System

Abstract

A system is provided.SOLUTION: The system includes a means for inputting an explanation material of a commodity to be promoted by a company to the system, a means for changing a presenter from an initially set image to a custom avatar or a new image, a means for generating a presentation moving image obtained by combining a generated script and the image of the presenter, and a means for providing a download link of the generated moving image and performing notification.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] Companies need compelling, professional presentation videos to effectively promote their products and services. However, creating such videos requires specialized knowledge and skills, and not all companies have the resources to do so. It is also difficult to quickly create high-quality videos that meet individual requirements, such as presenter settings. This invention solves these problems and provides a system for easily generating high-quality presentation videos. [Means for solving the problem]

[0005] The system of the present invention includes the following means. First, it provides a means for inputting explanatory materials for products that a company wishes to promote into the system. Next, it provides a means for changing the presenter's image from the default image to a custom avatar or a new image. Finally, it provides a means for generating a presentation video that combines the generated script with the presenter's image. It also includes a means for providing and notifying the user of a download link for the generated video. This makes it possible to easily create high-quality presentation videos without requiring specialized knowledge or skills.

[0006] "Company" refers to a corporation or organization that engages in activities to promote products or services.

[0007] "Explanatory materials" refers to materials consisting of documents, diagrams, or a combination thereof that explain the features, benefits, and usage of a product.

[0008] "Input" refers to the act of entering data or information into a system.

[0009] A "presenter" refers to a person or avatar whose role is to explain a product or service within a presentation video.

[0010] "Initial settings" refers to the settings and values ​​provided by the system by default.

[0011] "Custom avatar" refers to a character image for a presenter that is freely selected or created by a user.

[0012] "Script" refers to the text data of the script or dialogue used in a presentation video.

[0013] "Presentation video" refers to video content created to explain a product or service.

[0014] "Generative AI" refers to a system that uses artificial intelligence technology to process data and information and automatically generate scenarios, videos, etc.

[0015] "Download link" refers to the URL that allows a user to obtain a file via the Internet.

[0016] "Initial costs" refer to the costs paid only once when starting to use a system or service.

[0017] "Monthly fee" refers to the regular fee paid each month to use a system or service.

[0018] "Billing Information" means data regarding fees and payments for use of the Service. [Brief explanation of the drawings]

[0019] [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

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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."

[0040] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. The system consists of a server and a user terminal, and uses generation AI to create high-quality videos.

[0041] System Operation

[0042] Input of explanatory materials

[0043] A user prepares explanatory materials (e.g., PDF files) for the products their company wants to promote, and logs in with their company account information to access the system. After logging in, the user accesses the dashboard and opens the explanatory materials upload page. Next, the user uploads the explanatory materials file using drag and drop or the file selection button. The terminal reads this file and sends it to the server. The server saves the received explanatory materials and converts them into an appropriate internal format (e.g., performs text analysis and extracts key points).

[0044] Presenter Settings

[0045] The user accesses the presenter settings page and sees the default presenter image (e.g., an image of the company CEO). Then, the user selects and uploads a new presenter image (e.g., a custom avatar). The device reads the selected image file and sends it to the server. The server saves the image and updates the presenter's settings information.

[0046] Video generation

[0047] The server uses a generative AI to create a script based on the explanatory materials and the presenter's settings. This script includes text data for the script and dialogue to be used in the presentation video. The server then combines the generated script with the presenter's image to generate the presentation video. The generated video file is saved in the storage area associated with the user's account.

[0048] Video notification and provision

[0049] The server notifies the user of the generated download link for the video, and the user can receive this notification and click the link to download the video.

[0050] Pricing

[0051] The system will calculate the initial and monthly fees based on the videos generated and add the billing information to the user's account. The server will calculate these fees and apply them to the next billing cycle. The user will receive a payment notification and pay the fees through the provided payment link.

[0052] Specific examples

[0053] Input of explanatory materials

[0054] A company's marketing manager, Mr. A, prepared explanatory materials in PDF format for a new product, "Smart Gadget." He logged into the system and uploaded the materials by dragging and dropping them onto the upload page on the dashboard. The server then performed a text analysis of the materials and extracted key points.

[0055] Presenter Settings

[0056] Person A went to the presenter settings page and saw the default CEO image. Person A uploaded a custom avatar and the server saved this new image and updated the settings.

[0057] Video generation

[0058] The server created a script using generative AI based on the explanatory materials and the new presenter image, and generated a presentation video. The server associated this video with Mr. A's account, saved it, and sent him a download link.

[0059] Video notification and provision

[0060] Mr. A received a notification and got a professionally generated presentation video from the download link.

[0061] Pricing

[0062] The system calculated the initial and monthly fees based on A's usage and added the billing information to his account. A received a payment notification and made the payment via the provided link.

[0063] As described above, the present invention provides a system that enables companies to easily generate high-quality presentation videos even without specialized knowledge.

[0064] The processing flow will be explained below.

[0065] Step 1:

[0066] The user accesses the system and enters their company account information on the login screen to log in. The server sends the entered account information to the authentication system and returns the authentication result.

[0067] Step 2:

[0068] The user accesses the dashboard and opens the upload page for the instructional materials. The device displays a file selection button, allowing the user to select a local file.

[0069] Step 3:

[0070] The user selects a file (e.g. PDF) of the product description they want to promote and clicks the upload button. The device reads the selected file and sends it to the server.

[0071] Step 4:

[0072] The server stores the received files and converts them into a suitable internal format, for example by performing text analysis and extracting key points.

[0073] Step 5:

[0074] The user accesses the presenter settings page, and the device displays the default presenter image (e.g., an image of the company CEO) on the screen.

[0075] Step 6:

[0076] The user selects and uploads a new presenter image. The device reads the selected image file and sends it to the server.

[0077] Step 7:

[0078] The server stores the received image and updates the presenter's setting information.

[0079] Step 8:

[0080] The server uses generative AI to create a presentation script based on the content of the input explanatory materials (text information).

[0081] Step 9:

[0082] Based on the created script, the server generates a presentation video that combines the presenter's settings (avatar and image).

[0083] Step 10:

[0084] The server stores the generated video file in association with the user's account.

[0085] Step 11:

[0086] The server notifies the user that the video has been generated and provides a download link, which the user clicks to download the video.

[0087] Step 12:

[0088] The server calculates the initial fee and monthly fee based on the user's usage and adds the billing information to the user's account.

[0089] Step 13:

[0090] The server sends a payment notification to the user and provides a payment link, and the user receives the payment notification and pays the fee through the provided link.

[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] Creating professional presentation videos for corporate sales promotion requires a great deal of effort and expertise. While systems exist for automatically generating presentation videos, further improvements are needed to effectively extract key points from explanatory materials and generate high-quality scripts. A system that solves these problems and generates efficient, high-quality presentation videos 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 analyzing explanatory materials for products that a company wants to promote, extracting key points, and converting them into an internal format, means for creating a script from the explanatory materials using a generative AI model, and means for generating a presentation video that combines the generated script with an image of the presenter, thereby enabling companies to automatically generate high-quality presentation videos even without specialized knowledge.

[0096] An "enterprise" is an organization that provides goods and services and engages in commercial activities.

[0097] "Sales promotion" is a part of marketing activities carried out to increase sales of a product.

[0098] "Explanatory materials" are documents that describe the features and benefits of a product and are used in sales promotion activities.

[0099] A "system" is a collection of hardware and software combined to achieve a particular purpose.

[0100] A "server" is a computer that provides services to other computers on a network.

[0101] "Analysis" is the process of breaking down the content of materials or data and extracting meaning and key points.

[0102] "Major points" are sections that highlight important information or key points contained in the presentation material.

[0103] An "internal format" is a standardized data format used within a system.

[0104] A "presenter" is a person or character who gives explanations in a presentation video.

[0105] A "custom avatar" is a virtual character created for a specific purpose or individual.

[0106] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to automatically generate data.

[0107] A "script" is text data that describes the content and dialogue of a presentation video.

[0108] A "presentation video" is video content that visually explains the features and benefits of a product.

[0109] "Download link" means a URL link for downloading a file over the Internet.

[0110] A "notification" is a message or alert that informs a user of certain information.

[0111] "Initial costs" are one-time costs paid when you start using the system.

[0112] "Monthly fee" refers to the fee paid each month for the continued use of the system.

[0113] "Billing Information" means information that describes the charges incurred by the User.

[0114] A "prompt" is input text that gives instructions or questions to a generative AI model.

[0115] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. The system consists of a server and a user terminal, and uses generation AI to create high-quality videos.

[0116] Input of explanatory materials

[0117] A user prepares explanatory materials (e.g., PDF files) for the products their company wants to promote, and logs in with their company's account information to access the system. After logging in, the user accesses the dashboard and opens the explanatory materials upload page. Next, the user uploads the explanatory materials file using drag and drop or the file selection button. The terminal reads this file and sends it to the server.

[0118] The server temporarily stores the received explanatory materials, analyzes the text content using a text extraction tool such as PDFMiner, extracts key points using a natural language processing library (e.g., SpaCy), converts the extracted information into an internal format, and stores it in a database.

[0119] Presenter Settings

[0120] The user accesses the presenter settings page, sees the default presenter image (e.g., an image of the company CEO), selects a new presenter image (e.g., a custom avatar), and uploads it. The device reads the selected image file and sends it to the server.

[0121] The server saves this image file and updates the presenter's configuration information using an image processing library such as OpenCV.

[0122] Video generation

[0123] Based on the saved explanatory materials and the presenter's settings, the server sends a prompt such as, "Generate a professional presentation video for our new product, 'Smart Gadget.' Create a script based on the explanatory materials below and use the configured custom avatar." to the generation AI model (e.g., GPT-4) and creates a script.

[0124] The generated script can be checked and edited as necessary. The edited script is then combined with the presenter image to generate a presentation video using a generation AI such as DALL-E. The created video file is saved and associated with the user's account.

[0125] Video notification and provision

[0126] The server notifies the user of the generated download link for the video. The user can receive this notification and click the link to download the video. Notification can be done using an email sending API (e.g., SendGrid).

[0127] Pricing

[0128] The server calculates the fee based on the generated video information. It uses a fee calculation algorithm to calculate the initial fee and monthly fee. The calculated fee is added to the user's account and reflected in the next billing cycle. A payment notification email is sent to the user, and the fee can be paid via the provided payment link. An online payment service such as Stripe API is used.

[0129] The above are specific embodiments of the present invention based on the claims. This system allows companies to easily generate high-quality presentation videos without specialized knowledge.

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

[0131] Step 1:

[0132] User: Access the system login page and log in with your account information.

[0133] Input: User account information (e.g. username, password)

[0134] Output: After successful login, redirect to dashboard

[0135] Specific operation: The user opens a browser, accesses the system's URL, enters the required information in the login form, and clicks the "Login" button.

[0136] Step 2:

[0137] User: Open the "Upload Materials" page on your dashboard and select your materials.

[0138] Input: Explanation materials (e.g. PDF file)

[0139] Output: Explanation file uploaded

[0140] Specific operation: The user clicks the "Upload explanatory materials" button or page, drags and drops explanatory materials from the file selection dialog that appears, or selects a file using the "Select File" button, and clicks the "Start Upload" button.

[0141] Step 3:

[0142] Terminal: Reads the selected file and sends it to the server.

[0143] Input: explanatory file

[0144] Output: File data sent to the server

[0145] Specific operation: The terminal reads the selected file data as output from the file selection dialog and sends it to the server via an HTTP request.

[0146] Step 4:

[0147] Server: Temporarily stores the received explanatory material files and analyzes the text content using a text extraction tool such as PDFMiner.

[0148] Input: explanatory file

[0149] Output: Extracted text data

[0150] What it does: The server saves the file in a specific directory and uses a tool like PDFMiner to extract the text from the PDF.

[0151] Step 5:

[0152] Server: Analyze the extracted text data using a natural language processing library (e.g., SpaCy) and extract key points.

[0153] Input: Text data

[0154] Output: Text data containing key points

[0155] How it works: The server applies SpaCy to the extracted text data to extract noun phrases and identify keywords, then stores the key points in a database.

[0156] Step 6:

[0157] Users: Visit the Presenter Settings page to view the default presenter image and upload a new one.

[0158] Input: New presenter image (e.g. JPEG, PNG file)

[0159] Output: New presenter image uploaded

[0160] What happens: On the Presenter Settings page, the user clicks the "Change Presenter Image" button, selects a new image file, and uploads it.

[0161] Step 7:

[0162] On the device: Load the selected image file and send it to the server.

[0163] Input: New presenter image

[0164] Output: Image data sent to the server

[0165] Specific operation: The terminal reads the image data selected as the output of the file selection dialog and sends it to the server via an HTTP request.

[0166] Step 8:

[0167] Server: Saves the received image files and updates the presenter's settings using an image processing library such as OpenCV.

[0168] Input: New presenter image

[0169] Output: Updated presenter settings

[0170] Specific operation: The server saves image files in a specific directory, analyzes and processes the images using OpenCV, and updates the configuration information in the database.

[0171] Step 9:

[0172] Server: Based on the saved explanatory materials and presenter settings, it sends prompts to the generative AI model (e.g., GPT-4) and generates a script.

[0173] Input: Main points of the presentation materials, presenter setting information

[0174] Output: Generated script

[0175] Specific operation: The server generates a prompt saying, "Please generate a professional presentation video for our new product, 'Smart Gadget'. Please create a script based on the explanatory materials below and use the custom avatar you set." and sends it to the generation AI to generate the script.

[0176] Step 10:

[0177] Server: Review the generated script and make any necessary modifications.

[0178] Input: Generated script

[0179] Output: The modified script

[0180] What happens: The server administrator or an automated proofreader checks the script and makes corrections if necessary.

[0181] Step 11:

[0182] Server: The modified script is combined with the presenter image and a generative AI such as DALL-E is used to generate a presentation video.

[0183] Input: modified script, presenter image

[0184] Output: Generated presentation video

[0185] Specific operation: The server inputs the script and images into the generation AI and executes the video generation process.

[0186] Step 12:

[0187] Server: Stores the created video file in association with the user's account.

[0188] Input: Generated presentation video

[0189] Output: Video files associated with the user's account

[0190] What happens: The server stores the video file in a database and links it to the appropriate user account.

[0191] Step 13:

[0192] Server: Sends the generated video download link to the user.

[0193] Input: Link to the generated video file

[0194] Output: Notification email sent to user

[0195] Specific operation: The server uses an email sending API (e.g. SendGrid) to send a notification email to the user containing a download link.

[0196] Step 14:

[0197] User: Receives notification email and clicks link to download video.

[0198] Input: Download link in the notification email

[0199] Output: Downloaded presentation video

[0200] Specific behavior: The user clicks on the link in the received email, accesses the video download page, and downloads the video file.

[0201] Step 15:

[0202] Server: Calculates fees based on the generated video information. A fee calculation algorithm is used to calculate the initial fee and monthly fee.

[0203] Input: Generated video information

[0204] Output: Charge calculation result

[0205] Specific operation: The server analyzes the video information stored in the database and calculates the fee using a specific algorithm.

[0206] Step 16:

[0207] Server: Adds the calculated fee to the user's account and applies it to the next billing cycle.

[0208] Input: Fee calculation result

[0209] Output: Billing information added to the user's account

[0210] Specific operation: The server saves the calculation results in the database and reflects them in the next billing cycle.

[0211] Step 17:

[0212] Server: Sends payment notification email to user and provides payment link.

[0213] Enter: Billing Information

[0214] Output: Payment notification email

[0215] Specific operation: The server uses the Email Sending API to send a payment notification email to the user.

[0216] Step 18:

[0217] User: Receives payment notification and clicks link to visit payment page.

[0218] Input: Payment link in payment notification email

[0219] Output: Payment completion screen

[0220] Specific behavior: The user clicks on the link in the email and completes the payment using an online payment service (e.g., Stripe API).

[0221] The above is the detailed processing flow of the program of this system.

[0222] (Application example 1)

[0223] 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."

[0224] Conventional presentation video generation systems require specialized knowledge, making it difficult to easily generate high-quality promotional videos. Furthermore, they lack the functionality to manage and download videos using smartphones, making it difficult for marketers and advertising agencies to carry out their work efficiently.

[0225] 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.

[0226] In this invention, the server includes means for inputting explanatory materials for products that a company wants to promote into the system, means for changing the presenter's image from a default image to a custom avatar or a new image, means for generating a presentation video that combines the generated script and the presenter's image, means for providing and notifying a download link for the generated video, means for including a user interface optimized for smartphones, means for calculating a fee based on the generated video and notifying payment, means for creating a script from the explanatory materials using a generative AI model, and means for managing and downloading the video using a smartphone. This allows high-quality promotional videos to be easily generated without specialized knowledge, and allows efficient management and download of the videos using a smartphone.

[0227] An "enterprise" is a legal entity that provides a specific product or service to the market and pursues profits.

[0228] "Sales promotion" refers to marketing activities that help sell a product or service and make consumers aware of its value.

[0229] "Explanatory materials" are documents or data intended for consumers or interested parties that provide information about a particular product or service.

[0230] A "system" is a device or procedure that combines multiple elements (hardware, software, data, etc.) to achieve a specific purpose.

[0231] "Input" refers to the act of entering information or data into a system.

[0232] A "presenter" is a person or avatar whose role is to visually and audibly convey information or ideas.

[0233] "Custom Avatar" means a custom-made digital character or image created by a user.

[0234] A "script" is a sequence of scripts or scenarios using audio or text.

[0235] A "generative AI model" is an algorithm that uses artificial intelligence to generate or transform data.

[0236] "Presentation Video" means a video presentation for conveying information visually and audibly.

[0237] A "download link" is a URL or hyperlink that allows you to obtain a particular file on the Internet.

[0238] A "notification" is a message or alert that informs the user of specific information or events.

[0239] A "user interface" is a means or screen through which a system and a user can interact with each other to exchange information.

[0240] "Fees" means money payable for the provision of services or the purchase of products.

[0241] "Payment Notice" means a message or notice sent to a User to notify the User of a particular payment.

[0242] A "smartphone" is a small mobile device that combines the functionality of a mobile phone with that of a computer.

[0243] This section describes the specific steps for companies to upload product promotion materials to the system and generate professional presentation videos using a generative AI model. It also provides a user interface that allows users to manage and download videos using a smartphone.

[0244] Required Hardware and Software

[0245] Server: Analyzes the text of explanatory materials, generates scripts using generative AI models, generates videos, calculates fees, and processes notifications.

[0246] Devices: Provide an interface for users to upload presentation materials and set presenter images. This includes mobile devices such as smartphones and tablets.

[0247] Generative AI models: Artificial intelligence models for generating scripts from explanatory materials, such as OpenAI's GPT-3.

[0248] Software: PyPDF2 (PDF reading), Pillow (image processing), requests (HTTP requests), OpenAI API library.

[0249] System Operation

[0250] 1. Explanatory Material Input:

[0251] A user prepares explanatory materials in PDF or other formats for products that a company is promoting.

[0252] Users access the system via an internet browser, log in, and then upload explanatory materials to the system.

[0253] The server receives the uploaded explanatory material and uses PyPDF2 to parse the text and extract the main points.

[0254] 2. Presenter Settings:

[0255] The presenter settings page allows users to view the default images and upload new presenter images (custom avatars or new images).

[0256] The server receives and stores the new image file.

[0257] 3. Video generation:

[0258] The server uses a generative AI model to generate a script for the presentation video from the text of the explanatory materials, with the following prompt:

[0259] Prompt: "Generate a promo video script based on the following brief:\n\n[Text of brief]"

[0260] The server combines the generated script with the presenter's image and generates a video file using an image processing library such as Pillow.

[0261] 4. Video Notification and Provision:

[0262] The server stores the generated presentation video file and associates it with the user's account.

[0263] The user will be notified when the video is complete and provided with a download link, which they can use to download the video using their smartphone.

[0264] 5. Calculation and Notification of Fees:

[0265] The server calculates the initial and monthly fees based on the video production and adds the billing information to the user's account.

[0266] The user will be notified of the payment and will be provided with a link to complete the payment.

[0267] Specific examples

[0268] Input of explanatory materials: A marketing person prepares explanatory materials for new product X in PDF format and uploads them after logging in to the system.

[0269] Presenter settings: The presenter sets a custom avatar and uploads it to the server.

[0270] Video generation: The server analyzes the text of the explanatory materials and uses a generative AI model (such as GPT-3) to generate a script for the promotional video, which is then combined with an image of the presenter to create the video.

[0271] Video notification and provision: The server associates the generated video with the agent's account and notifies the agent of the download link, which the agent clicks to download the video to their smartphone.

[0272] Calculation and notification of fees: The server calculates the fee for video generation and sends a payment notification to the person in charge.

[0273] In this way, companies can easily generate high-quality promotional videos without specialized knowledge, and can efficiently manage and download the videos using a smartphone.

