharts using Python libraries such as Matplotlib and Plotly.

[0316] Video generation: The server uses video generation software (such as Adobe Premiere API or FFmpeg) to edit and create a promotional video based on the emotional information. The inputs are key points and emotional information, and the output is presentation materials such as slides, diagrams, flow charts, and videos.

[0317] Step 5: Send your presentation materials

[0318] The server sends the presentation materials generated in step 4 to the terminal. Specifically, the generated materials (PDF, PPT, video files, etc.) are compressed into a ZIP file and sent via an HTTP response or a dedicated API. The input is the generated presentation materials, and the output is the data sent back to the terminal.

[0319] Step 6: View your presentation materials

[0320] The terminal displays the presentation materials received in step 5 to the user. Specifically, it displays the extracted materials using an appropriate viewer or player (PDF viewer, video player, etc.). The user can also view and edit the materials as needed. The input is the presentation materials sent from the server, and the output is the materials to be displayed. The user prepares the presentation based on these materials.

[0321] (Application example 2)

[0322] 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."

[0323] Creating presentation materials requires time and effort, and it is particularly difficult to create effective presentation materials that reflect the user's emotions and intentions. Furthermore, there is a need for a method to quickly create appropriate materials when staff in physical stores explain products and provide promotions to customers. Conventional methods have difficulty generating presentation materials that incorporate the user's emotions, making it difficult to provide effective explanations to customers.

[0324] 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.

[0325] In this invention, the server includes means for analyzing ideas and content input by a user and extracting key points, means for generating presentation materials based on the extracted key points, and means for recognizing the user's emotions and adjusting the tone and style of the presentation materials based on those emotions, thereby enabling the rapid creation of presentation materials that reflect the user's emotions.

[0326] "User" refers to a person who inputs ideas and content for creating presentation materials.

[0327] "Server" refers to a computer system that analyzes ideas and content sent by users and generates presentation materials.

[0328] "Means for accepting input of ideas or content" refers to an interface through which users can input their own thoughts or information.

[0329] "Means for transmitting ideas or content to a server" refers to a device or software that transmits information entered by a user to a server.

[0330] "Means for extracting key points" refers to technology that identifies and extracts important elements and information from the content entered by the user.

[0331] "Means for generating presentation materials" refers to a technology for creating presentation materials such as slides, diagrams, flow charts, and videos based on the extracted key points.

[0332] The term "means for transmitting presentation materials to a user's terminal" refers to a device or software for transmitting the generated presentation materials to a device used by a user.

[0333] The term "means for displaying presentation materials" refers to a device or software that visually displays the presentation materials generated on a user's terminal.

[0334] "Means for recognizing emotions" refers to technology that analyzes the user's voice and facial expressions to determine the user's emotional state.

[0335] "Means for adjusting the tone and style of presentation materials based on emotions" refers to techniques that change the visual and content style of presentation materials in response to perceived emotions.

[0336] "Users in physical stores" refers to staff who need presentation materials when explaining products and promotions in stores.

[0337] The system for automatically creating presentation materials based on this invention consists of four main components: a user, a terminal, a server, and an emotion engine. This system aims to effectively generate presentation materials, and is characterized by its ability to reflect the user's emotions.

[0338] Overall system overview

[0339] When a user uses a device to input ideas and content for a presentation, the emotion engine recognizes the user's emotions. The input data is sent from the device to the server, which analyzes the data and extracts key points. Presentation materials are generated based on the extracted key points and edited to match the user's emotions. The generated presentation materials are then sent to the device, where the user can view and use them.

[0340] Hardware and software used

[0341] Hardware: smartphone, microphone, camera

[0342] Software: Python, requests, emotion recognition model, presentation generation AI model (e.g., Transformers)

[0343] Functions of each component

[0344] 1. User idea input and emotion recognition

[0345] Users use devices such as smartphones to input ideas and content for their presentations using voice or text. At this time, the emotion engine analyzes the user's voice and facial expressions to recognize their emotions. For example, if a user inputs "I would like to introduce a new product," the voice data is analyzed to determine whether the user is excited or calm.

[0346] 2. Data transmission

[0347] The device sends the text and emotion data entered by the user to the server using HTTP requests and a dedicated API to ensure accurate transmission of the data.

[0348] 3. Server analysis and keypoint extraction

[0349] The server analyzes the received user input data and emotional information. It uses natural language processing technology to analyze the text data and understand the content of the sentences. This analysis involves tokenization, POS tagging, and entity recognition. Furthermore, important key points are extracted from the data based on the emotions identified by the emotion engine. For example, "new product," "features," and "target market" are extracted, and the user's excitement level is also recorded.

[0350] 4. Generate presentation materials

[0351] The server generates presentation materials based on the extracted key points and emotion information. These materials include slides, diagrams, flow charts, and videos. For example, a "product overview" slide, a "feature" diagram, and a "sales process flow" are generated. The tone and style of the materials are adjusted to match the user's emotions. For example, if the user is excited, vibrant colors and dynamic elements are incorporated.

[0352] 5. Sending and Displaying Presentation Materials

[0353] The generated presentation materials are sent from the server to the terminal, which displays them to the user. The user can use the displayed materials to prepare a presentation and edit and customize the materials as needed.

[0354] Specific examples

[0355] For example, consider a case where a store staff member wants to explain the features of a new large-screen TV to a customer. The staff member uses a smartphone to voice-input, "This TV is 4K compatible, making it especially great for watching sports. What's more, it has great smart features." The emotion engine recognizes the staff member's excitement, and the data along with their emotion is sent to the server. The server analyzes the input data, extracts key points, and uses a generative AI model to create a presentation. The generated presentation includes a slide showing "Details about 4K compatibility" and a flowchart showing "How to use the smart features," all of which are vividly colored to convey the user's excitement.

[0356] Prompt Sentence Examples

[0357] "I want to create a presentation that explains the features of a new large-screen TV. I want people to pay particular attention to its 4K compatibility and smart features."

[0358] The above is an embodiment of the system for automatically creating presentation materials of the present invention. By using this system, users can create presentation materials quickly and effectively.

[0359] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0360] Step 1:

[0361] The user uses the device to input the ideas and content of the presentation using voice or text. At this point, input data is generated, and the emotion engine recognizes emotions from the voice or text. Specifically, when the user launches a smartphone app and says, "I'd like to introduce a new product, especially about its 4K compatibility and smart features," the voice data is passed to the emotion engine. The emotion engine processes the voice data and recognizes emotions such as "excitement." The input for this step is voice or text data, and the output is recognized emotion data.

[0362] Step 2:

[0363] The device sends the text entered by the user and the recognized emotion data to the server. This is done using HTTP requests or dedicated APIs. For example, the device converts voice data into text and sends the text data and emotion data to the server in JSON format. The input of this step is the text data and emotion data, and the data sent to the server is the output.

[0364] Step 3:

[0365] The server analyzes the received user input data and emotional data. Natural language processing technology is used for the analysis, and the entire sentence is understood based on the extracted key points. Specifically, the server performs tokenization, POS tagging, entity recognition, etc. on the received text data to extract key points such as "new product," "4K compatible," and "smart features." The input for this step is text data and emotional data, and the output is the extracted key points.

[0366] Step 4:

[0367] The server generates presentation materials based on the extracted key points and emotion data. Specifically, it creates slide templates, diagrams, flows, and videos. Generative AI models are used to adjust the tone and style to match the user's emotions. For example, the server might generate a title slide about a "new product," a diagram showing "4K compatibility details," and a "process flow for smart features." The input for this step is the extracted key points and emotion data, and the output is the generated presentation materials.

[0368] Step 5:

[0369] The generated presentation materials are sent from the server to the terminal. The generated materials are returned to the terminal via an HTTP response or a dedicated API. For example, the server sends the generated slides, diagrams, and flow to the terminal in JSON format. The input of this step is the generated presentation materials, and the output is the sent presentation materials.

[0370] Step 6:

[0371] The device displays the received presentation materials to the user. The user can prepare a presentation based on the displayed materials and edit and customize them as needed. For example, the device displays generated slides, and the user reviews them while practicing their presentation. The input of this step is the received presentation materials, and the output is the presentation materials displayed to the user.

[0372] The above is a specific processing flow of the automatic presentation material creation system.

[0373] 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.

[0374] 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.

[0375] 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.

[0376] [Second embodiment]

[0377] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0378] 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.

[0379] 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).

[0380] 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.

[0381] 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.

[0382] 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).

[0383] 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.

[0384] 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.

[0385] 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.

[0386] 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.

[0387] 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.

[0388] 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."

[0389] The AI ​​system for automatically creating presentation materials according to the present invention consists of three main components: a user, a terminal, and a server. This system is a technology that converts a user's ideas and content into easy-to-understand, effective presentation materials.

[0390] System Overview

[0391] The system begins by a user entering the idea and content of a presentation using a device. The entered data is sent from the device to a server, which analyzes the data and extracts key points. Presentation materials such as slides, diagrams, flow charts, and videos are then generated based on the key points. The generated presentation materials are then sent to the device and displayed to the user.

[0392] Detailed system description

[0393] 1. User idea input

[0394] The user uses the device to input the ideas and content of the presentation. Input is in text format. For example, the user might input something like, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[0395] 2. Data transmission

[0396] The device sends the user's input data to the server using an HTTP request or a dedicated API. The server receives this data and proceeds to the next step.

[0397] 3. Server analysis and keypoint extraction

[0398] The server analyzes the received data using natural language processing technology. As a result of the analysis, important key points are extracted from the data. For example, from the above input, key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24" are extracted.

[0399] 4. Generate presentation materials

[0400] The server generates presentation materials based on the extracted key points. Specifically, the following elements are generated:

[0401] Slides: Includes a title slide, an overview of your marketing strategy, details of your target market, the campaign implementation process, and success stories.

[0402] Figures: Generate age distribution maps of your target market, social media usage statistics, and graphs showing campaign effectiveness.

[0403] Flow: A flow diagram is generated showing the steps to execute the campaign.

[0404] Video: A scenario for a promotional video for the campaign is generated and the actual video is created.

[0405] 5. Sending presentation materials

[0406] The generated presentation materials are sent from the server to the device, using HTTP responses and dedicated APIs.

[0407] 6. Displaying presentation materials

[0408] The terminal displays the received presentation materials to the user, who can then use the displayed materials to prepare and practice their presentation.

[0409] Specific examples

[0410] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[0411] 1. User idea input: User inputs, "As a new marketing strategy, we are thinking of introducing a social media campaign. Our main target is young people aged 18-24."

[0412] 2. Sending data: The device sends this information to the server.

[0413] 3. Server analysis and key point extraction: The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24."

[0414] 4. Presentation material generation: Based on the key points, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios.

[0415] 5. Sending the presentation materials: The server sends these artifacts to the terminal.

[0416] 6. Displaying presentation materials: The terminal displays these to the user, who then uses the materials to prepare the presentation.

[0417] This concludes the description of an embodiment of the AI ​​system for automatically creating presentation materials of the present invention. By using this system, users can save time and effort while giving effective and attractive presentations.

[0418] The processing flow will be explained below.

[0419] Step 1:

[0420] The user uses the device to enter the idea or content of the presentation in text format. For example, the user might enter, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[0421] Step 2:

[0422] The device sends the user's input data to the server using HTTP requests or dedicated APIs, where the text entered by the user is accurately transferred to the server.

[0423] Step 3:

[0424] The server processes the received user input data. First, it uses natural language processing technology to analyze the text data and understand the content of the sentence. This analysis uses techniques such as tokenization, POS tagging, and entity recognition.

[0425] Step 4:

[0426] The server extracts key points from the analysis results. Key point extraction uses an algorithm to identify important phrases and concepts. For example, key points such as "marketing strategy," "social media campaign," and "target: 18-24 years old" are extracted.

[0427] Step 5:

[0428] The server generates the presentation materials based on the extracted key points. In this process, the following elements are generated:

[0429] Slide generation: Automatically generate presentation slides by combining slide templates stored in the server with key points, such as "Title slide," "Target market overview," "Campaign details," and "Success stories."

[0430] Diagram and flow generation: Generate graphs, charts, and flowcharts based on data related to key points. For example, a "target age distribution map" or a "campaign implementation process flow" can be generated.

[0431] Video generation: Create promotional video scenarios and videos using scripts and video templates.

[0432] Step 6:

[0433] The server sends the generated presentation materials to the device. This transmission is also done using HTTP responses or a dedicated API. The materials sent include slides, diagrams, flow charts, videos, etc.

[0434] Step 7:

[0435] The device displays the received presentation materials to the user, who can then use them to prepare and practice their presentation. The user can also edit and customize the materials as needed.

[0436] These are the processing steps of the generative AI system that automatically creates presentation materials. This specific processing flow enables users to quickly create high-quality presentation materials.

[0437] Example 1

[0438] 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."

[0439] In today's world, creating effective and engaging presentation materials in a short amount of time is an important challenge. However, many users find creating presentation materials time-consuming and laborious, and often fail to achieve satisfactory results due to a lack of technical knowledge. Furthermore, advanced analysis and generation techniques are required to effectively organize the content of presentation materials. Therefore, an efficient and effective method to solve these problems is needed.

[0440] 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.

[0441] In this invention, the server includes means for accepting input of ideas and content from a user, means for transmitting the input ideas and content to the server, means for analyzing the input ideas and content in the server using natural language processing technology and extracting key points, means for generating presentation materials using a generative AI model based on the key points, means for transmitting the generated presentation materials to a user's terminal, and means for displaying the generated presentation materials on the terminal, thereby enabling a user to automatically create effective presentation materials in a short amount of time.

[0442] "User" refers to an individual or organization that uses the system to create presentation materials.

[0443] "Ideas" refer to thoughts and ideas that a user inputs as content for presentation materials.

[0444] "Content" refers to the specific information or data that a user enters for inclusion in a presentation.

[0445] "Terminal" refers to an electronic device used by a user, such as a computer, smartphone, or tablet.

[0446] "Server" refers to a computer system that analyzes user input data and generates presentation materials.

[0447] "Natural language processing technology" is a technology that enables computers to understand and analyze human language.

[0448] "Key points" refer to important elements or information extracted from input ideas or content.

[0449] A "generative AI model" refers to an algorithm that uses artificial intelligence to automatically generate content such as text, images, and videos.

[0450] "Presentation materials" refers to materials in the form of slides, diagrams, flow charts, videos, etc. that are generated based on user input data.

[0451] An "HTTP request" is a type of protocol for sending data from a client to a server.

[0452] "API" is an abbreviation for Application Programming Interface, and refers to an interface that allows different software programs to communicate with each other.

[0453] MODE FOR CARRYING OUT THE INVENTION

[0454] The AI ​​system for automatically creating presentation materials according to the present invention is composed of three main components: a user, a terminal, and a server. The system of the present invention is a technology for converting a user's ideas and content into easy-to-understand, effective presentation materials.

[0455] The system begins operation when the user uses a device to input the idea and content of the presentation. For example, the user might input, "We are considering introducing a social media campaign as a new marketing strategy. Our main target is young people aged 18-24." The input data is sent from the device to a server, which analyzes the data and extracts key points. The server then implements natural language processing technology using spaCy and NLTK, natural language processing libraries for Python. As a result of the analysis, important key points are extracted from the data. For example, "new marketing strategy," "social media campaign," and "main target is young people aged 18-24."

[0456] The server then uses a generative AI model (e.g., OpenAI's GPT-4) to generate a presentation based on the extracted key points, including the following elements:

[0457] Slides: Title slide, marketing strategy overview, target market details, campaign implementation process, success stories, etc.

[0458] Figures: Age distribution of your target market, social media usage statistics, graphs showing campaign effectiveness, etc.

[0459] Flow: A flow diagram showing the steps to execute the campaign.

[0460] Video: A scenario for a promotional video for the campaign is generated, and the actual video may be created using FFmpeg and OpenCV.