[0274] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0275] Step 1:

[0276] (Input of explanatory materials)

[0277] Users access the system, log in, and then upload a PDF file describing the product they want to promote. The device then sends the uploaded PDF file to the server, which then uses PyPDF2 to analyze the PDF and extract text data. The key points of the extracted text data are then retrieved and used as input for the generative AI model.

[0278] Input: PDF format explanatory materials

[0279] Output: Text data extracted from the explanatory materials

[0280] Step 2:

[0281] (Presenter settings)

[0282] The user sees the default presenter image on the presenter settings page. If the user chooses to upload a new presenter image (custom avatar or new image), the device sends this image to the server. The server saves the new presenter image and updates the presenter information.

[0283] Input: New presenter image

[0284] Output: Updated presenter information

[0285] Step 3:

[0286] (Script generation)

[0287] The server uses a generative AI model to generate a script for the video based on the text data extracted from the explanatory materials. Specifically, a prompt sentence is input into the generative AI model to generate an appropriate script. An example of the prompt sentence is as follows:

[0288] Prompt: "Generate a promo video script based on the following brief:\n\n[Text of brief]"

[0289] The server receives the generated script and prepares it as the basic data for the presentation video.

[0290] Input: Text data extracted from explanatory materials, prompt text

[0291] Output: Script for video

[0292] Step 4:

[0293] (Video generation)

[0294] The server combines the generated script with the presenter's image to generate a presentation video. It uses an image processing library such as Pillow to set the timing and effects of the text based on the script, and to position the presenter's image appropriately. The generated video file is saved on the server.

[0295] Input: video script, presenter image

[0296] Output: Generated presentation video

[0297] Step 5:

[0298] (Video notification and provision)

[0299] The server generates a link to the location where the generated video is saved and notifies the user of this link. The user can download the generated video from the provided link. If downloading using a smartphone, this operation is performed through a user interface optimized for smartphones.

[0300] Input: Generated presentation video

[0301] Output: Video download link, notification

[0302] Step 6:

[0303] (Calculation and notification of fees)

[0304] The server calculates the initial and monthly fees based on the generated video and adds the billing information to the user's account. The server sends a payment notice to the user based on the billing information. The user confirms the notice and pays the fee via the provided payment link.

[0305] Input: Generated video, pricing criteria

[0306] Output: Initial and monthly fees, payment notice

[0307] By following these steps, businesses can easily generate high-quality promotional videos without specialized knowledge, and efficiently manage, download, and pay for the videos using their smartphones.

[0308] 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.

[0309] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. This system also incorporates an emotion engine that recognizes user emotions, enabling more personalized video generation. The system consists of a server, a user device, and an emotion engine, and utilizes generative AI to create high-quality videos.

[0310] System Operation

[0311] Input of explanatory materials

[0312] A user prepares explanatory materials (e.g., PDF files) for the products their company wants to promote, and logs in with their company account information to access the system. After logging in, the user accesses the dashboard and opens the explanatory materials upload page. Next, the user uploads the explanatory materials file using drag and drop or the file selection button. The terminal reads this file and sends it to the server. The server saves the received explanatory materials and converts them into an appropriate internal format (e.g., performs text analysis and extracts key points).

[0313] Presenter Settings

[0314] The user accesses the presenter settings page and sees the default presenter image (e.g., an image of the company CEO). Then, the user selects and uploads a new presenter image (e.g., a custom avatar). The device reads the selected image file and sends it to the server. The server saves the image and updates the presenter's settings information.

[0315] Emotion recognition and reflection

[0316] While the user is interacting with the upload page, the emotion engine recognizes emotions from the user's facial expressions and voice. The emotion engine then transmits the user's emotional information to the server in real time. Based on this information, the server adjusts the content of the presentation video (e.g., the presenter's facial expressions and tone of voice).

[0317] Video generation

[0318] The server uses a generative AI to create a script based on the explanatory materials, emotional information obtained from the emotion engine, and the presenter's settings. This script includes text data for the script and dialogue to be used in the presentation video. The generated script is then combined with the presenter's image to generate the presentation video. The generated video file is saved in the storage area associated with the user's account.

[0319] Video notification and provision

[0320] The server notifies the user of the generated download link for the video, and the user can receive this notification and click the link to download the video.

[0321] Pricing

[0322] The system will calculate the initial and monthly fees based on the videos generated and add the billing information to the user's account. The server will calculate these fees and apply them to the next billing cycle. The user will receive a payment notification and pay the fees through the provided payment link.

[0323] Specific examples

[0324] Input of explanatory materials

[0325] A company's marketing manager, Mr. A, prepared explanatory materials in PDF format for a new product, "Smart Gadget." He logged into the system and uploaded the materials by dragging and dropping them onto the upload page on the dashboard. The server then performed a text analysis of the materials and extracted key points.

[0326] Presenter Settings

[0327] Person A went to the presenter settings page and saw the default CEO image. Person A uploaded a custom avatar and the server saved this new image and updated the settings.

[0328] Emotion recognition and reflection

[0329] While Ms. A was uploading her materials, the emotion engine analyzed her facial expressions and voice and sent her emotional information to the server. The server analyzed Ms. A's emotions, such as joy and anticipation, and adjusted the presenter's facial expressions and tone of voice based on those.

[0330] Video generation

[0331] The server used generative AI to create a script based on the explanatory materials, emotional information, and presenter image, and generated a presentation video. The server associated this video with Person A's account, saved it, and sent Person A a download link.

[0332] Video notification and provision

[0333] Mr. A received a notification and got a professionally generated presentation video from the download link.

[0334] Pricing

[0335] The system calculated the initial and monthly fees based on A's usage and added the billing information to his account. A received a payment notification and made the payment via the provided link.

[0336] As described above, the present invention provides a system that enables companies to easily generate high-quality, personalized presentation videos without requiring specialized knowledge.

[0337] The processing flow will be explained below.

[0338] Step 1:

[0339] The user accesses the system and enters their company account information on the login screen to log in. The server sends the entered account information to the authentication system and returns the authentication result.

[0340] Step 2:

[0341] The user accesses the dashboard and opens the upload page for the instructional materials. The device displays a file selection button, allowing the user to select a local file.

[0342] Step 3:

[0343] The user selects a file (e.g. PDF) of the product description they want to promote and clicks the upload button. The device reads the selected file and sends it to the server.

[0344] Step 4:

[0345] The server stores the received files and converts them into a suitable internal format, for example by performing text analysis and extracting key points.

[0346] Step 5:

[0347] The user accesses the presenter settings page, and the device displays the default presenter image (e.g., an image of the company CEO) on the screen.

[0348] Step 6:

[0349] The user selects and uploads a new presenter image. The device reads the selected image file and sends it to the server.

[0350] Step 7:

[0351] The server stores the received image and updates the presenter's setting information.

[0352] Step 8:

[0353] While the user is operating the upload page, the emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional information.

[0354] Step 9:

[0355] The emotion engine transmits the acquired emotion information to the server, which stores it and reflects it in the presentation content.

[0356] Step 10:

[0357] The server uses generative AI to create a presentation script based on the content of the input explanatory materials (text information) and emotional information.

[0358] Step 11:

[0359] Based on the created script, the server generates a presentation video that combines the presenter's settings (avatar and image) with emotional information.

[0360] Step 12:

[0361] The server stores the generated video file in association with the user's account.

[0362] Step 13:

[0363] The server notifies the user that the video has been generated and provides a download link, which the user clicks to download the video.

[0364] Step 14:

[0365] The server calculates the initial fee and monthly fee based on the user's usage and adds the billing information to the user's account.

[0366] Step 15:

[0367] The server sends a payment notification to the user and provides a payment link, and the user receives the payment notification and pays the fee through the provided link.

[0368] Example 2

[0369] 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."

[0370] Conventional presentation video creation systems lack the technology to automatically generate high-quality, personalized videos, making it difficult for companies without specialized knowledge to easily create high-quality presentation videos. Furthermore, personalization that reflects customer emotional information is not easy, resulting in a problem of low quality in the generated videos.

[0371] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for inputting explanatory materials for products that a company wants to promote into the system, a means for changing the presenter's image from a default image to a custom avatar or a new image, a means for combining the generated script with the presenter's image to generate a presentation video that reflects emotional information, a means for providing and notifying a download link for the generated video, and a means for recognizing emotions in real time and transmitting that information to the system. This makes it possible to easily create high-quality, personalized presentation videos even without specialized knowledge.

[0372] "Company" refers to a legal entity or organization that promotes a particular product or service.

[0373] An "explanatory material" refers to a document (e.g., a PDF file) containing information about a product or service prepared by a company for sales promotion purposes.

[0374] "Presenter" refers to a virtual character or person who explains a product or service within a presentation video.

[0375] "Custom Avatar" refers to a unique presenter image created or selected by a user.

[0376] "Generated script" refers to the text data of the script and dialogue of a presentation video that is automatically generated based on the content of the explanatory materials and other information.

[0377] "Emotion information" refers to data related to emotions recognized in real time from the user's facial expressions and voice.

[0378] "Generative AI" refers to a system or software that uses artificial intelligence technology to automatically generate scripts, presentation videos, etc.

[0379] "Download link" refers to the URL for obtaining the generated presentation video via the Internet.

[0380] An "emotion engine" refers to software or hardware that has the ability to recognize emotions from a user's facial expressions and voice and transmit that information to the system.

[0381] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products that companies want to promote. This system consists of a server, user terminals, and an emotion engine, and utilizes generation AI to create high-quality videos.

[0382] The system operates in the following specific steps:

[0383] Input of explanatory materials

[0384] Users access the system's login page and log in by entering their company's account information. After logging in, they move to the dashboard page and click the "Upload Materials" button to access the upload page. Then, they drag and drop explanatory materials (e.g., PDF files) or click the "Select File" button to select a file.

[0385] The device reads the selected file and sends its contents to the server, which stores the received file and performs text analysis, extracting key points and elements and storing them in an internal database.

[0386] Presenter Settings

[0387] Users access the reconfigured Presenter Settings page in their dashboard, review the default presenter image (e.g., an image of the company CEO), and click the "Change Image" button to upload a new presenter image (e.g., a custom avatar).

[0388] The device reads the uploaded image file and sends it to the server, which saves the new image and updates the presenter setting information.

[0389] Emotion recognition and reflection

[0390] While the user is uploading explanatory materials, the emotion engine uses the camera and microphone to analyze emotions from the user's facial expressions and voice in real time, and sends emotional information (e.g., joy, surprise, concentration, etc.) to the server.

[0391] The server adjusts the content of the presentation video based on the emotion information, so that the presenter's facial expressions and tone of voice change to match the user's emotions.

[0392] Video generation

[0393] The server uses a generative AI model to create a script for the presentation video based on the analysis results of the explanatory materials, emotional information, and presenter settings. The generated script is combined with an image of the presenter to generate a video.

[0394] The generated video file is saved in the storage area associated with the user's account.

[0395] Video notification and provision

[0396] Once the server has completed generating the video, it will send a notification to the user with a download link. The user will receive the notification and click the link to download the presentation video.

[0397] Pricing

[0398] The system calculates the fee based on the usage of the generated videos. The initial and monthly fees are calculated, and the server adds these fees to the user's account as billing information and reflects them in the next billing cycle. The user receives a payment notification and makes the payment via the provided link.

[0399] Examples of concrete examples and prompts

[0400] Example: Input of explanatory materials

[0401] The user logs into the system with their company account and uploads a PDF file of information about a new product. The device reads the file and sends it to the server, which performs text analysis and extracts key points.

[0402] Example: Setting the presenter

[0403] Users navigate to the presenter settings page, see the default CEO image, then upload a custom avatar and the server updates the settings.

[0404] Example: Emotion recognition and reflection

[0405] While the user is uploading materials, the emotion engine analyzes the user's facial expressions and voice and transmits his / her emotional information to the server, which then adjusts the presenter's facial expressions and tone of voice based on the emotional information.

[0406] Example: Video Generation

[0407] The server creates a script using a generative AI model based on the explanatory materials, emotional information, and presenter image, and generates a presentation video. The video is saved in the user's account storage area.

[0408] Example: Video notification and provision

[0409] The user receives a notification from the server and retrieves the generated presentation video from the provided download link.

[0410] Example: Setting prices

[0411] The system calculates the initial and monthly fees based on the user's usage, adds the billing information to the user's account, and the user receives a payment notification and makes the payment via the provided link.

[0412] Prompt Sentence Examples

[0413] "Generate a video of a company representative giving a presentation based on a new product's explanatory materials. Adjust the presenter's tone of voice and facial expressions based on emotional information."

[0414] "To auto-generate a professional presentation video, upload the PDF file below, use a custom avatar as the presenter, and create a video that reflects the user's emotional information."

[0415] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0416] Step 1: Input of explanatory materials

[0417] The user accesses the system's login page and logs in by entering their company's account information. After successful login, they are redirected to the dashboard page. Next, the user clicks the "Upload Materials" button to access the upload page. They drag and drop explanatory materials (e.g., PDF files) or click the "Select File" button to select a file and upload it. This process receives input that explanatory materials will be uploaded. The terminal reads the selected file and sends the file contents to the server. The server saves the received file, performs text analysis to extract key points, and stores them in an internal database. This is the output data.

[0418] Step 2: Presenter Settings

[0419] The user navigates to the "Presenter Settings" page from the dashboard menu. They check the default presenter image (e.g., an image of the company CEO) and click the "Change Image" button to upload a new presenter image (e.g., a custom avatar). This process receives input that the presenter image will be uploaded. The device reads the uploaded image file and sends it to the server. The server saves the new image and updates the presenter setting information. This is the output data.

[0420] Step 3: Emotional awareness and reflection

[0421] While the user is uploading explanatory materials, the emotion engine uses the camera and microphone to analyze emotions from the user's facial expressions and voice in real time. This process inputs the user's facial expression and voice data. The emotion engine sends emotional information (e.g., joy, surprise, concentration, etc.) to the server. This emotional information is the output data. Based on the emotional information, the server adjusts the content of the presentation video, changing the presenter's facial expressions and tone of voice. This adjusted content is the output data.

[0422] Step 4: Generate the video

[0423] The server uses a generative AI model to create a presentation video script based on the analysis results of the explanatory materials, emotional information, and presenter setting information. This process inputs the analysis results, emotional information, and presenter setting information. The server combines the generated script with the presenter's image to generate a video. The generated video file is saved in the storage area associated with the user's account. This is the output data.

[0424] Step 5: Notify and provide the video

[0425] When the server completes the video generation, it sends a notification to the user with a download link. This process inputs the generated video file. The user receives the notification and clicks the link to download the presentation video. The downloaded video is the output data.

[0426] Step 6: Set your prices

[0427] The system calculates fees based on the usage of the generated videos. This process inputs video usage data. Initial and monthly fees are calculated, and the server adds these fees to the user's account as billing information and reflects them in the next billing cycle. The billing information is the output data. The user receives a payment notification and makes the payment via the provided link. The payment information is the final output data.

[0428] (Application example 2)

[0429] 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."

[0430] Conventional presentation video generation systems require advanced editing techniques and dedicated software, making them difficult for non-experts to use. Furthermore, typical presentation videos have uniform content and lack personalization for viewers. As a result, they fail to attract viewers' attention, making it difficult to carry out effective sales promotions.

[0431] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting explanatory materials for products that a company wants to promote into the system, means for changing the presenter's image from a default image to a custom avatar or a new image, means for generating a presentation video that combines the generated script and the presenter's image, means for providing and notifying a user of a download link for the generated video, means for using an emotion engine that analyzes the user's facial expressions and voice in real time, and means for reflecting emotion information obtained from the emotion engine in the presentation video. This makes it possible to easily generate high-quality, personalized presentation videos without specialized knowledge.

[0432] "Sales promotion" is a marketing activity aimed at increasing sales of a product or service.

[0433] "Explanatory materials" are written and media content used to explain in detail the features and benefits of a product.

[0434] "Inputting into the system" means that a user uploads or enters data or files into the system.

[0435] A "presenter" is a person or character who provides explanations and guidance during a presentation.

[0436] A "custom avatar" is an original virtual character that a user can freely create or select.

[0437] A "generated script" is a presentation script or dialogue generated by the system from explanatory materials.

[0438] "Presentation video" is video content that conveys information visually and audibly.

[0439] The "download link" is a URL for downloading the generated video via the Internet.

[0440] The "emotion engine" is a system that analyzes emotions from a user's facial expressions and voice and provides that information as data.

[0441] "Analyzing in real time" means analyzing data on the fly while the user is operating the device.

[0442] "Generative AI" is a system that uses artificial intelligence technology to automatically generate new content and information from data.

[0443] "Initial costs" are one-time costs incurred when starting to use a service or system.

[0444] "Monthly fee" refers to the fee paid each month to continue using a service or system.

[0445] "Billing Information" means detailed information about charges and payments owed by the User.

[0446] These definitions can be used to clarify the meaning of important terms contained in the claims.

[0447] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. The system is easy to operate using a smartphone app and includes an emotion engine that analyzes the user's emotional information in real time.

[0448] Upload explanatory materials

[0449] A user accesses the system using a smartphone and uploads explanatory materials (e.g., PDF files). The device sends the files to the server, which stores the received explanatory materials and converts them into an internal format. This conversion is performed using software that uses text analysis techniques to extract key points.

[0450] Presenter Settings

[0451] The user configures the presenter settings through a smartphone app. They can check the default presenter image (e.g., an image of a company representative) and select and upload a new presenter image (e.g., a custom avatar). The device reads this image file and sends it to the server. The server saves the image and updates the presenter settings information.

[0452] Emotion recognition and reflection

[0453] While the user is uploading their presentation materials, the emotion engine analyzes the user's facial expressions and voice in real time to determine their emotions. This emotion engine uses a library called EmotionEngine. The analyzed emotional information is sent to the server and reflected in the presentation video. Specifically, it is reflected in the presenter's facial expressions and tone of voice.

[0454] Video generation

[0455] The server uses a generative AI model to create a script based on explanatory materials, emotional information, and the presenter's image. This script includes text data for the script and dialogue to be used in the presentation video. The server then combines the generated script with the presenter's image to generate a presentation video. A library called VideoGenerator is used to generate high-quality videos. The generated video files are saved in the storage area associated with the user's account.

[0456] Video notification and provision

[0457] The server notifies the user of the download link for the generated video. The notification method is to use the email sending API. The user receives the notification and can click the link to download the video.

[0458] Specific examples

[0459] A company's marketing manager, Mr. A, prepared explanatory materials for a new product, "Smart Gadget," in PDF format. He logged into the system using a smartphone app and uploaded the materials. The server analyzed the text of the materials and extracted key points. Next, Mr. A selected and uploaded a custom avatar on the presenter settings page. The emotion engine analyzed Mr. A's emotions, such as joy and anticipation, and reflected them in the presenter's facial expressions and tone of voice. Finally, the server used generative AI to generate a presentation video and sent Mr. A a download link.

[0460] Prompt Sentence Examples

[0461] We have uploaded an explanatory document for our new product, a "smartwatch." This is a next-generation wearable device that can record heart rate, steps, calorie consumption, and more in real time. Use an emotion recognition engine to analyze the user's facial expressions and tone of voice to create a more engaging presentation video. Use a company character as the presenter image.

[0462] The above is a detailed description of the embodiment of the present invention. This system makes it possible to easily generate high-quality personalized presentation videos without requiring specialized knowledge.

[0463] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0464] Step 1:

[0465] A user logs in to the system using a smartphone and uploads explanatory materials. When the user uploads a PDF file, the device reads the file and sends it to the server. The server receives and saves the file. The input is the PDF file uploaded by the user, and the output is the saved explanatory materials.

[0466] Step 2:

[0467] The server converts the uploaded explanatory materials into an internal format using text analysis technology, specifically extracting and organizing key points. The input is the saved explanatory materials, and the output is the text data of the extracted key points.

[0468] Step 3:

[0469] The user opens the presenter settings page on the smartphone app and checks the default presenter image. They then select and upload a new presenter image. The device reads this new image and sends it to the server. The input is the presenter image uploaded by the user, and the output is the presenter image saved on the server.

[0470] Step 4:

[0471] While the user is uploading explanatory materials, the emotion engine analyzes the user's facial expressions and voice in real time. The analysis results are sent to the server. The input is the user's facial expressions and voice data, and the output is the analyzed emotional information.

[0472] Step 5:

[0473] The server uses a generative AI model to create a script based on the explanatory materials, extracted key points, emotional information, and the presenter image. The inputs are the extracted key points, emotional information, and the presenter image, and the output is the generated script.

[0474] Step 6:

[0475] The server generates a presentation video by combining the generated script and the presenter image. It uses the VideoGenerator library to generate high-quality videos. The input is the generated script and the presenter image, and the output is the generated presentation video.

[0476] Step 7:

[0477] The server notifies the user of the download link for the generated video. The notification method uses an email sending API. The input is the generated presentation video, and the output is the download link sent to the user.

[0478] Step 8:

[0479] The user receives a notification and clicks the download link to download the generated presentation video. The input is the download link sent from the server, and the output is the presentation video downloaded by the user.

[0480] 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.

[0481] 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.

[0482] 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.

[0483] [Second embodiment]

[0484] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0485] 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.

[0486] 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).

[0487] 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.

[0488] 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.

[0489] 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).

[0490] 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.

[0491] 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.

[0492] 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.

[0493] 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.

[0494] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0495] 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."

[0496] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. The system consists of a server and a user terminal, and uses generation AI to create high-quality videos.

[0497] System Operation

[0498] Input of explanatory materials

[0499] A user prepares explanatory materials (e.g., PDF files) for the products their company wants to promote, and logs in with their company account information to access the system. After logging in, the user accesses the dashboard and opens the explanatory materials upload page. Next, the user uploads the explanatory materials file using drag and drop or the file selection button. The terminal reads this file and sends it to the server. The server saves the received explanatory materials and converts them into an appropriate internal format (e.g., performs text analysis and extracts key points).

[0500] Presenter Settings

[0501] The user accesses the presenter settings page and sees the default presenter image (e.g., an image of the company CEO). Then, the user selects and uploads a new presenter image (e.g., a custom avatar). The device reads the selected image file and sends it to the server. The server saves the image and updates the presenter's settings information.

[0502] Video generation

[0503] The server uses a generative AI to create a script based on the explanatory materials and the presenter's settings. This script includes text data for the script and dialogue to be used in the presentation video. The server then combines the generated script with the presenter's image to generate the presentation video. The generated video file is saved in the storage area associated with the user's account.

[0504] Video notification and provision

[0505] The server notifies the user of the generated download link for the video, and the user can receive this notification and click the link to download the video.

[0506] Pricing

[0507] The system will calculate the initial and monthly fees based on the videos generated and add the billing information to the user's account. The server will calculate these fees and apply them to the next billing cycle. The user will receive a payment notification and pay the fees through the provided payment link.

[0508] Specific examples

[0509] Input of explanatory materials

[0510] A company's marketing manager, Mr. A, prepared explanatory materials in PDF format for a new product, "Smart Gadget." He logged into the system and uploaded the materials by dragging and dropping them onto the upload page on the dashboard. The server then performed a text analysis of the materials and extracted key points.

[0511] Presenter Settings

[0512] Person A went to the presenter settings page and saw the default CEO image. Person A uploaded a custom avatar and the server saved this new image and updated the settings.

[0513] Video generation

[0514] The server created a script using generative AI based on the explanatory materials and the new presenter image, and generated a presentation video. The server associated this video with Mr. A's account, saved it, and sent him a download link.

[0515] Video notification and provision

[0516] Mr. A received a notification and got a professionally generated presentation video from the download link.

[0517] Pricing

[0518] The system calculated the initial and monthly fees based on A's usage and added the billing information to his account. A received a payment notification and made the payment via the provided link.

[0519] As described above, the present invention provides a system that enables companies to easily generate high-quality presentation videos even without specialized knowledge.

[0520] The processing flow will be explained below.

[0521] Step 1:

[0522] The user accesses the system and enters their company account information on the login screen to log in. The server sends the entered account information to the authentication system and returns the authentication result.

[0523] Step 2:

[0524] The user accesses the dashboard and opens the upload page for the instructional materials. The device displays a file selection button, allowing the user to select a local file.

[0525] Step 3:

[0526] The user selects a file (e.g. PDF) of the product description they want to promote and clicks the upload button. The device reads the selected file and sends it to the server.

[0527] Step 4:

[0528] The server stores the received files and converts them into a suitable internal format, for example by performing text analysis and extracting key points.

[0529] Step 5:

[0530] The user accesses the presenter settings page, and the device displays the default presenter image (e.g., an image of the company CEO) on the screen.

[0531] Step 6:

[0532] The user selects and uploads a new presenter image. The device reads the selected image file and sends it to the server.

[0533] Step 7:

[0534] The server stores the received image and updates the presenter's setting information.

[0535] Step 8:

[0536] The server uses generative AI to create a presentation script based on the content of the input explanatory materials (text information).

[0537] Step 9:

[0538] Based on the created script, the server generates a presentation video that combines the presenter's settings (avatar and image).

[0539] Step 10:

[0540] The server stores the generated video file in association with the user's account.

[0541] Step 11:

[0542] The server notifies the user that the video has been generated and provides a download link, which the user clicks to download the video.

[0543] Step 12:

[0544] The server calculates the initial fee and monthly fee based on the user's usage and adds the billing information to the user's account.

[0545] Step 13:

[0546] The server sends a payment notification to the user and provides a payment link, and the user receives the payment notification and pays the fee through the provided link.

[0547] Example 1

[0548] 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."

[0549] Creating professional presentation videos for corporate sales promotion requires a great deal of effort and expertise. While systems exist for automatically generating presentation videos, further improvements are needed to effectively extract key points from explanatory materials and generate high-quality scripts. A system that solves these problems and generates efficient, high-quality presentation videos is needed.

[0550] 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.

[0551] In this invention, the server includes means for analyzing explanatory materials for products that a company wants to promote, extracting key points, and converting them into an internal format, means for creating a script from the explanatory materials using a generative AI model, and means for generating a presentation video that combines the generated script with an image of the presenter, thereby enabling companies to automatically generate high-quality presentation videos even without specialized knowledge.

[0552] An "enterprise" is an organization that provides goods and services and engages in commercial activities.

[0553] "Sales promotion" is a part of marketing activities carried out to increase sales of a product.

[0554] "Explanatory materials" are documents that describe the features and benefits of a product and are used in sales promotion activities.

[0555] A "system" is a collection of hardware and software combined to achieve a particular purpose.

[0556] A "server" is a computer that provides services to other computers on a network.

[0557] "Analysis" is the process of breaking down the content of materials or data and extracting meaning and key points.

[0558] "Major points" are sections that highlight important information or key points contained in the presentation material.

[0559] An "internal format" is a standardized data format used within a system.

[0560] A "presenter" is a person or character who gives explanations in a presentation video.

[0561] A "custom avatar" is a virtual character created for a specific purpose or individual.

[0562] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to automatically generate data.

[0563] A "script" is text data that describes the content and dialogue of a presentation video.

[0564] A "presentation video" is video content that visually explains the features and benefits of a product.

[0565] "Download link" means a URL link for downloading a file over the Internet.

[0566] A "notification" is a message or alert that informs a user of certain information.

[0567] "Initial costs" are one-time costs paid when you start using the system.

[0568] "Monthly fee" refers to the fee paid each month for the continued use of the system.

[0569] "Billing Information" means information that describes the charges incurred by the User.

[0570] A "prompt" is input text that gives instructions or questions to a generative AI model.

[0571] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. The system consists of a server and a user terminal, and uses generation AI to create high-quality videos.

[0572] Input of explanatory materials

[0573] A user prepares explanatory materials (e.g., PDF files) for the products their company wants to promote, and logs in with their company's account information to access the system. After logging in, the user accesses the dashboard and opens the explanatory materials upload page. Next, the user uploads the explanatory materials file using drag and drop or the file selection button. The terminal reads this file and sends it to the server.

[0574] The server temporarily stores the received explanatory materials, analyzes the text content using a text extraction tool such as PDFMiner, extracts key points using a natural language processing library (e.g., SpaCy), converts the extracted information into an internal format, and stores it in a database.

[0575] Presenter Settings

[0576] The user accesses the presenter settings page, sees the default presenter image (e.g., an image of the company CEO), selects a new presenter image (e.g., a custom avatar), and uploads it. The device reads the selected image file and sends it to the server.

[0577] The server saves this image file and updates the presenter's configuration information using an image processing library such as OpenCV.

[0578] Video generation

[0579] Based on the saved explanatory materials and the presenter's settings, the server sends a prompt such as, "Generate a professional presentation video for our new product, 'Smart Gadget.' Create a script based on the explanatory materials below and use the configured custom avatar." to the generation AI model (e.g., GPT-4) and creates a script.

[0580] The generated script can be checked and edited as necessary. The edited script is then combined with the presenter image to generate a presentation video using a generation AI such as DALL-E. The created video file is saved and associated with the user's account.

[0581] Video notification and provision

[0582] The server notifies the user of the generated download link for the video. The user can receive this notification and click the link to download the video. Notification can be done using an email sending API (e.g., SendGrid).

[0583] Pricing

[0584] The server calculates the fee based on the generated video information. It uses a fee calculation algorithm to calculate the initial fee and monthly fee. The calculated fee is added to the user's account and reflected in the next billing cycle. A payment notification email is sent to the user, and the fee can be paid via the provided payment link. An online payment service such as Stripe API is used.

[0585] The above are specific embodiments of the present invention based on the claims. This system allows companies to easily generate high-quality presentation videos without specialized knowledge.

[0586] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0587] Step 1:

[0588] User: Access the system login page and log in with your account information.

[0589] Input: User account information (e.g. username, password)

[0590] Output: After successful login, redirect to dashboard

[0591] Specific operation: The user opens a browser, accesses the system's URL, enters the required information in the login form, and clicks the "Login" button.

[0592] Step 2:

[0593] User: Open the "Upload Materials" page on your dashboard and select your materials.

[0594] Input: Explanation materials (e.g. PDF file)

[0595] Output: Explanation file uploaded

[0596] Specific operation: The user clicks the "Upload explanatory materials" button or page, drags and drops explanatory materials from the file selection dialog that appears, or selects a file using the "Select File" button, and clicks the "Start Upload" button.

[0597] Step 3:

[0598] Terminal: Reads the selected file and sends it to the server.

[0599] Input: explanatory file

[0600] Output: File data sent to the server

[0601] Specific operation: The terminal reads the selected file data as output from the file selection dialog and sends it to the server via an HTTP request.

[0602] Step 4:

[0603] Server: Temporarily stores the received explanatory material files and analyzes the text content using a text extraction tool such as PDFMiner.

[0604] Input: explanatory file

[0605] Output: Extracted text data

[0606] What it does: The server saves the file in a specific directory and uses a tool like PDFMiner to extract the text from the PDF.

[0607] Step 5:

[0608] Server: Analyze the extracted text data using a natural language processing library (e.g., SpaCy) and extract key points.

[0609] Input: Text data

[0610] Output: Text data containing key points

[0611] How it works: The server applies SpaCy to the extracted text data to extract noun phrases and identify keywords, then stores the key points in a database.

[0612] Step 6:

[0613] Users: Visit the Presenter Settings page to view the default presenter image and upload a new one.

[0614] Input: New presenter image (e.g. JPEG, PNG file)

[0615] Output: New presenter image uploaded

[0616] What happens: On the Presenter Settings page, the user clicks the "Change Presenter Image" button, selects a new image file, and uploads it.

[0617] Step 7:

[0618] On the device: Load the selected image file and send it to the server.

[0619] Input: New presenter image

[0620] Output: Image data sent to the server

[0621] Specific operation: The terminal reads the image data selected as the output of the file selection dialog and sends it to the server via an HTTP request.

[0622] Step 8:

[0623] Server: Saves the received image files and updates the presenter's settings using an image processing library such as OpenCV.

[0624] Input: New presenter image

[0625] Output: Updated presenter settings

[0626] Specific operation: The server saves image files in a specific directory, analyzes and processes the images using OpenCV, and updates the configuration information in the database.

[0627] Step 9:

[0628] Server: Based on the saved explanatory materials and presenter settings, it sends prompts to the generative AI model (e.g., GPT-4) and generates a script.

[0629] Input: Main points of the presentation materials, presenter setting information

[0630] Output: Generated script

[0631] Specific operation: The server generates a prompt saying, "Please generate a professional presentation video for our new product, 'Smart Gadget'. Please create a script based on the explanatory materials below and use the custom avatar you set." and sends it to the generation AI to generate the script.

[0632] Step 10:

[0633] Server: Review the generated script and make any necessary modifications.

[0634] Input: Generated script

[0635] Output: The modified script

[0636] What happens: The server administrator or an automated proofreader checks the script and makes corrections if necessary.

[0637] Step 11:

[0638] Server: The modified script is combined with the presenter image and a generative AI such as DALL-E is used to generate a presentation video.

[0639] Input: modified script, presenter image

[0640] Output: Generated presentation video

[0641] Specific operation: The server inputs the script and images into the generation AI and executes the video generation process.

[0642] Step 12:

[0643] Server: Stores the created video file in association with the user's account.

[0644] Input: Generated presentation video

[0645] Output: Video files associated with the user's account

[0646] What happens: The server stores the video file in a database and links it to the appropriate user account.

[0647] Step 13:

[0648] Server: Sends the generated video download link to the user.

[0649] Input: Link to the generated video file

[0650] Output: Notification email sent to user

[0651] Specific operation: The server uses an email sending API (e.g. SendGrid) to send a notification email to the user containing a download link.

[0652] Step 14:

[0653] User: Receives notification email and clicks link to download video.

[0654] Input: Download link in the notification email

[0655] Output: Downloaded presentation video

[0656] Specific behavior: The user clicks on the link in the received email, accesses the video download page, and downloads the video file.

[0657] Step 15:

[0658] Server: Calculates fees based on the generated video information. A fee calculation algorithm is used to calculate the initial fee and monthly fee.

[0659] Input: Generated video information

[0660] Output: Charge calculation result

[0661] Specific operation: The server analyzes the video information stored in the database and calculates the fee using a specific algorithm.

[0662] Step 16:

[0663] Server: Adds the calculated fee to the user's account and applies it to the next billing cycle.

[0664] Input: Fee calculation result

[0665] Output: Billing information added to the user's account

[0666] Specific operation: The server saves the calculation results in the database and reflects them in the next billing cycle.

[0667] Step 17:

[0668] Server: Sends payment notification email to user and provides payment link.

[0669] Enter: Billing Information

[0670] Output: Payment notification email

[0671] Specific operation: The server uses the Email Sending API to send a payment notification email to the user.

[0672] Step 18:

[0673] User: Receives payment notification and clicks link to visit payment page.

[0674] Input: Payment link in payment notification email

[0675] Output: Payment completion screen

[0676] Specific behavior: The user clicks on the link in the email and completes the payment using an online payment service (e.g., Stripe API).

[0677] The above is the detailed processing flow of the program of this system.

[0678] (Application example 1)

[0679] 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."

[0680] Conventional presentation video generation systems require specialized knowledge, making it difficult to easily generate high-quality promotional videos. Furthermore, they lack the functionality to manage and download videos using smartphones, making it difficult for marketers and advertising agencies to carry out their work efficiently.

[0681] 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.

[0682] In this invention, the server includes means for inputting explanatory materials for products that a company wants to promote into the system, means for changing the presenter's image from a default image to a custom avatar or a new image, means for generating a presentation video that combines the generated script and the presenter's image, means for providing and notifying a download link for the generated video, means for including a user interface optimized for smartphones, means for calculating a fee based on the generated video and notifying payment, means for creating a script from the explanatory materials using a generative AI model, and means for managing and downloading the video using a smartphone. This allows high-quality promotional videos to be easily generated without specialized knowledge, and allows efficient management and download of the videos using a smartphone.

[0683] An "enterprise" is a legal entity that provides a specific product or service to the market and pursues profits.

[0684] "Sales promotion" refers to marketing activities that help sell a product or service and make consumers aware of its value.

[0685] "Explanatory materials" are documents or data intended for consumers or interested parties that provide information about a particular product or service.

[0686] A "system" is a device or procedure that combines multiple elements (hardware, software, data, etc.) to achieve a specific purpose.

[0687] "Input" refers to the act of entering information or data into a system.

[0688] A "presenter" is a person or avatar whose role is to visually and audibly convey information or ideas.

[0689] "Custom Avatar" means a custom-made digital character or image created by a user.

[0690] A "script" is a sequence of scripts or scenarios using audio or text.

[0691] A "generative AI model" is an algorithm that uses artificial intelligence to generate or transform data.

[0692] "Presentation Video" means a video presentation for conveying information visually and audibly.

[0693] A "download link" is a URL or hyperlink that allows you to obtain a particular file on the Internet.

[0694] A "notification" is a message or alert that informs the user of specific information or events.

[0695] A "user interface" is a means or screen through which a system and a user can interact with each other to exchange information.

[0696] "Fees" means money payable for the provision of services or the purchase of products.

[0697] "Payment Notice" means a message or notice sent to a User to notify the User of a particular payment.

[0698] A "smartphone" is a small mobile device that combines the functionality of a mobile phone with that of a computer.

[0699] This section describes the specific steps for companies to upload product promotion materials to the system and generate professional presentation videos using a generative AI model. It also provides a user interface that allows users to manage and download videos using a smartphone.

[0700] Required Hardware and Software

[0701] Server: Analyzes the text of explanatory materials, generates scripts using generative AI models, generates videos, calculates fees, and processes notifications.

[0702] Devices: Provide an interface for users to upload presentation materials and set presenter images. This includes mobile devices such as smartphones and tablets.

[0703] Generative AI models: Artificial intelligence models for generating scripts from explanatory materials, such as OpenAI's GPT-3.

[0704] Software: PyPDF2 (PDF reading), Pillow (image processing), requests (HTTP requests), OpenAI API library.

[0705] System Operation

[0706] 1. Explanatory Material Input:

[0707] A user prepares explanatory materials in PDF or other formats for products that a company is promoting.

[0708] Users access the system via an internet browser, log in, and then upload explanatory materials to the system.

[0709] The server receives the uploaded explanatory material and uses PyPDF2 to parse the text and extract the main points.

[0710] 2. Presenter Settings:

[0711] The presenter settings page allows users to view the default images and upload new presenter images (custom avatars or new images).

[0712] The server receives and stores the new image file.

[0713] 3. Video generation:

[0714] The server uses a generative AI model to generate a script for the presentation video from the text of the explanatory materials, with the following prompt:

[0715] Prompt: "Generate a promo video script based on the following brief:\n\n[Text of brief]"

[0716] The server combines the generated script with the presenter's image and generates a video file using an image processing library such as Pillow.

[0717] 4. Video Notification and Provision:

[0718] The server stores the generated presentation video file and associates it with the user's account.

[0719] The user will be notified when the video is complete and provided with a download link, which they can use to download the video using their smartphone.

[0720] 5. Calculation and Notification of Fees:

[0721] The server calculates the initial and monthly fees based on the video production and adds the billing information to the user's account.

[0722] The user will be notified of the payment and will be provided with a link to complete the payment.

[0723] Specific examples

[0724] Input of explanatory materials: A marketing person prepares explanatory materials for new product X in PDF format and uploads them after logging in to the system.

[0725] Presenter settings: The presenter sets a custom avatar and uploads it to the server.

[0726] Video generation: The server analyzes the text of the explanatory materials and uses a generative AI model (such as GPT-3) to generate a script for the promotional video, which is then combined with an image of the presenter to create the video.

[0727] Video notification and provision: The server associates the generated video with the agent's account and notifies the agent of the download link, which the agent clicks to download the video to their smartphone.

[0728] Calculation and notification of fees: The server calculates the fee for video generation and sends a payment notification to the person in charge.

[0729] In this way, companies can easily generate high-quality promotional videos without specialized knowledge, and can efficiently manage and download the videos using a smartphone.

[0730] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0731] Step 1:

[0732] (Input of explanatory materials)

[0733] Users access the system, log in, and then upload a PDF file describing the product they want to promote. The device then sends the uploaded PDF file to the server, which then uses PyPDF2 to analyze the PDF and extract text data. The key points of the extracted text data are then retrieved and used as input for the generative AI model.

[0734] Input: PDF format explanatory materials

[0735] Output: Text data extracted from the explanatory materials

[0736] Step 2:

[0737] (Presenter settings)

[0738] The user sees the default presenter image on the presenter settings page. If the user chooses to upload a new presenter image (custom avatar or new image), the device sends this image to the server. The server saves the new presenter image and updates the presenter information.

[0739] Input: New presenter image

[0740] Output: Updated presenter information

[0741] Step 3:

[0742] (Script generation)

[0743] The server uses a generative AI model to generate a script for the video based on the text data extracted from the explanatory materials. Specifically, a prompt sentence is input into the generative AI model to generate an appropriate script. An example of the prompt sentence is as follows:

[0744] Prompt: "Generate a promo video script based on the following brief:\n\n[Text of brief]"

[0745] The server receives the generated script and prepares it as the basic data for the presentation video.

[0746] Input: Text data extracted from explanatory materials, prompt text

[0747] Output: Script for video

[0748] Step 4:

[0749] (Video generation)

[0750] The server combines the generated script with the presenter's image to generate a presentation video. It uses an image processing library such as Pillow to set the timing and effects of the text based on the script, and to position the presenter's image appropriately. The generated video file is saved on the server.