[0461] The generated presentation materials are sent from the server to the device using HTTP responses or a dedicated API. The device displays the received presentation materials to the user, who can then use the displayed materials to prepare and practice their presentation.

[0462] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[0463] 1. User idea input:

[0464] The user types, "We're looking to launch a social media campaign as a new marketing strategy. Our primary target audience will be young people aged 18-24."

[0465] 2. Data transmission:

[0466] The terminal sends this information to the server.

[0467] 3. Server analysis and keypoint extraction:

[0468] The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24."

[0469] 4. Generate presentation materials:

[0470] Based on the key points, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios.

[0471] 5. Submitting presentation materials:

[0472] The server sends these products to the terminal.

[0473] 6. Viewing Presentation Materials:

[0474] The terminal displays this to the user, who then prepares a presentation based on the materials.

[0475] This system allows users to save time and effort while delivering effective and engaging presentations. It also utilizes generative AI models and natural language processing technology to automatically generate high-quality presentation materials.

[0476] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0477] Step 1:

[0478] The user uses the device to input the idea or content of the presentation in text format, for example, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[0479] Input: Presentation ideas and content

[0480] Output: Text data as user input

[0481] Step 2:

[0482] The terminal sends the text data entered by the user to the server using an HTTP request or a dedicated API. The transmission is triggered when the user clicks the "Send" button.

[0483] Input: Text data as user input

[0484] Output: Text data sent to the server

[0485] Step 3:

[0486] The server analyzes the received text data using natural language processing techniques, such as spaCy or NLTK, a Python natural language processing library, to extract key points from the text.

[0487] During the analysis process, important phrases and sentences are identified and listed as key points.

[0488] Input: Text data sent to the server

[0489] Output: List of key points (e.g., "New marketing strategy," "Social media campaign," "Primary target is young people aged 18-24")

[0490] Step 4:

[0491] The server generates presentation materials using a generative AI model (e.g., OpenAI's GPT-4) based on the extracted keypoints. The generation of presentation materials includes the following elements:

[0492] Slides: Title slide, marketing strategy overview, target market details, campaign implementation process, success stories, etc.

[0493] Figures: Age distribution of your target market, social media usage statistics, graphs showing campaign effectiveness, etc.

[0494] Flow: A flow diagram showing the steps to execute the campaign.

[0495] Video: A scenario for a promotional video for the campaign is generated, and the actual video may be created using FFmpeg and OpenCV.

[0496] Input: List of keypoints

[0497] Output: Generated presentation materials (slides, diagrams, flow charts, videos)

[0498] Step 5:

[0499] The server sends the generated presentation materials to the terminal via HTTP responses or a dedicated API. The materials are compressed and sent in JSON or XML format.

[0500] Input: Generated presentation materials

[0501] Output: Presentation materials sent to the device

[0502] Step 6:

[0503] The device displays the received presentation materials to the user, either using a dedicated viewer or through a web browser, where the user can review the materials and make corrections or additions as needed.

[0504] Input: Presentation materials received from the server

[0505] Output: Presentation material displayed to the user

[0506] The above are the specific processing steps of this system, which enables users to automatically generate high-quality presentation materials in a short amount of time.

[0507] (Application example 1)

[0508] 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."

[0509] Creating effective materials for advertising campaigns requires specialized knowledge and time, which places a significant burden on small businesses in particular. It is also difficult to consistently create high-quality materials that are appropriate for the target audience and key messages. Furthermore, it is often difficult to devote human resources and time to solving these problems, so automated methods are needed.

[0510] 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.

[0511] In this invention, the server includes means for accepting input of ideas and content from a user, means for transmitting the entered ideas and content to the server, means for analyzing the entered ideas and content in the server and extracting key points, means for accepting a target demographic, main messages, and a promotion plan from the user, means for automatically generating advertising campaign materials based on the accepted data, means for transmitting the generated presentation materials to the user's terminal, and means for displaying the generated presentation materials on the terminal, thereby enabling the automatic generation of advertising campaign materials and the provision of effective presentation materials.

[0512] "User" refers to any individual or legal entity that uses the System.

[0513] "Ideas" refer to ideas, concepts, and suggestions provided by users.

[0514] "Content" refers to information, data, theme settings, etc. provided by users.

[0515] "Server" refers to a computer system for processing data.

[0516] "Key points" refer to important items or main points extracted from ideas or content.

[0517] "Presentation materials" refers to materials that include slides, diagrams, flow charts, videos, etc., that allow users to visually convey information.

[0518] "Terminal" refers to an electronic device such as a computer, smartphone, or tablet that can be directly operated by a user.

[0519] "Target demographic" refers to the specific group of the population that a particular ad or campaign is aimed at.

[0520] "Key messages" are the most important information or concepts you want to communicate in your ad or campaign.

[0521] A "promotion plan" refers to a detailed strategy and execution plan for effectively promoting a product or service.

[0522] "Advertising Campaign Materials" means presentation materials and related materials generated for use for advertising purposes.

[0523] "Automatic generation" refers to the system autonomously creating materials with minimal human intervention.

[0524] "Natural language processing technology" refers to technology that enables computers to understand and analyze human language.

[0525] The system of the present invention consists of three main components: a user, a terminal, and a server, which enable the automatic generation of presentation materials for advertising campaigns.

[0526] User Input

[0527] The user uses the terminal to input the idea, content, target audience, main message, and promotion plan for the advertising campaign in text format. For example, they might input, "I'm thinking of creating an advertising campaign for the market launch of a new product. The main target audience is urban residents aged 25-35. The main message of the product is 'environmentally friendly.'"

[0528] Sending data

[0529] The terminal sends the user's input data to the server as an HTTP request using TLS (Transport Layer Security). This transmission method ensures data security and communication reliability.

[0530] Keypoint Extraction

[0531] The server analyzes the received data using natural language processing technology and extracts key points. The generative AI model used is OpenAI's "text-davinci-003," which extracts key points from the input data, such as "new product launch," "urban dwellers aged 25-35," and "environmentally friendly." Specifically, the following prompt sentences are used:

[0532] Extract the main key points from the following passage: "You are considering an advertising campaign for the launch of a new product. The primary target audience is urban dwellers aged 25-35. The key message of the product is 'environmentally friendly'."

[0533] Generate presentation materials

[0534] The server automatically generates presentation materials based on the extracted key points, including slides, diagrams, flow charts, videos, etc. Based on the generated presentation content, it generates detailed materials using the following prompt sentences:

[0535] Create a presentation for an advertising campaign based on the following key points: "New product launch, urban dwellers aged 25-35, environmentally friendly."

[0536] Sending and Displaying Data

[0537] The generated presentation materials are sent to the terminal via an HTTP response, and the terminal displays the received materials to the user, allowing the user to prepare for the presentation.

[0538] This system allows users to automatically generate presentation materials for advertising campaigns efficiently and with high quality. For example, based on the input data mentioned above, presentation materials emphasizing messages such as "new product launch" and "environmental friendliness" are displayed on the terminal.

[0539] This completes the description of the embodiment of the invention. By using this system, it is possible to automatically generate advertising campaign materials and provide effective presentation materials.

[0540] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0541] Step 1:

[0542] The user uses the terminal to input the idea, content, target audience, main message, and promotion plan for the advertising campaign in text format. The input information is, "We are thinking of an advertising campaign for the market launch of a new product. The main target audience is urban residents aged 25-35. The main message of the product is 'environmentally friendly'." The input data is prepared.

[0543] Step 2:

[0544] The terminal sends the input data to the server using an HTTP request. At this time, TLS (Transport Layer Security) is used to ensure the security and reliability of the data. The sent data is then received by the server.

[0545] Step 3:

[0546] The server analyzes the received data and extracts key points using natural language processing techniques. It uses OpenAI's "text-davinci-003" as a generative AI model and executes prompts.

[0547] Extract the main key points from the following passage: "You are considering an advertising campaign for the launch of a new product. The primary target audience is urban dwellers aged 25-35. The key message of the product is 'environmentally friendly'."

[0548] From the input data, key points such as "new product launch," "urban residents aged 25-35," and "environmentally friendly" are extracted.

[0549] Step 4:

[0550] The server generates a presentation based on the extracted key points, again using the OpenAI API and the following prompt:

[0551] Create a presentation for an advertising campaign based on the following key points: "New product launch, urban dwellers aged 25-35, environmentally friendly."

[0552] The generative AI model takes the key points as input and generates presentation materials including slides, diagrams, flow charts, and videos. The generated materials are prepared.

[0553] Step 5:

[0554] The server sends the generated presentation materials to the terminal via an HTTP response. The materials are packaged in JSON format and transmitted via a secure communication method.

[0555] Step 6:

[0556] The terminal displays the received presentation materials on a user interface, allowing the user to review the displayed materials and prepare for the presentation. The displayed content includes generated slides, diagrams, flow charts, and videos.

[0557] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0558] The AI ​​system for automatically creating presentation materials according to the present invention consists of four main components: a user, a terminal, a server, and an emotion engine. This system is a technology that converts the user's ideas and content into easy-to-understand and effective presentation materials, and also combines an emotion engine that recognizes and reflects the user's emotions.

[0559] System Overview

[0560] When a user uses a device to input ideas and content for a presentation, the emotion engine recognizes the user's emotions. The input data is sent from the device to a server, which analyzes the data and extracts key points. Presentation materials such as slides, diagrams, flow charts, and videos are generated based on the key points and edited to match the user's emotions. The generated presentation materials are then sent to the device and displayed to the user.

[0561] Detailed system description

[0562] 1. User idea input and emotion recognition

[0563] The user uses the device to input the idea and content of the presentation. At this time, the emotion engine analyzes the user's facial expressions, voice, and input content to identify their emotions. For example, if the user inputs, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target is young people aged 18-24," the engine will determine whether the user is excited or nervous.

[0564] 2. Data transmission

[0565] The device sends the user's input data and emotion information to the server using HTTP requests and dedicated APIs. The text and emotion data entered by the user are accurately transferred to the server.

[0566] 3. Server analysis and keypoint extraction

[0567] The server processes the received user input data and emotional information. First, it uses natural language processing technology to analyze the text data and understand the content of the sentences. This analysis uses techniques such as tokenization, POS tagging, and entity recognition. Next, it extracts important key points from the data, including the emotions identified by the emotion engine. For example, key points such as "marketing strategy," "social media campaign," and "target: 18-24 years old" are extracted, and the user's emotions are also recorded.

[0568] 4. Generate presentation materials

[0569] The server generates the presentation materials based on the extracted key points and emotion information. Specifically, the following elements are generated:

[0570] Slide generation: Automatically generate presentation slides by combining slide templates stored on the server with key points. For example, slides such as "title slide," "target market overview," "campaign details," and "success stories" are generated. The tone and style are adjusted to match the user's emotions.

[0571] Diagram and flow generation: Graphs, charts, and flowcharts are generated based on data related to key points. For example, a "target age distribution map" or a "campaign implementation process flow" can be generated. The design of the diagrams and flows is also adjusted according to the user's emotions to reflect their feelings.

[0572] Video Generation: Scripts and video templates are used to create promotional video scripts and animations, with the tone and style of the scripts and animations tailored to the emotions identified by the emotion engine.

[0573] 5. Sending presentation materials

[0574] The generated presentation materials are sent from the server to the device using HTTP responses or a dedicated API. The materials sent include slides, diagrams, flow charts, videos, and more.

[0575] 6. Displaying presentation materials

[0576] The device displays the received presentation materials to the user. The user can use the displayed materials to prepare and practice their presentation. They can also edit and customize the materials as needed. Materials generated based on the emotions identified by the emotion engine can more effectively convey the user's intentions.

[0577] Specific examples

[0578] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[0579] 1. User idea input and emotion recognition: The user inputs, "As a new marketing strategy, we are thinking of introducing a social media campaign. Our main target is young people aged 18-24." The emotion engine recognizes the user's excitement.

[0580] 2. Data transmission: The device transmits this information and emotion data to the server.

[0581] 3. Server analysis and key point extraction: The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24," while recording what the user is excited about.

[0582] 4. Presentation generation: Based on key points and emotion data, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios. The tone and style of the materials are adjusted to reflect the user's excitement and create a lively presentation.

[0583] 5. Sending the presentation materials: The server sends these artifacts to the terminal.

[0584] 6. Displaying presentation materials: The terminal displays these to the user, who then uses the materials to prepare the presentation.

[0585] The above is an embodiment of the present invention, which combines an emotion engine with a generative AI system for automatically creating presentation materials. By using this system, users can quickly create high-quality presentation materials that reflect their own emotions.

[0586] The processing flow will be explained below.

[0587] Step 1:

[0588] The user uses the device to enter the idea or content of the presentation in text format. For example, the user might enter, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[0589] Step 2:

[0590] The device's built-in emotion engine analyzes the user's facial expressions, voice, and input content while they are typing. For example, it can determine whether the user is excited or calm by capturing facial expressions with a camera and recording audio with a microphone.

[0591] Step 3:

[0592] The device sends the analyzed emotion data and the user's input text data to the server. This transmission uses data formatting and an HTTP request. The emotion data and text data are accurately transferred to the server.

[0593] Step 4:

[0594] The server analyzes the received text data using natural language processing technology to understand the content of the text. Specific analysis steps include tokenization, POS tagging, and entity recognition.

[0595] Step 5:

[0596] The server extracts key points from the analysis results. This process identifies and summarizes important phrases and concepts. For example, key points such as "marketing strategy," "social media campaign," and "target age group: 18-24 years old" are extracted.

[0597] Step 6:

[0598] The server analyzes the received emotional data and identifies the user's emotional state. The emotion engine determines whether the user is excited or calm based on data obtained from facial expression and voice analysis.

[0599] Step 7:

[0600] The server generates presentation materials based on the extracted key points and emotion data. The specific generation process includes the following elements:

[0601] Slide generation: The server automatically generates presentation slides using slide templates that reflect key points, including title slides, target market overviews, campaign details, and success stories. The tone and style are also adjusted to match the user's emotions.

[0602] Diagram and flow generation: Graphs, charts, and flowcharts are generated based on key points and related data. For example, a "target age distribution map" or a "campaign process flow" can be generated. Furthermore, the design tone and coloring can be adjusted based on the user's emotions.

[0603] Video Generation: Create promotional video scenarios and animations using scripts and video templates. The tone and style of the video are also adjusted based on user sentiment data.

[0604] Step 8:

[0605] The server sends the generated presentation materials to the device using HTTP responses or a dedicated API. The materials sent include slides, diagrams, flow charts, videos, etc.

[0606] Step 9:

[0607] The terminal displays the received presentation materials to the user, who can then practice and prepare for the presentation. The displayed materials can also be edited as needed. Materials that reflect the user's emotions will help them give more effective presentations.

[0608] These are the specific processing steps of the automatic presentation material generation system that combines an emotion engine that recognizes the user's emotions. These steps enable users to quickly create high-quality presentation materials that reflect their own emotions.

[0609] Example 2

[0610] 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."

[0611] Conventional presentation material creation systems require a great deal of time and effort for users to create their own materials, and it is difficult to create effective materials that reflect the user's emotions. Furthermore, materials that do not reflect emotions often fail to make an appropriate impact on the audience.

[0612] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting input of ideas or content from a user, means for analyzing the input idea or content and identifying the user's emotion, and means for transmitting the input idea or content and emotion information to the server. This enables the user to quickly create high-quality presentation materials that reflect his or her own emotions.

[0613] "User" refers to any individual or entity that uses this system to input ideas or content.

[0614] "Emotion engine" refers to a software component that analyzes input ideas and content and identifies the user's emotions.

[0615] "Terminal" refers to an electronic device that a user uses to input ideas or content and transmit that data to a server.

[0616] "Server" refers to a computer system that analyzes received data and generates presentation materials.

[0617] "Ideas" refer to thoughts and plans that users come up with and input into the system.

[0618] "Key points" refer to important information or key points extracted from input ideas or content.