[0751] Input: video script, presenter image

[0752] Output: Generated presentation video

[0753] Step 5:

[0754] (Video notification and provision)

[0755] The server generates a link to the location where the generated video is saved and notifies the user of this link. The user can download the generated video from the provided link. If downloading using a smartphone, this operation is performed through a user interface optimized for smartphones.

[0756] Input: Generated presentation video

[0757] Output: Video download link, notification

[0758] Step 6:

[0759] (Calculation and notification of fees)

[0760] The server calculates the initial and monthly fees based on the generated video and adds the billing information to the user's account. The server sends a payment notice to the user based on the billing information. The user confirms the notice and pays the fee via the provided payment link.

[0761] Input: Generated video, pricing criteria

[0762] Output: Initial and monthly fees, payment notice

[0763] By following these steps, businesses can easily generate high-quality promotional videos without specialized knowledge, and efficiently manage, download, and pay for the videos using their smartphones.

[0764] 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.

[0765] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. This system also incorporates an emotion engine that recognizes user emotions, enabling more personalized video generation. The system consists of a server, a user device, and an emotion engine, and utilizes generative AI to create high-quality videos.

[0766] System Operation

[0767] Input of explanatory materials

[0768] A user prepares explanatory materials (e.g., PDF files) for the products their company wants to promote, and logs in with their company account information to access the system. After logging in, the user accesses the dashboard and opens the explanatory materials upload page. Next, the user uploads the explanatory materials file using drag and drop or the file selection button. The terminal reads this file and sends it to the server. The server saves the received explanatory materials and converts them into an appropriate internal format (e.g., performs text analysis and extracts key points).

[0769] Presenter Settings

[0770] The user accesses the presenter settings page and sees the default presenter image (e.g., an image of the company CEO). Then, the user selects and uploads a new presenter image (e.g., a custom avatar). The device reads the selected image file and sends it to the server. The server saves the image and updates the presenter's settings information.

[0771] Emotion recognition and reflection

[0772] While the user is interacting with the upload page, the emotion engine recognizes emotions from the user's facial expressions and voice. The emotion engine then transmits the user's emotional information to the server in real time. Based on this information, the server adjusts the content of the presentation video (e.g., the presenter's facial expressions and tone of voice).

[0773] Video generation

[0774] The server uses a generative AI to create a script based on the explanatory materials, emotional information obtained from the emotion engine, and the presenter's settings. This script includes text data for the script and dialogue to be used in the presentation video. The generated script is then combined with the presenter's image to generate the presentation video. The generated video file is saved in the storage area associated with the user's account.

[0775] Video notification and provision

[0776] The server notifies the user of the generated download link for the video, and the user can receive this notification and click the link to download the video.

[0777] Pricing

[0778] The system will calculate the initial and monthly fees based on the videos generated and add the billing information to the user's account. The server will calculate these fees and apply them to the next billing cycle. The user will receive a payment notification and pay the fees through the provided payment link.

[0779] Specific examples

[0780] Input of explanatory materials

[0781] A company's marketing manager, Mr. A, prepared explanatory materials in PDF format for a new product, "Smart Gadget." He logged into the system and uploaded the materials by dragging and dropping them onto the upload page on the dashboard. The server then performed a text analysis of the materials and extracted key points.

[0782] Presenter Settings

[0783] Person A went to the presenter settings page and saw the default CEO image. Person A uploaded a custom avatar and the server saved this new image and updated the settings.

[0784] Emotion recognition and reflection

[0785] While Ms. A was uploading her materials, the emotion engine analyzed her facial expressions and voice and sent her emotional information to the server. The server analyzed Ms. A's emotions, such as joy and anticipation, and adjusted the presenter's facial expressions and tone of voice based on those.

[0786] Video generation

[0787] The server used generative AI to create a script based on the explanatory materials, emotional information, and presenter image, and generated a presentation video. The server associated this video with Person A's account, saved it, and sent Person A a download link.

[0788] Video notification and provision

[0789] Mr. A received a notification and got a professionally generated presentation video from the download link.

[0790] Pricing

[0791] The system calculated the initial and monthly fees based on A's usage and added the billing information to his account. A received a payment notification and made the payment via the provided link.

[0792] As described above, the present invention provides a system that enables companies to easily generate high-quality, personalized presentation videos without requiring specialized knowledge.

[0793] The processing flow will be explained below.

[0794] Step 1:

[0795] The user accesses the system and enters their company account information on the login screen to log in. The server sends the entered account information to the authentication system and returns the authentication result.

[0796] Step 2:

[0797] The user accesses the dashboard and opens the upload page for the instructional materials. The device displays a file selection button, allowing the user to select a local file.

[0798] Step 3:

[0799] The user selects a file (e.g. PDF) of the product description they want to promote and clicks the upload button. The device reads the selected file and sends it to the server.

[0800] Step 4:

[0801] The server stores the received files and converts them into a suitable internal format, for example by performing text analysis and extracting key points.

[0802] Step 5:

[0803] The user accesses the presenter settings page, and the device displays the default presenter image (e.g., an image of the company CEO) on the screen.

[0804] Step 6:

[0805] The user selects and uploads a new presenter image. The device reads the selected image file and sends it to the server.

[0806] Step 7:

[0807] The server stores the received image and updates the presenter's setting information.

[0808] Step 8:

[0809] While the user is operating the upload page, the emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional information.

[0810] Step 9:

[0811] The emotion engine transmits the acquired emotion information to the server, which stores it and reflects it in the presentation content.

[0812] Step 10:

[0813] The server uses generative AI to create a presentation script based on the content of the input explanatory materials (text information) and emotional information.

[0814] Step 11:

[0815] Based on the created script, the server generates a presentation video that combines the presenter's settings (avatar and image) with emotional information.

[0816] Step 12:

[0817] The server stores the generated video file in association with the user's account.

[0818] Step 13:

[0819] The server notifies the user that the video has been generated and provides a download link, which the user clicks to download the video.

[0820] Step 14:

[0821] The server calculates the initial fee and monthly fee based on the user's usage and adds the billing information to the user's account.

[0822] Step 15:

[0823] The server sends a payment notification to the user and provides a payment link, and the user receives the payment notification and pays the fee through the provided link.

[0824] Example 2

[0825] 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."

[0826] Conventional presentation video creation systems lack the technology to automatically generate high-quality, personalized videos, making it difficult for companies without specialized knowledge to easily create high-quality presentation videos. Furthermore, personalization that reflects customer emotional information is not easy, resulting in a problem of low quality in the generated videos.

[0827] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for inputting explanatory materials for products that a company wants to promote into the system, a means for changing the presenter's image from a default image to a custom avatar or a new image, a means for combining the generated script with the presenter's image to generate a presentation video that reflects emotional information, a means for providing and notifying a download link for the generated video, and a means for recognizing emotions in real time and transmitting that information to the system. This makes it possible to easily create high-quality, personalized presentation videos even without specialized knowledge.

[0828] "Company" refers to a legal entity or organization that promotes a particular product or service.

[0829] An "explanatory material" refers to a document (e.g., a PDF file) containing information about a product or service prepared by a company for sales promotion purposes.

[0830] "Presenter" refers to a virtual character or person who explains a product or service within a presentation video.

[0831] "Custom Avatar" refers to a unique presenter image created or selected by a user.

[0832] "Generated script" refers to the text data of the script and dialogue of a presentation video that is automatically generated based on the content of the explanatory materials and other information.

[0833] "Emotion information" refers to data related to emotions recognized in real time from the user's facial expressions and voice.

[0834] "Generative AI" refers to a system or software that uses artificial intelligence technology to automatically generate scripts, presentation videos, etc.

[0835] "Download link" refers to the URL for obtaining the generated presentation video via the Internet.

[0836] An "emotion engine" refers to software or hardware that has the ability to recognize emotions from a user's facial expressions and voice and transmit that information to the system.

[0837] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products that companies want to promote. This system consists of a server, user terminals, and an emotion engine, and utilizes generation AI to create high-quality videos.

[0838] The system operates in the following specific steps:

[0839] Input of explanatory materials

[0840] Users access the system's login page and log in by entering their company's account information. After logging in, they move to the dashboard page and click the "Upload Materials" button to access the upload page. Then, they drag and drop explanatory materials (e.g., PDF files) or click the "Select File" button to select a file.

[0841] The device reads the selected file and sends its contents to the server, which stores the received file and performs text analysis, extracting key points and elements and storing them in an internal database.

[0842] Presenter Settings

[0843] Users access the reconfigured Presenter Settings page in their dashboard, review the default presenter image (e.g., an image of the company CEO), and click the "Change Image" button to upload a new presenter image (e.g., a custom avatar).

[0844] The device reads the uploaded image file and sends it to the server, which saves the new image and updates the presenter setting information.

[0845] Emotion recognition and reflection

[0846] While the user is uploading explanatory materials, the emotion engine uses the camera and microphone to analyze emotions from the user's facial expressions and voice in real time, and sends emotional information (e.g., joy, surprise, concentration, etc.) to the server.

[0847] The server adjusts the content of the presentation video based on the emotion information, so that the presenter's facial expressions and tone of voice change to match the user's emotions.

[0848] Video generation

[0849] The server uses a generative AI model to create a script for the presentation video based on the analysis results of the explanatory materials, emotional information, and presenter settings. The generated script is combined with an image of the presenter to generate a video.

[0850] The generated video file is saved in the storage area associated with the user's account.

[0851] Video notification and provision

[0852] Once the server has completed generating the video, it will send a notification to the user with a download link. The user will receive the notification and click the link to download the presentation video.

[0853] Pricing

[0854] The system calculates the fee based on the usage of the generated videos. The initial and monthly fees are calculated, and the server adds these fees to the user's account as billing information and reflects them in the next billing cycle. The user receives a payment notification and makes the payment via the provided link.

[0855] Examples of concrete examples and prompts

[0856] Example: Input of explanatory materials

[0857] The user logs into the system with their company account and uploads a PDF file of information about a new product. The device reads the file and sends it to the server, which performs text analysis and extracts key points.

[0858] Example: Setting the presenter

[0859] Users navigate to the presenter settings page, see the default CEO image, then upload a custom avatar and the server updates the settings.

[0860] Example: Emotion recognition and reflection

[0861] While the user is uploading materials, the emotion engine analyzes the user's facial expressions and voice and transmits his / her emotional information to the server, which then adjusts the presenter's facial expressions and tone of voice based on the emotional information.

[0862] Example: Video Generation

[0863] The server creates a script using a generative AI model based on the explanatory materials, emotional information, and presenter image, and generates a presentation video. The video is saved in the user's account storage area.

[0864] Example: Video notification and provision

[0865] The user receives a notification from the server and retrieves the generated presentation video from the provided download link.

[0866] Example: Setting prices

[0867] The system calculates the initial and monthly fees based on the user's usage, adds the billing information to the user's account, and the user receives a payment notification and makes the payment via the provided link.

[0868] Prompt Sentence Examples

[0869] "Generate a video of a company representative giving a presentation based on a new product's explanatory materials. Adjust the presenter's tone of voice and facial expressions based on emotional information."

[0870] "To auto-generate a professional presentation video, upload the PDF file below, use a custom avatar as the presenter, and create a video that reflects the user's emotional information."

[0871] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0872] Step 1: Input of explanatory materials

[0873] The user accesses the system's login page and logs in by entering their company's account information. After successful login, they are redirected to the dashboard page. Next, the user clicks the "Upload Materials" button to access the upload page. They drag and drop explanatory materials (e.g., PDF files) or click the "Select File" button to select a file and upload it. This process receives input that explanatory materials will be uploaded. The terminal reads the selected file and sends the file contents to the server. The server saves the received file, performs text analysis to extract key points, and stores them in an internal database. This is the output data.

[0874] Step 2: Presenter Settings

[0875] The user navigates to the "Presenter Settings" page from the dashboard menu. They check the default presenter image (e.g., an image of the company CEO) and click the "Change Image" button to upload a new presenter image (e.g., a custom avatar). This process receives input that the presenter image will be uploaded. The device reads the uploaded image file and sends it to the server. The server saves the new image and updates the presenter setting information. This is the output data.

[0876] Step 3: Emotional awareness and reflection

[0877] While the user is uploading explanatory materials, the emotion engine uses the camera and microphone to analyze emotions from the user's facial expressions and voice in real time. This process inputs the user's facial expression and voice data. The emotion engine sends emotional information (e.g., joy, surprise, concentration, etc.) to the server. This emotional information is the output data. Based on the emotional information, the server adjusts the content of the presentation video, changing the presenter's facial expressions and tone of voice. This adjusted content is the output data.

[0878] Step 4: Generate the video

[0879] The server uses a generative AI model to create a presentation video script based on the analysis results of the explanatory materials, emotional information, and presenter setting information. This process inputs the analysis results, emotional information, and presenter setting information. The server combines the generated script with the presenter's image to generate a video. The generated video file is saved in the storage area associated with the user's account. This is the output data.

[0880] Step 5: Notify and provide the video

[0881] When the server completes the video generation, it sends a notification to the user with a download link. This process inputs the generated video file. The user receives the notification and clicks the link to download the presentation video. The downloaded video is the output data.

[0882] Step 6: Set your prices

[0883] The system calculates fees based on the usage of the generated videos. This process inputs video usage data. Initial and monthly fees are calculated, and the server adds these fees to the user's account as billing information and reflects them in the next billing cycle. The billing information is the output data. The user receives a payment notification and makes the payment via the provided link. The payment information is the final output data.

[0884] (Application example 2)

[0885] 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."

[0886] Conventional presentation video generation systems require advanced editing techniques and dedicated software, making them difficult for non-experts to use. Furthermore, typical presentation videos have uniform content and lack personalization for viewers. As a result, they fail to attract viewers' attention, making it difficult to carry out effective sales promotions.

[0887] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting explanatory materials for products that a company wants to promote into the system, means for changing the presenter's image from a default image to a custom avatar or a new image, means for generating a presentation video that combines the generated script and the presenter's image, means for providing and notifying a user of a download link for the generated video, means for using an emotion engine that analyzes the user's facial expressions and voice in real time, and means for reflecting emotion information obtained from the emotion engine in the presentation video. This makes it possible to easily generate high-quality, personalized presentation videos without specialized knowledge.

[0888] "Sales promotion" is a marketing activity aimed at increasing sales of a product or service.

[0889] "Explanatory materials" are written and media content used to explain in detail the features and benefits of a product.

[0890] "Inputting into the system" means that a user uploads or enters data or files into the system.

[0891] A "presenter" is a person or character who provides explanations and guidance during a presentation.

[0892] A "custom avatar" is an original virtual character that a user can freely create or select.

[0893] A "generated script" is a presentation script or dialogue generated by the system from explanatory materials.

[0894] "Presentation video" is video content that conveys information visually and audibly.

[0895] The "download link" is a URL for downloading the generated video via the Internet.

[0896] The "emotion engine" is a system that analyzes emotions from a user's facial expressions and voice and provides that information as data.

[0897] "Analyzing in real time" means analyzing data on the fly while the user is operating the device.

[0898] "Generative AI" is a system that uses artificial intelligence technology to automatically generate new content and information from data.

[0899] "Initial costs" are one-time costs incurred when starting to use a service or system.

[0900] "Monthly fee" refers to the fee paid each month to continue using a service or system.

[0901] "Billing Information" means detailed information about charges and payments owed by the User.

[0902] These definitions can be used to clarify the meaning of important terms contained in the claims.

[0903] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. The system is easy to operate using a smartphone app and includes an emotion engine that analyzes the user's emotional information in real time.

[0904] Upload explanatory materials

[0905] A user accesses the system using a smartphone and uploads explanatory materials (e.g., PDF files). The device sends the files to the server, which stores the received explanatory materials and converts them into an internal format. This conversion is performed using software that uses text analysis techniques to extract key points.

[0906] Presenter Settings

[0907] The user configures the presenter settings through a smartphone app. They can check the default presenter image (e.g., an image of a company representative) and select and upload a new presenter image (e.g., a custom avatar). The device reads this image file and sends it to the server. The server saves the image and updates the presenter settings information.

[0908] Emotion recognition and reflection

[0909] While the user is uploading their presentation materials, the emotion engine analyzes the user's facial expressions and voice in real time to determine their emotions. This emotion engine uses a library called EmotionEngine. The analyzed emotional information is sent to the server and reflected in the presentation video. Specifically, it is reflected in the presenter's facial expressions and tone of voice.

[0910] Video generation

[0911] The server uses a generative AI model to create a script based on explanatory materials, emotional information, and the presenter's image. This script includes text data for the script and dialogue to be used in the presentation video. The server then combines the generated script with the presenter's image to generate a presentation video. A library called VideoGenerator is used to generate high-quality videos. The generated video files are saved in the storage area associated with the user's account.

[0912] Video notification and provision

[0913] The server notifies the user of the download link for the generated video. The notification method is to use the email sending API. The user receives the notification and can click the link to download the video.

[0914] Specific examples

[0915] A company's marketing manager, Mr. A, prepared explanatory materials for a new product, "Smart Gadget," in PDF format. He logged into the system using a smartphone app and uploaded the materials. The server analyzed the text of the materials and extracted key points. Next, Mr. A selected and uploaded a custom avatar on the presenter settings page. The emotion engine analyzed Mr. A's emotions, such as joy and anticipation, and reflected them in the presenter's facial expressions and tone of voice. Finally, the server used generative AI to generate a presentation video and sent Mr. A a download link.

[0916] Prompt Sentence Examples

[0917] We have uploaded an explanatory document for our new product, a "smartwatch." This is a next-generation wearable device that can record heart rate, steps, calorie consumption, and more in real time. Use an emotion recognition engine to analyze the user's facial expressions and tone of voice to create a more engaging presentation video. Use a company character as the presenter image.

[0918] The above is a detailed description of the embodiment of the present invention. This system makes it possible to easily generate high-quality personalized presentation videos without requiring specialized knowledge.

[0919] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0920] Step 1:

[0921] A user logs in to the system using a smartphone and uploads explanatory materials. When the user uploads a PDF file, the device reads the file and sends it to the server. The server receives and saves the file. The input is the PDF file uploaded by the user, and the output is the saved explanatory materials.

[0922] Step 2:

[0923] The server converts the uploaded explanatory materials into an internal format using text analysis technology, specifically extracting and organizing key points. The input is the saved explanatory materials, and the output is the text data of the extracted key points.

[0924] Step 3:

[0925] The user opens the presenter settings page on the smartphone app and checks the default presenter image. They then select and upload a new presenter image. The device reads this new image and sends it to the server. The input is the presenter image uploaded by the user, and the output is the presenter image saved on the server.

[0926] Step 4:

[0927] While the user is uploading explanatory materials, the emotion engine analyzes the user's facial expressions and voice in real time. The analysis results are sent to the server. The input is the user's facial expressions and voice data, and the output is the analyzed emotional information.

[0928] Step 5:

[0929] The server uses a generative AI model to create a script based on the explanatory materials, extracted key points, emotional information, and the presenter image. The inputs are the extracted key points, emotional information, and the presenter image, and the output is the generated script.

[0930] Step 6:

[0931] The server generates a presentation video by combining the generated script and the presenter image. It uses the VideoGenerator library to generate high-quality videos. The input is the generated script and the presenter image, and the output is the generated presentation video.

[0932] Step 7:

[0933] The server notifies the user of the download link for the generated video. The notification method uses an email sending API. The input is the generated presentation video, and the output is the download link sent to the user.

[0934] Step 8:

[0935] The user receives a notification and clicks the download link to download the generated presentation video. The input is the download link sent from the server, and the output is the presentation video downloaded by the user.

[0936] 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.

[0937] 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.

[0938] 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.

[0939] [Third embodiment]

[0940] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0941] 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.

[0942] 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).

[0943] 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.

[0944] 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.

[0945] 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).

[0946] 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.

[0947] 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.

[0948] 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.

[0949] 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.

[0950] 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.

[0951] 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."

[0952] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. The system consists of a server and a user terminal, and uses generation AI to create high-quality videos.

[0953] System Operation

[0954] Input of explanatory materials

[0955] A user prepares explanatory materials (e.g., PDF files) for the products their company wants to promote, and logs in with their company account information to access the system. After logging in, the user accesses the dashboard and opens the explanatory materials upload page. Next, the user uploads the explanatory materials file using drag and drop or the file selection button. The terminal reads this file and sends it to the server. The server saves the received explanatory materials and converts them into an appropriate internal format (e.g., performs text analysis and extracts key points).

[0956] Presenter Settings

[0957] The user accesses the presenter settings page and sees the default presenter image (e.g., an image of the company CEO). Then, the user selects and uploads a new presenter image (e.g., a custom avatar). The device reads the selected image file and sends it to the server. The server saves the image and updates the presenter's settings information.

[0958] Video generation

[0959] The server uses a generative AI to create a script based on the explanatory materials and the presenter's settings. This script includes text data for the script and dialogue to be used in the presentation video. The server then combines the generated script with the presenter's image to generate the presentation video. The generated video file is saved in the storage area associated with the user's account.