[0619] "Presentation materials" refers to materials including slides, diagrams, flows, videos, etc. that are generated based on the user's ideas, content, and emotional information.

[0620] "Natural language processing technology" refers to technology that enables computers to understand, interpret, and generate human language.

[0621] "Slide generation" refers to the process of automatically creating slides based on key points and emotional information as part of a presentation deck.

[0622] "Diagram and flow generation" refers to the process of automatically creating graphs, charts, and flowcharts using data related to key points as part of a presentation deck.

[0623] The AI ​​system for automatically creating presentation materials according to the present invention consists of four main components: a user, a terminal, a server, and an emotion engine. This system is a technology that converts the user's ideas and content into easy-to-understand and effective presentation materials, and also combines an emotion engine that recognizes and reflects the user's emotions.

[0624] System Overview

[0625] When a user uses a device to input ideas and content for a presentation, the emotion engine recognizes the user's emotions. The input data is sent from the device to a server, which analyzes the data and extracts key points. Presentation materials such as slides, diagrams, flow charts, and videos are generated based on the key points and edited to match the user's emotions. The generated presentation materials are then sent to the device and displayed to the user.

[0626] Detailed system description

[0627] 1. User idea input and emotion recognition

[0628] The user uses the device to input ideas and content for the presentation. The device then uses a camera and microphone and an emotion engine to analyze the user's facial expressions, voice, and input to identify emotions. For example, if the user inputs, "As a new marketing strategy, we are considering introducing a social media campaign. Our primary target is young people aged 18-24," the device will analyze the user's emotions (such as excitement or nervousness) in real time.

[0629] 2. Data transmission

[0630] The device sends the user's input data and emotion information to the server using an HTTP request or a dedicated API. The device converts the emotion data into JSON format and sends it along with the user's text data. For example, the device sends the data to the endpoint using a POST request.

[0631] 3. Server analysis and keypoint extraction

[0632] The server processes the received user input data and emotional information. First, it uses natural language processing (NLP) techniques to analyze the text data. Python NLP libraries (such as SpaCy and NLTK) are used for this analysis. The server then integrates the emotions identified by the emotion engine and extracts important key points from the data. For example, key points such as "marketing strategy," "social media campaign," and "target age group: 18-24 years old" are extracted, and the user's emotions are also recorded.

[0633] 4. Generate presentation materials

[0634] The server generates a presentation based on the extracted key points and emotion information. The following elements are generated:

[0635] Slide generation: The server selects an appropriate template from multiple saved templates and arranges content based on key points. For example, slides such as "title slide," "target market overview," "campaign details," and "success stories" are generated. In this process, the server considers the user's emotional state (e.g., excitement) to select a lively design.

[0636] Figure and flow generation: The server automatically generates graphs, charts, and flowcharts based on data related to key points. Specifically, the server draws graphs based on the data using Python libraries such as Matplotlib and Plotly.

[0637] Video generation: The server uses scripts and video templates to generate promotional videos for presentations. The server uses video generation software (e.g., Adobe Premiere API or FFmpeg) based on emotion information to edit and create videos.

[0638] 5. Sending presentation materials

[0639] The server sends the generated presentation materials to the terminal. This is done using HTTP responses or a dedicated API. The server compresses the generated materials (PDF, PPT, video files, etc.) into a ZIP file and sends it as an HTTP response.

[0640] 6. Displaying presentation materials

[0641] The device displays the received presentation materials to the user. To display the materials in the appropriate format, the device uses tools such as a PDF viewer or video player. Specifically, the device unzips the received files and displays them in the interface so that the user can easily view and edit them.

[0642] Specific examples

[0643] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[0644] 1. User idea input and emotion recognition: When a user inputs, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target is young people aged 18-24," the device uses its emotion engine to recognize the user's state of excitement.

[0645] 2. Data transmission: The device transmits this information and emotion data to the server.

[0646] 3. Server analysis and key point extraction: The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24," while also recording what the user is excited about.

[0647] 4. Presentation generation: Based on key points and emotion data, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios. The tone and style of the presentation materials are adjusted to reflect the user's excitement and make them more lively.

[0648] 5. Sending presentation materials: The server sends the generated materials to the terminal.

[0649] 6. Displaying presentation materials: The terminal displays the materials to the user, who then prepares the presentation based on them.

[0650] The above is a detailed description of an embodiment of the AI ​​system for automatically creating presentation materials of the present invention. By using this system, users can quickly create high-quality presentation materials that reflect their own emotions.

[0651] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0652] Step 1: User idea input and emotion recognition

[0653] The user uses the device to input the ideas and content of the presentation. Specifically, they input text information using the device's keyboard or voice input function. At the same time, the device uses its built-in camera and microphone to capture the user's facial expressions and voice. Based on this, the device uses an emotion engine to perform facial expression recognition and voice analysis to identify the user's emotions (excitement, nervousness, etc.) in real time. Input data (text information) and emotional data (excitement, nervousness, etc.) are generated.

[0654] Step 2: Sending data

[0655] The device sends the input data (text information) and emotion data obtained in step 1 to the server. Specifically, this data is converted into JSON format and sent to the server's API endpoint via an HTTP POST request. The input includes text data and emotion data, and the output is the accurate transfer of this data to the server.

[0656] Step 3: Server analysis and keypoint extraction

[0657] The server analyzes the data received in step 2. First, the server uses natural language processing (NLP) techniques to analyze the text data. Specifically, the server uses a Python NLP library (such as SpaCy or NLTK) to perform tokenization, POS tagging, and entity recognition. This analyzes the content of the text and extracts key points. In parallel, the server also analyzes the sentiment data and records the user's sentiment information. The inputs are text data and sentiment data, and the output is key points and sentiment information.

[0658] Step 4: Generate presentation materials

[0659] The server generates the presentation materials based on the key points and emotion information obtained in step 3. Specifically, the following elements are generated:

[0660] Slide generation: The server selects an appropriate template from multiple stored templates and arranges content based on key points. The template and design are selected taking into account the user's emotional state.

[0661] Figure and flow generation: The server uses data related to key points to automatically generate graphs, charts, and flowcharts using Python libraries such as Matplotlib and Plotly.

[0662] Video generation: The server uses video generation software (such as Adobe Premiere API or FFmpeg) to edit and create a promotional video based on the emotional information. The inputs are key points and emotional information, and the output is presentation materials such as slides, diagrams, flow charts, and videos.

[0663] Step 5: Send your presentation materials

[0664] The server sends the presentation materials generated in step 4 to the terminal. Specifically, the generated materials (PDF, PPT, video files, etc.) are compressed into a ZIP file and sent via an HTTP response or a dedicated API. The input is the generated presentation materials, and the output is the data sent back to the terminal.

[0665] Step 6: View your presentation materials

[0666] The terminal displays the presentation materials received in step 5 to the user. Specifically, it displays the extracted materials using an appropriate viewer or player (PDF viewer, video player, etc.). The user can also view and edit the materials as needed. The input is the presentation materials sent from the server, and the output is the materials to be displayed. The user prepares the presentation based on these materials.

[0667] (Application example 2)

[0668] 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."

[0669] Creating presentation materials requires time and effort, and it is particularly difficult to create effective presentation materials that reflect the user's emotions and intentions. Furthermore, there is a need for a method to quickly create appropriate materials when staff in physical stores explain products and provide promotions to customers. Conventional methods have difficulty generating presentation materials that incorporate the user's emotions, making it difficult to provide effective explanations to customers.

[0670] 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.

[0671] In this invention, the server includes means for analyzing ideas and content input by a user and extracting key points, means for generating presentation materials based on the extracted key points, and means for recognizing the user's emotions and adjusting the tone and style of the presentation materials based on those emotions, thereby enabling the rapid creation of presentation materials that reflect the user's emotions.

[0672] "User" refers to a person who inputs ideas and content for creating presentation materials.

[0673] "Server" refers to a computer system that analyzes ideas and content sent by users and generates presentation materials.

[0674] "Means for accepting input of ideas or content" refers to an interface through which users can input their own thoughts or information.

[0675] "Means for transmitting ideas or content to a server" refers to a device or software that transmits information entered by a user to a server.

[0676] "Means for extracting key points" refers to technology that identifies and extracts important elements and information from the content entered by the user.

[0677] "Means for generating presentation materials" refers to a technology for creating presentation materials such as slides, diagrams, flow charts, and videos based on the extracted key points.

[0678] The term "means for transmitting presentation materials to a user's terminal" refers to a device or software for transmitting the generated presentation materials to a device used by a user.

[0679] The term "means for displaying presentation materials" refers to a device or software that visually displays the presentation materials generated on a user's terminal.

[0680] "Means for recognizing emotions" refers to technology that analyzes the user's voice and facial expressions to determine the user's emotional state.

[0681] "Means for adjusting the tone and style of presentation materials based on emotions" refers to techniques that change the visual and content style of presentation materials in response to perceived emotions.

[0682] "Users in physical stores" refers to staff who need presentation materials when explaining products and promotions in stores.

[0683] The system for automatically creating presentation materials based on this invention consists of four main components: a user, a terminal, a server, and an emotion engine. This system aims to effectively generate presentation materials, and is characterized by its ability to reflect the user's emotions.

[0684] Overall system overview

[0685] When a user uses a device to input ideas and content for a presentation, the emotion engine recognizes the user's emotions. The input data is sent from the device to the server, which analyzes the data and extracts key points. Presentation materials are generated based on the extracted key points and edited to match the user's emotions. The generated presentation materials are then sent to the device, where the user can view and use them.

[0686] Hardware and software used

[0687] Hardware: smartphone, microphone, camera

[0688] Software: Python, requests, emotion recognition model, presentation generation AI model (e.g., Transformers)

[0689] Functions of each component

[0690] 1. User idea input and emotion recognition

[0691] Users use devices such as smartphones to input ideas and content for their presentations using voice or text. At this time, the emotion engine analyzes the user's voice and facial expressions to recognize their emotions. For example, if a user inputs "I would like to introduce a new product," the voice data is analyzed to determine whether the user is excited or calm.

[0692] 2. Data transmission

[0693] The device sends the text and emotion data entered by the user to the server using HTTP requests and a dedicated API to ensure accurate transmission of the data.

[0694] 3. Server analysis and keypoint extraction

[0695] The server analyzes the received user input data and emotional information. It uses natural language processing technology to analyze the text data and understand the content of the sentences. This analysis involves tokenization, POS tagging, and entity recognition. Furthermore, important key points are extracted from the data based on the emotions identified by the emotion engine. For example, "new product," "features," and "target market" are extracted, and the user's excitement level is also recorded.

[0696] 4. Generate presentation materials

[0697] The server generates presentation materials based on the extracted key points and emotion information. These materials include slides, diagrams, flow charts, and videos. For example, a "product overview" slide, a "feature" diagram, and a "sales process flow" are generated. The tone and style of the materials are adjusted to match the user's emotions. For example, if the user is excited, vibrant colors and dynamic elements are incorporated.

[0698] 5. Sending and Displaying Presentation Materials

[0699] The generated presentation materials are sent from the server to the terminal, which displays them to the user. The user can use the displayed materials to prepare a presentation and edit and customize the materials as needed.

[0700] Specific examples

[0701] For example, consider a case where a store staff member wants to explain the features of a new large-screen TV to a customer. The staff member uses a smartphone to voice-input, "This TV is 4K compatible, making it especially great for watching sports. What's more, it has great smart features." The emotion engine recognizes the staff member's excitement, and the data along with their emotion is sent to the server. The server analyzes the input data, extracts key points, and uses a generative AI model to create a presentation. The generated presentation includes a slide showing "Details about 4K compatibility" and a flowchart showing "How to use the smart features," all of which are vividly colored to convey the user's excitement.

[0702] Prompt Sentence Examples

[0703] "I want to create a presentation that explains the features of a new large-screen TV. I want people to pay particular attention to its 4K compatibility and smart features."

[0704] The above is an embodiment of the system for automatically creating presentation materials of the present invention. By using this system, users can create presentation materials quickly and effectively.

[0705] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0706] Step 1:

[0707] The user uses the device to input the ideas and content of the presentation using voice or text. At this point, input data is generated, and the emotion engine recognizes emotions from the voice or text. Specifically, when the user launches a smartphone app and says, "I'd like to introduce a new product, especially about its 4K compatibility and smart features," the voice data is passed to the emotion engine. The emotion engine processes the voice data and recognizes emotions such as "excitement." The input for this step is voice or text data, and the output is recognized emotion data.

[0708] Step 2:

[0709] The device sends the text entered by the user and the recognized emotion data to the server. This is done using HTTP requests or dedicated APIs. For example, the device converts voice data into text and sends the text data and emotion data to the server in JSON format. The input of this step is the text data and emotion data, and the data sent to the server is the output.

[0710] Step 3:

[0711] The server analyzes the received user input data and emotional data. Natural language processing technology is used for the analysis, and the entire sentence is understood based on the extracted key points. Specifically, the server performs tokenization, POS tagging, entity recognition, etc. on the received text data to extract key points such as "new product," "4K compatible," and "smart features." The input for this step is text data and emotional data, and the output is the extracted key points.

[0712] Step 4:

[0713] The server generates presentation materials based on the extracted key points and emotion data. Specifically, it creates slide templates, diagrams, flows, and videos. Generative AI models are used to adjust the tone and style to match the user's emotions. For example, the server might generate a title slide about a "new product," a diagram showing "4K compatibility details," and a "process flow for smart features." The input for this step is the extracted key points and emotion data, and the output is the generated presentation materials.

[0714] Step 5:

[0715] The generated presentation materials are sent from the server to the terminal. The generated materials are returned to the terminal via an HTTP response or a dedicated API. For example, the server sends the generated slides, diagrams, and flow to the terminal in JSON format. The input of this step is the generated presentation materials, and the output is the sent presentation materials.

[0716] Step 6:

[0717] The device displays the received presentation materials to the user. The user can prepare a presentation based on the displayed materials and edit and customize them as needed. For example, the device displays generated slides, and the user reviews them while practicing their presentation. The input of this step is the received presentation materials, and the output is the presentation materials displayed to the user.

[0718] The above is a specific processing flow of the automatic presentation material creation system.

[0719] 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.

[0720] 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.

[0721] 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.

[0722] [Third embodiment]

[0723] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0724] 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.

[0725] 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).

[0726] 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.

[0727] 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.

[0728] 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).

[0729] 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.

[0730] 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.

[0731] 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.

[0732] 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.

[0733] 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.

[0734] 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."

[0735] The AI ​​system for automatically creating presentation materials according to the present invention consists of three main components: a user, a terminal, and a server. This system is a technology that converts a user's ideas and content into easy-to-understand, effective presentation materials.

[0736] System Overview

[0737] The system begins by a user entering the idea and content of a presentation using a device. The entered data is sent from the device to a server, which analyzes the data and extracts key points. Presentation materials such as slides, diagrams, flow charts, and videos are then generated based on the key points. The generated presentation materials are then sent to the device and displayed to the user.

[0738] Detailed system description

[0739] 1. User idea input

[0740] The user uses the device to input the ideas and content of the presentation. Input is in text format. For example, the user might input something like, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[0741] 2. Data transmission

[0742] The device sends the user's input data to the server using an HTTP request or a dedicated API. The server receives this data and proceeds to the next step.

[0743] 3. Server analysis and keypoint extraction

[0744] The server analyzes the received data using natural language processing technology. As a result of the analysis, important key points are extracted from the data. For example, from the above input, key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24" are extracted.

[0745] 4. Generate presentation materials

[0746] The server generates presentation materials based on the extracted key points. Specifically, the following elements are generated:

[0747] Slides: Includes a title slide, an overview of your marketing strategy, details of your target market, the campaign implementation process, and success stories.

[0748] Figures: Generate age distribution maps of your target market, social media usage statistics, and graphs showing campaign effectiveness.

[0749] Flow: A flow diagram is generated showing the steps to execute the campaign.