[0960] Video notification and provision

[0961] The server notifies the user of the generated download link for the video, and the user can receive this notification and click the link to download the video.

[0962] Pricing

[0963] The system will calculate the initial and monthly fees based on the videos generated and add the billing information to the user's account. The server will calculate these fees and apply them to the next billing cycle. The user will receive a payment notification and pay the fees through the provided payment link.

[0964] Specific examples

[0965] Input of explanatory materials

[0966] A company's marketing manager, Mr. A, prepared explanatory materials in PDF format for a new product, "Smart Gadget." He logged into the system and uploaded the materials by dragging and dropping them onto the upload page on the dashboard. The server then performed a text analysis of the materials and extracted key points.

[0967] Presenter Settings

[0968] Person A went to the presenter settings page and saw the default CEO image. Person A uploaded a custom avatar and the server saved this new image and updated the settings.

[0969] Video generation

[0970] The server created a script using generative AI based on the explanatory materials and the new presenter image, and generated a presentation video. The server associated this video with Mr. A's account, saved it, and sent him a download link.

[0971] Video notification and provision

[0972] Mr. A received a notification and got a professionally generated presentation video from the download link.

[0973] Pricing

[0974] The system calculated the initial and monthly fees based on A's usage and added the billing information to his account. A received a payment notification and made the payment via the provided link.

[0975] As described above, the present invention provides a system that enables companies to easily generate high-quality presentation videos even without specialized knowledge.

[0976] The processing flow will be explained below.

[0977] Step 1:

[0978] The user accesses the system and enters their company account information on the login screen to log in. The server sends the entered account information to the authentication system and returns the authentication result.

[0979] Step 2:

[0980] The user accesses the dashboard and opens the upload page for the instructional materials. The device displays a file selection button, allowing the user to select a local file.

[0981] Step 3:

[0982] The user selects a file (e.g. PDF) of the product description they want to promote and clicks the upload button. The device reads the selected file and sends it to the server.

[0983] Step 4:

[0984] The server stores the received files and converts them into a suitable internal format, for example by performing text analysis and extracting key points.

[0985] Step 5:

[0986] The user accesses the presenter settings page, and the device displays the default presenter image (e.g., an image of the company CEO) on the screen.

[0987] Step 6:

[0988] The user selects and uploads a new presenter image. The device reads the selected image file and sends it to the server.

[0989] Step 7:

[0990] The server stores the received image and updates the presenter's setting information.

[0991] Step 8:

[0992] The server uses generative AI to create a presentation script based on the content of the input explanatory materials (text information).

[0993] Step 9:

[0994] Based on the created script, the server generates a presentation video that combines the presenter's settings (avatar and image).

[0995] Step 10:

[0996] The server stores the generated video file in association with the user's account.

[0997] Step 11:

[0998] The server notifies the user that the video has been generated and provides a download link, which the user clicks to download the video.

[0999] Step 12:

[1000] The server calculates the initial fee and monthly fee based on the user's usage and adds the billing information to the user's account.

[1001] Step 13:

[1002] The server sends a payment notification to the user and provides a payment link, and the user receives the payment notification and pays the fee through the provided link.

[1003] Example 1

[1004] 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."

[1005] Creating professional presentation videos for corporate sales promotion requires a great deal of effort and expertise. While systems exist for automatically generating presentation videos, further improvements are needed to effectively extract key points from explanatory materials and generate high-quality scripts. A system that solves these problems and generates efficient, high-quality presentation videos is needed.

[1006] 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.

[1007] In this invention, the server includes means for analyzing explanatory materials for products that a company wants to promote, extracting key points, and converting them into an internal format, means for creating a script from the explanatory materials using a generative AI model, and means for generating a presentation video that combines the generated script with an image of the presenter, thereby enabling companies to automatically generate high-quality presentation videos even without specialized knowledge.

[1008] An "enterprise" is an organization that provides goods and services and engages in commercial activities.

[1009] "Sales promotion" is a part of marketing activities carried out to increase sales of a product.

[1010] "Explanatory materials" are documents that describe the features and benefits of a product and are used in sales promotion activities.

[1011] A "system" is a collection of hardware and software combined to achieve a particular purpose.

[1012] A "server" is a computer that provides services to other computers on a network.

[1013] "Analysis" is the process of breaking down the content of materials or data and extracting meaning and key points.

[1014] "Major points" are sections that highlight important information or key points contained in the presentation material.

[1015] An "internal format" is a standardized data format used within a system.

[1016] A "presenter" is a person or character who gives explanations in a presentation video.

[1017] A "custom avatar" is a virtual character created for a specific purpose or individual.

[1018] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to automatically generate data.

[1019] A "script" is text data that describes the content and dialogue of a presentation video.

[1020] A "presentation video" is video content that visually explains the features and benefits of a product.

[1021] "Download link" means a URL link for downloading a file over the Internet.

[1022] A "notification" is a message or alert that informs a user of certain information.

[1023] "Initial costs" are one-time costs paid when you start using the system.

[1024] "Monthly fee" refers to the fee paid each month for the continued use of the system.

[1025] "Billing Information" means information that describes the charges incurred by the User.

[1026] A "prompt" is input text that gives instructions or questions to a generative AI model.

[1027] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. The system consists of a server and a user terminal, and uses generation AI to create high-quality videos.

[1028] Input of explanatory materials

[1029] A user prepares explanatory materials (e.g., PDF files) for the products their company wants to promote, and logs in with their company's account information to access the system. After logging in, the user accesses the dashboard and opens the explanatory materials upload page. Next, the user uploads the explanatory materials file using drag and drop or the file selection button. The terminal reads this file and sends it to the server.

[1030] The server temporarily stores the received explanatory materials, analyzes the text content using a text extraction tool such as PDFMiner, extracts key points using a natural language processing library (e.g., SpaCy), converts the extracted information into an internal format, and stores it in a database.

[1031] Presenter Settings

[1032] The user accesses the presenter settings page, sees the default presenter image (e.g., an image of the company CEO), selects a new presenter image (e.g., a custom avatar), and uploads it. The device reads the selected image file and sends it to the server.

[1033] The server saves this image file and updates the presenter's configuration information using an image processing library such as OpenCV.

[1034] Video generation

[1035] Based on the saved explanatory materials and the presenter's settings, the server sends a prompt such as, "Generate a professional presentation video for our new product, 'Smart Gadget.' Create a script based on the explanatory materials below and use the configured custom avatar." to the generation AI model (e.g., GPT-4) and creates a script.

[1036] The generated script can be checked and edited as necessary. The edited script is then combined with the presenter image to generate a presentation video using a generation AI such as DALL-E. The created video file is saved and associated with the user's account.

[1037] Video notification and provision

[1038] The server notifies the user of the generated download link for the video. The user can receive this notification and click the link to download the video. Notification can be done using an email sending API (e.g., SendGrid).

[1039] Pricing

[1040] The server calculates the fee based on the generated video information. It uses a fee calculation algorithm to calculate the initial fee and monthly fee. The calculated fee is added to the user's account and reflected in the next billing cycle. A payment notification email is sent to the user, and the fee can be paid via the provided payment link. An online payment service such as Stripe API is used.

[1041] The above are specific embodiments of the present invention based on the claims. This system allows companies to easily generate high-quality presentation videos without specialized knowledge.

[1042] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1043] Step 1:

[1044] User: Access the system login page and log in with your account information.

[1045] Input: User account information (e.g. username, password)

[1046] Output: After successful login, redirect to dashboard

[1047] Specific operation: The user opens a browser, accesses the system's URL, enters the required information in the login form, and clicks the "Login" button.

[1048] Step 2:

[1049] User: Open the "Upload Materials" page on your dashboard and select your materials.

[1050] Input: Explanation materials (e.g. PDF file)

[1051] Output: Explanation file uploaded

[1052] Specific operation: The user clicks the "Upload explanatory materials" button or page, drags and drops explanatory materials from the file selection dialog that appears, or selects a file using the "Select File" button, and clicks the "Start Upload" button.

[1053] Step 3:

[1054] Terminal: Reads the selected file and sends it to the server.

[1055] Input: explanatory file

[1056] Output: File data sent to the server

[1057] Specific operation: The terminal reads the selected file data as output from the file selection dialog and sends it to the server via an HTTP request.

[1058] Step 4:

[1059] Server: Temporarily stores the received explanatory material files and analyzes the text content using a text extraction tool such as PDFMiner.

[1060] Input: explanatory file

[1061] Output: Extracted text data

[1062] What it does: The server saves the file in a specific directory and uses a tool like PDFMiner to extract the text from the PDF.

[1063] Step 5:

[1064] Server: Analyze the extracted text data using a natural language processing library (e.g., SpaCy) and extract key points.

[1065] Input: Text data

[1066] Output: Text data containing key points

[1067] How it works: The server applies SpaCy to the extracted text data to extract noun phrases and identify keywords, then stores the key points in a database.

[1068] Step 6:

[1069] Users: Visit the Presenter Settings page to view the default presenter image and upload a new one.

[1070] Input: New presenter image (e.g. JPEG, PNG file)

[1071] Output: New presenter image uploaded

[1072] What happens: On the Presenter Settings page, the user clicks the "Change Presenter Image" button, selects a new image file, and uploads it.

[1073] Step 7:

[1074] On the device: Load the selected image file and send it to the server.

[1075] Input: New presenter image

[1076] Output: Image data sent to the server

[1077] Specific operation: The terminal reads the image data selected as the output of the file selection dialog and sends it to the server via an HTTP request.

[1078] Step 8:

[1079] Server: Saves the received image files and updates the presenter's settings using an image processing library such as OpenCV.

[1080] Input: New presenter image

[1081] Output: Updated presenter settings

[1082] Specific operation: The server saves image files in a specific directory, analyzes and processes the images using OpenCV, and updates the configuration information in the database.

[1083] Step 9:

[1084] Server: Based on the saved explanatory materials and presenter settings, it sends prompts to the generative AI model (e.g., GPT-4) and generates a script.

[1085] Input: Main points of the presentation materials, presenter setting information

[1086] Output: Generated script

[1087] Specific operation: The server generates a prompt saying, "Please generate a professional presentation video for our new product, 'Smart Gadget'. Please create a script based on the explanatory materials below and use the custom avatar you set." and sends it to the generation AI to generate the script.

[1088] Step 10:

[1089] Server: Review the generated script and make any necessary modifications.

[1090] Input: Generated script

[1091] Output: The modified script

[1092] What happens: The server administrator or an automated proofreader checks the script and makes corrections if necessary.

[1093] Step 11:

[1094] Server: The modified script is combined with the presenter image and a generative AI such as DALL-E is used to generate a presentation video.

[1095] Input: modified script, presenter image

[1096] Output: Generated presentation video

[1097] Specific operation: The server inputs the script and images into the generation AI and executes the video generation process.

[1098] Step 12:

[1099] Server: Stores the created video file in association with the user's account.

[1100] Input: Generated presentation video

[1101] Output: Video files associated with the user's account

[1102] What happens: The server stores the video file in a database and links it to the appropriate user account.

[1103] Step 13:

[1104] Server: Sends the generated video download link to the user.

[1105] Input: Link to the generated video file

[1106] Output: Notification email sent to user

[1107] Specific operation: The server uses an email sending API (e.g. SendGrid) to send a notification email to the user containing a download link.

[1108] Step 14:

[1109] User: Receives notification email and clicks link to download video.

[1110] Input: Download link in the notification email

[1111] Output: Downloaded presentation video

[1112] Specific behavior: The user clicks on the link in the received email, accesses the video download page, and downloads the video file.

[1113] Step 15:

[1114] Server: Calculates fees based on the generated video information. A fee calculation algorithm is used to calculate the initial fee and monthly fee.

[1115] Input: Generated video information

[1116] Output: Charge calculation result

[1117] Specific operation: The server analyzes the video information stored in the database and calculates the fee using a specific algorithm.

[1118] Step 16:

[1119] Server: Adds the calculated fee to the user's account and applies it to the next billing cycle.

[1120] Input: Fee calculation result

[1121] Output: Billing information added to the user's account

[1122] Specific operation: The server saves the calculation results in the database and reflects them in the next billing cycle.

[1123] Step 17:

[1124] Server: Sends payment notification email to user and provides payment link.

[1125] Enter: Billing Information

[1126] Output: Payment notification email

[1127] Specific operation: The server uses the Email Sending API to send a payment notification email to the user.

[1128] Step 18:

[1129] User: Receives payment notification and clicks link to visit payment page.

[1130] Input: Payment link in payment notification email

[1131] Output: Payment completion screen

[1132] Specific behavior: The user clicks on the link in the email and completes the payment using an online payment service (e.g., Stripe API).

[1133] The above is the detailed processing flow of the program of this system.

[1134] (Application example 1)

[1135] 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."

[1136] Conventional presentation video generation systems require specialized knowledge, making it difficult to easily generate high-quality promotional videos. Furthermore, they lack the functionality to manage and download videos using smartphones, making it difficult for marketers and advertising agencies to carry out their work efficiently.

[1137] 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.

[1138] In this invention, the server includes means for inputting explanatory materials for products that a company wants to promote into the system, means for changing the presenter's image from a default image to a custom avatar or a new image, means for generating a presentation video that combines the generated script and the presenter's image, means for providing and notifying a download link for the generated video, means for including a user interface optimized for smartphones, means for calculating a fee based on the generated video and notifying payment, means for creating a script from the explanatory materials using a generative AI model, and means for managing and downloading the video using a smartphone. This allows high-quality promotional videos to be easily generated without specialized knowledge, and allows efficient management and download of the videos using a smartphone.

[1139] An "enterprise" is a legal entity that provides a specific product or service to the market and pursues profits.

[1140] "Sales promotion" refers to marketing activities that help sell a product or service and make consumers aware of its value.

[1141] "Explanatory materials" are documents or data intended for consumers or interested parties that provide information about a particular product or service.

[1142] A "system" is a device or procedure that combines multiple elements (hardware, software, data, etc.) to achieve a specific purpose.

[1143] "Input" refers to the act of entering information or data into a system.

[1144] A "presenter" is a person or avatar whose role is to visually and audibly convey information or ideas.

[1145] "Custom Avatar" means a custom-made digital character or image created by a user.

[1146] A "script" is a sequence of scripts or scenarios using audio or text.

[1147] A "generative AI model" is an algorithm that uses artificial intelligence to generate or transform data.

[1148] "Presentation Video" means a video presentation for conveying information visually and audibly.

[1149] A "download link" is a URL or hyperlink that allows you to obtain a particular file on the Internet.

[1150] A "notification" is a message or alert that informs the user of specific information or events.

[1151] A "user interface" is a means or screen through which a system and a user can interact with each other to exchange information.

[1152] "Fees" means money payable for the provision of services or the purchase of products.

[1153] "Payment Notice" means a message or notice sent to a User to notify the User of a particular payment.

[1154] A "smartphone" is a small mobile device that combines the functionality of a mobile phone with that of a computer.

[1155] This section describes the specific steps for companies to upload product promotion materials to the system and generate professional presentation videos using a generative AI model. It also provides a user interface that allows users to manage and download videos using a smartphone.

[1156] Required Hardware and Software

[1157] Server: Analyzes the text of explanatory materials, generates scripts using generative AI models, generates videos, calculates fees, and processes notifications.

[1158] Devices: Provide an interface for users to upload presentation materials and set presenter images. This includes mobile devices such as smartphones and tablets.

[1159] Generative AI models: Artificial intelligence models for generating scripts from explanatory materials, such as OpenAI's GPT-3.

[1160] Software: PyPDF2 (PDF reading), Pillow (image processing), requests (HTTP requests), OpenAI API library.

[1161] System Operation

[1162] 1. Explanatory Material Input:

[1163] A user prepares explanatory materials in PDF or other formats for products that a company is promoting.

[1164] Users access the system via an internet browser, log in, and then upload explanatory materials to the system.

[1165] The server receives the uploaded explanatory material and uses PyPDF2 to parse the text and extract the main points.

[1166] 2. Presenter Settings:

[1167] The presenter settings page allows users to view the default images and upload new presenter images (custom avatars or new images).

[1168] The server receives and stores the new image file.

[1169] 3. Video generation:

[1170] The server uses a generative AI model to generate a script for the presentation video from the text of the explanatory materials, with the following prompt:

[1171] Prompt: "Generate a promo video script based on the following brief:\n\n[Text of brief]"

[1172] The server combines the generated script with the presenter's image and generates a video file using an image processing library such as Pillow.

[1173] 4. Video Notification and Provision:

[1174] The server stores the generated presentation video file and associates it with the user's account.

[1175] The user will be notified when the video is complete and provided with a download link, which they can use to download the video using their smartphone.

[1176] 5. Calculation and Notification of Fees:

[1177] The server calculates the initial and monthly fees based on the video production and adds the billing information to the user's account.

[1178] The user will be notified of the payment and will be provided with a link to complete the payment.

[1179] Specific examples

[1180] Input of explanatory materials: A marketing person prepares explanatory materials for new product X in PDF format and uploads them after logging in to the system.

[1181] Presenter settings: The presenter sets a custom avatar and uploads it to the server.

[1182] Video generation: The server analyzes the text of the explanatory materials and uses a generative AI model (such as GPT-3) to generate a script for the promotional video, which is then combined with an image of the presenter to create the video.

[1183] Video notification and provision: The server associates the generated video with the agent's account and notifies the agent of the download link, which the agent clicks to download the video to their smartphone.

[1184] Calculation and notification of fees: The server calculates the fee for video generation and sends a payment notification to the person in charge.

[1185] In this way, companies can easily generate high-quality promotional videos without specialized knowledge, and can efficiently manage and download the videos using a smartphone.

[1186] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1187] Step 1:

[1188] (Input of explanatory materials)

[1189] Users access the system, log in, and then upload a PDF file describing the product they want to promote. The device then sends the uploaded PDF file to the server, which then uses PyPDF2 to analyze the PDF and extract text data. The key points of the extracted text data are then retrieved and used as input for the generative AI model.

[1190] Input: PDF format explanatory materials

[1191] Output: Text data extracted from the explanatory materials

[1192] Step 2:

[1193] (Presenter settings)

[1194] The user sees the default presenter image on the presenter settings page. If the user chooses to upload a new presenter image (custom avatar or new image), the device sends this image to the server. The server saves the new presenter image and updates the presenter information.

[1195] Input: New presenter image

[1196] Output: Updated presenter information

[1197] Step 3:

[1198] (Script generation)

[1199] The server uses a generative AI model to generate a script for the video based on the text data extracted from the explanatory materials. Specifically, a prompt sentence is input into the generative AI model to generate an appropriate script. An example of the prompt sentence is as follows:

[1200] Prompt: "Generate a promo video script based on the following brief:\n\n[Text of brief]"

[1201] The server receives the generated script and prepares it as the basic data for the presentation video.

[1202] Input: Text data extracted from explanatory materials, prompt text

[1203] Output: Script for video

[1204] Step 4:

[1205] (Video generation)

[1206] The server combines the generated script with the presenter's image to generate a presentation video. It uses an image processing library such as Pillow to set the timing and effects of the text based on the script, and to position the presenter's image appropriately. The generated video file is saved on the server.

[1207] Input: video script, presenter image

[1208] Output: Generated presentation video

[1209] Step 5:

[1210] (Video notification and provision)

[1211] The server generates a link to the location where the generated video is saved and notifies the user of this link. The user can download the generated video from the provided link. If downloading using a smartphone, this operation is performed through a user interface optimized for smartphones.

[1212] Input: Generated presentation video

[1213] Output: Video download link, notification

[1214] Step 6:

[1215] (Calculation and notification of fees)

[1216] The server calculates the initial and monthly fees based on the generated video and adds the billing information to the user's account. The server sends a payment notice to the user based on the billing information. The user confirms the notice and pays the fee via the provided payment link.

[1217] Input: Generated video, pricing criteria

[1218] Output: Initial and monthly fees, payment notice

[1219] By following these steps, businesses can easily generate high-quality promotional videos without specialized knowledge, and efficiently manage, download, and pay for the videos using their smartphones.

[1220] 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.

[1221] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. This system also incorporates an emotion engine that recognizes user emotions, enabling more personalized video generation. The system consists of a server, a user device, and an emotion engine, and utilizes generative AI to create high-quality videos.

[1222] System Operation

[1223] Input of explanatory materials

[1224] A user prepares explanatory materials (e.g., PDF files) for the products their company wants to promote, and logs in with their company account information to access the system. After logging in, the user accesses the dashboard and opens the explanatory materials upload page. Next, the user uploads the explanatory materials file using drag and drop or the file selection button. The terminal reads this file and sends it to the server. The server saves the received explanatory materials and converts them into an appropriate internal format (e.g., performs text analysis and extracts key points).

[1225] Presenter Settings

[1226] The user accesses the presenter settings page and sees the default presenter image (e.g., an image of the company CEO). Then, the user selects and uploads a new presenter image (e.g., a custom avatar). The device reads the selected image file and sends it to the server. The server saves the image and updates the presenter's settings information.

[1227] Emotion recognition and reflection

[1228] While the user is interacting with the upload page, the emotion engine recognizes emotions from the user's facial expressions and voice. The emotion engine then transmits the user's emotional information to the server in real time. Based on this information, the server adjusts the content of the presentation video (e.g., the presenter's facial expressions and tone of voice).

[1229] Video generation

[1230] The server uses a generative AI to create a script based on the explanatory materials, emotional information obtained from the emotion engine, and the presenter's settings. This script includes text data for the script and dialogue to be used in the presentation video. The generated script is then combined with the presenter's image to generate the presentation video. The generated video file is saved in the storage area associated with the user's account.

[1231] Video notification and provision

[1232] The server notifies the user of the generated download link for the video, and the user can receive this notification and click the link to download the video.

[1233] Pricing

[1234] The system will calculate the initial and monthly fees based on the videos generated and add the billing information to the user's account. The server will calculate these fees and apply them to the next billing cycle. The user will receive a payment notification and pay the fees through the provided payment link.

[1235] Specific examples

[1236] Input of explanatory materials

[1237] A company's marketing manager, Mr. A, prepared explanatory materials in PDF format for a new product, "Smart Gadget." He logged into the system and uploaded the materials by dragging and dropping them onto the upload page on the dashboard. The server then performed a text analysis of the materials and extracted key points.

[1238] Presenter Settings

[1239] Person A went to the presenter settings page and saw the default CEO image. Person A uploaded a custom avatar and the server saved this new image and updated the settings.

[1240] Emotion recognition and reflection

[1241] While Ms. A was uploading her materials, the emotion engine analyzed her facial expressions and voice and sent her emotional information to the server. The server analyzed Ms. A's emotions, such as joy and anticipation, and adjusted the presenter's facial expressions and tone of voice based on those.

[1242] Video generation

[1243] The server used generative AI to create a script based on the explanatory materials, emotional information, and presenter image, and generated a presentation video. The server associated this video with Person A's account, saved it, and sent Person A a download link.

[1244] Video notification and provision

[1245] Mr. A received a notification and got a professionally generated presentation video from the download link.

[1246] Pricing

[1247] The system calculated the initial and monthly fees based on A's usage and added the billing information to his account. A received a payment notification and made the payment via the provided link.

[1248] As described above, the present invention provides a system that enables companies to easily generate high-quality, personalized presentation videos without requiring specialized knowledge.

[1249] The processing flow will be explained below.

[1250] Step 1:

[1251] The user accesses the system and enters their company account information on the login screen to log in. The server sends the entered account information to the authentication system and returns the authentication result.

[1252] Step 2:

[1253] The user accesses the dashboard and opens the upload page for the instructional materials. The device displays a file selection button, allowing the user to select a local file.

[1254] Step 3:

[1255] The user selects a file (e.g. PDF) of the product description they want to promote and clicks the upload button. The device reads the selected file and sends it to the server.

[1256] Step 4:

[1257] The server stores the received files and converts them into a suitable internal format, for example by performing text analysis and extracting key points.

[1258] Step 5:

[1259] The user accesses the presenter settings page, and the device displays the default presenter image (e.g., an image of the company CEO) on the screen.

[1260] Step 6:

[1261] The user selects and uploads a new presenter image. The device reads the selected image file and sends it to the server.

[1262] Step 7:

[1263] The server stores the received image and updates the presenter's setting information.

[1264] Step 8:

[1265] While the user is operating the upload page, the emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional information.

[1266] Step 9:

[1267] The emotion engine transmits the acquired emotion information to the server, which stores it and reflects it in the presentation content.

[1268] Step 10:

[1269] The server uses generative AI to create a presentation script based on the content of the input explanatory materials (text information) and emotional information.

[1270] Step 11:

[1271] Based on the created script, the server generates a presentation video that combines the presenter's settings (avatar and image) with emotional information.

[1272] Step 12:

[1273] The server stores the generated video file in association with the user's account.

[1274] Step 13:

[1275] The server notifies the user that the video has been generated and provides a download link, which the user clicks to download the video.

[1276] Step 14:

[1277] The server calculates the initial fee and monthly fee based on the user's usage and adds the billing information to the user's account.

[1278] Step 15:

[1279] The server sends a payment notification to the user and provides a payment link, and the user receives the payment notification and pays the fee through the provided link.

[1280] Example 2

[1281] 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."

[1282] Conventional presentation video creation systems lack the technology to automatically generate high-quality, personalized videos, making it difficult for companies without specialized knowledge to easily create high-quality presentation videos. Furthermore, personalization that reflects customer emotional information is not easy, resulting in a problem of low quality in the generated videos.

[1283] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for inputting explanatory materials for products that a company wants to promote into the system, a means for changing the presenter's image from a default image to a custom avatar or a new image, a means for combining the generated script with the presenter's image to generate a presentation video that reflects emotional information, a means for providing and notifying a download link for the generated video, and a means for recognizing emotions in real time and transmitting that information to the system. This makes it possible to easily create high-quality, personalized presentation videos even without specialized knowledge.

[1284] "Company" refers to a legal entity or organization that promotes a particular product or service.

[1285] An "explanatory material" refers to a document (e.g., a PDF file) containing information about a product or service prepared by a company for sales promotion purposes.

[1286] "Presenter" refers to a virtual character or person who explains a product or service within a presentation video.

[1287] "Custom Avatar" refers to a unique presenter image created or selected by a user.

[1288] "Generated script" refers to the text data of the script and dialogue of a presentation video that is automatically generated based on the content of the explanatory materials and other information.

[1289] "Emotion information" refers to data related to emotions recognized in real time from the user's facial expressions and voice.

[1290] "Generative AI" refers to a system or software that uses artificial intelligence technology to automatically generate scripts, presentation videos, etc.

[1291] "Download link" refers to the URL for obtaining the generated presentation video via the Internet.

[1292] An "emotion engine" refers to software or hardware that has the ability to recognize emotions from a user's facial expressions and voice and transmit that information to the system.

[1293] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products that companies want to promote. This system consists of a server, user terminals, and an emotion engine, and utilizes generation AI to create high-quality videos.

[1294] The system operates in the following specific steps:

[1295] Input of explanatory materials

[1296] Users access the system's login page and log in by entering their company's account information. After logging in, they move to the dashboard page and click the "Upload Materials" button to access the upload page. Then, they drag and drop explanatory materials (e.g., PDF files) or click the "Select File" button to select a file.

[1297] The device reads the selected file and sends its contents to the server, which stores the received file and performs text analysis, extracting key points and elements and storing them in an internal database.

[1298] Presenter Settings

[1299] Users access the reconfigured Presenter Settings page in their dashboard, review the default presenter image (e.g., an image of the company CEO), and click the "Change Image" button to upload a new presenter image (e.g., a custom avatar).

[1300] The device reads the uploaded image file and sends it to the server, which saves the new image and updates the presenter setting information.

[1301] Emotion recognition and reflection

[1302] While the user is uploading explanatory materials, the emotion engine uses the camera and microphone to analyze emotions from the user's facial expressions and voice in real time, and sends emotional information (e.g., joy, surprise, concentration, etc.) to the server.

[1303] The server adjusts the content of the presentation video based on the emotion information, so that the presenter's facial expressions and tone of voice change to match the user's emotions.

[1304] Video generation

[1305] The server uses a generative AI model to create a script for the presentation video based on the analysis results of the explanatory materials, emotional information, and presenter settings. The generated script is combined with an image of the presenter to generate a video.

[1306] The generated video file is saved in the storage area associated with the user's account.

[1307] Video notification and provision

[1308] Once the server has completed generating the video, it will send a notification to the user with a download link. The user will receive the notification and click the link to download the presentation video.

[1309] Pricing

[1310] The system calculates the fee based on the usage of the generated videos. The initial and monthly fees are calculated, and the server adds these fees to the user's account as billing information and reflects them in the next billing cycle. The user receives a payment notification and makes the payment via the provided link.

[1311] Examples of concrete examples and prompts

[1312] Example: Input of explanatory materials

[1313] The user logs into the system with their company account and uploads a PDF file of information about a new product. The device reads the file and sends it to the server, which performs text analysis and extracts key points.

[1314] Example: Setting the presenter

[1315] Users navigate to the presenter settings page, see the default CEO image, then upload a custom avatar and the server updates the settings.

[1316] Example: Emotion recognition and reflection

[1317] While the user is uploading materials, the emotion engine analyzes the user's facial expressions and voice and transmits his / her emotional information to the server, which then adjusts the presenter's facial expressions and tone of voice based on the emotional information.

[1318] Example: Video Generation

[1319] The server creates a script using a generative AI model based on the explanatory materials, emotional information, and presenter image, and generates a presentation video. The video is saved in the user's account storage area.

[1320] Example: Video notification and provision

[1321] The user receives a notification from the server and retrieves the generated presentation video from the provided download link.

[1322] Example: Setting prices

[1323] The system calculates the initial and monthly fees based on the user's usage, adds the billing information to the user's account, and the user receives a payment notification and makes the payment via the provided link.

[1324] Prompt Sentence Examples

[1325] "Generate a video of a company representative giving a presentation based on a new product's explanatory materials. Adjust the presenter's tone of voice and facial expressions based on emotional information."

[1326] "To auto-generate a professional presentation video, upload the PDF file below, use a custom avatar as the presenter, and create a video that reflects the user's emotional information."

[1327] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1328] Step 1: Input of explanatory materials

[1329] The user accesses the system's login page and logs in by entering their company's account information. After successful login, they are redirected to the dashboard page. Next, the user clicks the "Upload Materials" button to access the upload page. They drag and drop explanatory materials (e.g., PDF files) or click the "Select File" button to select a file and upload it. This process receives input that explanatory materials will be uploaded. The terminal reads the selected file and sends the file contents to the server. The server saves the received file, performs text analysis to extract key points, and stores them in an internal database. This is the output data.

[1330] Step 2: Presenter Settings

[1331] The user navigates to the "Presenter Settings" page from the dashboard menu. They check the default presenter image (e.g., an image of the company CEO) and click the "Change Image" button to upload a new presenter image (e.g., a custom avatar). This process receives input that the presenter image will be uploaded. The device reads the uploaded image file and sends it to the server. The server saves the new image and updates the presenter setting information. This is the output data.

[1332] Step 3: Emotional awareness and reflection

[1333] While the user is uploading explanatory materials, the emotion engine uses the camera and microphone to analyze emotions from the user's facial expressions and voice in real time. This process inputs the user's facial expression and voice data. The emotion engine sends emotional information (e.g., joy, surprise, concentration, etc.) to the server. This emotional information is the output data. Based on the emotional information, the server adjusts the content of the presentation video, changing the presenter's facial expressions and tone of voice. This adjusted content is the output data.

[1334] Step 4: Generate the video

[1335] The server uses a generative AI model to create a presentation video script based on the analysis results of the explanatory materials, emotional information, and presenter setting information. This process inputs the analysis results, emotional information, and presenter setting information. The server combines the generated script with the presenter's image to generate a video. The generated video file is saved in the storage area associated with the user's account. This is the output data.

[1336] Step 5: Notify and provide the video

[1337] When the server completes the video generation, it sends a notification to the user with a download link. This process inputs the generated video file. The user receives the notification and clicks the link to download the presentation video. The downloaded video is the output data.

[1338] Step 6: Set your prices

[1339] The system calculates fees based on the usage of the generated videos. This process inputs video usage data. Initial and monthly fees are calculated, and the server adds these fees to the user's account as billing information and reflects them in the next billing cycle. The billing information is the output data. The user receives a payment notification and makes the payment via the provided link. The payment information is the final output data.

[1340] (Application example 2)

[1341] 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."

[1342] Conventional presentation video generation systems require advanced editing techniques and dedicated software, making them difficult for non-experts to use. Furthermore, typical presentation videos have uniform content and lack personalization for viewers. As a result, they fail to attract viewers' attention, making it difficult to carry out effective sales promotions.

[1343] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting explanatory materials for products that a company wants to promote into the system, means for changing the presenter's image from a default image to a custom avatar or a new image, means for generating a presentation video that combines the generated script and the presenter's image, means for providing and notifying a user of a download link for the generated video, means for using an emotion engine that analyzes the user's facial expressions and voice in real time, and means for reflecting emotion information obtained from the emotion engine in the presentation video. This makes it possible to easily generate high-quality, personalized presentation videos without specialized knowledge.

[1344] "Sales promotion" is a marketing activity aimed at increasing sales of a product or service.

[1345] "Explanatory materials" are written and media content used to explain in detail the features and benefits of a product.

[1346] "Inputting into the system" means that a user uploads or enters data or files into the system.

[1347] A "presenter" is a person or character who provides explanations and guidance during a presentation.

[1348] A "custom avatar" is an original virtual character that a user can freely create or select.

[1349] A "generated script" is a presentation script or dialogue generated by the system from explanatory materials.

[1350] "Presentation video" is video content that conveys information visually and audibly.

[1351] The "download link" is a URL for downloading the generated video via the Internet.

[1352] The "emotion engine" is a system that analyzes emotions from a user's facial expressions and voice and provides that information as data.

[1353] "Analyzing in real time" means analyzing data on the fly while the user is operating the device.

[1354] "Generative AI" is a system that uses artificial intelligence technology to automatically generate new content and information from data.

[1355] "Initial costs" are one-time costs incurred when starting to use a service or system.

[1356] "Monthly fee" refers to the fee paid each month to continue using a service or system.

[1357] "Billing Information" means detailed information about charges and payments owed by the User.

[1358] These definitions can be used to clarify the meaning of important terms contained in the claims.

[1359] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. The system is easy to operate using a smartphone app and includes an emotion engine that analyzes the user's emotional information in real time.

[1360] Upload explanatory materials

[1361] A user accesses the system using a smartphone and uploads explanatory materials (e.g., PDF files). The device sends the files to the server, which stores the received explanatory materials and converts them into an internal format. This conversion is performed using software that uses text analysis techniques to extract key points.

[1362] Presenter Settings

[1363] The user configures the presenter settings through a smartphone app. They can check the default presenter image (e.g., an image of a company representative) and select and upload a new presenter image (e.g., a custom avatar). The device reads this image file and sends it to the server. The server saves the image and updates the presenter settings information.

[1364] Emotion recognition and reflection

[1365] While the user is uploading their presentation materials, the emotion engine analyzes the user's facial expressions and voice in real time to determine their emotions. This emotion engine uses a library called EmotionEngine. The analyzed emotional information is sent to the server and reflected in the presentation video. Specifically, it is reflected in the presenter's facial expressions and tone of voice.

[1366] Video generation

[1367] The server uses a generative AI model to create a script based on explanatory materials, emotional information, and the presenter's image. This script includes text data for the script and dialogue to be used in the presentation video. The server then combines the generated script with the presenter's image to generate a presentation video. A library called VideoGenerator is used to generate high-quality videos. The generated video files are saved in the storage area associated with the user's account.

[1368] Video notification and provision

[1369] The server notifies the user of the download link for the generated video. The notification method is to use the email sending API. The user receives the notification and can click the link to download the video.

[1370] Specific examples

[1371] A company's marketing manager, Mr. A, prepared explanatory materials for a new product, "Smart Gadget," in PDF format. He logged into the system using a smartphone app and uploaded the materials. The server analyzed the text of the materials and extracted key points. Next, Mr. A selected and uploaded a custom avatar on the presenter settings page. The emotion engine analyzed Mr. A's emotions, such as joy and anticipation, and reflected them in the presenter's facial expressions and tone of voice. Finally, the server used generative AI to generate a presentation video and sent Mr. A a download link.

[1372] Prompt Sentence Examples

[1373] We have uploaded an explanatory document for our new product, a "smartwatch." This is a next-generation wearable device that can record heart rate, steps, calorie consumption, and more in real time. Use an emotion recognition engine to analyze the user's facial expressions and tone of voice to create a more engaging presentation video. Use a company character as the presenter image.

[1374] The above is a detailed description of the embodiment of the present invention. This system makes it possible to easily generate high-quality personalized presentation videos without requiring specialized knowledge.

[1375] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1376] Step 1:

[1377] A user logs in to the system using a smartphone and uploads explanatory materials. When the user uploads a PDF file, the device reads the file and sends it to the server. The server receives and saves the file. The input is the PDF file uploaded by the user, and the output is the saved explanatory materials.

[1378] Step 2:

[1379] The server converts the uploaded explanatory materials into an internal format using text analysis technology, specifically extracting and organizing key points. The input is the saved explanatory materials, and the output is the text data of the extracted key points.

[1380] Step 3:

[1381] The user opens the presenter settings page on the smartphone app and checks the default presenter image. They then select and upload a new presenter image. The device reads this new image and sends it to the server. The input is the presenter image uploaded by the user, and the output is the presenter image saved on the server.

[1382] Step 4:

[1383] While the user is uploading explanatory materials, the emotion engine analyzes the user's facial expressions and voice in real time. The analysis results are sent to the server. The input is the user's facial expressions and voice data, and the output is the analyzed emotional information.

[1384] Step 5:

[1385] The server uses a generative AI model to create a script based on the explanatory materials, extracted key points, emotional information, and the presenter image. The inputs are the extracted key points, emotional information, and the presenter image, and the output is the generated script.

[1386] Step 6:

[1387] The server generates a presentation video by combining the generated script and the presenter image. It uses the VideoGenerator library to generate high-quality videos. The input is the generated script and the presenter image, and the output is the generated presentation video.

[1388] Step 7:

[1389] The server notifies the user of the download link for the generated video. The notification method uses an email sending API. The input is the generated presentation video, and the output is the download link sent to the user.

[1390] Step 8:

[1391] The user receives a notification and clicks the download link to download the generated presentation video. The input is the download link sent from the server, and the output is the presentation video downloaded by the user.

[1392] 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.

[1393] 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.

[1394] 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.

[1395] [Fourth embodiment]

[1396] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1397] 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.

[1398] 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).

[1399] 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.

[1400] 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.

[1401] 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).

[1402] 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.

[1403] 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.

[1404] 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.

[1405] 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.

[1406] 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.

[1407] 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.

[1408] 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."

[1409] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. The system consists of a server and a user terminal, and uses generation AI to create high-quality videos.

[1410] System Operation

[1411] Input of explanatory materials

[1412] A user prepares explanatory materials (e.g., PDF files) for the products their company wants to promote, and logs in with their company account information to access the system. After logging in, the user accesses the dashboard and opens the explanatory materials upload page. Next, the user uploads the explanatory materials file using drag and drop or the file selection button. The terminal reads this file and sends it to the server. The server saves the received explanatory materials and converts them into an appropriate internal format (e.g., performs text analysis and extracts key points).

[1413] Presenter Settings

[1414] The user accesses the presenter settings page and sees the default presenter image (e.g., an image of the company CEO). Then, the user selects and uploads a new presenter image (e.g., a custom avatar). The device reads the selected image file and sends it to the server. The server saves the image and updates the presenter's settings information.

[1415] Video generation

[1416] The server uses a generative AI to create a script based on the explanatory materials and the presenter's settings. This script includes text data for the script and dialogue to be used in the presentation video. The server then combines the generated script with the presenter's image to generate the presentation video. The generated video file is saved in the storage area associated with the user's account.

[1417] Video notification and provision

[1418] The server notifies the user of the generated download link for the video, and the user can receive this notification and click the link to download the video.

[1419] Pricing

[1420] The system will calculate the initial and monthly fees based on the videos generated and add the billing information to the user's account. The server will calculate these fees and apply them to the next billing cycle. The user will receive a payment notification and pay the fees through the provided payment link.

[1421] Specific examples

[1422] Input of explanatory materials

[1423] A company's marketing manager, Mr. A, prepared explanatory materials in PDF format for a new product, "Smart Gadget." He logged into the system and uploaded the materials by dragging and dropping them onto the upload page on the dashboard. The server then performed a text analysis of the materials and extracted key points.

[1424] Presenter Settings

[1425] Person A went to the presenter settings page and saw the default CEO image. Person A uploaded a custom avatar and the server saved this new image and updated the settings.

[1426] Video generation

[1427] The server created a script using generative AI based on the explanatory materials and the new presenter image, and generated a presentation video. The server associated this video with Mr. A's account, saved it, and sent him a download link.

[1428] Video notification and provision

[1429] Mr. A received a notification and got a professionally generated presentation video from the download link.

[1430] Pricing

[1431] The system calculated the initial and monthly fees based on A's usage and added the billing information to his account. A received a payment notification and made the payment via the provided link.

[1432] As described above, the present invention provides a system that enables companies to easily generate high-quality presentation videos even without specialized knowledge.

[1433] The processing flow will be explained below.

[1434] Step 1:

[1435] The user accesses the system and enters their company account information on the login screen to log in. The server sends the entered account information to the authentication system and returns the authentication result.