[0750] Video: A scenario for a promotional video for the campaign is generated and the actual video is created.

[0751] 5. Sending presentation materials

[0752] The generated presentation materials are sent from the server to the device, using HTTP responses and dedicated APIs.

[0753] 6. Displaying presentation materials

[0754] The terminal displays the received presentation materials to the user, who can then use the displayed materials to prepare and practice their presentation.

[0755] Specific examples

[0756] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[0757] 1. User idea input: User inputs, "As a new marketing strategy, we are thinking of introducing a social media campaign. Our main target is young people aged 18-24."

[0758] 2. Sending data: The device sends this information to the server.

[0759] 3. Server analysis and key point extraction: The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24."

[0760] 4. Presentation material generation: Based on the key points, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios.

[0761] 5. Sending the presentation materials: The server sends these artifacts to the terminal.

[0762] 6. Displaying presentation materials: The terminal displays these to the user, who then uses the materials to prepare the presentation.

[0763] This concludes the description of an embodiment of the AI ​​system for automatically creating presentation materials of the present invention. By using this system, users can save time and effort while giving effective and attractive presentations.

[0764] The processing flow will be explained below.

[0765] Step 1:

[0766] The user uses the device to enter the idea or content of the presentation in text format. For example, the user might enter, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[0767] Step 2:

[0768] The device sends the user's input data to the server using HTTP requests or dedicated APIs, where the text entered by the user is accurately transferred to the server.

[0769] Step 3:

[0770] The server processes the received user input data. First, it uses natural language processing technology to analyze the text data and understand the content of the sentence. This analysis uses techniques such as tokenization, POS tagging, and entity recognition.

[0771] Step 4:

[0772] The server extracts key points from the analysis results. Key point extraction uses an algorithm to identify important phrases and concepts. For example, key points such as "marketing strategy," "social media campaign," and "target: 18-24 years old" are extracted.

[0773] Step 5:

[0774] The server generates the presentation materials based on the extracted key points. In this process, the following elements are generated:

[0775] Slide generation: Automatically generate presentation slides by combining slide templates stored in the server with key points, such as "Title slide," "Target market overview," "Campaign details," and "Success stories."

[0776] Diagram and flow generation: Generate graphs, charts, and flowcharts based on data related to key points. For example, a "target age distribution map" or a "campaign implementation process flow" can be generated.

[0777] Video generation: Create promotional video scenarios and videos using scripts and video templates.

[0778] Step 6:

[0779] The server sends the generated presentation materials to the device. This transmission is also done using HTTP responses or a dedicated API. The materials sent include slides, diagrams, flow charts, videos, etc.

[0780] Step 7:

[0781] The device displays the received presentation materials to the user, who can then use them to prepare and practice their presentation. The user can also edit and customize the materials as needed.

[0782] These are the processing steps of the generative AI system that automatically creates presentation materials. This specific processing flow enables users to quickly create high-quality presentation materials.

[0783] Example 1

[0784] 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."

[0785] In today's world, creating effective and engaging presentation materials in a short amount of time is an important challenge. However, many users find creating presentation materials time-consuming and laborious, and often fail to achieve satisfactory results due to a lack of technical knowledge. Furthermore, advanced analysis and generation techniques are required to effectively organize the content of presentation materials. Therefore, an efficient and effective method to solve these problems is needed.

[0786] 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.

[0787] In this invention, the server includes means for accepting input of ideas and content from a user, means for transmitting the input ideas and content to the server, means for analyzing the input ideas and content in the server using natural language processing technology and extracting key points, means for generating presentation materials using a generative AI model based on the key points, means for transmitting the generated presentation materials to a user's terminal, and means for displaying the generated presentation materials on the terminal, thereby enabling a user to automatically create effective presentation materials in a short amount of time.

[0788] "User" refers to an individual or organization that uses the system to create presentation materials.

[0789] "Ideas" refer to thoughts and ideas that a user inputs as content for presentation materials.

[0790] "Content" refers to the specific information or data that a user enters for inclusion in a presentation.

[0791] "Terminal" refers to an electronic device used by a user, such as a computer, smartphone, or tablet.

[0792] "Server" refers to a computer system that analyzes user input data and generates presentation materials.

[0793] "Natural language processing technology" is a technology that enables computers to understand and analyze human language.

[0794] "Key points" refer to important elements or information extracted from input ideas or content.

[0795] A "generative AI model" refers to an algorithm that uses artificial intelligence to automatically generate content such as text, images, and videos.

[0796] "Presentation materials" refers to materials in the form of slides, diagrams, flow charts, videos, etc. that are generated based on user input data.

[0797] An "HTTP request" is a type of protocol for sending data from a client to a server.

[0798] "API" is an abbreviation for Application Programming Interface, and refers to an interface that allows different software programs to communicate with each other.

[0799] MODE FOR CARRYING OUT THE INVENTION

[0800] The AI ​​system for automatically creating presentation materials according to the present invention is composed of three main components: a user, a terminal, and a server. The system of the present invention is a technology for converting a user's ideas and content into easy-to-understand, effective presentation materials.

[0801] The system begins operation when the user uses a device to input the idea and content of the presentation. For example, the user might input, "We are considering introducing a social media campaign as a new marketing strategy. Our main target is young people aged 18-24." The input data is sent from the device to a server, which analyzes the data and extracts key points. The server then implements natural language processing technology using spaCy and NLTK, natural language processing libraries for Python. As a result of the analysis, important key points are extracted from the data. For example, "new marketing strategy," "social media campaign," and "main target is young people aged 18-24."

[0802] The server then uses a generative AI model (e.g., OpenAI's GPT-4) to generate a presentation based on the extracted key points, including the following elements:

[0803] Slides: Title slide, marketing strategy overview, target market details, campaign implementation process, success stories, etc.

[0804] Figures: Age distribution of your target market, social media usage statistics, graphs showing campaign effectiveness, etc.

[0805] Flow: A flow diagram showing the steps to execute the campaign.

[0806] Video: A scenario for a promotional video for the campaign is generated, and the actual video may be created using FFmpeg and OpenCV.

[0807] The generated presentation materials are sent from the server to the device using HTTP responses or a dedicated API. The device displays the received presentation materials to the user, who can then use the displayed materials to prepare and practice their presentation.

[0808] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[0809] 1. User idea input:

[0810] The user types, "We're looking to launch a social media campaign as a new marketing strategy. Our primary target audience will be young people aged 18-24."

[0811] 2. Data transmission:

[0812] The terminal sends this information to the server.

[0813] 3. Server analysis and keypoint extraction:

[0814] The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24."

[0815] 4. Generate presentation materials:

[0816] Based on the key points, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios.

[0817] 5. Submitting presentation materials:

[0818] The server sends these products to the terminal.

[0819] 6. Viewing Presentation Materials:

[0820] The terminal displays this to the user, who then prepares a presentation based on the materials.

[0821] This system allows users to save time and effort while delivering effective and engaging presentations. It also utilizes generative AI models and natural language processing technology to automatically generate high-quality presentation materials.

[0822] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0823] Step 1:

[0824] The user uses the device to input the idea or content of the presentation in text format, for example, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[0825] Input: Presentation ideas and content

[0826] Output: Text data as user input

[0827] Step 2:

[0828] The terminal sends the text data entered by the user to the server using an HTTP request or a dedicated API. The transmission is triggered when the user clicks the "Send" button.

[0829] Input: Text data as user input

[0830] Output: Text data sent to the server

[0831] Step 3:

[0832] The server analyzes the received text data using natural language processing techniques, such as spaCy or NLTK, a Python natural language processing library, to extract key points from the text.

[0833] During the analysis process, important phrases and sentences are identified and listed as key points.

[0834] Input: Text data sent to the server

[0835] Output: List of key points (e.g., "New marketing strategy," "Social media campaign," "Primary target is young people aged 18-24")

[0836] Step 4:

[0837] The server generates presentation materials using a generative AI model (e.g., OpenAI's GPT-4) based on the extracted keypoints. The generation of presentation materials includes the following elements:

[0838] Slides: Title slide, marketing strategy overview, target market details, campaign implementation process, success stories, etc.

[0839] Figures: Age distribution of your target market, social media usage statistics, graphs showing campaign effectiveness, etc.

[0840] Flow: A flow diagram showing the steps to execute the campaign.

[0841] Video: A scenario for a promotional video for the campaign is generated, and the actual video may be created using FFmpeg and OpenCV.

[0842] Input: List of keypoints

[0843] Output: Generated presentation materials (slides, diagrams, flow charts, videos)

[0844] Step 5:

[0845] The server sends the generated presentation materials to the terminal via HTTP responses or a dedicated API. The materials are compressed and sent in JSON or XML format.

[0846] Input: Generated presentation materials

[0847] Output: Presentation materials sent to the device

[0848] Step 6:

[0849] The device displays the received presentation materials to the user, either using a dedicated viewer or through a web browser, where the user can review the materials and make corrections or additions as needed.

[0850] Input: Presentation materials received from the server

[0851] Output: Presentation material displayed to the user

[0852] The above are the specific processing steps of this system, which enables users to automatically generate high-quality presentation materials in a short amount of time.

[0853] (Application example 1)

[0854] 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."

[0855] Creating effective materials for advertising campaigns requires specialized knowledge and time, which places a significant burden on small businesses in particular. It is also difficult to consistently create high-quality materials that are appropriate for the target audience and key messages. Furthermore, it is often difficult to devote human resources and time to solving these problems, so automated methods are needed.

[0856] 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.

[0857] In this invention, the server includes means for accepting input of ideas and content from a user, means for transmitting the entered ideas and content to the server, means for analyzing the entered ideas and content in the server and extracting key points, means for accepting a target demographic, main messages, and a promotion plan from the user, means for automatically generating advertising campaign materials based on the accepted data, means for transmitting the generated presentation materials to the user's terminal, and means for displaying the generated presentation materials on the terminal, thereby enabling the automatic generation of advertising campaign materials and the provision of effective presentation materials.

[0858] "User" refers to any individual or legal entity that uses the System.

[0859] "Ideas" refer to ideas, concepts, and suggestions provided by users.

[0860] "Content" refers to information, data, theme settings, etc. provided by users.

[0861] "Server" refers to a computer system for processing data.

[0862] "Key points" refer to important items or main points extracted from ideas or content.

[0863] "Presentation materials" refers to materials that include slides, diagrams, flow charts, videos, etc., that allow users to visually convey information.

[0864] "Terminal" refers to an electronic device such as a computer, smartphone, or tablet that can be directly operated by a user.

[0865] "Target demographic" refers to the specific group of the population that a particular ad or campaign is aimed at.

[0866] "Key messages" are the most important information or concepts you want to communicate in your ad or campaign.

[0867] A "promotion plan" refers to a detailed strategy and execution plan for effectively promoting a product or service.

[0868] "Advertising Campaign Materials" means presentation materials and related materials generated for use for advertising purposes.

[0869] "Automatic generation" refers to the system autonomously creating materials with minimal human intervention.

[0870] "Natural language processing technology" refers to technology that enables computers to understand and analyze human language.

[0871] The system of the present invention consists of three main components: a user, a terminal, and a server, which enable the automatic generation of presentation materials for advertising campaigns.

[0872] User Input

[0873] The user uses the terminal to input the idea, content, target audience, main message, and promotion plan for the advertising campaign in text format. For example, they might input, "I'm thinking of creating an advertising campaign for the market launch of a new product. The main target audience is urban residents aged 25-35. The main message of the product is 'environmentally friendly.'"

[0874] Sending data

[0875] The terminal sends the user's input data to the server as an HTTP request using TLS (Transport Layer Security). This transmission method ensures data security and communication reliability.

[0876] Keypoint Extraction

[0877] The server analyzes the received data using natural language processing technology and extracts key points. The generative AI model used is OpenAI's "text-davinci-003," which extracts key points from the input data, such as "new product launch," "urban dwellers aged 25-35," and "environmentally friendly." Specifically, the following prompt sentences are used:

[0878] Extract the main key points from the following passage: "You are considering an advertising campaign for the launch of a new product. The primary target audience is urban dwellers aged 25-35. The key message of the product is 'environmentally friendly'."

[0879] Generate presentation materials

[0880] The server automatically generates presentation materials based on the extracted key points, including slides, diagrams, flow charts, videos, etc. Based on the generated presentation content, it generates detailed materials using the following prompt sentences:

[0881] Create a presentation for an advertising campaign based on the following key points: "New product launch, urban dwellers aged 25-35, environmentally friendly."

[0882] Sending and Displaying Data

[0883] The generated presentation materials are sent to the terminal via an HTTP response, and the terminal displays the received materials to the user, allowing the user to prepare for the presentation.

[0884] This system allows users to automatically generate presentation materials for advertising campaigns efficiently and with high quality. For example, based on the input data mentioned above, presentation materials emphasizing messages such as "new product launch" and "environmental friendliness" are displayed on the terminal.

[0885] This completes the description of the embodiment of the invention. By using this system, it is possible to automatically generate advertising campaign materials and provide effective presentation materials.

[0886] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0887] Step 1:

[0888] The user uses the terminal to input the idea, content, target audience, main message, and promotion plan for the advertising campaign in text format. The input information is, "We are thinking of an advertising campaign for the market launch of a new product. The main target audience is urban residents aged 25-35. The main message of the product is 'environmentally friendly'." The input data is prepared.

[0889] Step 2:

[0890] The terminal sends the input data to the server using an HTTP request. At this time, TLS (Transport Layer Security) is used to ensure the security and reliability of the data. The sent data is then received by the server.

[0891] Step 3:

[0892] The server analyzes the received data and extracts key points using natural language processing techniques. It uses OpenAI's "text-davinci-003" as a generative AI model and executes prompts.

[0893] Extract the main key points from the following passage: "You are considering an advertising campaign for the launch of a new product. The primary target audience is urban dwellers aged 25-35. The key message of the product is 'environmentally friendly'."

[0894] From the input data, key points such as "new product launch," "urban residents aged 25-35," and "environmentally friendly" are extracted.

[0895] Step 4:

[0896] The server generates a presentation based on the extracted key points, again using the OpenAI API and the following prompt:

[0897] Create a presentation for an advertising campaign based on the following key points: "New product launch, urban dwellers aged 25-35, environmentally friendly."

[0898] The generative AI model takes the key points as input and generates presentation materials including slides, diagrams, flow charts, and videos. The generated materials are prepared.

[0899] Step 5:

[0900] The server sends the generated presentation materials to the terminal via an HTTP response. The materials are packaged in JSON format and transmitted via a secure communication method.

[0901] Step 6:

[0902] The terminal displays the received presentation materials on a user interface, allowing the user to review the displayed materials and prepare for the presentation. The displayed content includes generated slides, diagrams, flow charts, and videos.

[0903] 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.

[0904] The AI ​​system for automatically creating presentation materials according to the present invention consists of four main components: a user, a terminal, a server, and an emotion engine. This system is a technology that converts the user's ideas and content into easy-to-understand and effective presentation materials, and also combines an emotion engine that recognizes and reflects the user's emotions.

[0905] System Overview

[0906] When a user uses a device to input ideas and content for a presentation, the emotion engine recognizes the user's emotions. The input data is sent from the device to a server, which analyzes the data and extracts key points. Presentation materials such as slides, diagrams, flow charts, and videos are generated based on the key points and edited to match the user's emotions. The generated presentation materials are then sent to the device and displayed to the user.

[0907] Detailed system description

[0908] 1. User idea input and emotion recognition

[0909] The user uses the device to input the idea and content of the presentation. At this time, the emotion engine analyzes the user's facial expressions, voice, and input content to identify their emotions. For example, if the user inputs, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target is young people aged 18-24," the engine will determine whether the user is excited or nervous.

[0910] 2. Data transmission

[0911] The device sends the user's input data and emotion information to the server using HTTP requests and dedicated APIs. The text and emotion data entered by the user are accurately transferred to the server.