[1436] Step 2:

[1437] The user accesses the dashboard and opens the upload page for the instructional materials. The device displays a file selection button, allowing the user to select a local file.

[1438] Step 3:

[1439] The user selects a file (e.g. PDF) of the product description they want to promote and clicks the upload button. The device reads the selected file and sends it to the server.

[1440] Step 4:

[1441] The server stores the received files and converts them into a suitable internal format, for example by performing text analysis and extracting key points.

[1442] Step 5:

[1443] The user accesses the presenter settings page, and the device displays the default presenter image (e.g., an image of the company CEO) on the screen.

[1444] Step 6:

[1445] The user selects and uploads a new presenter image. The device reads the selected image file and sends it to the server.

[1446] Step 7:

[1447] The server stores the received image and updates the presenter's setting information.

[1448] Step 8:

[1449] The server uses generative AI to create a presentation script based on the content of the input explanatory materials (text information).

[1450] Step 9:

[1451] Based on the created script, the server generates a presentation video that combines the presenter's settings (avatar and image).

[1452] Step 10:

[1453] The server stores the generated video file in association with the user's account.

[1454] Step 11:

[1455] The server notifies the user that the video has been generated and provides a download link, which the user clicks to download the video.

[1456] Step 12:

[1457] The server calculates the initial fee and monthly fee based on the user's usage and adds the billing information to the user's account.

[1458] Step 13:

[1459] The server sends a payment notification to the user and provides a payment link, and the user receives the payment notification and pays the fee through the provided link.

[1460] Example 1

[1461] 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."

[1462] Creating professional presentation videos for corporate sales promotion requires a great deal of effort and expertise. While systems exist for automatically generating presentation videos, further improvements are needed to effectively extract key points from explanatory materials and generate high-quality scripts. A system that solves these problems and generates efficient, high-quality presentation videos is needed.

[1463] 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.

[1464] In this invention, the server includes means for analyzing explanatory materials for products that a company wants to promote, extracting key points, and converting them into an internal format, means for creating a script from the explanatory materials using a generative AI model, and means for generating a presentation video that combines the generated script with an image of the presenter, thereby enabling companies to automatically generate high-quality presentation videos even without specialized knowledge.

[1465] An "enterprise" is an organization that provides goods and services and engages in commercial activities.

[1466] "Sales promotion" is a part of marketing activities carried out to increase sales of a product.

[1467] "Explanatory materials" are documents that describe the features and benefits of a product and are used in sales promotion activities.

[1468] A "system" is a collection of hardware and software combined to achieve a particular purpose.

[1469] A "server" is a computer that provides services to other computers on a network.

[1470] "Analysis" is the process of breaking down the content of materials or data and extracting meaning and key points.

[1471] "Major points" are sections that highlight important information or key points contained in the presentation material.

[1472] An "internal format" is a standardized data format used within a system.

[1473] A "presenter" is a person or character who gives explanations in a presentation video.

[1474] A "custom avatar" is a virtual character created for a specific purpose or individual.

[1475] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to automatically generate data.

[1476] A "script" is text data that describes the content and dialogue of a presentation video.

[1477] A "presentation video" is video content that visually explains the features and benefits of a product.

[1478] "Download link" means a URL link for downloading a file over the Internet.

[1479] A "notification" is a message or alert that informs a user of certain information.

[1480] "Initial costs" are one-time costs paid when you start using the system.

[1481] "Monthly fee" refers to the fee paid each month for the continued use of the system.

[1482] "Billing Information" means information that describes the charges incurred by the User.

[1483] A "prompt" is input text that gives instructions or questions to a generative AI model.

[1484] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. The system consists of a server and a user terminal, and uses generation AI to create high-quality videos.

[1485] Input of explanatory materials

[1486] A user prepares explanatory materials (e.g., PDF files) for the products their company wants to promote, and logs in with their company's account information to access the system. After logging in, the user accesses the dashboard and opens the explanatory materials upload page. Next, the user uploads the explanatory materials file using drag and drop or the file selection button. The terminal reads this file and sends it to the server.

[1487] The server temporarily stores the received explanatory materials, analyzes the text content using a text extraction tool such as PDFMiner, extracts key points using a natural language processing library (e.g., SpaCy), converts the extracted information into an internal format, and stores it in a database.

[1488] Presenter Settings

[1489] The user accesses the presenter settings page, sees the default presenter image (e.g., an image of the company CEO), selects a new presenter image (e.g., a custom avatar), and uploads it. The device reads the selected image file and sends it to the server.

[1490] The server saves this image file and updates the presenter's configuration information using an image processing library such as OpenCV.

[1491] Video generation

[1492] Based on the saved explanatory materials and the presenter's settings, the server sends a prompt such as, "Generate a professional presentation video for our new product, 'Smart Gadget.' Create a script based on the explanatory materials below and use the configured custom avatar." to the generation AI model (e.g., GPT-4) and creates a script.

[1493] The generated script can be checked and edited as necessary. The edited script is then combined with the presenter image to generate a presentation video using a generation AI such as DALL-E. The created video file is saved and associated with the user's account.

[1494] Video notification and provision

[1495] The server notifies the user of the generated download link for the video. The user can receive this notification and click the link to download the video. Notification can be done using an email sending API (e.g., SendGrid).

[1496] Pricing

[1497] The server calculates the fee based on the generated video information. It uses a fee calculation algorithm to calculate the initial fee and monthly fee. The calculated fee is added to the user's account and reflected in the next billing cycle. A payment notification email is sent to the user, and the fee can be paid via the provided payment link. An online payment service such as Stripe API is used.

[1498] The above are specific embodiments of the present invention based on the claims. This system allows companies to easily generate high-quality presentation videos without specialized knowledge.

[1499] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1500] Step 1:

[1501] User: Access the system login page and log in with your account information.

[1502] Input: User account information (e.g. username, password)

[1503] Output: After successful login, redirect to dashboard

[1504] Specific operation: The user opens a browser, accesses the system's URL, enters the required information in the login form, and clicks the "Login" button.

[1505] Step 2:

[1506] User: Open the "Upload Materials" page on your dashboard and select your materials.

[1507] Input: Explanation materials (e.g. PDF file)

[1508] Output: Explanation file uploaded

[1509] Specific operation: The user clicks the "Upload explanatory materials" button or page, drags and drops explanatory materials from the file selection dialog that appears, or selects a file using the "Select File" button, and clicks the "Start Upload" button.

[1510] Step 3:

[1511] Terminal: Reads the selected file and sends it to the server.

[1512] Input: explanatory file

[1513] Output: File data sent to the server

[1514] Specific operation: The terminal reads the selected file data as output from the file selection dialog and sends it to the server via an HTTP request.

[1515] Step 4:

[1516] Server: Temporarily stores the received explanatory material files and analyzes the text content using a text extraction tool such as PDFMiner.

[1517] Input: explanatory file

[1518] Output: Extracted text data

[1519] What it does: The server saves the file in a specific directory and uses a tool like PDFMiner to extract the text from the PDF.

[1520] Step 5:

[1521] Server: Analyze the extracted text data using a natural language processing library (e.g., SpaCy) and extract key points.

[1522] Input: Text data

[1523] Output: Text data containing key points

[1524] How it works: The server applies SpaCy to the extracted text data to extract noun phrases and identify keywords, then stores the key points in a database.

[1525] Step 6:

[1526] Users: Visit the Presenter Settings page to view the default presenter image and upload a new one.

[1527] Input: New presenter image (e.g. JPEG, PNG file)

[1528] Output: New presenter image uploaded

[1529] What happens: On the Presenter Settings page, the user clicks the "Change Presenter Image" button, selects a new image file, and uploads it.

[1530] Step 7:

[1531] On the device: Load the selected image file and send it to the server.

[1532] Input: New presenter image

[1533] Output: Image data sent to the server

[1534] Specific operation: The terminal reads the image data selected as the output of the file selection dialog and sends it to the server via an HTTP request.

[1535] Step 8:

[1536] Server: Saves the received image files and updates the presenter's settings using an image processing library such as OpenCV.

[1537] Input: New presenter image

[1538] Output: Updated presenter settings

[1539] Specific operation: The server saves image files in a specific directory, analyzes and processes the images using OpenCV, and updates the configuration information in the database.

[1540] Step 9:

[1541] Server: Based on the saved explanatory materials and presenter settings, it sends prompts to the generative AI model (e.g., GPT-4) and generates a script.

[1542] Input: Main points of the presentation materials, presenter setting information

[1543] Output: Generated script

[1544] Specific operation: The server generates a prompt saying, "Please generate a professional presentation video for our new product, 'Smart Gadget'. Please create a script based on the explanatory materials below and use the custom avatar you set." and sends it to the generation AI to generate the script.

[1545] Step 10:

[1546] Server: Review the generated script and make any necessary modifications.

[1547] Input: Generated script

[1548] Output: The modified script

[1549] What happens: The server administrator or an automated proofreader checks the script and makes corrections if necessary.

[1550] Step 11:

[1551] Server: The modified script is combined with the presenter image and a generative AI such as DALL-E is used to generate a presentation video.

[1552] Input: modified script, presenter image

[1553] Output: Generated presentation video

[1554] Specific operation: The server inputs the script and images into the generation AI and executes the video generation process.

[1555] Step 12:

[1556] Server: Stores the created video file in association with the user's account.

[1557] Input: Generated presentation video

[1558] Output: Video files associated with the user's account

[1559] What happens: The server stores the video file in a database and links it to the appropriate user account.

[1560] Step 13:

[1561] Server: Sends the generated video download link to the user.

[1562] Input: Link to the generated video file

[1563] Output: Notification email sent to user

[1564] Specific operation: The server uses an email sending API (e.g. SendGrid) to send a notification email to the user containing a download link.

[1565] Step 14:

[1566] User: Receives notification email and clicks link to download video.

[1567] Input: Download link in the notification email

[1568] Output: Downloaded presentation video

[1569] Specific behavior: The user clicks on the link in the received email, accesses the video download page, and downloads the video file.

[1570] Step 15:

[1571] Server: Calculates fees based on the generated video information. A fee calculation algorithm is used to calculate the initial fee and monthly fee.

[1572] Input: Generated video information

[1573] Output: Charge calculation result

[1574] Specific operation: The server analyzes the video information stored in the database and calculates the fee using a specific algorithm.

[1575] Step 16:

[1576] Server: Adds the calculated fee to the user's account and applies it to the next billing cycle.

[1577] Input: Fee calculation result

[1578] Output: Billing information added to the user's account

[1579] Specific operation: The server saves the calculation results in the database and reflects them in the next billing cycle.

[1580] Step 17:

[1581] Server: Sends payment notification email to user and provides payment link.

[1582] Enter: Billing Information

[1583] Output: Payment notification email

[1584] Specific operation: The server uses the Email Sending API to send a payment notification email to the user.

[1585] Step 18:

[1586] User: Receives payment notification and clicks link to visit payment page.

[1587] Input: Payment link in payment notification email

[1588] Output: Payment completion screen

[1589] Specific behavior: The user clicks on the link in the email and completes the payment using an online payment service (e.g., Stripe API).

[1590] The above is the detailed processing flow of the program of this system.

[1591] (Application example 1)

[1592] 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."

[1593] Conventional presentation video generation systems require specialized knowledge, making it difficult to easily generate high-quality promotional videos. Furthermore, they lack the functionality to manage and download videos using smartphones, making it difficult for marketers and advertising agencies to carry out their work efficiently.

[1594] 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.

[1595] In this invention, the server includes means for inputting explanatory materials for products that a company wants to promote into the system, means for changing the presenter's image from a default image to a custom avatar or a new image, means for generating a presentation video that combines the generated script and the presenter's image, means for providing and notifying a download link for the generated video, means for including a user interface optimized for smartphones, means for calculating a fee based on the generated video and notifying payment, means for creating a script from the explanatory materials using a generative AI model, and means for managing and downloading the video using a smartphone. This allows high-quality promotional videos to be easily generated without specialized knowledge, and allows efficient management and download of the videos using a smartphone.

[1596] An "enterprise" is a legal entity that provides a specific product or service to the market and pursues profits.

[1597] "Sales promotion" refers to marketing activities that help sell a product or service and make consumers aware of its value.

[1598] "Explanatory materials" are documents or data intended for consumers or interested parties that provide information about a particular product or service.

[1599] A "system" is a device or procedure that combines multiple elements (hardware, software, data, etc.) to achieve a specific purpose.

[1600] "Input" refers to the act of entering information or data into a system.

[1601] A "presenter" is a person or avatar whose role is to visually and audibly convey information or ideas.

[1602] "Custom Avatar" means a custom-made digital character or image created by a user.

[1603] A "script" is a sequence of scripts or scenarios using audio or text.

[1604] A "generative AI model" is an algorithm that uses artificial intelligence to generate or transform data.

[1605] "Presentation Video" means a video presentation for conveying information visually and audibly.

[1606] A "download link" is a URL or hyperlink that allows you to obtain a particular file on the Internet.

[1607] A "notification" is a message or alert that informs the user of specific information or events.

[1608] A "user interface" is a means or screen through which a system and a user can interact with each other to exchange information.

[1609] "Fees" means money payable for the provision of services or the purchase of products.

[1610] "Payment Notice" means a message or notice sent to a User to notify the User of a particular payment.

[1611] A "smartphone" is a small mobile device that combines the functionality of a mobile phone with that of a computer.

[1612] This section describes the specific steps for companies to upload product promotion materials to the system and generate professional presentation videos using a generative AI model. It also provides a user interface that allows users to manage and download videos using a smartphone.

[1613] Required Hardware and Software

[1614] Server: Analyzes the text of explanatory materials, generates scripts using generative AI models, generates videos, calculates fees, and processes notifications.

[1615] Devices: Provide an interface for users to upload presentation materials and set presenter images. This includes mobile devices such as smartphones and tablets.

[1616] Generative AI models: Artificial intelligence models for generating scripts from explanatory materials, such as OpenAI's GPT-3.

[1617] Software: PyPDF2 (PDF reading), Pillow (image processing), requests (HTTP requests), OpenAI API library.

[1618] System Operation

[1619] 1. Explanatory Material Input:

[1620] A user prepares explanatory materials in PDF or other formats for products that a company is promoting.

[1621] Users access the system via an internet browser, log in, and then upload explanatory materials to the system.

[1622] The server receives the uploaded explanatory material and uses PyPDF2 to parse the text and extract the main points.

[1623] 2. Presenter Settings:

[1624] The presenter settings page allows users to view the default images and upload new presenter images (custom avatars or new images).

[1625] The server receives and stores the new image file.

[1626] 3. Video generation:

[1627] The server uses a generative AI model to generate a script for the presentation video from the text of the explanatory materials, with the following prompt:

[1628] Prompt: "Generate a promo video script based on the following brief:\n\n[Text of brief]"

[1629] The server combines the generated script with the presenter's image and generates a video file using an image processing library such as Pillow.

[1630] 4. Video Notification and Provision:

[1631] The server stores the generated presentation video file and associates it with the user's account.

[1632] The user will be notified when the video is complete and provided with a download link, which they can use to download the video using their smartphone.

[1633] 5. Calculation and Notification of Fees:

[1634] The server calculates the initial and monthly fees based on the video production and adds the billing information to the user's account.

[1635] The user will be notified of the payment and will be provided with a link to complete the payment.

[1636] Specific examples

[1637] Input of explanatory materials: A marketing person prepares explanatory materials for new product X in PDF format and uploads them after logging in to the system.

[1638] Presenter settings: The presenter sets a custom avatar and uploads it to the server.

[1639] Video generation: The server analyzes the text of the explanatory materials and uses a generative AI model (such as GPT-3) to generate a script for the promotional video, which is then combined with an image of the presenter to create the video.

[1640] Video notification and provision: The server associates the generated video with the agent's account and notifies the agent of the download link, which the agent clicks to download the video to their smartphone.

[1641] Calculation and notification of fees: The server calculates the fee for video generation and sends a payment notification to the person in charge.

[1642] In this way, companies can easily generate high-quality promotional videos without specialized knowledge, and can efficiently manage and download the videos using a smartphone.

[1643] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1644] Step 1:

[1645] (Input of explanatory materials)

[1646] Users access the system, log in, and then upload a PDF file describing the product they want to promote. The device then sends the uploaded PDF file to the server, which then uses PyPDF2 to analyze the PDF and extract text data. The key points of the extracted text data are then retrieved and used as input for the generative AI model.

[1647] Input: PDF format explanatory materials

[1648] Output: Text data extracted from the explanatory materials

[1649] Step 2:

[1650] (Presenter settings)

[1651] The user sees the default presenter image on the presenter settings page. If the user chooses to upload a new presenter image (custom avatar or new image), the device sends this image to the server. The server saves the new presenter image and updates the presenter information.

[1652] Input: New presenter image

[1653] Output: Updated presenter information

[1654] Step 3:

[1655] (Script generation)

[1656] The server uses a generative AI model to generate a script for the video based on the text data extracted from the explanatory materials. Specifically, a prompt sentence is input into the generative AI model to generate an appropriate script. An example of the prompt sentence is as follows:

[1657] Prompt: "Generate a promo video script based on the following brief:\n\n[Text of brief]"

[1658] The server receives the generated script and prepares it as the basic data for the presentation video.

[1659] Input: Text data extracted from explanatory materials, prompt text

[1660] Output: Script for video

[1661] Step 4:

[1662] (Video generation)

[1663] The server combines the generated script with the presenter's image to generate a presentation video. It uses an image processing library such as Pillow to set the timing and effects of the text based on the script, and to position the presenter's image appropriately. The generated video file is saved on the server.

[1664] Input: video script, presenter image

[1665] Output: Generated presentation video

[1666] Step 5:

[1667] (Video notification and provision)

[1668] The server generates a link to the location where the generated video is saved and notifies the user of this link. The user can download the generated video from the provided link. If downloading using a smartphone, this operation is performed through a user interface optimized for smartphones.

[1669] Input: Generated presentation video

[1670] Output: Video download link, notification

[1671] Step 6:

[1672] (Calculation and notification of fees)

[1673] The server calculates the initial and monthly fees based on the generated video and adds the billing information to the user's account. The server sends a payment notice to the user based on the billing information. The user confirms the notice and pays the fee via the provided payment link.

[1674] Input: Generated video, pricing criteria

[1675] Output: Initial and monthly fees, payment notice

[1676] By following these steps, businesses can easily generate high-quality promotional videos without specialized knowledge, and efficiently manage, download, and pay for the videos using their smartphones.

[1677] 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.

[1678] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. This system also incorporates an emotion engine that recognizes user emotions, enabling more personalized video generation. The system consists of a server, a user device, and an emotion engine, and utilizes generative AI to create high-quality videos.

[1679] System Operation

[1680] Input of explanatory materials

[1681] A user prepares explanatory materials (e.g., PDF files) for the products their company wants to promote, and logs in with their company account information to access the system. After logging in, the user accesses the dashboard and opens the explanatory materials upload page. Next, the user uploads the explanatory materials file using drag and drop or the file selection button. The terminal reads this file and sends it to the server. The server saves the received explanatory materials and converts them into an appropriate internal format (e.g., performs text analysis and extracts key points).

[1682] Presenter Settings

[1683] The user accesses the presenter settings page and sees the default presenter image (e.g., an image of the company CEO). Then, the user selects and uploads a new presenter image (e.g., a custom avatar). The device reads the selected image file and sends it to the server. The server saves the image and updates the presenter's settings information.

[1684] Emotion recognition and reflection

[1685] While the user is interacting with the upload page, the emotion engine recognizes emotions from the user's facial expressions and voice. The emotion engine then transmits the user's emotional information to the server in real time. Based on this information, the server adjusts the content of the presentation video (e.g., the presenter's facial expressions and tone of voice).

[1686] Video generation

[1687] The server uses a generative AI to create a script based on the explanatory materials, emotional information obtained from the emotion engine, and the presenter's settings. This script includes text data for the script and dialogue to be used in the presentation video. The generated script is then combined with the presenter's image to generate the presentation video. The generated video file is saved in the storage area associated with the user's account.

[1688] Video notification and provision

[1689] The server notifies the user of the generated download link for the video, and the user can receive this notification and click the link to download the video.

[1690] Pricing

[1691] The system will calculate the initial and monthly fees based on the videos generated and add the billing information to the user's account. The server will calculate these fees and apply them to the next billing cycle. The user will receive a payment notification and pay the fees through the provided payment link.

[1692] Specific examples

[1693] Input of explanatory materials

[1694] A company's marketing manager, Mr. A, prepared explanatory materials in PDF format for a new product, "Smart Gadget." He logged into the system and uploaded the materials by dragging and dropping them onto the upload page on the dashboard. The server then performed a text analysis of the materials and extracted key points.

[1695] Presenter Settings

[1696] Person A went to the presenter settings page and saw the default CEO image. Person A uploaded a custom avatar and the server saved this new image and updated the settings.