[0912] 3. Server analysis and keypoint extraction

[0913] The server processes the received user input data and emotional information. First, it uses natural language processing technology to analyze the text data and understand the content of the sentences. This analysis uses techniques such as tokenization, POS tagging, and entity recognition. Next, it extracts important key points from the data, including the emotions identified by the emotion engine. For example, key points such as "marketing strategy," "social media campaign," and "target: 18-24 years old" are extracted, and the user's emotions are also recorded.

[0914] 4. Generate presentation materials

[0915] The server generates the presentation materials based on the extracted key points and emotion information. Specifically, the following elements are generated:

[0916] Slide generation: Automatically generate presentation slides by combining slide templates stored on the server with key points. For example, slides such as "title slide," "target market overview," "campaign details," and "success stories" are generated. The tone and style are adjusted to match the user's emotions.

[0917] Diagram and flow generation: Graphs, charts, and flowcharts are generated based on data related to key points. For example, a "target age distribution map" or a "campaign implementation process flow" can be generated. The design of the diagrams and flows is also adjusted according to the user's emotions to reflect their feelings.

[0918] Video Generation: Scripts and video templates are used to create promotional video scripts and animations, with the tone and style of the scripts and animations tailored to the emotions identified by the emotion engine.

[0919] 5. Sending presentation materials

[0920] The generated presentation materials are sent from the server to the device using HTTP responses or a dedicated API. The materials sent include slides, diagrams, flow charts, videos, and more.

[0921] 6. Displaying presentation materials

[0922] The device displays the received presentation materials to the user. The user can use the displayed materials to prepare and practice their presentation. They can also edit and customize the materials as needed. Materials generated based on the emotions identified by the emotion engine can more effectively convey the user's intentions.

[0923] Specific examples

[0924] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[0925] 1. User idea input and emotion recognition: The user inputs, "As a new marketing strategy, we are thinking of introducing a social media campaign. Our main target is young people aged 18-24." The emotion engine recognizes the user's excitement.

[0926] 2. Data transmission: The device transmits this information and emotion data to the server.

[0927] 3. Server analysis and key point extraction: The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24," while recording what the user is excited about.

[0928] 4. Presentation generation: Based on key points and emotion data, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios. The tone and style of the materials are adjusted to reflect the user's excitement and create a lively presentation.

[0929] 5. Sending the presentation materials: The server sends these artifacts to the terminal.

[0930] 6. Displaying presentation materials: The terminal displays these to the user, who then uses the materials to prepare the presentation.

[0931] The above is an embodiment of the present invention, which combines an emotion engine with a generative AI system for automatically creating presentation materials. By using this system, users can quickly create high-quality presentation materials that reflect their own emotions.

[0932] The processing flow will be explained below.

[0933] Step 1:

[0934] The user uses the device to enter the idea or content of the presentation in text format. For example, the user might enter, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[0935] Step 2:

[0936] The device's built-in emotion engine analyzes the user's facial expressions, voice, and input content while they are typing. For example, it can determine whether the user is excited or calm by capturing facial expressions with a camera and recording audio with a microphone.

[0937] Step 3:

[0938] The device sends the analyzed emotion data and the user's input text data to the server. This transmission uses data formatting and an HTTP request. The emotion data and text data are accurately transferred to the server.

[0939] Step 4:

[0940] The server analyzes the received text data using natural language processing technology to understand the content of the text. Specific analysis steps include tokenization, POS tagging, and entity recognition.

[0941] Step 5:

[0942] The server extracts key points from the analysis results. This process identifies and summarizes important phrases and concepts. For example, key points such as "marketing strategy," "social media campaign," and "target age group: 18-24 years old" are extracted.

[0943] Step 6:

[0944] The server analyzes the received emotional data and identifies the user's emotional state. The emotion engine determines whether the user is excited or calm based on data obtained from facial expression and voice analysis.

[0945] Step 7:

[0946] The server generates presentation materials based on the extracted key points and emotion data. The specific generation process includes the following elements:

[0947] Slide generation: The server automatically generates presentation slides using slide templates that reflect key points, including title slides, target market overviews, campaign details, and success stories. The tone and style are also adjusted to match the user's emotions.

[0948] Diagram and flow generation: Graphs, charts, and flowcharts are generated based on key points and related data. For example, a "target age distribution map" or a "campaign process flow" can be generated. Furthermore, the design tone and coloring can be adjusted based on the user's emotions.

[0949] Video Generation: Create promotional video scenarios and animations using scripts and video templates. The tone and style of the video are also adjusted based on user sentiment data.

[0950] Step 8:

[0951] The server sends the generated presentation materials to the device using HTTP responses or a dedicated API. The materials sent include slides, diagrams, flow charts, videos, etc.

[0952] Step 9:

[0953] The terminal displays the received presentation materials to the user, who can then practice and prepare for the presentation. The displayed materials can also be edited as needed. Materials that reflect the user's emotions will help them give more effective presentations.

[0954] These are the specific processing steps of the automatic presentation material generation system that combines an emotion engine that recognizes the user's emotions. These steps enable users to quickly create high-quality presentation materials that reflect their own emotions.

[0955] Example 2

[0956] 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."

[0957] Conventional presentation material creation systems require a great deal of time and effort for users to create their own materials, and it is difficult to create effective materials that reflect the user's emotions. Furthermore, materials that do not reflect emotions often fail to make an appropriate impact on the audience.

[0958] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting input of ideas or content from a user, means for analyzing the input idea or content and identifying the user's emotion, and means for transmitting the input idea or content and emotion information to the server. This enables the user to quickly create high-quality presentation materials that reflect his or her own emotions.

[0959] "User" refers to any individual or entity that uses this system to input ideas or content.

[0960] "Emotion engine" refers to a software component that analyzes input ideas and content and identifies the user's emotions.

[0961] "Terminal" refers to an electronic device that a user uses to input ideas or content and transmit that data to a server.

[0962] "Server" refers to a computer system that analyzes received data and generates presentation materials.

[0963] "Ideas" refer to thoughts and plans that users come up with and input into the system.

[0964] "Key points" refer to important information or key points extracted from input ideas or content.

[0965] "Presentation materials" refers to materials including slides, diagrams, flows, videos, etc. that are generated based on the user's ideas, content, and emotional information.

[0966] "Natural language processing technology" refers to technology that enables computers to understand, interpret, and generate human language.

[0967] "Slide generation" refers to the process of automatically creating slides based on key points and emotional information as part of a presentation deck.

[0968] "Diagram and flow generation" refers to the process of automatically creating graphs, charts, and flowcharts using data related to key points as part of a presentation deck.

[0969] The AI ​​system for automatically creating presentation materials according to the present invention consists of four main components: a user, a terminal, a server, and an emotion engine. This system is a technology that converts the user's ideas and content into easy-to-understand and effective presentation materials, and also combines an emotion engine that recognizes and reflects the user's emotions.

[0970] System Overview

[0971] When a user uses a device to input ideas and content for a presentation, the emotion engine recognizes the user's emotions. The input data is sent from the device to a server, which analyzes the data and extracts key points. Presentation materials such as slides, diagrams, flow charts, and videos are generated based on the key points and edited to match the user's emotions. The generated presentation materials are then sent to the device and displayed to the user.

[0972] Detailed system description

[0973] 1. User idea input and emotion recognition

[0974] The user uses the device to input ideas and content for the presentation. The device then uses a camera and microphone and an emotion engine to analyze the user's facial expressions, voice, and input to identify emotions. For example, if the user inputs, "As a new marketing strategy, we are considering introducing a social media campaign. Our primary target is young people aged 18-24," the device will analyze the user's emotions (such as excitement or nervousness) in real time.

[0975] 2. Data transmission

[0976] The device sends the user's input data and emotion information to the server using an HTTP request or a dedicated API. The device converts the emotion data into JSON format and sends it along with the user's text data. For example, the device sends the data to the endpoint using a POST request.

[0977] 3. Server analysis and keypoint extraction

[0978] The server processes the received user input data and emotional information. First, it uses natural language processing (NLP) techniques to analyze the text data. Python NLP libraries (such as SpaCy and NLTK) are used for this analysis. The server then integrates the emotions identified by the emotion engine and extracts important key points from the data. For example, key points such as "marketing strategy," "social media campaign," and "target age group: 18-24 years old" are extracted, and the user's emotions are also recorded.

[0979] 4. Generate presentation materials

[0980] The server generates a presentation based on the extracted key points and emotion information. The following elements are generated:

[0981] Slide generation: The server selects an appropriate template from multiple saved templates and arranges content based on key points. For example, slides such as "title slide," "target market overview," "campaign details," and "success stories" are generated. In this process, the server considers the user's emotional state (e.g., excitement) to select a lively design.

[0982] Figure and flow generation: The server automatically generates graphs, charts, and flowcharts based on data related to key points. Specifically, the server draws graphs based on the data using Python libraries such as Matplotlib and Plotly.

[0983] Video generation: The server uses scripts and video templates to generate promotional videos for presentations. The server uses video generation software (e.g., Adobe Premiere API or FFmpeg) based on emotion information to edit and create videos.

[0984] 5. Sending presentation materials

[0985] The server sends the generated presentation materials to the terminal. This is done using HTTP responses or a dedicated API. The server compresses the generated materials (PDF, PPT, video files, etc.) into a ZIP file and sends it as an HTTP response.

[0986] 6. Displaying presentation materials

[0987] The device displays the received presentation materials to the user. To display the materials in the appropriate format, the device uses tools such as a PDF viewer or video player. Specifically, the device unzips the received files and displays them in the interface so that the user can easily view and edit them.

[0988] Specific examples

[0989] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[0990] 1. User idea input and emotion recognition: When a user inputs, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target is young people aged 18-24," the device uses its emotion engine to recognize the user's state of excitement.

[0991] 2. Data transmission: The device transmits this information and emotion data to the server.

[0992] 3. Server analysis and key point extraction: The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24," while also recording what the user is excited about.

[0993] 4. Presentation generation: Based on key points and emotion data, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios. The tone and style of the presentation materials are adjusted to reflect the user's excitement and make them more lively.

[0994] 5. Sending presentation materials: The server sends the generated materials to the terminal.

[0995] 6. Displaying presentation materials: The terminal displays the materials to the user, who then prepares the presentation based on them.

[0996] The above is a detailed description of an embodiment of the AI ​​system for automatically creating presentation materials of the present invention. By using this system, users can quickly create high-quality presentation materials that reflect their own emotions.

[0997] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0998] Step 1: User idea input and emotion recognition

[0999] The user uses the device to input the ideas and content of the presentation. Specifically, they input text information using the device's keyboard or voice input function. At the same time, the device uses its built-in camera and microphone to capture the user's facial expressions and voice. Based on this, the device uses an emotion engine to perform facial expression recognition and voice analysis to identify the user's emotions (excitement, nervousness, etc.) in real time. Input data (text information) and emotional data (excitement, nervousness, etc.) are generated.

[1000] Step 2: Sending data

[1001] The device sends the input data (text information) and emotion data obtained in step 1 to the server. Specifically, this data is converted into JSON format and sent to the server's API endpoint via an HTTP POST request. The input includes text data and emotion data, and the output is the accurate transfer of this data to the server.

[1002] Step 3: Server analysis and keypoint extraction

[1003] The server analyzes the data received in step 2. First, the server uses natural language processing (NLP) techniques to analyze the text data. Specifically, the server uses a Python NLP library (such as SpaCy or NLTK) to perform tokenization, POS tagging, and entity recognition. This analyzes the content of the text and extracts key points. In parallel, the server also analyzes the sentiment data and records the user's sentiment information. The inputs are text data and sentiment data, and the output is key points and sentiment information.

[1004] Step 4: Generate presentation materials

[1005] The server generates the presentation materials based on the key points and emotion information obtained in step 3. Specifically, the following elements are generated:

[1006] Slide generation: The server selects an appropriate template from multiple stored templates and arranges content based on key points. The template and design are selected taking into account the user's emotional state.

[1007] Figure and flow generation: The server uses data related to key points to automatically generate graphs, charts, and flowcharts using Python libraries such as Matplotlib and Plotly.

[1008] Video generation: The server uses video generation software (such as Adobe Premiere API or FFmpeg) to edit and create a promotional video based on the emotional information. The inputs are key points and emotional information, and the output is presentation materials such as slides, diagrams, flow charts, and videos.

[1009] Step 5: Send your presentation materials

[1010] The server sends the presentation materials generated in step 4 to the terminal. Specifically, the generated materials (PDF, PPT, video files, etc.) are compressed into a ZIP file and sent via an HTTP response or a dedicated API. The input is the generated presentation materials, and the output is the data sent back to the terminal.

[1011] Step 6: View your presentation materials

[1012] The terminal displays the presentation materials received in step 5 to the user. Specifically, it displays the extracted materials using an appropriate viewer or player (PDF viewer, video player, etc.). The user can also view and edit the materials as needed. The input is the presentation materials sent from the server, and the output is the materials to be displayed. The user prepares the presentation based on these materials.

[1013] (Application example 2)

[1014] 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."

[1015] Creating presentation materials requires time and effort, and it is particularly difficult to create effective presentation materials that reflect the user's emotions and intentions. Furthermore, there is a need for a method to quickly create appropriate materials when staff in physical stores explain products and provide promotions to customers. Conventional methods have difficulty generating presentation materials that incorporate the user's emotions, making it difficult to provide effective explanations to customers.

[1016] 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.

[1017] In this invention, the server includes means for analyzing ideas and content input by a user and extracting key points, means for generating presentation materials based on the extracted key points, and means for recognizing the user's emotions and adjusting the tone and style of the presentation materials based on those emotions, thereby enabling the rapid creation of presentation materials that reflect the user's emotions.

[1018] "User" refers to a person who inputs ideas and content for creating presentation materials.

[1019] "Server" refers to a computer system that analyzes ideas and content sent by users and generates presentation materials.

[1020] "Means for accepting input of ideas or content" refers to an interface through which users can input their own thoughts or information.

[1021] "Means for transmitting ideas or content to a server" refers to a device or software that transmits information entered by a user to a server.

[1022] "Means for extracting key points" refers to technology that identifies and extracts important elements and information from the content entered by the user.

[1023] "Means for generating presentation materials" refers to a technology for creating presentation materials such as slides, diagrams, flow charts, and videos based on the extracted key points.

[1024] The term "means for transmitting presentation materials to a user's terminal" refers to a device or software for transmitting the generated presentation materials to a device used by a user.

[1025] The term "means for displaying presentation materials" refers to a device or software that visually displays the presentation materials generated on a user's terminal.

[1026] "Means for recognizing emotions" refers to technology that analyzes the user's voice and facial expressions to determine the user's emotional state.

[1027] "Means for adjusting the tone and style of presentation materials based on emotions" refers to techniques that change the visual and content style of presentation materials in response to perceived emotions.

[1028] "Users in physical stores" refers to staff who need presentation materials when explaining products and promotions in stores.

[1029] The system for automatically creating presentation materials based on this invention consists of four main components: a user, a terminal, a server, and an emotion engine. This system aims to effectively generate presentation materials, and is characterized by its ability to reflect the user's emotions.

[1030] Overall system overview

[1031] When a user uses a device to input ideas and content for a presentation, the emotion engine recognizes the user's emotions. The input data is sent from the device to the server, which analyzes the data and extracts key points. Presentation materials are generated based on the extracted key points and edited to match the user's emotions. The generated presentation materials are then sent to the device, where the user can view and use them.

[1032] Hardware and software used

[1033] Hardware: smartphone, microphone, camera

[1034] Software: Python, requests, emotion recognition model, presentation generation AI model (e.g., Transformers)

[1035] Functions of each component

[1036] 1. User idea input and emotion recognition

[1037] Users use devices such as smartphones to input ideas and content for their presentations using voice or text. At this time, the emotion engine analyzes the user's voice and facial expressions to recognize their emotions. For example, if a user inputs "I would like to introduce a new product," the voice data is analyzed to determine whether the user is excited or calm.

[1038] 2. Data transmission

[1039] The device sends the text and emotion data entered by the user to the server using HTTP requests and a dedicated API to ensure accurate transmission of the data.

[1040] 3. Server analysis and keypoint extraction

[1041] The server analyzes the received user input data and emotional information. It uses natural language processing technology to analyze the text data and understand the content of the sentences. This analysis involves tokenization, POS tagging, and entity recognition. Furthermore, important key points are extracted from the data based on the emotions identified by the emotion engine. For example, "new product," "features," and "target market" are extracted, and the user's excitement level is also recorded.

[1042] 4. Generate presentation materials

[1043] The server generates presentation materials based on the extracted key points and emotion information. These materials include slides, diagrams, flow charts, and videos. For example, a "product overview" slide, a "feature" diagram, and a "sales process flow" are generated. The tone and style of the materials are adjusted to match the user's emotions. For example, if the user is excited, vibrant colors and dynamic elements are incorporated.

[1044] 5. Sending and Displaying Presentation Materials

[1045] The generated presentation materials are sent from the server to the terminal, which displays them to the user. The user can use the displayed materials to prepare a presentation and edit and customize the materials as needed.

[1046] Specific examples

[1047] For example, consider a case where a store staff member wants to explain the features of a new large-screen TV to a customer. The staff member uses a smartphone to voice-input, "This TV is 4K compatible, making it especially great for watching sports. What's more, it has great smart features." The emotion engine recognizes the staff member's excitement, and the data along with their emotion is sent to the server. The server analyzes the input data, extracts key points, and uses a generative AI model to create a presentation. The generated presentation includes a slide showing "Details about 4K compatibility" and a flowchart showing "How to use the smart features," all of which are vividly colored to convey the user's excitement.

[1048] Prompt Sentence Examples

[1049] "I want to create a presentation that explains the features of a new large-screen TV. I want people to pay particular attention to its 4K compatibility and smart features."

[1050] The above is an embodiment of the system for automatically creating presentation materials of the present invention. By using this system, users can create presentation materials quickly and effectively.

[1051] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1052] Step 1:

[1053] The user uses the device to input the ideas and content of the presentation using voice or text. At this point, input data is generated, and the emotion engine recognizes emotions from the voice or text. Specifically, when the user launches a smartphone app and says, "I'd like to introduce a new product, especially about its 4K compatibility and smart features," the voice data is passed to the emotion engine. The emotion engine processes the voice data and recognizes emotions such as "excitement." The input for this step is voice or text data, and the output is recognized emotion data.

[1054] Step 2:

[1055] The device sends the text entered by the user and the recognized emotion data to the server. This is done using HTTP requests or dedicated APIs. For example, the device converts voice data into text and sends the text data and emotion data to the server in JSON format. The input of this step is the text data and emotion data, and the data sent to the server is the output.

[1056] Step 3:

[1057] The server analyzes the received user input data and emotional data. Natural language processing technology is used for the analysis, and the entire sentence is understood based on the extracted key points. Specifically, the server performs tokenization, POS tagging, entity recognition, etc. on the received text data to extract key points such as "new product," "4K compatible," and "smart features." The input for this step is text data and emotional data, and the output is the extracted key points.

[1058] Step 4:

[1059] The server generates presentation materials based on the extracted key points and emotion data. Specifically, it creates slide templates, diagrams, flows, and videos. Generative AI models are used to adjust the tone and style to match the user's emotions. For example, the server might generate a title slide about a "new product," a diagram showing "4K compatibility details," and a "process flow for smart features." The input for this step is the extracted key points and emotion data, and the output is the generated presentation materials.

[1060] Step 5:

[1061] The generated presentation materials are sent from the server to the terminal. The generated materials are returned to the terminal via an HTTP response or a dedicated API. For example, the server sends the generated slides, diagrams, and flow to the terminal in JSON format. The input of this step is the generated presentation materials, and the output is the sent presentation materials.

[1062] Step 6:

[1063] The device displays the received presentation materials to the user. The user can prepare a presentation based on the displayed materials and edit and customize them as needed. For example, the device displays generated slides, and the user reviews them while practicing their presentation. The input of this step is the received presentation materials, and the output is the presentation materials displayed to the user.

[1064] The above is a specific processing flow of the automatic presentation material creation system.

[1065] 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.

[1066] 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.

[1067] 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.

[1068] [Fourth embodiment]

[1069] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1070] 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.

[1071] 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).

[1072] 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.

[1073] 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.

[1074] 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).

[1075] 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.

[1076] 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.

[1077] 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.

[1078] 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.

[1079] 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.

[1080] 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.

[1081] 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."

[1082] The AI ​​system for automatically creating presentation materials according to the present invention consists of three main components: a user, a terminal, and a server. This system is a technology that converts a user's ideas and content into easy-to-understand, effective presentation materials.

[1083] System Overview

[1084] The system begins by a user entering the idea and content of a presentation using a device. The entered data is sent from the device to a server, which analyzes the data and extracts key points. Presentation materials such as slides, diagrams, flow charts, and videos are then generated based on the key points. The generated presentation materials are then sent to the device and displayed to the user.

[1085] Detailed system description

[1086] 1. User idea input

[1087] The user uses the device to input the ideas and content of the presentation. Input is in text format. For example, the user might input something like, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[1088] 2. Data transmission

[1089] The device sends the user's input data to the server using an HTTP request or a dedicated API. The server receives this data and proceeds to the next step.

[1090] 3. Server analysis and keypoint extraction

[1091] The server analyzes the received data using natural language processing technology. As a result of the analysis, important key points are extracted from the data. For example, from the above input, key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24" are extracted.

[1092] 4. Generate presentation materials

[1093] The server generates presentation materials based on the extracted key points. Specifically, the following elements are generated:

[1094] Slides: Includes a title slide, an overview of your marketing strategy, details of your target market, the campaign implementation process, and success stories.

[1095] Figures: Generate age distribution maps of your target market, social media usage statistics, and graphs showing campaign effectiveness.

[1096] Flow: A flow diagram is generated showing the steps to execute the campaign.

[1097] Video: A scenario for a promotional video for the campaign is generated and the actual video is created.

[1098] 5. Sending presentation materials

[1099] The generated presentation materials are sent from the server to the device, using HTTP responses and dedicated APIs.

[1100] 6. Displaying presentation materials

[1101] The terminal displays the received presentation materials to the user, who can then use the displayed materials to prepare and practice their presentation.

[1102] Specific examples

[1103] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[1104] 1. User idea input: User inputs, "As a new marketing strategy, we are thinking of introducing a social media campaign. Our main target is young people aged 18-24."

[1105] 2. Sending data: The device sends this information to the server.

[1106] 3. Server analysis and key point extraction: The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24."

[1107] 4. Presentation material generation: Based on the key points, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios.

[1108] 5. Sending the presentation materials: The server sends these artifacts to the terminal.

[1109] 6. Displaying presentation materials: The terminal displays these to the user, who then uses the materials to prepare the presentation.

[1110] This concludes the description of an embodiment of the AI ​​system for automatically creating presentation materials of the present invention. By using this system, users can save time and effort while giving effective and attractive presentations.

[1111] The processing flow will be explained below.

[1112] Step 1:

[1113] The user uses the device to enter the idea or content of the presentation in text format. For example, the user might enter, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[1114] Step 2:

[1115] The device sends the user's input data to the server using HTTP requests or dedicated APIs, where the text entered by the user is accurately transferred to the server.

[1116] Step 3:

[1117] The server processes the received user input data. First, it uses natural language processing technology to analyze the text data and understand the content of the sentence. This analysis uses techniques such as tokenization, POS tagging, and entity recognition.

[1118] Step 4:

[1119] The server extracts key points from the analysis results. Key point extraction uses an algorithm to identify important phrases and concepts. For example, key points such as "marketing strategy," "social media campaign," and "target: 18-24 years old" are extracted.

[1120] Step 5:

[1121] The server generates the presentation materials based on the extracted key points. In this process, the following elements are generated:

[1122] Slide generation: Automatically generate presentation slides by combining slide templates stored in the server with key points, such as "Title slide," "Target market overview," "Campaign details," and "Success stories."

[1123] Diagram and flow generation: Generate graphs, charts, and flowcharts based on data related to key points. For example, a "target age distribution map" or a "campaign implementation process flow" can be generated.

[1124] Video generation: Create promotional video scenarios and videos using scripts and video templates.

[1125] Step 6:

[1126] The server sends the generated presentation materials to the device. This transmission is also done using HTTP responses or a dedicated API. The materials sent include slides, diagrams, flow charts, videos, etc.

[1127] Step 7:

[1128] The device displays the received presentation materials to the user, who can then use them to prepare and practice their presentation. The user can also edit and customize the materials as needed.

[1129] These are the processing steps of the generative AI system that automatically creates presentation materials. This specific processing flow enables users to quickly create high-quality presentation materials.

[1130] Example 1

[1131] 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."

[1132] In today's world, creating effective and engaging presentation materials in a short amount of time is an important challenge. However, many users find creating presentation materials time-consuming and laborious, and often fail to achieve satisfactory results due to a lack of technical knowledge. Furthermore, advanced analysis and generation techniques are required to effectively organize the content of presentation materials. Therefore, an efficient and effective method to solve these problems is needed.

[1133] 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.

[1134] In this invention, the server includes means for accepting input of ideas and content from a user, means for transmitting the input ideas and content to the server, means for analyzing the input ideas and content in the server using natural language processing technology and extracting key points, means for generating presentation materials using a generative AI model based on the key points, means for transmitting the generated presentation materials to a user's terminal, and means for displaying the generated presentation materials on the terminal, thereby enabling a user to automatically create effective presentation materials in a short amount of time.

[1135] "User" refers to an individual or organization that uses the system to create presentation materials.

[1136] "Ideas" refer to thoughts and ideas that a user inputs as content for presentation materials.

[1137] "Content" refers to the specific information or data that a user enters for inclusion in a presentation.

[1138] "Terminal" refers to an electronic device used by a user, such as a computer, smartphone, or tablet.

[1139] "Server" refers to a computer system that analyzes user input data and generates presentation materials.

[1140] "Natural language processing technology" is a technology that enables computers to understand and analyze human language.

[1141] "Key points" refer to important elements or information extracted from input ideas or content.

[1142] A "generative AI model" refers to an algorithm that uses artificial intelligence to automatically generate content such as text, images, and videos.

[1143] "Presentation materials" refers to materials in the form of slides, diagrams, flow charts, videos, etc. that are generated based on user input data.

[1144] An "HTTP request" is a type of protocol for sending data from a client to a server.

[1145] "API" is an abbreviation for Application Programming Interface, and refers to an interface that allows different software programs to communicate with each other.

[1146] MODE FOR CARRYING OUT THE INVENTION

[1147] The AI ​​system for automatically creating presentation materials according to the present invention is composed of three main components: a user, a terminal, and a server. The system of the present invention is a technology for converting a user's ideas and content into easy-to-understand, effective presentation materials.

[1148] The system begins operation when the user uses a device to input the idea and content of the presentation. For example, the user might input, "We are considering introducing a social media campaign as a new marketing strategy. Our main target is young people aged 18-24." The input data is sent from the device to a server, which analyzes the data and extracts key points. The server then implements natural language processing technology using spaCy and NLTK, natural language processing libraries for Python. As a result of the analysis, important key points are extracted from the data. For example, "new marketing strategy," "social media campaign," and "main target is young people aged 18-24."

[1149] The server then uses a generative AI model (e.g., OpenAI's GPT-4) to generate a presentation based on the extracted key points, including the following elements:

[1150] Slides: Title slide, marketing strategy overview, target market details, campaign implementation process, success stories, etc.

[1151] Figures: Age distribution of your target market, social media usage statistics, graphs showing campaign effectiveness, etc.

[1152] Flow: A flow diagram showing the steps to execute the campaign.

[1153] Video: A scenario for a promotional video for the campaign is generated, and the actual video may be created using FFmpeg and OpenCV.

[1154] The generated presentation materials are sent from the server to the device using HTTP responses or a dedicated API. The device displays the received presentation materials to the user, who can then use the displayed materials to prepare and practice their presentation.

[1155] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[1156] 1. User idea input:

[1157] The user types, "We're looking to launch a social media campaign as a new marketing strategy. Our primary target audience will be young people aged 18-24."

[1158] 2. Data transmission:

[1159] The terminal sends this information to the server.

[1160] 3. Server analysis and keypoint extraction:

[1161] The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24."

[1162] 4. Generate presentation materials:

[1163] Based on the key points, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios.

[1164] 5. Submitting presentation materials:

[1165] The server sends these products to the terminal.

[1166] 6. Viewing Presentation Materials:

[1167] The terminal displays this to the user, who then prepares a presentation based on the materials.

[1168] This system allows users to save time and effort while delivering effective and engaging presentations. It also utilizes generative AI models and natural language processing technology to automatically generate high-quality presentation materials.

[1169] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1170] Step 1:

[1171] The user uses the device to input the idea or content of the presentation in text format, for example, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[1172] Input: Presentation ideas and content

[1173] Output: Text data as user input

[1174] Step 2:

[1175] The terminal sends the text data entered by the user to the server using an HTTP request or a dedicated API. The transmission is triggered when the user clicks the "Send" button.

[1176] Input: Text data as user input

[1177] Output: Text data sent to the server

[1178] Step 3:

[1179] The server analyzes the received text data using natural language processing techniques, such as spaCy or NLTK, a Python natural language processing library, to extract key points from the text.

[1180] During the analysis process, important phrases and sentences are identified and listed as key points.

[1181] Input: Text data sent to the server

[1182] Output: List of key points (e.g., "New marketing strategy," "Social media campaign," "Primary target is young people aged 18-24")

[1183] Step 4:

[1184] The server generates presentation materials using a generative AI model (e.g., OpenAI's GPT-4) based on the extracted keypoints. The generation of presentation materials includes the following elements:

[1185] Slides: Title slide, marketing strategy overview, target market details, campaign implementation process, success stories, etc.

[1186] Figures: Age distribution of your target market, social media usage statistics, graphs showing campaign effectiveness, etc.

[1187] Flow: A flow diagram showing the steps to execute the campaign.

[1188] Video: A scenario for a promotional video for the campaign is generated, and the actual video may be created using FFmpeg and OpenCV.

[1189] Input: List of keypoints

[1190] Output: Generated presentation materials (slides, diagrams, flow charts, videos)

[1191] Step 5:

[1192] The server sends the generated presentation materials to the terminal via HTTP responses or a dedicated API. The materials are compressed and sent in JSON or XML format.

[1193] Input: Generated presentation materials

[1194] Output: Presentation materials sent to the device

[1195] Step 6:

[1196] The device displays the received presentation materials to the user, either using a dedicated viewer or through a web browser, where the user can review the materials and make corrections or additions as needed.

[1197] Input: Presentation materials received from the server

[1198] Output: Presentation material displayed to the user

[1199] The above are the specific processing steps of this system, which enables users to automatically generate high-quality presentation materials in a short amount of time.

[1200] (Application example 1)

[1201] 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."

[1202] Creating effective materials for advertising campaigns requires specialized knowledge and time, which places a significant burden on small businesses in particular. It is also difficult to consistently create high-quality materials that are appropriate for the target audience and key messages. Furthermore, it is often difficult to devote human resources and time to solving these problems, so automated methods are needed.

[1203] 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.

[1204] In this invention, the server includes means for accepting input of ideas and content from a user, means for transmitting the entered ideas and content to the server, means for analyzing the entered ideas and content in the server and extracting key points, means for accepting a target demographic, main messages, and a promotion plan from the user, means for automatically generating advertising campaign materials based on the accepted data, means for transmitting the generated presentation materials to the user's terminal, and means for displaying the generated presentation materials on the terminal, thereby enabling the automatic generation of advertising campaign materials and the provision of effective presentation materials.