[1697] Emotion recognition and reflection

[1698] While Ms. A was uploading her materials, the emotion engine analyzed her facial expressions and voice and sent her emotional information to the server. The server analyzed Ms. A's emotions, such as joy and anticipation, and adjusted the presenter's facial expressions and tone of voice based on those.

[1699] Video generation

[1700] The server used generative AI to create a script based on the explanatory materials, emotional information, and presenter image, and generated a presentation video. The server associated this video with Person A's account, saved it, and sent Person A a download link.

[1701] Video notification and provision

[1702] Mr. A received a notification and got a professionally generated presentation video from the download link.

[1703] Pricing

[1704] The system calculated the initial and monthly fees based on A's usage and added the billing information to his account. A received a payment notification and made the payment via the provided link.

[1705] As described above, the present invention provides a system that enables companies to easily generate high-quality, personalized presentation videos without requiring specialized knowledge.

[1706] The processing flow will be explained below.

[1707] Step 1:

[1708] The user accesses the system and enters their company account information on the login screen to log in. The server sends the entered account information to the authentication system and returns the authentication result.

[1709] Step 2:

[1710] The user accesses the dashboard and opens the upload page for the instructional materials. The device displays a file selection button, allowing the user to select a local file.

[1711] Step 3:

[1712] The user selects a file (e.g. PDF) of the product description they want to promote and clicks the upload button. The device reads the selected file and sends it to the server.

[1713] Step 4:

[1714] The server stores the received files and converts them into a suitable internal format, for example by performing text analysis and extracting key points.

[1715] Step 5:

[1716] The user accesses the presenter settings page, and the device displays the default presenter image (e.g., an image of the company CEO) on the screen.

[1717] Step 6:

[1718] The user selects and uploads a new presenter image. The device reads the selected image file and sends it to the server.

[1719] Step 7:

[1720] The server stores the received image and updates the presenter's setting information.

[1721] Step 8:

[1722] While the user is operating the upload page, the emotion engine analyzes the user's facial expressions and voice in real time to obtain emotional information.

[1723] Step 9:

[1724] The emotion engine transmits the acquired emotion information to the server, which stores it and reflects it in the presentation content.

[1725] Step 10:

[1726] The server uses generative AI to create a presentation script based on the content of the input explanatory materials (text information) and emotional information.

[1727] Step 11:

[1728] Based on the created script, the server generates a presentation video that combines the presenter's settings (avatar and image) with emotional information.

[1729] Step 12:

[1730] The server stores the generated video file in association with the user's account.

[1731] Step 13:

[1732] The server notifies the user that the video has been generated and provides a download link, which the user clicks to download the video.

[1733] Step 14:

[1734] The server calculates the initial fee and monthly fee based on the user's usage and adds the billing information to the user's account.

[1735] Step 15:

[1736] The server sends a payment notification to the user and provides a payment link, and the user receives the payment notification and pays the fee through the provided link.

[1737] Example 2

[1738] 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."

[1739] Conventional presentation video creation systems lack the technology to automatically generate high-quality, personalized videos, making it difficult for companies without specialized knowledge to easily create high-quality presentation videos. Furthermore, personalization that reflects customer emotional information is not easy, resulting in a problem of low quality in the generated videos.

[1740] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for inputting explanatory materials for products that a company wants to promote into the system, a means for changing the presenter's image from a default image to a custom avatar or a new image, a means for combining the generated script with the presenter's image to generate a presentation video that reflects emotional information, a means for providing and notifying a download link for the generated video, and a means for recognizing emotions in real time and transmitting that information to the system. This makes it possible to easily create high-quality, personalized presentation videos even without specialized knowledge.

[1741] "Company" refers to a legal entity or organization that promotes a particular product or service.

[1742] An "explanatory material" refers to a document (e.g., a PDF file) containing information about a product or service prepared by a company for sales promotion purposes.

[1743] "Presenter" refers to a virtual character or person who explains a product or service within a presentation video.

[1744] "Custom Avatar" refers to a unique presenter image created or selected by a user.

[1745] "Generated script" refers to the text data of the script and dialogue of a presentation video that is automatically generated based on the content of the explanatory materials and other information.

[1746] "Emotion information" refers to data related to emotions recognized in real time from the user's facial expressions and voice.

[1747] "Generative AI" refers to a system or software that uses artificial intelligence technology to automatically generate scripts, presentation videos, etc.

[1748] "Download link" refers to the URL for obtaining the generated presentation video via the Internet.

[1749] An "emotion engine" refers to software or hardware that has the ability to recognize emotions from a user's facial expressions and voice and transmit that information to the system.

[1750] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products that companies want to promote. This system consists of a server, user terminals, and an emotion engine, and utilizes generation AI to create high-quality videos.

[1751] The system operates in the following specific steps:

[1752] Input of explanatory materials

[1753] Users access the system's login page and log in by entering their company's account information. After logging in, they move to the dashboard page and click the "Upload Materials" button to access the upload page. Then, they drag and drop explanatory materials (e.g., PDF files) or click the "Select File" button to select a file.

[1754] The device reads the selected file and sends its contents to the server, which stores the received file and performs text analysis, extracting key points and elements and storing them in an internal database.

[1755] Presenter Settings

[1756] Users access the reconfigured Presenter Settings page in their dashboard, review the default presenter image (e.g., an image of the company CEO), and click the "Change Image" button to upload a new presenter image (e.g., a custom avatar).

[1757] The device reads the uploaded image file and sends it to the server, which saves the new image and updates the presenter setting information.

[1758] Emotion recognition and reflection

[1759] While the user is uploading explanatory materials, the emotion engine uses the camera and microphone to analyze emotions from the user's facial expressions and voice in real time, and sends emotional information (e.g., joy, surprise, concentration, etc.) to the server.

[1760] The server adjusts the content of the presentation video based on the emotion information, so that the presenter's facial expressions and tone of voice change to match the user's emotions.

[1761] Video generation

[1762] The server uses a generative AI model to create a script for the presentation video based on the analysis results of the explanatory materials, emotional information, and presenter settings. The generated script is combined with an image of the presenter to generate a video.

[1763] The generated video file is saved in the storage area associated with the user's account.

[1764] Video notification and provision

[1765] Once the server has completed generating the video, it will send a notification to the user with a download link. The user will receive the notification and click the link to download the presentation video.

[1766] Pricing

[1767] The system calculates the fee based on the usage of the generated videos. The initial and monthly fees are calculated, and the server adds these fees to the user's account as billing information and reflects them in the next billing cycle. The user receives a payment notification and makes the payment via the provided link.

[1768] Examples of concrete examples and prompts

[1769] Example: Input of explanatory materials

[1770] The user logs into the system with their company account and uploads a PDF file of information about a new product. The device reads the file and sends it to the server, which performs text analysis and extracts key points.

[1771] Example: Setting the presenter

[1772] Users navigate to the presenter settings page, see the default CEO image, then upload a custom avatar and the server updates the settings.

[1773] Example: Emotion recognition and reflection

[1774] While the user is uploading materials, the emotion engine analyzes the user's facial expressions and voice and transmits his / her emotional information to the server, which then adjusts the presenter's facial expressions and tone of voice based on the emotional information.

[1775] Example: Video Generation

[1776] The server creates a script using a generative AI model based on the explanatory materials, emotional information, and presenter image, and generates a presentation video. The video is saved in the user's account storage area.

[1777] Example: Video notification and provision

[1778] The user receives a notification from the server and retrieves the generated presentation video from the provided download link.

[1779] Example: Setting prices

[1780] The system calculates the initial and monthly fees based on the user's usage, adds the billing information to the user's account, and the user receives a payment notification and makes the payment via the provided link.

[1781] Prompt Sentence Examples

[1782] "Generate a video of a company representative giving a presentation based on a new product's explanatory materials. Adjust the presenter's tone of voice and facial expressions based on emotional information."

[1783] "To auto-generate a professional presentation video, upload the PDF file below, use a custom avatar as the presenter, and create a video that reflects the user's emotional information."

[1784] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1785] Step 1: Input of explanatory materials

[1786] The user accesses the system's login page and logs in by entering their company's account information. After successful login, they are redirected to the dashboard page. Next, the user clicks the "Upload Materials" button to access the upload page. They drag and drop explanatory materials (e.g., PDF files) or click the "Select File" button to select a file and upload it. This process receives input that explanatory materials will be uploaded. The terminal reads the selected file and sends the file contents to the server. The server saves the received file, performs text analysis to extract key points, and stores them in an internal database. This is the output data.

[1787] Step 2: Presenter Settings

[1788] The user navigates to the "Presenter Settings" page from the dashboard menu. They check the default presenter image (e.g., an image of the company CEO) and click the "Change Image" button to upload a new presenter image (e.g., a custom avatar). This process receives input that the presenter image will be uploaded. The device reads the uploaded image file and sends it to the server. The server saves the new image and updates the presenter setting information. This is the output data.

[1789] Step 3: Emotional awareness and reflection

[1790] While the user is uploading explanatory materials, the emotion engine uses the camera and microphone to analyze emotions from the user's facial expressions and voice in real time. This process inputs the user's facial expression and voice data. The emotion engine sends emotional information (e.g., joy, surprise, concentration, etc.) to the server. This emotional information is the output data. Based on the emotional information, the server adjusts the content of the presentation video, changing the presenter's facial expressions and tone of voice. This adjusted content is the output data.

[1791] Step 4: Generate the video

[1792] The server uses a generative AI model to create a presentation video script based on the analysis results of the explanatory materials, emotional information, and presenter setting information. This process inputs the analysis results, emotional information, and presenter setting information. The server combines the generated script with the presenter's image to generate a video. The generated video file is saved in the storage area associated with the user's account. This is the output data.

[1793] Step 5: Notify and provide the video

[1794] When the server completes the video generation, it sends a notification to the user with a download link. This process inputs the generated video file. The user receives the notification and clicks the link to download the presentation video. The downloaded video is the output data.

[1795] Step 6: Set your prices

[1796] The system calculates fees based on the usage of the generated videos. This process inputs video usage data. Initial and monthly fees are calculated, and the server adds these fees to the user's account as billing information and reflects them in the next billing cycle. The billing information is the output data. The user receives a payment notification and makes the payment via the provided link. The payment information is the final output data.

[1797] (Application example 2)

[1798] 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."

[1799] Conventional presentation video generation systems require advanced editing techniques and dedicated software, making them difficult for non-experts to use. Furthermore, typical presentation videos have uniform content and lack personalization for viewers. As a result, they fail to attract viewers' attention, making it difficult to carry out effective sales promotions.

[1800] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting explanatory materials for products that a company wants to promote into the system, means for changing the presenter's image from a default image to a custom avatar or a new image, means for generating a presentation video that combines the generated script and the presenter's image, means for providing and notifying a user of a download link for the generated video, means for using an emotion engine that analyzes the user's facial expressions and voice in real time, and means for reflecting emotion information obtained from the emotion engine in the presentation video. This makes it possible to easily generate high-quality, personalized presentation videos without specialized knowledge.

[1801] "Sales promotion" is a marketing activity aimed at increasing sales of a product or service.

[1802] "Explanatory materials" are written and media content used to explain in detail the features and benefits of a product.

[1803] "Inputting into the system" means that a user uploads or enters data or files into the system.

[1804] A "presenter" is a person or character who provides explanations and guidance during a presentation.

[1805] A "custom avatar" is an original virtual character that a user can freely create or select.

[1806] A "generated script" is a presentation script or dialogue generated by the system from explanatory materials.

[1807] "Presentation video" is video content that conveys information visually and audibly.

[1808] The "download link" is a URL for downloading the generated video via the Internet.

[1809] The "emotion engine" is a system that analyzes emotions from a user's facial expressions and voice and provides that information as data.

[1810] "Analyzing in real time" means analyzing data on the fly while the user is operating the device.

[1811] "Generative AI" is a system that uses artificial intelligence technology to automatically generate new content and information from data.

[1812] "Initial costs" are one-time costs incurred when starting to use a service or system.

[1813] "Monthly fee" refers to the fee paid each month to continue using a service or system.

[1814] "Billing Information" means detailed information about charges and payments owed by the User.

[1815] These definitions can be used to clarify the meaning of important terms contained in the claims.

[1816] This invention is a system that automatically generates professional presentation videos based on explanatory materials for products or services that companies want to promote. The system is easy to operate using a smartphone app and includes an emotion engine that analyzes the user's emotional information in real time.

[1817] Upload explanatory materials

[1818] A user accesses the system using a smartphone and uploads explanatory materials (e.g., PDF files). The device sends the files to the server, which stores the received explanatory materials and converts them into an internal format. This conversion is performed using software that uses text analysis techniques to extract key points.

[1819] Presenter Settings

[1820] The user configures the presenter settings through a smartphone app. They can check the default presenter image (e.g., an image of a company representative) and select and upload a new presenter image (e.g., a custom avatar). The device reads this image file and sends it to the server. The server saves the image and updates the presenter settings information.

[1821] Emotion recognition and reflection

[1822] While the user is uploading their presentation materials, the emotion engine analyzes the user's facial expressions and voice in real time to determine their emotions. This emotion engine uses a library called EmotionEngine. The analyzed emotional information is sent to the server and reflected in the presentation video. Specifically, it is reflected in the presenter's facial expressions and tone of voice.

[1823] Video generation

[1824] The server uses a generative AI model to create a script based on explanatory materials, emotional information, and the presenter's image. This script includes text data for the script and dialogue to be used in the presentation video. The server then combines the generated script with the presenter's image to generate a presentation video. A library called VideoGenerator is used to generate high-quality videos. The generated video files are saved in the storage area associated with the user's account.

[1825] Video notification and provision

[1826] The server notifies the user of the download link for the generated video. The notification method is to use the email sending API. The user receives the notification and can click the link to download the video.

[1827] Specific examples

[1828] A company's marketing manager, Mr. A, prepared explanatory materials for a new product, "Smart Gadget," in PDF format. He logged into the system using a smartphone app and uploaded the materials. The server analyzed the text of the materials and extracted key points. Next, Mr. A selected and uploaded a custom avatar on the presenter settings page. The emotion engine analyzed Mr. A's emotions, such as joy and anticipation, and reflected them in the presenter's facial expressions and tone of voice. Finally, the server used generative AI to generate a presentation video and sent Mr. A a download link.

[1829] Prompt Sentence Examples

[1830] We have uploaded an explanatory document for our new product, a "smartwatch." This is a next-generation wearable device that can record heart rate, steps, calorie consumption, and more in real time. Use an emotion recognition engine to analyze the user's facial expressions and tone of voice to create a more engaging presentation video. Use a company character as the presenter image.

[1831] The above is a detailed description of the embodiment of the present invention. This system makes it possible to easily generate high-quality personalized presentation videos without requiring specialized knowledge.

[1832] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1833] Step 1:

[1834] A user logs in to the system using a smartphone and uploads explanatory materials. When the user uploads a PDF file, the device reads the file and sends it to the server. The server receives and saves the file. The input is the PDF file uploaded by the user, and the output is the saved explanatory materials.

[1835] Step 2:

[1836] The server converts the uploaded explanatory materials into an internal format using text analysis technology, specifically extracting and organizing key points. The input is the saved explanatory materials, and the output is the text data of the extracted key points.

[1837] Step 3:

[1838] The user opens the presenter settings page on the smartphone app and checks the default presenter image. They then select and upload a new presenter image. The device reads this new image and sends it to the server. The input is the presenter image uploaded by the user, and the output is the presenter image saved on the server.

[1839] Step 4:

[1840] While the user is uploading explanatory materials, the emotion engine analyzes the user's facial expressions and voice in real time. The analysis results are sent to the server. The input is the user's facial expressions and voice data, and the output is the analyzed emotional information.

[1841] Step 5:

[1842] The server uses a generative AI model to create a script based on the explanatory materials, extracted key points, emotional information, and the presenter image. The inputs are the extracted key points, emotional information, and the presenter image, and the output is the generated script.

[1843] Step 6:

[1844] The server generates a presentation video by combining the generated script and the presenter image. It uses the VideoGenerator library to generate high-quality videos. The input is the generated script and the presenter image, and the output is the generated presentation video.

[1845] Step 7:

[1846] The server notifies the user of the download link for the generated video. The notification method uses an email sending API. The input is the generated presentation video, and the output is the download link sent to the user.

[1847] Step 8:

[1848] The user receives a notification and clicks the download link to download the generated presentation video. The input is the download link sent from the server, and the output is the presentation video downloaded by the user.

[1849] 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.

[1850] 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.

[1851] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1852] 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.

[1853] 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.

[1854] 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.

[1855] 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).

[1856] 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.

[1857] 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."

[1858] 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.

[1859] 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).

[1860] 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.

[1861] 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.

[1862] 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.

[1863] 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.

[1864] 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.

[1865] 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.

[1866] 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.

[1867] 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.

[1868] 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.

[1869] 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.

[1870] The following is further disclosed regarding the above embodiment.

[1871] (Claim 1)

[1872] A means for companies to input explanatory materials for products they want to promote into the system,

[1873] A means to change the presenter from the default image to a custom avatar or a new image;

[1874] a means for generating a presentation video by combining the generated script and an image of the presenter;

[1875] The system includes a means for providing and notifying a download link for the generated video.

[1876] (Claim 2)

[1877] 2. The system of claim 1, further comprising means for generating a script from explanatory materials using a generating AI.

[1878] (Claim 3)

[1879] 10. The system of claim 1, further comprising means for calculating initial and monthly fees along with the generation of the video and for managing billing information.

[1880] "Example 1"

[1881] (Claim 1)

[1882] A means for companies to input explanatory materials for products they want to promote into the system,

[1883] A means to analyze the explanatory materials on the server, extract the main points, and convert them into an internal format;

[1884] A means to change the presenter from the default image to a custom avatar or a new image;

[1885] A means for generating scripts from explanatory materials using a generative AI model; and

[1886] a means for generating a presentation video by combining the generated script and an image of the presenter;

[1887] A means for providing and notifying a download link for the generated video;

[1888] The system includes a means for calculating initial and monthly fees based on the generated video and managing billing information.

[1889] (Claim 2)

[1890] 10. The system of claim 1.

[1891] (Claim 3)

[1892] 2. The system of claim 1, further comprising means for inputting a prompt sentence into the generative AI model to generate a script.

[1893] "Application Example 1"

[1894] (Claim 1)

[1895] A means for companies to input explanatory materials for products they want to promote into the system,

[1896] A means to change the presenter from the default image to a custom avatar or a new image;

[1897] a means for generating a presentation video by combining the generated script and an image of the presenter;

[1898] A means for providing and notifying a download link for the generated video;

[1899] a means including a user interface optimized for a smartphone;

[1900] The system includes means for calculating fees based on the generated video and providing payment advice.

[1901] (Claim 2)

[1902] 10. The system of claim 1, further comprising means for generating a script from explanatory material using a generative AI model.

[1903] (Claim 3)

[1904] The system of claim 1, further comprising means for managing and downloading videos using a smartphone.

[1905] "Example 2: Combining Emotion Engines"

[1906] (Claim 1)

[1907] A means for companies to input explanatory materials for products they want to promote into the system,

[1908] A means to change the presenter from the default image to a custom avatar or a new image;

[1909] A means for generating a presentation video that reflects emotional information by combining the generated script with an image of the presenter;

[1910] A means for providing and notifying a download link for the generated video;

[1911] A system including a means for recognizing emotions in real time and transmitting that information to the system.

[1912] (Claim 2)

[1913] 2. The system of claim 1, further comprising means for generating a script from explanatory materials using a generative AI.

[1914] (Claim 3)

[1915] 10. The system of claim 1, further comprising means for calculating initial and monthly fees along with video generation and managing billing information.

[1916] "Application example 2 when combining emotion engines"

[1917] (Claim 1)

[1918] A means for companies to input explanatory materials for products they want to promote into the system,

[1919] A means to change the presenter from the default image to a custom avatar or a new image;

[1920] a means for generating a presentation video by combining the generated script and an image of the presenter;

[1921] A means for providing and notifying a download link for the generated video;

[1922] A means using an emotion engine that analyzes the user's facial expressions and voice in real time;

[1923] A system including a means for reflecting emotional information obtained from an emotion engine in a presentation video.

[1924] (Claim 2)

[1925] 2. The system of claim 1, further comprising means for generating a script from explanatory materials using a generative AI.

[1926] (Claim 3)

[1927] 10. The system of claim 1, further comprising means for calculating initial and monthly fees along with video generation and managing billing information. [Explanation of symbols]

[1928] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for companies to input explanatory materials for products they want to promote into the system, A means to change the presenter from the default image to a custom avatar or a new image; a means for generating a presentation video by combining the generated script and an image of the presenter; The system includes a means for providing and notifying a download link for the generated video.

2. 2. The system of claim 1, further comprising means for generating a script from explanatory materials using a generating AI.

3. 10. The system of claim 1, further comprising means for calculating initial and monthly fees along with the creation of the video and for managing billing information.

Images