[1205] "User" refers to any individual or legal entity that uses the System.

[1206] "Ideas" refer to ideas, concepts, and suggestions provided by users.

[1207] "Content" refers to information, data, theme settings, etc. provided by users.

[1208] "Server" refers to a computer system for processing data.

[1209] "Key points" refer to important items or main points extracted from ideas or content.

[1210] "Presentation materials" refers to materials that include slides, diagrams, flow charts, videos, etc., that allow users to visually convey information.

[1211] "Terminal" refers to an electronic device such as a computer, smartphone, or tablet that can be directly operated by a user.

[1212] "Target demographic" refers to the specific group of the population that a particular ad or campaign is aimed at.

[1213] "Key messages" are the most important information or concepts you want to communicate in your ad or campaign.

[1214] A "promotion plan" refers to a detailed strategy and execution plan for effectively promoting a product or service.

[1215] "Advertising Campaign Materials" means presentation materials and related materials generated for use for advertising purposes.

[1216] "Automatic generation" refers to the system autonomously creating materials with minimal human intervention.

[1217] "Natural language processing technology" refers to technology that enables computers to understand and analyze human language.

[1218] The system of the present invention consists of three main components: a user, a terminal, and a server, which enable the automatic generation of presentation materials for advertising campaigns.

[1219] User Input

[1220] The user uses the terminal to input the idea, content, target audience, main message, and promotion plan for the advertising campaign in text format. For example, they might input, "I'm thinking of creating an advertising campaign for the market launch of a new product. The main target audience is urban residents aged 25-35. The main message of the product is 'environmentally friendly.'"

[1221] Sending data

[1222] The terminal sends the user's input data to the server as an HTTP request using TLS (Transport Layer Security). This transmission method ensures data security and communication reliability.

[1223] Keypoint Extraction

[1224] The server analyzes the received data using natural language processing technology and extracts key points. The generative AI model used is OpenAI's "text-davinci-003," which extracts key points from the input data, such as "new product launch," "urban dwellers aged 25-35," and "environmentally friendly." Specifically, the following prompt sentences are used:

[1225] Extract the main key points from the following passage: "You are considering an advertising campaign for the launch of a new product. The primary target audience is urban dwellers aged 25-35. The key message of the product is 'environmentally friendly'."

[1226] Generate presentation materials

[1227] The server automatically generates presentation materials based on the extracted key points, including slides, diagrams, flow charts, videos, etc. Based on the generated presentation content, it generates detailed materials using the following prompt sentences:

[1228] Create a presentation for an advertising campaign based on the following key points: "New product launch, urban dwellers aged 25-35, environmentally friendly."

[1229] Sending and Displaying Data

[1230] The generated presentation materials are sent to the terminal via an HTTP response, and the terminal displays the received materials to the user, allowing the user to prepare for the presentation.

[1231] This system allows users to automatically generate presentation materials for advertising campaigns efficiently and with high quality. For example, based on the input data mentioned above, presentation materials emphasizing messages such as "new product launch" and "environmental friendliness" are displayed on the terminal.

[1232] This completes the description of the embodiment of the invention. By using this system, it is possible to automatically generate advertising campaign materials and provide effective presentation materials.

[1233] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1234] Step 1:

[1235] The user uses the terminal to input the idea, content, target audience, main message, and promotion plan for the advertising campaign in text format. The input information is, "We are thinking of an advertising campaign for the market launch of a new product. The main target audience is urban residents aged 25-35. The main message of the product is 'environmentally friendly'." The input data is prepared.

[1236] Step 2:

[1237] The terminal sends the input data to the server using an HTTP request. At this time, TLS (Transport Layer Security) is used to ensure the security and reliability of the data. The sent data is then received by the server.

[1238] Step 3:

[1239] The server analyzes the received data and extracts key points using natural language processing techniques. It uses OpenAI's "text-davinci-003" as a generative AI model and executes prompts.

[1240] Extract the main key points from the following passage: "You are considering an advertising campaign for the launch of a new product. The primary target audience is urban dwellers aged 25-35. The key message of the product is 'environmentally friendly'."

[1241] From the input data, key points such as "new product launch," "urban residents aged 25-35," and "environmentally friendly" are extracted.

[1242] Step 4:

[1243] The server generates a presentation based on the extracted key points, again using the OpenAI API and the following prompt:

[1244] Create a presentation for an advertising campaign based on the following key points: "New product launch, urban dwellers aged 25-35, environmentally friendly."

[1245] The generative AI model takes the key points as input and generates presentation materials including slides, diagrams, flow charts, and videos. The generated materials are prepared.

[1246] Step 5:

[1247] The server sends the generated presentation materials to the terminal via an HTTP response. The materials are packaged in JSON format and transmitted via a secure communication method.

[1248] Step 6:

[1249] The terminal displays the received presentation materials on a user interface, allowing the user to review the displayed materials and prepare for the presentation. The displayed content includes generated slides, diagrams, flow charts, and videos.

[1250] 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.

[1251] The AI ​​system for automatically creating presentation materials according to the present invention consists of four main components: a user, a terminal, a server, and an emotion engine. This system is a technology that converts the user's ideas and content into easy-to-understand and effective presentation materials, and also combines an emotion engine that recognizes and reflects the user's emotions.

[1252] System Overview

[1253] When a user uses a device to input ideas and content for a presentation, the emotion engine recognizes the user's emotions. The input data is sent from the device to a server, which analyzes the data and extracts key points. Presentation materials such as slides, diagrams, flow charts, and videos are generated based on the key points and edited to match the user's emotions. The generated presentation materials are then sent to the device and displayed to the user.

[1254] Detailed system description

[1255] 1. User idea input and emotion recognition

[1256] The user uses the device to input the idea and content of the presentation. At this time, the emotion engine analyzes the user's facial expressions, voice, and input content to identify their emotions. For example, if the user inputs, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target is young people aged 18-24," the engine will determine whether the user is excited or nervous.

[1257] 2. Data transmission

[1258] The device sends the user's input data and emotion information to the server using HTTP requests and dedicated APIs. The text and emotion data entered by the user are accurately transferred to the server.

[1259] 3. Server analysis and keypoint extraction

[1260] The server processes the received user input data and emotional information. First, it uses natural language processing technology to analyze the text data and understand the content of the sentences. This analysis uses techniques such as tokenization, POS tagging, and entity recognition. Next, it extracts important key points from the data, including the emotions identified by the emotion engine. For example, key points such as "marketing strategy," "social media campaign," and "target: 18-24 years old" are extracted, and the user's emotions are also recorded.

[1261] 4. Generate presentation materials

[1262] The server generates the presentation materials based on the extracted key points and emotion information. Specifically, the following elements are generated:

[1263] Slide generation: Automatically generate presentation slides by combining slide templates stored on the server with key points. For example, slides such as "title slide," "target market overview," "campaign details," and "success stories" are generated. The tone and style are adjusted to match the user's emotions.

[1264] Diagram and flow generation: Graphs, charts, and flowcharts are generated based on data related to key points. For example, a "target age distribution map" or a "campaign implementation process flow" can be generated. The design of the diagrams and flows is also adjusted according to the user's emotions to reflect their feelings.

[1265] Video Generation: Scripts and video templates are used to create promotional video scripts and animations, with the tone and style of the scripts and animations tailored to the emotions identified by the emotion engine.

[1266] 5. Sending presentation materials

[1267] The generated presentation materials are sent from the server to the device using HTTP responses or a dedicated API. The materials sent include slides, diagrams, flow charts, videos, and more.

[1268] 6. Displaying presentation materials

[1269] The device displays the received presentation materials to the user. The user can use the displayed materials to prepare and practice their presentation. They can also edit and customize the materials as needed. Materials generated based on the emotions identified by the emotion engine can more effectively convey the user's intentions.

[1270] Specific examples

[1271] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[1272] 1. User idea input and emotion recognition: The user inputs, "As a new marketing strategy, we are thinking of introducing a social media campaign. Our main target is young people aged 18-24." The emotion engine recognizes the user's excitement.

[1273] 2. Data transmission: The device transmits this information and emotion data to the server.

[1274] 3. Server analysis and key point extraction: The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24," while recording what the user is excited about.

[1275] 4. Presentation generation: Based on key points and emotion data, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios. The tone and style of the materials are adjusted to reflect the user's excitement and create a lively presentation.

[1276] 5. Sending the presentation materials: The server sends these artifacts to the terminal.

[1277] 6. Displaying presentation materials: The terminal displays these to the user, who then uses the materials to prepare the presentation.

[1278] The above is an embodiment of the present invention, which combines an emotion engine with a generative AI system for automatically creating presentation materials. By using this system, users can quickly create high-quality presentation materials that reflect their own emotions.

[1279] The processing flow will be explained below.

[1280] Step 1:

[1281] The user uses the device to enter the idea or content of the presentation in text format. For example, the user might enter, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target audience is young people aged 18-24."

[1282] Step 2:

[1283] The device's built-in emotion engine analyzes the user's facial expressions, voice, and input content while they are typing. For example, it can determine whether the user is excited or calm by capturing facial expressions with a camera and recording audio with a microphone.

[1284] Step 3:

[1285] The device sends the analyzed emotion data and the user's input text data to the server. This transmission uses data formatting and an HTTP request. The emotion data and text data are accurately transferred to the server.

[1286] Step 4:

[1287] The server analyzes the received text data using natural language processing technology to understand the content of the text. Specific analysis steps include tokenization, POS tagging, and entity recognition.

[1288] Step 5:

[1289] The server extracts key points from the analysis results. This process identifies and summarizes important phrases and concepts. For example, key points such as "marketing strategy," "social media campaign," and "target age group: 18-24 years old" are extracted.

[1290] Step 6:

[1291] The server analyzes the received emotional data and identifies the user's emotional state. The emotion engine determines whether the user is excited or calm based on data obtained from facial expression and voice analysis.

[1292] Step 7:

[1293] The server generates presentation materials based on the extracted key points and emotion data. The specific generation process includes the following elements:

[1294] Slide generation: The server automatically generates presentation slides using slide templates that reflect key points, including title slides, target market overviews, campaign details, and success stories. The tone and style are also adjusted to match the user's emotions.

[1295] Diagram and flow generation: Graphs, charts, and flowcharts are generated based on key points and related data. For example, a "target age distribution map" or a "campaign process flow" can be generated. Furthermore, the design tone and coloring can be adjusted based on the user's emotions.

[1296] Video Generation: Create promotional video scenarios and animations using scripts and video templates. The tone and style of the video are also adjusted based on user sentiment data.

[1297] Step 8:

[1298] The server sends the generated presentation materials to the device using HTTP responses or a dedicated API. The materials sent include slides, diagrams, flow charts, videos, etc.

[1299] Step 9:

[1300] The terminal displays the received presentation materials to the user, who can then practice and prepare for the presentation. The displayed materials can also be edited as needed. Materials that reflect the user's emotions will help them give more effective presentations.

[1301] These are the specific processing steps of the automatic presentation material generation system that combines an emotion engine that recognizes the user's emotions. These steps enable users to quickly create high-quality presentation materials that reflect their own emotions.

[1302] Example 2

[1303] 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."

[1304] Conventional presentation material creation systems require a great deal of time and effort for users to create their own materials, and it is difficult to create effective materials that reflect the user's emotions. Furthermore, materials that do not reflect emotions often fail to make an appropriate impact on the audience.

[1305] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting input of ideas or content from a user, means for analyzing the input idea or content and identifying the user's emotion, and means for transmitting the input idea or content and emotion information to the server. This enables the user to quickly create high-quality presentation materials that reflect his or her own emotions.

[1306] "User" refers to any individual or entity that uses this system to input ideas or content.

[1307] "Emotion engine" refers to a software component that analyzes input ideas and content and identifies the user's emotions.

[1308] "Terminal" refers to an electronic device that a user uses to input ideas or content and transmit that data to a server.

[1309] "Server" refers to a computer system that analyzes received data and generates presentation materials.

[1310] "Ideas" refer to thoughts and plans that users come up with and input into the system.

[1311] "Key points" refer to important information or key points extracted from input ideas or content.

[1312] "Presentation materials" refers to materials including slides, diagrams, flows, videos, etc. that are generated based on the user's ideas, content, and emotional information.

[1313] "Natural language processing technology" refers to technology that enables computers to understand, interpret, and generate human language.

[1314] "Slide generation" refers to the process of automatically creating slides based on key points and emotional information as part of a presentation deck.

[1315] "Diagram and flow generation" refers to the process of automatically creating graphs, charts, and flowcharts using data related to key points as part of a presentation deck.

[1316] The AI ​​system for automatically creating presentation materials according to the present invention consists of four main components: a user, a terminal, a server, and an emotion engine. This system is a technology that converts the user's ideas and content into easy-to-understand and effective presentation materials, and also combines an emotion engine that recognizes and reflects the user's emotions.

[1317] System Overview

[1318] When a user uses a device to input ideas and content for a presentation, the emotion engine recognizes the user's emotions. The input data is sent from the device to a server, which analyzes the data and extracts key points. Presentation materials such as slides, diagrams, flow charts, and videos are generated based on the key points and edited to match the user's emotions. The generated presentation materials are then sent to the device and displayed to the user.

[1319] Detailed system description

[1320] 1. User idea input and emotion recognition

[1321] The user uses the device to input ideas and content for the presentation. The device then uses a camera and microphone and an emotion engine to analyze the user's facial expressions, voice, and input to identify emotions. For example, if the user inputs, "As a new marketing strategy, we are considering introducing a social media campaign. Our primary target is young people aged 18-24," the device will analyze the user's emotions (such as excitement or nervousness) in real time.

[1322] 2. Data transmission

[1323] The device sends the user's input data and emotion information to the server using an HTTP request or a dedicated API. The device converts the emotion data into JSON format and sends it along with the user's text data. For example, the device sends the data to the endpoint using a POST request.

[1324] 3. Server analysis and keypoint extraction

[1325] The server processes the received user input data and emotional information. First, it uses natural language processing (NLP) techniques to analyze the text data. Python NLP libraries (such as SpaCy and NLTK) are used for this analysis. The server then integrates the emotions identified by the emotion engine and extracts important key points from the data. For example, key points such as "marketing strategy," "social media campaign," and "target age group: 18-24 years old" are extracted, and the user's emotions are also recorded.

[1326] 4. Generate presentation materials

[1327] The server generates a presentation based on the extracted key points and emotion information. The following elements are generated:

[1328] Slide generation: The server selects an appropriate template from multiple saved templates and arranges content based on key points. For example, slides such as "title slide," "target market overview," "campaign details," and "success stories" are generated. In this process, the server considers the user's emotional state (e.g., excitement) to select a lively design.

[1329] Figure and flow generation: The server automatically generates graphs, charts, and flowcharts based on data related to key points. Specifically, the server draws graphs based on the data using Python libraries such as Matplotlib and Plotly.

[1330] Video generation: The server uses scripts and video templates to generate promotional videos for presentations. The server uses video generation software (e.g., Adobe Premiere API or FFmpeg) based on emotion information to edit and create videos.

[1331] 5. Sending presentation materials

[1332] The server sends the generated presentation materials to the terminal. This is done using HTTP responses or a dedicated API. The server compresses the generated materials (PDF, PPT, video files, etc.) into a ZIP file and sends it as an HTTP response.

[1333] 6. Displaying presentation materials

[1334] The device displays the received presentation materials to the user. To display the materials in the appropriate format, the device uses tools such as a PDF viewer or video player. Specifically, the device unzips the received files and displays them in the interface so that the user can easily view and edit them.

[1335] Specific examples

[1336] As a concrete example, the process of generating a "presentation of a new marketing strategy" will be described.

[1337] 1. User idea input and emotion recognition: When a user inputs, "As a new marketing strategy, we are considering introducing a social media campaign. Our main target is young people aged 18-24," the device uses its emotion engine to recognize the user's state of excitement.

[1338] 2. Data transmission: The device transmits this information and emotion data to the server.

[1339] 3. Server analysis and key point extraction: The server analyzes the input and extracts key points such as "new marketing strategy," "social media campaign," and "primary target is young people aged 18-24," while also recording what the user is excited about.

[1340] 4. Presentation generation: Based on key points and emotion data, the server generates slides, target market diagrams, campaign process flows, and promotional video scenarios. The tone and style of the presentation materials are adjusted to reflect the user's excitement and make them more lively.

[1341] 5. Sending presentation materials: The server sends the generated materials to the terminal.

[1342] 6. Displaying presentation materials: The terminal displays the materials to the user, who then prepares the presentation based on them.

[1343] The above is a detailed description of an embodiment of the AI ​​system for automatically creating presentation materials of the present invention. By using this system, users can quickly create high-quality presentation materials that reflect their own emotions.

[1344] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1345] Step 1: User idea input and emotion recognition

[1346] The user uses the device to input the ideas and content of the presentation. Specifically, they input text information using the device's keyboard or voice input function. At the same time, the device uses its built-in camera and microphone to capture the user's facial expressions and voice. Based on this, the device uses an emotion engine to perform facial expression recognition and voice analysis to identify the user's emotions (excitement, nervousness, etc.) in real time. Input data (text information) and emotional data (excitement, nervousness, etc.) are generated.

[1347] Step 2: Sending data

[1348] The device sends the input data (text information) and emotion data obtained in step 1 to the server. Specifically, this data is converted into JSON format and sent to the server's API endpoint via an HTTP POST request. The input includes text data and emotion data, and the output is the accurate transfer of this data to the server.

[1349] Step 3: Server analysis and keypoint extraction

[1350] The server analyzes the data received in step 2. First, the server uses natural language processing (NLP) techniques to analyze the text data. Specifically, the server uses a Python NLP library (such as SpaCy or NLTK) to perform tokenization, POS tagging, and entity recognition. This analyzes the content of the text and extracts key points. In parallel, the server also analyzes the sentiment data and records the user's sentiment information. The inputs are text data and sentiment data, and the output is key points and sentiment information.

[1351] Step 4: Generate presentation materials

[1352] The server generates the presentation materials based on the key points and emotion information obtained in step 3. Specifically, the following elements are generated:

[1353] Slide generation: The server selects an appropriate template from multiple stored templates and arranges content based on key points. The template and design are selected taking into account the user's emotional state.

[1354] Figure and flow generation: The server uses data related to key points to automatically generate graphs, charts, and flowcharts using Python libraries such as Matplotlib and Plotly.

[1355] Video generation: The server uses video generation software (such as Adobe Premiere API or FFmpeg) to edit and create a promotional video based on the emotional information. The inputs are key points and emotional information, and the output is presentation materials such as slides, diagrams, flow charts, and videos.

[1356] Step 5: Send your presentation materials

[1357] The server sends the presentation materials generated in step 4 to the terminal. Specifically, the generated materials (PDF, PPT, video files, etc.) are compressed into a ZIP file and sent via an HTTP response or a dedicated API. The input is the generated presentation materials, and the output is the data sent back to the terminal.

[1358] Step 6: View your presentation materials

[1359] The terminal displays the presentation materials received in step 5 to the user. Specifically, it displays the extracted materials using an appropriate viewer or player (PDF viewer, video player, etc.). The user can also view and edit the materials as needed. The input is the presentation materials sent from the server, and the output is the materials to be displayed. The user prepares the presentation based on these materials.

[1360] (Application example 2)

[1361] 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."

[1362] Creating presentation materials requires time and effort, and it is particularly difficult to create effective presentation materials that reflect the user's emotions and intentions. Furthermore, there is a need for a method to quickly create appropriate materials when staff in physical stores explain products and provide promotions to customers. Conventional methods have difficulty generating presentation materials that incorporate the user's emotions, making it difficult to provide effective explanations to customers.

[1363] 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.

[1364] In this invention, the server includes means for analyzing ideas and content input by a user and extracting key points, means for generating presentation materials based on the extracted key points, and means for recognizing the user's emotions and adjusting the tone and style of the presentation materials based on those emotions, thereby enabling the rapid creation of presentation materials that reflect the user's emotions.

[1365] "User" refers to a person who inputs ideas and content for creating presentation materials.

[1366] "Server" refers to a computer system that analyzes ideas and content sent by users and generates presentation materials.

[1367] "Means for accepting input of ideas or content" refers to an interface through which users can input their own thoughts or information.

[1368] "Means for transmitting ideas or content to a server" refers to a device or software that transmits information entered by a user to a server.

[1369] "Means for extracting key points" refers to technology that identifies and extracts important elements and information from the content entered by the user.

[1370] "Means for generating presentation materials" refers to a technology for creating presentation materials such as slides, diagrams, flow charts, and videos based on the extracted key points.

[1371] The term "means for transmitting presentation materials to a user's terminal" refers to a device or software for transmitting the generated presentation materials to a device used by a user.

[1372] The term "means for displaying presentation materials" refers to a device or software that visually displays the presentation materials generated on a user's terminal.

[1373] "Means for recognizing emotions" refers to technology that analyzes the user's voice and facial expressions to determine the user's emotional state.

[1374] "Means for adjusting the tone and style of presentation materials based on emotions" refers to techniques that change the visual and content style of presentation materials in response to perceived emotions.

[1375] "Users in physical stores" refers to staff who need presentation materials when explaining products and promotions in stores.

[1376] The system for automatically creating presentation materials based on this invention consists of four main components: a user, a terminal, a server, and an emotion engine. This system aims to effectively generate presentation materials, and is characterized by its ability to reflect the user's emotions.

[1377] Overall system overview

[1378] When a user uses a device to input ideas and content for a presentation, the emotion engine recognizes the user's emotions. The input data is sent from the device to the server, which analyzes the data and extracts key points. Presentation materials are generated based on the extracted key points and edited to match the user's emotions. The generated presentation materials are then sent to the device, where the user can view and use them.

[1379] Hardware and software used

[1380] Hardware: smartphone, microphone, camera

[1381] Software: Python, requests, emotion recognition model, presentation generation AI model (e.g., Transformers)

[1382] Functions of each component

[1383] 1. User idea input and emotion recognition

[1384] Users use devices such as smartphones to input ideas and content for their presentations using voice or text. At this time, the emotion engine analyzes the user's voice and facial expressions to recognize their emotions. For example, if a user inputs "I would like to introduce a new product," the voice data is analyzed to determine whether the user is excited or calm.

[1385] 2. Data transmission

[1386] The device sends the text and emotion data entered by the user to the server using HTTP requests and a dedicated API to ensure accurate transmission of the data.

[1387] 3. Server analysis and keypoint extraction

[1388] The server analyzes the received user input data and emotional information. It uses natural language processing technology to analyze the text data and understand the content of the sentences. This analysis involves tokenization, POS tagging, and entity recognition. Furthermore, important key points are extracted from the data based on the emotions identified by the emotion engine. For example, "new product," "features," and "target market" are extracted, and the user's excitement level is also recorded.

[1389] 4. Generate presentation materials

[1390] The server generates presentation materials based on the extracted key points and emotion information. These materials include slides, diagrams, flow charts, and videos. For example, a "product overview" slide, a "feature" diagram, and a "sales process flow" are generated. The tone and style of the materials are adjusted to match the user's emotions. For example, if the user is excited, vibrant colors and dynamic elements are incorporated.

[1391] 5. Sending and Displaying Presentation Materials

[1392] The generated presentation materials are sent from the server to the terminal, which displays them to the user. The user can use the displayed materials to prepare a presentation and edit and customize the materials as needed.

[1393] Specific examples

[1394] For example, consider a case where a store staff member wants to explain the features of a new large-screen TV to a customer. The staff member uses a smartphone to voice-input, "This TV is 4K compatible, making it especially great for watching sports. What's more, it has great smart features." The emotion engine recognizes the staff member's excitement, and the data along with their emotion is sent to the server. The server analyzes the input data, extracts key points, and uses a generative AI model to create a presentation. The generated presentation includes a slide showing "Details about 4K compatibility" and a flowchart showing "How to use the smart features," all of which are vividly colored to convey the user's excitement.

[1395] Prompt Sentence Examples

[1396] "I want to create a presentation that explains the features of a new large-screen TV. I want people to pay particular attention to its 4K compatibility and smart features."

[1397] The above is an embodiment of the system for automatically creating presentation materials of the present invention. By using this system, users can create presentation materials quickly and effectively.

[1398] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1399] Step 1:

[1400] The user uses the device to input the ideas and content of the presentation using voice or text. At this point, input data is generated, and the emotion engine recognizes emotions from the voice or text. Specifically, when the user launches a smartphone app and says, "I'd like to introduce a new product, especially about its 4K compatibility and smart features," the voice data is passed to the emotion engine. The emotion engine processes the voice data and recognizes emotions such as "excitement." The input for this step is voice or text data, and the output is recognized emotion data.

[1401] Step 2:

[1402] The device sends the text entered by the user and the recognized emotion data to the server. This is done using HTTP requests or dedicated APIs. For example, the device converts voice data into text and sends the text data and emotion data to the server in JSON format. The input of this step is the text data and emotion data, and the data sent to the server is the output.

[1403] Step 3:

[1404] The server analyzes the received user input data and emotional data. Natural language processing technology is used for the analysis, and the entire sentence is understood based on the extracted key points. Specifically, the server performs tokenization, POS tagging, entity recognition, etc. on the received text data to extract key points such as "new product," "4K compatible," and "smart features." The input for this step is text data and emotional data, and the output is the extracted key points.

[1405] Step 4:

[1406] The server generates presentation materials based on the extracted key points and emotion data. Specifically, it creates slide templates, diagrams, flows, and videos. Generative AI models are used to adjust the tone and style to match the user's emotions. For example, the server might generate a title slide about a "new product," a diagram showing "4K compatibility details," and a "process flow for smart features." The input for this step is the extracted key points and emotion data, and the output is the generated presentation materials.

[1407] Step 5:

[1408] The generated presentation materials are sent from the server to the terminal. The generated materials are returned to the terminal via an HTTP response or a dedicated API. For example, the server sends the generated slides, diagrams, and flow to the terminal in JSON format. The input of this step is the generated presentation materials, and the output is the sent presentation materials.

[1409] Step 6:

[1410] The device displays the received presentation materials to the user. The user can prepare a presentation based on the displayed materials and edit and customize them as needed. For example, the device displays generated slides, and the user reviews them while practicing their presentation. The input of this step is the received presentation materials, and the output is the presentation materials displayed to the user.

[1411] The above is a specific processing flow of the automatic presentation material creation system.

[1412] 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.

[1413] 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.

[1414] 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 robot 414.

[1415] 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.

[1416] 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.

[1417] 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.

[1418] 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).

[1419] 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.

[1420] 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."

[1421] 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.

[1422] 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).

[1423] 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.

[1424] 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.

[1425] 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.

[1426] 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.

[1427] 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.

[1428] 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.

[1429] 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.

[1430] 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.

[1431] 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.

[1432] 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.

[1433] The following is further disclosed regarding the above embodiment.

[1434] (Claim 1)

[1435] means for accepting input of ideas or content from a user;

[1436] means for transmitting the input ideas and contents to a server;

[1437] means for analyzing the input ideas and contents in the server and extracting key points;

[1438] means for generating presentation materials based on the key points;

[1439] means for transmitting the generated presentation materials to a user terminal;

[1440] The system further comprises means for displaying the generated presentation material at the terminal.

[1441] (Claim 2)

[1442] 2. The system of claim 1, wherein the presentation material generating means includes means for creating slides, diagrams, flows, and videos.

[1443] (Claim 3)

[1444] 2. The system of claim 1, wherein the keypoint extraction means includes means for analyzing ideas and content using natural language processing techniques.

[1445] "Example 1"

[1446] (Claim 1)

[1447] means for accepting input of ideas or content from a user;

[1448] means for transmitting the input ideas and contents to a server;

[1449] means for analyzing the input ideas and contents in the server using natural language processing technology and extracting key points;

[1450] A means for generating presentation materials using a generative AI model based on the key points;

[1451] means for transmitting the generated presentation materials to a user terminal;

[1452] The system further comprises means for displaying the generated presentation material at the terminal.

[1453] (Claim 2)

[1454] 2. The system of claim 1, wherein the presentation material generating means includes means for creating slides, diagrams, flows, and videos.

[1455] (Claim 3)

[1456] 2. The system of claim 1, wherein the keypoint extraction means includes means for analyzing ideas and content using natural language processing techniques.

[1457] "Application Example 1"

[1458] (Claim 1)

[1459] means for accepting input of ideas or content from a user;

[1460] means for transmitting the input ideas and contents to a server;

[1461] means for analyzing the input ideas and contents in the server and extracting key points;

[1462] means for generating presentation materials based on the key points;

[1463] means for transmitting the generated presentation materials to a user terminal;

[1464] means for displaying the generated presentation materials on the terminal;

[1465] A means of receiving target demographics, key messages, and promotional plans from users;

[1466] means for automatically generating advertising campaign materials based on the received data;

[1467] A system including:

[1468] (Claim 2)

[1469] 2. The system of claim 1, wherein the presentation material generating means includes means for creating slides, diagrams, flows, and videos.

[1470] (Claim 3)

[1471] 2. The system of claim 1, wherein the keypoint extraction means includes means for analyzing ideas and content using natural language processing techniques.

[1472] "Example 2: Combining Emotion Engines"

[1473] (Claim 1)

[1474] means for accepting input of ideas or content from a user;

[1475] means for analyzing the input ideas and content and identifying the user's emotions;

[1476] means for transmitting the input ideas, contents and emotion information to a server;

[1477] means for analyzing the input ideas, contents and emotional information in the server and extracting key points;

[1478] means for generating presentation materials based on the key points and emotion information;

[1479] means for transmitting the generated presentation materials to a user terminal;

[1480] The system further comprises means for displaying the generated presentation material at the terminal.

[1481] (Claim 2)

[1482] 2. The system of claim 1, wherein the presentation material generating means includes means for creating slides, diagrams, flows, and videos.

[1483] (Claim 3)

[1484] 2. The system of claim 1, wherein the keypoint extraction means includes means for analyzing ideas and content using natural language processing techniques.

[1485] "Application example 2 when combining emotion engines"

[1486] (Claim 1)

[1487] means for accepting input of ideas or content from a user;

[1488] means for transmitting the input ideas and contents to a server;

[1489] means for analyzing the input ideas and contents in the server and extracting key points;

[1490] means for generating presentation materials based on the key points;

[1491] means for transmitting the generated presentation materials to a user terminal;

[1492] means for displaying the generated presentation materials on the terminal;

[1493] means for recognizing the emotion of the user;

[1494] A system that includes a means for adjusting the tone and style of presentation materials based on perceived emotions.

[1495] (Claim 2)

[1496] Includes means to create slides, diagrams, flows, and videos;

[1497] 10. The system of claim 1, wherein the means for generating presentation materials includes means for adjusting the materials based on the recognized emotions.

[1498] (Claim 3)

[1499] It includes a means to analyze ideas and content using natural language processing technology and extract key points,

[1500] The system according to claim 1, wherein the emotion recognition means includes means for analyzing facial expressions and voices of users in a physical store. [Explanation of symbols]

[1501] 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. means for accepting input of ideas or content from a user; means for transmitting the input ideas and contents to a server; means for analyzing the input ideas and contents in the server and extracting key points; means for generating presentation materials based on the key points; means for transmitting the generated presentation materials to a user terminal; The system further comprises means for displaying the generated presentation material at the terminal.

2. The system of claim 1 , wherein the presentation material generating means includes means for creating slides, diagrams, flows, and videos.

3. 2. The system of claim 1, wherein the keypoint extraction means includes means for analyzing ideas and contents using natural language processing techniques.

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